@article {1662569,
	title = {Efficient and precise single-cell reference atlas mapping with Symphony},
	journal = {Nature Communications},
	volume = {12},
	number = {5890},
	year = {2022},
	abstract = {Recent advances in single-cell technologies and integration algorithms make it possible to construct comprehensive reference atlases encompassing many donors, studies, disease states, and sequencing platforms. Much like mapping sequencing reads to a reference genome, it is essential to be able to map query cells onto complex, multimillion-cell reference atlases to rapidly identify relevant cell states and phenotypes. We present Symphony (https://github.com/immunogenomics/symphony), an algorithm for building large-scale, integrated reference atlases in a convenient, portable format that enables efficient query mapping within seconds. Symphony localizes query cells within a stable low-dimensional reference embedding, facilitating reproducible downstream transfer of reference-defined annotations to the query. We demonstrate the power of Symphony in multiple real-world datasets, including (1) mapping a multi-donor, multi-species query to predict pancreatic cell types, (2) localizing query cells along a developmental trajectory of fetal liver hematopoiesis, and (3) inferring surface protein expression with a multimodal CITE-seq atlas of memory T cells.},
	url = {https://www.nature.com/articles/s41467-021-25957-x},
	author = {Kang, J and Nathan, A and Weinand, K and Zhang, F. and Millard, N and Rumker, L and Moody, D. Branch and Korsunsky, I and Raychaudhuri, S}
}
@article {1653854,
	title = {Multimodal platform for assessing drug distribution and response in clinical trials},
	journal = {Neuro Oncol},
	volume = {24},
	number = {1},
	year = {2022},
	month = {2022 01 05},
	pages = {64-77},
	abstract = {
	BACKGROUND: Response to targeted therapy varies between patients for largely unknown reasons. Here, we developed and applied an integrative platform using mass spectrometry imaging (MSI), phosphoproteomics, and multiplexed tissue imaging for mapping drug distribution, target engagement, and adaptive response to gain insights into heterogeneous response to therapy.



	METHODS: Patient-derived xenograft (PDX) lines of glioblastoma were treated with adavosertib, a Wee1 inhibitor, and tissue drug distribution was measured with MALDI-MSI. Phosphoproteomics was measured in the same tumors to identify biomarkers of drug target engagement and cellular adaptive response. Multiplexed tissue imaging was performed on sister sections to evaluate spatial co-localization of drug and cellular response. The integrated platform was then applied on clinical specimens from glioblastoma patients enrolled in the phase 1 clinical trial.



	RESULTS: PDX tumors exposed to different doses of adavosertib revealed intra- and inter-tumoral heterogeneity of drug distribution and integration of the heterogeneous drug distribution with phosphoproteomics and multiplexed tissue imaging revealed new markers of molecular response to adavosertib. Analysis of paired clinical specimens from patients enrolled in the phase 1 clinical trial informed the translational potential of the identified biomarkers in studying patient{\textquoteright}s response to adavosertib.



	CONCLUSIONS: The multimodal platform identified a signature of drug efficacy and patient-specific adaptive responses applicable to preclinical and clinical drug development. The information generated by the approach may inform mechanisms of success and failure in future early phase clinical trials, providing information for optimizing clinical trial design and guiding future application into clinical practice.

},
	keywords = {Glioblastoma, Humans, Pharmaceutical Preparations},
	issn = {1523-5866},
	doi = {10.1093/neuonc/noab197},
	author = {Lopez, Bego{\~n}a G C and Kohale, Ishwar N and Du, Ziming and Korsunsky, Ilya and Abdelmoula, Walid M and Dai, Yang and Stopka, Sylwia A and Gaglia, Giorgio and Randall, Elizabeth C and Regan, Michael S and Basu, Sankha S and Clark, Amanda R and Marin, Bianca-Maria and Mladek, Ann C and Burgenske, Danielle M and Agar, Jeffrey N and Supko, Jeffrey G and Grossman, Stuart A and Nabors, Louis B and Raychaudhuri, Soumya and Ligon, Keith L and Wen, Patrick Y and Alexander, Brian and Lee, Eudocia Q and Santagata, Sandro and Sarkaria, Jann and White, Forest M and Agar, Nathalie Y R}
}
@article {1653853,
	title = {Repertoire analyses reveal T cell antigen receptor sequence features that influence T cell fate},
	journal = {Nat Immunol},
	volume = {23},
	number = {3},
	year = {2022},
	month = {2022 03},
	pages = {446-457},
	abstract = {T cells acquire a regulatory phenotype when their T cell antigen receptors (TCRs) experience an intermediate- to high-affinity interaction with a self-peptide presented via the major histocompatibility complex (MHC). Using TCRβ sequences from flow-sorted human cells, we identified TCR features that promote regulatory T cell (Treg) fate. From these results, we developed a scoring system to quantify TCR-intrinsic regulatory potential (TiRP). When applied to the tumor microenvironment, TiRP scoring helped to explain why only some T cell clones maintained the conventional T cell (Tconv) phenotype through expansion. To elucidate drivers of these predictive TCR features, we then examined the two elements of the Treg TCR ligand separately: the self-peptide and the human MHC class II molecule. These analyses revealed that hydrophobicity in the third complementarity-determining region (CDR3β) of the TCR promotes reactivity to self-peptides, while TCR variable gene (TRBV gene) usage shapes the TCR{\textquoteright}s general propensity for human MHC class II-restricted activation.},
	keywords = {Cell Lineage, Complementarity Determining Regions, Peptides, Receptors, Antigen, T-Cell, Receptors, Antigen, T-Cell, alpha-beta, T-Lymphocytes, Regulatory},
	issn = {1529-2916},
	doi = {10.1038/s41590-022-01129-x},
	author = {Lagattuta, Kaitlyn A and Kang, Joyce B and Nathan, Aparna and Pauken, Kristen E and Jonsson, Anna Helena and Rao, Deepak A and Sharpe, Arlene H and Ishigaki, Kazuyoshi and Raychaudhuri, Soumya}
}
@article {1653852,
	title = {TCR-sequencing in cancer and autoimmunity: barcodes and beyond},
	journal = {Trends Immunol},
	volume = {43},
	number = {3},
	year = {2022},
	month = {2022 03},
	pages = {180-194},
	abstract = {The T cell receptor (TCR) endows T cells with antigen specificity and is central to nearly all aspects of T cell function. Each na{\"\i}ve T cell has a unique TCR sequence that is stably maintained during cell division. In this way, the TCR serves as a molecular barcode that tracks processes such as migration, differentiation, and proliferation of T cells. Recent technological advances have enabled sequencing of the TCR from single cells alongside deep molecular phenotypes on an unprecedented scale. In this review, we discuss strengths and limitations of TCR sequences as molecular barcodes and their application to study immune responses following Programmed Death-1 (PD-1) blockade in cancer. Additionally, we consider applications of TCR data beyond use as a barcode.},
	keywords = {Autoimmunity, Humans, Neoplasms, Receptors, Antigen, T-Cell, T-Lymphocytes},
	issn = {1471-4981},
	doi = {10.1016/j.it.2022.01.002},
	author = {Pauken, Kristen E and Lagattuta, Kaitlyn A and Lu, Benjamin Y and Lucca, Liliana E and Daud, Adil I and Hafler, David A and Kluger, Harriet M and Raychaudhuri, Soumya and Sharpe, Arlene H}
}
@article {1653851,
	title = {Co-varying neighborhood analysis identifies cell populations associated with phenotypes of interest from single-cell transcriptomics},
	journal = {Nat Biotechnol},
	volume = {40},
	number = {3},
	year = {2022},
	month = {2022 03},
	pages = {355-363},
	abstract = {As single-cell datasets grow in sample size, there is a critical need to characterize cell states that vary across samples and associate with sample attributes, such as clinical phenotypes. Current statistical approaches typically map cells to clusters and then assess differences in cluster abundance. Here we present co-varying neighborhood analysis (CNA), an unbiased method to identify associated cell populations with greater flexibility than cluster-based approaches. CNA characterizes dominant axes of variation across samples by identifying groups of small regions in transcriptional space-termed neighborhoods-that co-vary in abundance across samples, suggesting shared function or regulation. CNA performs statistical testing for associations between any sample-level attribute and the abundances of these co-varying neighborhood groups. Simulations show that CNA enables more sensitive and accurate identification of disease-associated cell states than a cluster-based approach. When applied to published datasets, CNA captures a Notch activation signature in rheumatoid arthritis, identifies monocyte populations expanded in sepsis and identifies a novel T cell population associated with progression to active tuberculosis.},
	keywords = {Cluster Analysis, Phenotype, T-Lymphocytes, Transcriptome},
	issn = {1546-1696},
	doi = {10.1038/s41587-021-01066-4},
	author = {Reshef, Yakir and Rumker, Laurie and Kang, Joyce B and Nathan, Aparna and Korsunsky, Ilya and Asgari, Samira and Murray, Megan B and Moody, D Branch and Raychaudhuri, Soumya}
}
@article {1653850,
	title = {HLA autoimmune risk alleles restrict the hypervariable region of T cell receptors},
	journal = {Nat Genet},
	volume = {54},
	number = {4},
	year = {2022},
	month = {2022 04},
	pages = {393-402},
	abstract = {Polymorphisms in the human leukocyte antigen (HLA) genes strongly influence autoimmune disease risk. HLA risk alleles may influence thymic selection to increase the frequency of T cell receptors (TCRs) reactive to autoantigens (central hypothesis). However, research in human autoimmunity has provided little evidence supporting the central hypothesis. Here we investigated the influence of HLA alleles on TCR composition at the highly diverse complementarity determining region 3 (CDR3), which confers antigen recognition. We observed unexpectedly strong HLA-CDR3 associations. The strongest association was found at HLA-DRB1 amino acid position 13, the position that mediates genetic risk for multiple autoimmune diseases. We identified multiple CDR3 amino acid features enriched by HLA risk alleles. Moreover, the CDR3 features promoted by the HLA risk alleles are more enriched in candidate pathogenic TCRs than control TCRs (for example, citrullinated epitope-specific TCRs in patients with rheumatoid arthritis). Together, these results provide genetic evidence supporting the central hypothesis.},
	keywords = {Alleles, Amino Acids, Autoimmune Diseases, Complementarity Determining Regions, HLA-DRB1 Chains, Humans, Receptors, Antigen, T-Cell},
	issn = {1546-1718},
	doi = {10.1038/s41588-022-01032-z},
	author = {Ishigaki, Kazuyoshi and Lagattuta, Kaitlyn A and Luo, Yang and James, Eddie A and Buckner, Jane H and Raychaudhuri, Soumya}
}
@article {1653848,
	title = {Rheumatoid Arthritis Synovial Inflammation Quantification Using Computer Vision},
	journal = {ACR Open Rheumatol},
	volume = {4},
	number = {4},
	year = {2022},
	month = {2022 Apr},
	pages = {322-331},
	abstract = {OBJECTIVE: We quantified inflammatory burden in rheumatoid arthritis (RA) synovial tissue by using computer vision to automate the process of counting individual nuclei in hematoxylin and eosin images.

METHODS: We adapted and applied computer vision algorithms to quantify nuclei density (count of nuclei per unit area of tissue) on synovial tissue from arthroplasty samples. A pathologist validated algorithm results by labeling nuclei in synovial images that were mislabeled or missed by the algorithm. Nuclei density was compared with other measures of RA inflammation such as semiquantitative histology scores, gene-expression data, and clinical measures of disease activity.

RESULTS: The algorithm detected a median of 112,657 (range 8,160-821,717) nuclei per synovial sample. Based on pathologist-validated results, the sensitivity and specificity of the algorithm was 97\% and 100\%, respectively. The mean nuclei density calculated by the algorithm was significantly higher (P \&lt; 0.05) in synovium with increased histology scores for lymphocytic inflammation, plasma cells, and lining hyperplasia. Analysis of RNA sequencing identified 915 significantly differentially expressed genes in correlation with nuclei density (false discovery rate is less than 0.05). Mean nuclei density was significantly higher (P \&lt; 0.05) in patients with elevated levels of C-reactive protein, erythrocyte sedimentation rate, rheumatoid factor, and cyclized citrullinated protein antibody.

CONCLUSION: Nuclei density is a robust measurement of inflammatory burden in RA and correlates with multiple orthogonal measurements of inflammation.},
	issn = {2578-5745},
	doi = {10.1002/acr2.11381},
	author = {Guan, Steven and Mehta, Bella and Slater, David and Thompson, James R and DiCarlo, Edward and Pannellini, Tania and Pearce-Fisher, Diyu and Zhang, Fan and Raychaudhuri, Soumya and Hale, Caryn and Jiang, Caroline S and Goodman, Susan and Orange, Dana E}
}
@article {1653847,
	title = {A framework for employing longitudinally collected multicenter electronic health records to stratify heterogeneous patient populations on disease history},
	journal = {J Am Med Inform Assoc},
	volume = {29},
	number = {5},
	year = {2022},
	month = {2022 04 13},
	pages = {761-769},
	abstract = {OBJECTIVE: To facilitate patient disease subset and risk factor identification by constructing a pipeline which is generalizable, provides easily interpretable results, and allows replication by overcoming electronic health records (EHRs) batch effects.

MATERIAL AND METHODS: We used 1872 billing codes in EHRs of 102~880 patients from 12 healthcare systems. Using tools borrowed from single-cell omics, we mitigated center-specific batch effects and performed clustering to identify patients with highly similar medical history patterns across the various centers. Our visualization method (PheSpec) depicts the phenotypic profile of clusters, applies a novel filtering of noninformative codes (Ranked Scope Pervasion), and indicates the most distinguishing features.

RESULTS: We observed 114 clinically meaningful profiles, for example, linking prostate hyperplasia with cancer and diabetes with cardiovascular problems and grouping pediatric developmental disorders. Our framework identified disease subsets, exemplified by 6 "other headache" clusters, where phenotypic profiles suggested different underlying mechanisms: migraine, convulsion, injury, eye problems, joint pain, and pituitary gland disorders. Phenotypic patterns replicated well, with high correlations of >=0.75 to an average of 6 (2-8) of the 12 different cohorts, demonstrating the consistency with which our method discovers disease history profiles.

DISCUSSION: Costly clinical research ventures should be based on solid hypotheses. We repurpose methods from single-cell omics to build these hypotheses from observational EHR data, distilling useful information from complex data.

CONCLUSION: We establish a generalizable pipeline for the identification and replication of clinically meaningful (sub)phenotypes from widely available high-dimensional billing codes. This approach overcomes datatype problems and produces comprehensive visualizations of validation-ready phenotypes.},
	keywords = {Child, Cluster Analysis, Diabetes Mellitus, Electronic Health Records, Humans, Male, Phenotype},
	issn = {1527-974X},
	doi = {10.1093/jamia/ocac008},
	author = {Maurits, Marc P and Korsunsky, Ilya and Raychaudhuri, Soumya and Murphy, Shawn N and Smoller, Jordan W and Weiss, Scott T and Huizinga, Thomas W J and Reinders, Marcel J T and Karlson, Elizabeth W and van den Akker, Erik B and Knevel, Rachel}
}
@article {1653846,
	title = {Urine Proteomics and Renal Single-Cell Transcriptomics Implicate Interleukin-16 in Lupus Nephritis},
	journal = {Arthritis Rheumatol},
	volume = {74},
	number = {5},
	year = {2022},
	month = {2022 05},
	pages = {829-839},
	abstract = {OBJECTIVE: Current lupus nephritis (LN) treatments are effective in only 30\% of patients, emphasizing the need for novel therapeutic strategies. We undertook this study to develop mechanistic hypotheses and explore novel biomarkers by analyzing the longitudinal urinary proteomic profiles in LN patients undergoing treatment.

METHODS: We quantified 1,000 urinary proteins in 30 patients with LN at the time of the diagnostic renal biopsy and after 3, 6, and 12 months. The proteins and molecular pathways detected in the urine proteome were then analyzed with respect to baseline clinical features and longitudinal trajectories. The intrarenal expression of candidate biomarkers was evaluated using single-cell transcriptomics of renal biopsy sections from LN patients.

RESULTS: Our analysis revealed multiple biologic pathways, including chemotaxis, neutrophil activation, platelet degranulation, and extracellular matrix organization, which could be noninvasively quantified and monitored in the urine. We identified 237 urinary biomarkers associated with LN, as compared to controls without systemic lupus erythematosus. Interleukin-16 (IL-16), CD163, and transforming growth factor β mirrored intrarenal nephritis activity. Response to treatment was paralleled by a reduction in urinary IL-16, a CD4 ligand with proinflammatory and chemotactic properties. Single-cell RNA sequencing independently demonstrated that IL16 is the second most expressed cytokine by most infiltrating immune cells in LN kidneys. IL-16-producing cells were found at key sites of kidney injury.

CONCLUSION: Urine proteomics may profoundly change the diagnosis and management of LN by noninvasively monitoring active intrarenal biologic pathways. These findings implicate IL-16 in LN pathogenesis, designating it as a potentially treatable target and biomarker.},
	keywords = {Biological Products, Biomarkers, Female, Humans, Interleukin-16, Kidney, Lupus Nephritis, Male, Proteomics, Single-Cell Analysis, Transcriptome},
	issn = {2326-5205},
	doi = {10.1002/art.42023},
	author = {Fava, Andrea and Rao, Deepak A and Mohan, Chandra and Zhang, Ting and Rosenberg, Avi and Fenaroli, Paride and Belmont, H Michael and Izmirly, Peter and Clancy, Robert and Trujillo, Jose Monroy and Fine, Derek and Arazi, Arnon and Berthier, Celine C and Davidson, Anne and James, Judith A and Diamond, Betty and Hacohen, Nir and Wofsy, David and Raychaudhuri, Soumya and Apruzzese, William and Buyon, Jill and Petri, Michelle}
}
@article {1653844,
	title = {Monocytes transition to macrophages within the inflamed vasculature via monocyte CCR2 and endothelial TNFR2},
	journal = {J Exp Med},
	volume = {219},
	number = {5},
	year = {2022},
	month = {2022 05 02},
	abstract = {Monocytes undergo phenotypic and functional changes in response to inflammatory cues, but the molecular signals that drive different monocyte states remain largely undefined. We show that monocytes acquire macrophage markers upon glomerulonephritis and may be derived from CCR2+CX3CR1+ double-positive monocytes, which are preferentially recruited, dwell within glomerular capillaries, and acquire proinflammatory characteristics in the nephritic kidney. Mechanistically, the transition to immature macrophages begins within the vasculature and relies on CCR2 in circulating cells and TNFR2 in parenchymal cells, findings that are recapitulated in vitro with monocytes cocultured with TNF-TNFR2-activated endothelial cells generating CCR2 ligands. Single-cell RNA sequencing of cocultures defines a CCR2-dependent monocyte differentiation path associated with the acquisition of immune effector functions and generation of CCR2 ligands. Immature macrophages are detected in the urine of lupus nephritis patients, and their frequency correlates with clinical disease. In conclusion, CCR2-dependent functional specialization of monocytes into macrophages begins within the TNF-TNFR2-activated vasculature and may establish a CCR2-based autocrine, feed-forward loop that amplifies renal inflammation.},
	keywords = {Endothelial Cells, Humans, Ligands, Macrophages, Monocytes, Receptors, CCR2, Receptors, Tumor Necrosis Factor, Type II},
	issn = {1540-9538},
	doi = {10.1084/jem.20210562},
	author = {Mysore, Vijayashree and Tahir, Suhail and Furuhashi, Kazuhiro and Jatin Arora and Rosetti, Florencia and Cullere, Xavier and Yazbeck, Pascal and Sekulic, Miroslav and Lemieux, Madeleine E and Raychaudhuri, Soumya and Horwitz, Bruce H and Mayadas, Tanya N}
}
@article {1653841,
	title = {Single-cell eQTL models reveal dynamic T cell state dependence of disease loci},
	journal = {Nature},
	volume = {606},
	number = {7912},
	year = {2022},
	month = {2022 06},
	pages = {120-128},
	abstract = {Non-coding genetic variants may cause disease by modulating gene expression. However, identifying these expression quantitative trait loci (eQTLs) is complicated by differences in gene regulation across fluid functional cell states within cell types. These states-for example, neurotransmitter-driven programs in astrocytes or perivascular fibroblast differentiation-are obscured in eQTL studies that aggregate cells1,2. Here we modelled eQTLs at single-cell resolution in one complex cell type: memory T cells. Using more than 500,000 unstimulated memory T cells from 259 Peruvian individuals, we show that around one-third of 6,511 cis-eQTLs had effects that were mediated by continuous multimodally defined cell states, such as cytotoxicity and regulatory capacity. In some loci, independent eQTL variants had opposing cell-state relationships. Autoimmune variants were enriched in cell-state-dependent eQTLs, including risk variants for rheumatoid arthritis near ORMDL3 and CTLA4; this indicates that cell-state context is crucial to understanding potential eQTL pathogenicity. Moreover, continuous cell states explained more variation in eQTLs than did conventional discrete categories, such as CD4+ versus CD8+, suggesting that modelling eQTLs and cell states at single-cell resolution can expand insight into gene regulation in functionally heterogeneous cell types.},
	keywords = {Gene Expression Regulation, Genetic Predisposition to Disease, Humans, Memory T Cells, Peru, Quantitative Trait Loci},
	issn = {1476-4687},
	doi = {10.1038/s41586-022-04713-1},
	author = {Nathan, Aparna and Asgari, Samira and Ishigaki, Kazuyoshi and Valencia, Cristian and Amariuta, Tiffany and Luo, Yang and Beynor, Jessica I and Baglaenko, Yuriy and Suliman, Sara and Price, Alkes L and Lecca, Leonid and Murray, Megan B and Moody, D Branch and Raychaudhuri, Soumya}
}
@article {1653840,
	title = {Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases},
	journal = {Med (N Y)},
	volume = {3},
	number = {7},
	year = {2022},
	month = {2022 07 08},
	pages = {481-518.e14},
	abstract = {BACKGROUND: Pro-inflammatory fibroblasts are critical for pathogenesis in rheumatoid arthritis, inflammatory bowel disease, interstitial lung disease, and Sj{\"o}gren{\textquoteright}s syndrome and represent a novel therapeutic target for chronic inflammatory disease. However, the heterogeneity of fibroblast phenotypes, exacerbated by the lack of a common cross-tissue taxonomy, has limited our understanding of which pathways are shared by multiple diseases.

METHODS: We profiled fibroblasts derived from inflamed and non-inflamed synovium, intestine, lungs, and salivary glands from affected individuals with single-cell RNA sequencing. We integrated all fibroblasts into a multi-tissue atlas to characterize shared and tissue-specific phenotypes.

FINDINGS: Two shared clusters, CXCL10+CCL19+ immune-interacting and SPARC+COL3A1+ vascular-interacting fibroblasts, were expanded in all inflamed tissues and mapped to dermal analogs in a public atopic dermatitis atlas. We confirmed these human pro-inflammatory fibroblasts in animal models of lung, joint, and intestinal inflammation.

CONCLUSIONS: This work represents a thorough investigation into fibroblasts across organ systems, individual donors, and disease states that reveals shared pathogenic activation states across four chronic inflammatory diseases.

FUNDING: Grant from F. Hoffmann-La Roche (Roche) AG.},
	keywords = {Animals, Arthritis, Rheumatoid, Fibroblasts, Phenotype, Stromal Cells, Synovial Membrane},
	issn = {2666-6340},
	doi = {10.1016/j.medj.2022.05.002},
	author = {Korsunsky, Ilya and Wei, Kevin and Pohin, Mathilde and Kim, Edy Y and Barone, Francesca and Major, Triin and Taylor, Emily and Ravindran, Rahul and Kemble, Samuel and Watts, Gerald F M and Jonsson, A Helena and Jeong, Yunju and Athar, Humra and Windell, Dylan and Kang, Joyce B and Friedrich, Matthias and Turner, Jason and Nayar, Saba and Fisher, Benjamin A and Raza, Karim and Marshall, Jennifer L and Croft, Adam P and Tamura, Tomoyoshi and Sholl, Lynette M and Vivero, Marina and Rosas, Ivan O and Bowman, Simon J and Coles, Mark and Frei, Andreas P and Lassen, Kara and Filer, Andrew and Powrie, Fiona and Buckley, Christopher D and Brenner, Michael B and Raychaudhuri, Soumya}
}
@article {1653838,
	title = {Higher native Peruvian genetic ancestry proportion is associated with tuberculosis progression risk},
	journal = {Cell Genom},
	volume = {2},
	number = {7},
	year = {2022},
	month = {2022 Jul 13},
	abstract = {We investigated whether ancestry-specific genetic factors affect tuberculosis (TB) progression risk in a cohort of admixed Peruvians. We genotyped 2,105 patients with TB and 1,320 household contacts (HHCs) who were infected with Mycobacterium tuberculosis (M. tb) but did not develop TB and inferred each individual{\textquoteright}s proportion of native Peruvian genetic ancestry. Our HHC study design and our data on potential confounders allowed us to demonstrate increased risk independent of socioeconomic factors. A 10\% increase in individual-level native Peruvian genetic ancestry proportion corresponded to a 25\% increased TB progression risk. This corresponds to a 3-fold increased risk for individuals in the highest decile of native Peruvian genetic ancestry versus the lowest decile, making native Peruvian genetic ancestry comparable in effect to clinical factors such as diabetes. Our results suggest that genetic ancestry is a major contributor to TB progression risk and highlight the value of including diverse populations in host genetic studies.},
	issn = {2666-979X},
	doi = {10.1016/j.xgen.2022.100151},
	author = {Asgari, Samira and Luo, Yang and Huang, Chuan-Chin and Zhang, Zibiao and Calderon, Roger and Jimenez, Judith and Yataco, Rosa and Contreras, Carmen and Galea, Jerome T and Lecca, Leonid and Jones, David and Moody, D Branch and Murray, Megan B and Raychaudhuri, Soumya}
}
@article {1653828,
	title = {Association with HLA-DRβ1 position 37 distinguishes juvenile dermatomyositis from adult-onset myositis},
	journal = {Human Molecular Genetics},
	volume = {31},
	number = {14},
	year = {2022},
	pages = {2471{\textendash}2481},
	abstract = {
	\&nbsp;



	Juvenile dermatomyositis (JDM) is a rare, severe autoimmune disease and the most common idiopathic inflammatory myopathy of children. JDM and adult-onset dermatomyositis (DM) have similar clinical, biological and serological features, although these features differ in prevalence between childhood-onset and adult-onset disease, suggesting that age of disease onset may influence pathogenesis. Therefore, a JDM-focused genetic analysis was performed using the largest collection of JDM samples to date. Caucasian JDM samples (n = 952) obtained via international collaboration were genotyped using the Illumina HumanCoreExome chip. Additional non-assayed human leukocyte antigen (HLA) loci and genome-wide single-nucleotide polymorphisms (SNPs) were imputed. HLA-DRB1*03:01 was confirmed as the classical HLA allele most strongly associated with JDM [odds ratio (OR) 1.66; 95\% confidence interval (CI) 1.46, 1.89; P = 1.4 {\texttimes} 10-14], with an independent association at HLA-C*02:02 (OR = 1.74; 95\% CI 1.42, 2.13, P = 7.13 {\texttimes} 10-8). Analyses of amino acid positions within HLA-DRB1 indicated that the strongest association was at position 37 (omnibus P = 3.3 {\texttimes} 10-19), with suggestive evidence this association was independent of position 74 (omnibus P = 5.1 {\texttimes} 10-5), the position most strongly associated with adult-onset DM. Conditional analyses also suggested that the association at position 37 of HLA-DRB1 was independent of some alleles of the Caucasian HLA 8.1 ancestral haplotype (AH8.1) such as HLA-DQB1*02:01 (OR = 1.62; 95\% CI 1.36, 1.93; P = 8.70 {\texttimes} 10-8), but not HLA-DRB1*03:01 (OR = 1.49; 95\% CR 1.24, 1.80; P = 2.24 {\texttimes} 10-5). No associations outside the HLA region were identified. Our findings confirm previous associations with AH8.1 and HLA-DRB1*03:01, HLA-C*02:02 and identify a novel association with amino acid position 37 within HLA-DRB1, which may distinguish JDM from adult DM.

},
	author = {Deakin, Claire T and Bowes, John and Rider, Lisa G and Miller, Frederick W and Pachman, Lauren M and Sanner, Helga and Rouster-Stevens, Kelly and Mamyrova, Gulnara and Curiel, Rodolfo and Feldman, Brian M and Huber, Adam M and Reed, Ann M and Schmeling, Heinrike and Cook, Charlotte G and Marshall, Lucy R and Wilkinson, Meredyth G LI and Eyre, Stephen and Raychaudhuri, Soumya and Wedderburn, Lucy R and Juvenile Dermatomyositis Cohort and Biomarker Study, the Childhood Myositis Heterogeneity Study Group, and the Myositis Genetics}
}
@article {1594223,
	title = {IFN-γ and TNF-α drive a CXCL10+ CCL2+ macrophage phenotype expanded in severe COVID-19 lungs and inflammatory diseases with tissue inflammation},
	journal = {Genome Med},
	volume = {13},
	number = {1},
	year = {2021},
	pages = {64},
	abstract = {
	Background:\&nbsp;Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate immunomodulatory therapies.



	Methods:\&nbsp;To identify cellular phenotypes that may be shared across tissues affected by disparate inflammatory diseases, we developed a meta-analysis and integration pipeline that models and removes the effects of technology, tissue of origin, and donor that confound cell-type identification. Using this approach, we integrated \&gt; 300,000 single-cell transcriptomic profiles from COVID-19-affected lungs and tissues from healthy subjects and patients with five inflammatory diseases: rheumatoid arthritis (RA), Crohn{\textquoteright}s disease (CD), ulcerative colitis (UC), systemic lupus erythematosus (SLE), and interstitial lung disease. We tested the association of shared immune states with severe/inflamed status compared to healthy control using mixed-effects modeling. To define environmental factors within these tissues that shape shared macrophage phenotypes, we stimulated human blood-derived macrophages with defined combinations of inflammatory factors, emphasizing in particular antiviral interferons IFN-beta (IFN-β) and IFN-gamma (IFN-γ), and pro-inflammatory cytokines such as TNF.



	Results:\&nbsp;We built an immune cell reference consisting of \&gt; 300,000 single-cell profiles from 125 healthy or disease-affected donors from COVID-19 and five inflammatory diseases. We observed a CXCL10+ CCL2+ inflammatory macrophage state that is shared and strikingly abundant in severe COVID-19 bronchoalveolar lavage samples, inflamed RA synovium, inflamed CD ileum, and UC colon. These cells exhibited a distinct arrangement of pro-inflammatory and interferon response genes, including elevated levels of CXCL10, CXCL9, CCL2, CCL3, GBP1, STAT1, and IL1B. Further, we found this macrophage phenotype is induced upon co-stimulation by IFN-γ and TNF-α.



	Conclusions:\&nbsp;Our integrative analysis identified immune cell states shared across inflamed tissues affected by inflammatory diseases and COVID-19. Our study supports a key role for IFN-γ together with TNF-α in driving an abundant inflammatory macrophage phenotype in severe COVID-19-affected lungs, as well as inflamed RA synovium, CD ileum, and UC colon, which may be targeted by existing immunomodulatory therapies.



	Keywords:\&nbsp;COVID-19; Inflammatory diseases; Macrophage heterogeneity; Macrophage stimulation; Single-cell multi-disease tissue integration; Single-cell transcriptomics.

},
	author = {Zhang, F. and J Mears and L Shakib and J Beynor and Shanaj, S and Korsunsky, I and Nathan, A and AMP Consortium and L Donlin and Raychaudhuri, S}
}
@article {1594208,
	title = {Multimodally profiling memory T cells from a tuberculosis cohort identifies cell state associations with demographics, environment and disease},
	journal = {Nat Immunol},
	volume = {22},
	number = {6},
	year = {2021},
	pages = {781-793},
	abstract = {Multimodal T cell profiling can enable more precise characterization of elusive cell states underlying disease. Here, we integrated single-cell RNA and surface protein data from 500,089 memory T cells to define 31 cell states from 259 individuals in a Peruvian tuberculosis (TB) progression cohort. At immune steady state \&gt;4 years after infection and disease resolution, we found that, after accounting for significant effects of age, sex, season and genetic ancestry on T cell composition, a polyfunctional type 17 helper T (TH17) cell-like effector state was reduced in abundance and function in individuals who previously progressed from Mycobacterium tuberculosis (M.tb) infection to active TB disease. These cells are capable of responding to M.tb peptides. Deconvoluting this state-uniquely identifiable with multimodal analysis-from public data demonstrated that its depletion may precede and persist beyond active disease. Our study demonstrates the power of integrative multimodal single-cell profiling to define cell states relevant to disease and other traits.},
	author = {Nathan, A and Beynor, JI and Baglaenko, Y and Suliman, S and Ishigaki, K and Asgari, S and Huang, CC and Luo,Y. and Zhang, Z and Lopez, K and Lindestam Arlehamn, CS and Ernst, JD and J Jimenez and Calderon, RI and Lecca, L and Van Rhijin, I and Moody, DB and MB Murray and Raychaudhuri, S}
}
@article {SHOOPWORRALL2021e111,
	title = {Patient-reported wellbeing and clinical disease measures over time captured by multivariate trajectories of disease activity in individuals with juvenile idiopathic arthritis in the UK: a multicentre prospective longitudinal study},
	journal = {The Lancet Rheumatology},
	volume = {3},
	number = {2},
	year = {2021},
	pages = {e111-e121},
	abstract = {Summary Background Juvenile idiopathic arthritis (JIA) is a heterogeneous disease, the signs and symptoms of which can be summarised with use of composite disease activity measures, including the clinical Juvenile Arthritis Disease Activity Score (cJADAS). However, clusters of children and young people might experience different global patterns in their signs and symptoms of disease, which might run in parallel or diverge over time. We aimed to identify such clusters in the 3 years after a diagnosis of JIA. The identification of these clusters would allow for a greater understanding of disease progression in JIA, including how physician-reported and patient-reported outcomes relate to each other over the JIA disease course. Methods In this multicentre prospective longitudinal study, we included children and young people recruited before Jan 1, 2015, to the Childhood Arthritis Prospective Study (CAPS), a UK multicentre inception cohort. Participants without a cJADAS score were excluded. To assess groups of children and young people with similar disease patterns in active joint count, physician{\textquoteright}s global assessment, and patient or parental global evaluation, we used latent profile analysis at initial presentation to paediatric rheumatology and multivariate group-based trajectory models for the following 3 years. Optimal models were selected on the basis of a combination of model fit, clinical plausibility, and model parsimony. Finding Between Jan 1, 2001, and Dec 31, 2014, 1423 children and young people with JIA were recruited to CAPS, 239 of whom were excluded, resulting in a final study population of 1184 children and young people. We identified five clusters at baseline and six trajectory groups using longitudinal follow-up data. Disease course was not well predicted from clusters at baseline; however, in both cross-sectional and longitudinal analyses, substantial proportions of children and young people had high patient or parent global scores despite low or improving joint counts and physician global scores. Participants in these groups were older, and a higher proportion of them had enthesitis-related JIA and lower socioeconomic status, compared with those in other groups. Interpretation Almost one in four children and young people with JIA in our study reported persistent, high patient or parent global scores despite having low or improving active joint counts and physician{\textquoteright}s global scores. Distinct patient subgroups defined by disease manifestation or trajectories of progression could help to better personalise health-care services and treatment plans for individuals with JIA. Funding Medical Research Council, Versus Arthritis, Great Ormond Street Hospital Children{\textquoteright}s Charity, Olivia{\textquoteright}s Vision, and National Institute for Health Research.},
	issn = {2665-9913},
	doi = {https://doi.org/10.1016/S2665-9913(20)30269-1},
	author = {Stephanie J W Shoop-Worrall and Hyrich, Kimme L and Wedderburn, Lucy R and Thomson, Wendy and Nophar Geifman and Eileen Baildam and Barnes, Michael and Michael W Beresford and Emil Carlsson and Alice Chieng and Coziana Ciurtin and Gavin Cleary and Joyce Davidson and Fatjon Dekaj and Sally-Anne Dews and Andrew Dick and Gil Reynolds Diogo and Teresa Duerr and Joanna Fairlie and Helen Foster and Jenna F Gritzfeld and Yiannis Ioannou and Beth Jebson and Melissa Kartawinata and Toby Kent and Aline Kimonyo and Saskia Lawson-Tovey and Wei-Yu Lin and Martin, Paul and Flora McErlane and Fatema Merali and Morris, Andrew and Helen Neale and Jessica Neisen and Sandra Ng and Elizabeth Ralph and Athimalaipet V Ramanan and Raychaudhuri, Soumya and Robinson, Emily and Samantha Smith and Emma Sumner and Damian Tarasek and Wallace, Chris and Zoe Wanstall and Yarwood, Annie}
}
@article {KhanASN.2020091371,
	title = {Medical Records-Based Genetic Studies of the Complement System},
	journal = {Journal of the American Society of Nephrology},
	volume = {32},
	number = {8},
	year = {2021},
	pages = {2031-2047},
	publisher = {American Society of Nephrology},
	abstract = {The complement pathway represents one of the critical arms of the innate immune system. We combined genome-wide and phenome-wide association studies using medical records data for C3 and C4 levels to discover common genetic variants controlling systemic complement activation. Three genome-wide significant loci had large effects on complement levels. These loci encode three critical complement genes: CFH, C3, and C4. We performed detailed functional annotations of the significant loci, including multiallelic copy number variant analysis of the C4 locus to define two structural genomic variants with large effects on C4 levels. Blood C4 levels were strongly correlated with the copy number of C4A and C4B genes. Lastly, using genome-wide genetic correlations and electronic health records{\textendash}based phenome-wide association studies in 102,138 participants, we catalogued a spectrum of human diseases genetically related to systemic complement activation, including inflammatory, autoimmune, cardiometabolic, and kidney diseases.Background Genetic variants in complement genes have been associated with a wide range of human disease states, but well-powered genetic association studies of complement activation have not been performed in large multiethnic cohorts.Methods We performed medical records{\textendash}based genome-wide and phenome-wide association studies for plasma C3 and C4 levels among participants of the Electronic Medical Records and Genomics (eMERGE) network.Results In a GWAS for C3 levels in 3949 individuals, we detected two genome-wide significant loci: chr.1q31.3 (CFH locus; rs3753396-A; β=0.20; 95\% CI, 0.14 to 0.25; P=1.52x10-11) and chr.19p13.3 (C3 locus; rs11569470-G; β=0.19; 95\% CI, 0.13 to 0.24; P=1.29x10-8). These two loci explained approximately 2\% of variance in C3 levels. GWAS for C4 levels involved 3998 individuals and revealed a genome-wide significant locus at chr.6p21.32 (C4 locus; rs3135353-C; β=0.40; 95\% CI, 0.34 to 0.45; P=4.58x10-35). This locus explained approximately 13\% of variance in C4 levels. The multiallelic copy number variant analysis defined two structural genomic C4 variants with large effect on blood C4 levels: C4-BS (β=-0.36; 95\% CI, -0.42 to -0.30; P=2.98x10-22) and C4-AL-BS (β=0.25; 95\% CI, 0.21 to 0.29; P=8.11x10-23). Overall, C4 levels were strongly correlated with copy numbers of C4A and C4B genes. In comprehensive phenome-wide association studies involving 102,138 eMERGE participants, we cataloged a full spectrum of autoimmune, cardiometabolic, and kidney diseases genetically related to systemic complement activation.Conclusions We discovered genetic determinants of plasma C3 and C4 levels using eMERGE genomic data linked to electronic medical records. Genetic variants regulating C3 and C4 levels have large effects and multiple clinical correlations across the spectrum of complement-related diseases in humans.},
	issn = {1046-6673},
	doi = {10.1681/ASN.2020091371},
	author = {Khan, Atlas and Shang, Ning and Petukhova, Lynn and Zhang, Jun and Shen, Yufeng and Hebbring, Scott J. and Moncrieffe, Halima and Kottyan, Leah C. and Namjou-Khales, Bahram and Knevel, Rachel and Raychaudhuri, Soumya and Karlson, Elizabeth W. and Harley, John B. and Stanaway, Ian B. and Crosslin, David and Denny, Joshua C. and Elkind, Mitchell S.V. and Gharavi, Ali G. and Hripcsak, George and Weng, Chunhua and Kiryluk, Krzysztof}
}
@article {1594226,
	title = {Population-specific causal disease effect sizes in functionally important regions impacted by selection},
	journal = {Nat Commun},
	volume = {12},
	number = {1},
	year = {2021},
	pages = {1098},
	abstract = {Many diseases exhibit population-specific causal effect sizes with trans-ethnic genetic correlations significantly less than 1, limiting trans-ethnic polygenic risk prediction. We develop a new method, S-LDXR, for stratifying squared trans-ethnic genetic correlation across genomic annotations, and apply S-LDXR to genome-wide summary statistics for 31 diseases and complex traits in East Asians (average N = 90K) and Europeans (average N = 267K) with an average trans-ethnic genetic correlation of 0.85. We determine that squared trans-ethnic genetic correlation is 0.82{\texttimes} (s.e. 0.01) depleted in the top quintile of background selection statistic, implying more population-specific causal effect sizes. Accordingly, causal effect sizes are more population-specific in functionally important regions, including conserved and regulatory regions. In regions surrounding specifically expressed genes, causal effect sizes are most population-specific for skin and immune genes, and least population-specific for brain genes. Our results could potentially be explained by stronger gene-environment interaction at loci impacted by selection, particularly positive selection.},
	author = {H Shi and S Gazal and M Kanai and E M Koch and A P Schoech and K M Siewert and Kim, S S and Luo,Y. and Amariuta, T and H Huang and Okada, Y and Raychaudhuri, S and SR Sunyaev and Price, AL}
}
@article {1594224,
	title = {Accurate imputation of human leukocyte antigens with CookHLA},
	journal = {Nat Commun},
	volume = {12},
	number = {1},
	year = {2021},
	pages = {1264},
	abstract = {The recent development of imputation methods enabled the prediction of human leukocyte antigen (HLA) alleles from intergenic SNP data, allowing studies to fine-map HLA for immune phenotypes. Here we report an accurate HLA imputation method, CookHLA, which has superior imputation accuracy compared to previous methods. CookHLA differs from other approaches in that it locally embeds prediction markers into highly polymorphic exons to account for exonic variability, and in that it adaptively learns the genetic map within MHC from the data to facilitate imputation. Our benchmarking with real datasets shows that our method achieves high imputation accuracy in a wide range of scenarios, including situations where the reference panel is small or ethnically unmatched.},
	author = {S Cook and Choi, W and H Lim and Luo,Y. and Kim, K and X Jia and Raychaudhuri, S and Han, B}
}
@article {1594222,
	title = {HATK: HLA Analysis Toolkit},
	journal = {Bioinformatics},
	volume = {37},
	number = {3},
	year = {2021},
	pages = {416-418},
	author = {Choi, W and Luo,Y. and Raychaudhuri, S and Han, B}
}
@article {1594216,
	title = {Transethnic analysis of the human leukocyte antigen region for ulcerative colitis reveals not only shared but also ethnicity-specific disease associations},
	journal = {Hum Mol Genet},
	volume = {30},
	number = {5},
	year = {2021},
	pages = {356-369},
	abstract = {Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the gut. Genetic association studies have identified the highly variable human leukocyte antigen (HLA) region as the strongest susceptibility locus for IBD and specifically DRB1*01:03 as a determining factor for ulcerative colitis (UC). However, for most of the association signal such as delineation could not be made because of tight structures of linkage disequilibrium within the HLA. The aim of this study was therefore to further characterize the HLA signal using a transethnic approach. We performed a comprehensive fine mapping of single HLA alleles in UC in a cohort of 9272 individuals with African American, East Asian, Puerto Rican, Indian and Iranian descent and 40 691 previously analyzed Caucasians, additionally analyzing whole HLA haplotypes. We computationally characterized the binding of associated HLA alleles to human self-peptides and analyzed the physicochemical properties of the HLA proteins and predicted self-peptidomes. Highlighting alleles of the HLA-DRB1*15 group and their correlated HLA-DQ-DR haplotypes, we not only identified consistent associations (regarding effects directions/magnitudes) across different ethnicities but also identified population-specific signals (regarding differences in allele frequencies). We observed that DRB1*01:03 is mostly present in individuals of Western European descent and hardly present in non-Caucasian individuals. We found peptides predicted to bind to risk HLA alleles to be rich in positively charged amino acids. We conclude that the HLA plays an important role for UC susceptibility across different ethnicities. This research further implicates specific features of peptides that are predicted to bind risk and protective HLA proteins.},
	author = {F Degenhardt and Mayr, G and Wendorff, M and Boucher, G and Ellinghaus, E and Ellinghaus, D and ElAbd, H and Rosati, E and Hubenthal, M and Juzenas, S and Abedian, S and Vahedi, H and Thelma, B K and Yang, S-K and Ye, B D and Cheon, J H and Datta, L W and Daryani, N E and Ellul, P and Esaki, M and Fuyuno, Y and McGovern, D P B and Haritunians, T and Hong, M and Juyal, G and Jung, E S and Kubo, M and Kugathasan, S and Lenz, T L and Leslie, S and Malekzadeh, R and Midha, V and Motyer, A and Ng, S C and Okou, D T and Raychaudhuri, S and Schembri, J and Schreiber, S and Song, K and Sood, A and Takahashi, A and Torres, E A and Umeno, J and Alizadeh, B Z and Weersma, R K and Wong, S H and Yamazaki, K and Karlsen, T H and Rioux, J D and Brant, S R and MAAIS Recruitment Center and Franke, A and International IBD Genetics Consortium}
}
@article {1555006,
	title = {Maximizing statistical power to detect clinically associated cell states with scPOST},
	journal = {Cell Rep Methods},
	volume = {1},
	number = {8},
	year = {2021},
	pages = {PMCID: PMC8740883},
	abstract = {As advances in single-cell technologies enable the unbiased assay of thousands of cells simultaneously, human disease studies are able to identify clinically associated cell states using case-control study designs. These studies require precious clinical samples and costly technologies; therefore, it is critical to employ study design principles that maximize power to detect cell state frequency shifts between conditions, such as disease versus healthy. Here, we present single-cell Power Simulation Tool (scPOST), a method that enables users to estimate power under different study designs. To approximate the specific experimental and clinical scenarios being investigated, scPOST takes prototype (public or pilot) single-cell data as input and generates large numbers of single-cell datasets\&nbsp;in silico. We use scPOST to perform power analyses on three independent single-cell datasets that span diverse experimental conditions: a batch-corrected 21-sample rheumatoid arthritis dataset (5,265 cells) from synovial tissue, a 259-sample tuberculosis progression dataset (496,517 memory T cells) from peripheral blood mononuclear cells (PBMCs), and a 30-sample ulcerative colitis dataset (235,229 cells) from intestinal biopsies. Over thousands of simulations, we consistently observe that power to detect frequency shifts in cell states is maximized by larger numbers of independent clinical samples, reduced batch effects, and smaller variation in a cell state{\textquoteright}s frequency across samples.},
	author = {Millard, N and Korsunsky, I and Weinand, Kathryn and Fonseka, CY and Nathan, A and Kang, J B and Raychaudhuri, S}
}
@article {Luo2020.07.16.20155606,
	title = {A high-resolution HLA reference panel capturing global population diversity enables multi-ethnic fine-mapping in HIV host response},
	journal = {Nature Genetics},
	volume = {53},
	number = {10},
	year = {2020},
	pages = {1504-1516},
	publisher = {Cold Spring Harbor Laboratory Press},
	abstract = {Defining causal variation by fine-mapping can be more effective in multi-ethnic genetic studies, particularly in regions such as the MHC with highly population-specific structure. To enable such studies, we constructed a large (N=21,546) high resolution HLA reference panel spanning five global populations based on whole-genome sequencing data. Expectedly, we observed unique long-range HLA haplotypes within each population group. Despite this, we demonstrated consistently accurate imputation at G-group resolution (94.2\%, 93.7\%, 97.8\% and 93.7\% in Admixed African (AA), East Asian (EAS), European (EUR) and Latino (LAT)). We jointly analyzed genome-wide association studies (GWAS) of HIV-1 viral load from EUR, AA and LAT populations. Our analysis pinpointed the MHC association to three amino acid positions (97, 67 and 156) marking three consecutive pockets (C, B and D) within the HLA-B peptide binding groove, explaining 12.9\% of trait variance, and obviating effects of previously reported associations from population-specific HIV studies.Competing Interest StatementM.H.C. has received consulting or speaking fees from Illumina and AstraZeneca, and grant support from GSK and Bayer.Funding StatementThe study was supported by the National Institutes of Health (NIH) TB Research Unit Network, Grant U19 AI111224-01. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. The Genotype and Phenotype (GaP) Registry at The Feinstein Institute for Medical Research provided fresh, de-identified human plasma; blood was collected from control subjects under an IRB-approved protocol (IRB$\#$ 09-081) and processed to isolate plasma. The GaP is a sub-protocol of the Tissue Donation Program (TDP) at Northwell Health and a national resource for genotype-phenotype studies. https://www.feinsteininstitute.org/robert-s-boas-center-for-genomics-and-human-genetics/gap-registry/ A.M. is supported by Gentransmed grant 2014-2020.4.01.15-0012.; D.W.H. is supported by NIH grants AI110527, AI077505, TR000445, AI069439, and AI110527. D.H.S. was supported by R01 HL92301, R01 HL67348, R01 NS058700, R01 AR48797, R01 DK071891, R01 AG058921, the General Clinical Research Center of the Wake Forest University School of Medicine (M01 RR07122, F32 HL085989), the American Diabetes Association, and a pilot grant from the Claude Pepper Older Americans Independence Center of Wake Forest University Health Sciences (P60 AG10484). J.T.E. and P.E.S. were supported by NIH/NIAMS R01 AR042742, R01 AR050511, and R01 AR063611. For some HIV cohort participants, DNA and data collection was supported by NIH/NIAID AIDS Clinical Trial Group (ACTG) grants UM1 AI068634, UM1 AI068636 and UM1 AI106701, and ACTG clinical research site grants A1069412, A1069423, A1069424, A1069503, AI025859, AI025868, AI027658, AI027661, AI027666, AI027675, AI032782, AI034853, AI038858, AI045008, AI046370, AI046376, AI050409, AI050410, AI050410, AI058740, AI060354, AI068636, AI069412, AI069415, AI069418, AI069419, AI069423, AI069424, AI069428, AI069432, AI069432, AI069434, AI069439, AI069447, AI069450, AI069452, AI069465, AI069467, AI069470, AI069471, AI069472, AI069474, AI069477, AI069481, AI069484, AI069494, AI069495, AI069496, AI069501, AI069501, AI069502, AI069503, AI069511, AI069513, AI069532, AI069534, AI069556, AI072626, AI073961, RR000046, RR000425, RR023561, RR024156, RR024160, RR024996, RR025008, RR025747, RR025777, RR025780, TR000004, TR000058, TR000124, TR000170, TR000439, TR000445, TR000457, TR001079, TR001082, TR001111, and TR024160. Molecular data for the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung and Blood Institute (NHLBI). See the TOPMed Omics Support Table (Supplementary Table 16) for study specific omics support information. Core support including centralized genomic read mapping and genotype calling, along with variant quality metrics and filtering were provided by the TOPMed Informatics Research Center (3R01HL-117626-02S1; contract HHSN268201800002I). Core support including phenotype harmonization, data management, sample-identity QC, and general program coordination were provided by the TOPMed Data Coordinating Center (R01HL-120393; U01HL-120393; contract HHSN268201800001I). We gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed. The COPDGene project was supported by Award Number U01 HL089897 and Award Number U01 HL089856 from the National Heart, Lung, and Blood Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung, and Blood Institute or the National Institutes of Health. The COPDGene project is also supported by the COPD Foundation through contributions made to an Industry Advisory Board comprised of AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Novartis, Pfizer, Siemens and Sunovion. A full listing of COPDGene investigators can be found at: http://www.copdgene.org/directory The Jackson Heart Study (JHS) is supported and conducted in collaboration with Jackson State University (HHSN268201800013I), Tougaloo College (HHSN268201800014I), the Mississippi State Department of Health (HHSN268201800015I) and the University of Mississippi Medical Center (HHSN268201800010I, HHSN268201800011I and HHSN268201800012I) contracts from the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute on Minority Health and Health Disparities (NIMHD). The authors also wish to thank the staffs and participants of the JHS. MESA and the MESA SHARe project are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420. MESA Family is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support is provided by grants and contracts R01HL071051, R01HL071205, R01HL071250, R01HL071251, R01HL071258, R01HL071259, by the National Center for Research Resources, Grant UL1RR033176. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. This project has been funded in whole or in part with federal funds from the Frederick National Laboratory for Cancer Research, under Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. This Research was supported in part by the Intramural Research Program of the NIH, Frederick National Lab, Center for Cancer Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:The Genotype and Phenotype (GaP) Registry at The Feinstein Institute for Medical Research provided fresh, de-identified human plasma; blood was collected from control subjects under an IRB-approved protocol (IRB$\#$ 09-081) and processed to isolate plasma. The GaP is a sub-protocol of the Tissue Donation Program (TDP) at Northwell Health and a national resource for genotype-phenotype studies. Each study was previously approved by respective institutional review boards (IRBs), including for the generation of WGS data and association with phenotypes. All participants provided written consent.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesThe source code is available for download at https://github.com/immunogenomics},
	doi = {10.1101/2020.07.16.20155606},
	author = {Luo, Yang and Kanai, Masahiro and Choi, Wanson and Li, Xinyi and Yamamoto, Kenichi and Ogawa, Kotaro and Gutierrez-Arcelus, Maria and Gregersen, Peter K. and Stuart, Philip E. and Elder, James T. and Fellay, Jacques and Carrington, Mary and Haas, David W. and Guo, Xiuqing and Palmer, Nicholette D. and Chen, Yii-Der Ida and Rotter, Jerome. I. and Taylor, Kent. D. and Rich, Stephen. S. and Correa, Adolfo and Wilson, James G. and Kathiresan, Sekar and Cho, Michael H. and Metspalu, Andres and Esko, Tonu and Okada, Yukinori and Han, Buhm and NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium and McLaren, Paul J. and Raychaudhuri, Soumya}
}
@article {1555001,
	title = {Improving the trans-ancestry portability of polygenic risk scores by prioritizing variants in predicted cell-type-specific regulatory elements},
	journal = {Nature Genetics},
	volume = {52},
	year = {2020},
	pages = {1346-1354},
	abstract = {Poor trans-ancestry portability of polygenic risk scores is a consequence of Eurocentric genetic studies and limited knowledge of shared causal variants. Leveraging regulatory annotations may improve portability by prioritizing functional over tagging variants. We constructed a resource of 707 cell-type-specific IMPACT regulatory annotations by aggregating 5,345 epigenetic datasets to predict binding patterns of 142 transcription factors across 245 cell types. We then partitioned the common SNP heritability of 111 genome-wide association study summary statistics of European (average\&nbsp;n ≈ 189,000) and East Asian (average\&nbsp;n ≈ 157,000) origin. IMPACT annotations captured consistent SNP heritability between populations, suggesting prioritization of shared functional variants. Variant prioritization using IMPACT resulted in increased trans-ancestry portability of polygenic risk scores from Europeans to East Asians across all 21 phenotypes analyzed (49.9\% mean relative increase in\&nbsp;R2). Our study identifies a crucial role for functional annotations such as IMPACT to improve the trans-ancestry portability of genetic data.},
	author = {Amariuta, T and Ishigaki, K and Sugishita, H and Ohta, T and Koido, M and Dey, K K and Matsuda, K and Murakami, Y and Price, AL and Kawakami, E and Terao, C and Raychaudhuri, S}
}
@article {Asgari561241,
	title = {A positively selected, common, missense variant in FBN1 confers a 2.2 centimeter reduction of height in the Peruvian population},
	journal = {Nature  },
	volume = {582},
	number = {7811},
	year = {2020},
	pages = {234-239},
	publisher = {Cold Spring Harbor Laboratory},
	abstract = {Peruvians are among the shortest people in the world. To understand the genetic basis of short stature in Peru, we examined an ethnically diverse group of Peruvians and identified a novel, population-specific, missense variant in FBN1 (E1297G) that is significantly associated with lower height in the Peruvian population. Each copy of the minor allele (frequency = 4.7\%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). This is the largest effect size known for a common height-associated variant. This variant shows strong evidence of positive selection within the Peruvian population and is significantly more frequent in Native American populations from coastal regions of Peru compared to populations from the Andes or the Amazon, suggesting that short stature in Peruvians is the result of adaptation to the coastal environment.One Sentence Summary A mutation found in Peruvians has the largest known effect on height for a common variant. This variant is specific to Native American ancestry.},
	doi = {10.1101/561241},
	author = {Asgari, Samira and Luo, Yang and Belbin, Gillian M. and Bartell, Eric and Calderon, Roger and Slowikowski, Kamil and Contreras, Carmen and Yataco, Rosa and Galea, Jerome T. and Jimenez, Judith and Coit, Julia M. and Farro{\~n}ay, Chandel and Nazarian, Rosalynn M. and O{\textquoteright}Connor, Timothy D. and Dietz, Harry C. and Hirschhorn, Joel and Guio, Heinner and Lecca, Leonid and Kenny, Eimear E. and Freeman, Esther and Murray, Megan B. and Raychaudhuri, Soumya}
}
@article {1483823,
	title = {Allele-specific expression changes dynamically during T cell activation in HLA and other autoimmune loci},
	journal = {Nature Genetics},
	volume = {52},
	year = {2020},
	pages = {247-253},
	abstract = {Genetic studies have revealed that autoimmune susceptibility variants are over-represented in memory CD4+ T cell regulatory elements1-3. Understanding how genetic variation affects gene expression in different T cell physiological states is essential for deciphering genetic mechanisms of autoimmunity4,5. Here, we characterized the dynamics of genetic regulatory effects at eight time points during memory CD4+ T cell activation with high-depth RNA-seq in healthy individuals. We discovered widespread, dynamic allele-specific expression across the genome, where the balance of alleles changes over time. These genes were enriched fourfold within autoimmune loci. We found pervasive dynamic regulatory effects within six HLA genes. HLA-DQB1 alleles had one of three distinct transcriptional regulatory programs. Using CRISPR-Cas9 genomic editing we demonstrated that a promoter variant is causal for T cell-specific control of HLA-DQB1 expression. Our study shows that genetic variation in cis-regulatory elements affects gene expression in a manner dependent on lymphocyte activation status, contributing to the interindividual complexity of immune responses.},
	author = {Gutierrez-Arcelus, Maria$\#$ and Baglaenko, Yuriy$\#$ and Jatin Arora and Susan Hannes and Luo, Yang and Amariuta, Tiffany and Teslovich, Nikola and Rao, Deepak A. and Ermann, Joerg and A. Helena Jonsson and NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium and Cristina Navarrete and Rich, Stephen S. and Kent D. Taylor and Jerome I. Rotter and Gregersen, Peter K. and Esko, Tonu and Brenner, Michael B and Raychaudhuri, Soumya}
}
@article {1483808,
	title = {Notch signalling drives synovial fibroblast identity and arthritis pathology},
	journal = {Nature},
	volume = {582},
	number = {7811},
	year = {2020},
	pages = {259-264},
	author = {Wei, K$\#$ and Korsunsky, I$\#$ and JL Marshall and A Gao and Watts, GFM and T Major and Croft, AP and J Watts and P Blazar and J Lange and T Thornhill and Filer, A and K Raza and Donlin, LT and Accelerating Medicines Partnership-Rheumatoid arthritis/Systemic Lupus Erythematosus (AMP RA/SLE), and CW Siebel and Buckley, CD and Raychaudhuri, S* and MB. Brenner*}
}
@article {https://doi.org/10.1002/art.41414,
	title = {Interactions Between Genome-Wide Genetic Factors and Smoking Influencing Risk of Systemic Lupus Erythematosus},
	journal = {Arthritis \& Rheumatology},
	volume = {72},
	number = {11},
	year = {2020},
	pages = {1863-1871},
	abstract = {{Objective To identify interactions between genetic factors and current or recent smoking in relation to risk of developing systemic lupus erythematosus (SLE). Methods For the study, 673 patients with SLE (diagnosed according to the American College of Rheumatology 1997 updated classification criteria) were matched by age, sex, and race (first 3 genetic principal components) to 3,272 control subjects without a history of connective tissue disease. Smoking status was classified as current smoking/having recently quit smoking within 4 years before diagnosis (or matched index date for controls) versus distant past/never smoking. In total, 86 single-nucleotide polymorphisms and 10 classic HLA alleles previously associated with SLE were included in a weighted genetic risk score (wGRS), with scores dichotomized as either low or high based on the median value in control subjects (low wGRS being defined as less than or equal to the control median; high wGRS being defined as greater than the control median). Conditional logistic regression models were used to estimate both the risk of SLE and risk of anti{\textendash}double-stranded DNA autoantibody{\textendash}positive (dsDNA+) SLE. Additive interactions were assessed using the attributable proportion (AP) due to interaction, and multiplicative interactions were assessed using a chi-square test (with 1 degree of freedom) for the wGRS and for individual risk alleles. Separate repeated analyses were carried out among subjects of European ancestry only. Results The mean {\textpm} SD age of the SLE patients at the time of diagnosis was 36.4 {\textpm} 15.3 years. Among the 673 SLE patients included, 92.3\% were female and 59.3\% were dsDNA+. Ethnic distributions were as follows: 75.6\% of European ancestry, 4.5\% of Asian ancestry, 11.7\% of African ancestry, and 8.2\% classified as other ancestry. A high wGRS (odds ratio [OR] 2.0},
	doi = {https://doi.org/10.1002/art.41414},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/art.41414},
	author = {Cui, Jing and Raychaudhuri, Soumya and Karlson, Elizabeth W. and Speyer, Cameron and Malspeis, Susan and Guan, Hongshu and Sparks, Jeffrey A. and Ni, Hongru and Liu, Xinyi and Stevens, Emma and Williams, Jessica N. and Davenport, Emma E. and Knevel, Rachel and Costenbader, Karen H.}
}
@article {1555045,
	title = {HLA autoimmune risk alleles restrict the hypervariable region of T cell receptors},
	year = {2020},
	abstract = {Polymorphisms in the\&nbsp;human leukocyte antigen\&nbsp;(HLA) genes within the\&nbsp;major histocompatibility complex\&nbsp;(MHC) locus strongly influence autoimmune disease risk1{\textendash}5. Two non-exclusive hypotheses exist about the pathogenic role of\&nbsp;HLAalleles; i) the central hypothesis, where\&nbsp;HLA\&nbsp;risk alleles influence thymic selection so that the probability of T cell receptors (TCRs) reactive to pathogenic antigens is increased6{\textendash}8; and ii) the peripheral hypothesis, where\&nbsp;HLA\&nbsp;risk alleles increase the affinity for pathogenic antigens9{\textendash}11. The peripheral hypothesis has been the main research focus in autoimmunity, while human data on the central hypothesis are lacking. Here, we investigated the influence of\&nbsp;HLA\&nbsp;alleles on TCR composition at the highly diverse complementarity determining region 3 (CDR3), where TCR recognizes antigens. We demonstrated unexpectedly powerful\&nbsp;HLA-CDR3 associations. The strongest association was found at\&nbsp;HLA-DRB1\&nbsp;amino acid position 13 (n = 628 subjects, explained variance = 9.4\%;\&nbsp;P\&nbsp;= 4.1 x 10-138). This HLA position mediates genetic risk for multiple autoimmune diseases. In structural analysis of TCR-peptide-MHC complexes, we observed that HLA-DRB1 position 13 does not interact directly with CDR3, but is proximate to antigenic peptide residues that are also close to CDR3. We identified multiple CDR3 amino acid features enriched by\&nbsp;HLA\&nbsp;risk alleles; for example, the risk alleles of rheumatoid arthritis, type 1 diabetes, and celiac disease all increase the hydrophobicity of CDR3 position 109 (P\&nbsp;\&lt; 2.1 x 10-5). In the setting of celiac disease, the CDR3 features favored by\&nbsp;HLA\&nbsp;risk alleles are more enriched among candidate pathogenic TCRs than control TCRs (P\&nbsp;= 2.4 {\texttimes} 10-6\&nbsp;for gliadin specific TCRs). Together, these results provide novel genetic evidence supporting the central hypothesis.},
	url = {https://www.medrxiv.org/content/10.1101/2020.11.08.20227983v1},
	author = {Ishigaki, K and Lagattuta, K and Luo,Y. and James, E and Buckner, J and Raychaudhuri, S}
}
@article {1541731,
	title = {Disruptive innovation in rheumatology: new networks of global public{\textendash}private partnerships are needed to take advantage of scientific progress},
	journal = {Annals of the Rheumatic Diseases},
	volume = {79},
	number = {5},
	year = {2020},
	pages = {553-555},
	doi = {10.1136/annrheumdis-2019-216846},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/32139419/},
	author = {Huizinga, Tom W J and Holers, V Michael and Anolik, Jennifer and Brenner, Michael B and Buckley, Christopher Dominic and Bykerk, Vivian and Connolly, Sean E and Deane, Kevin D and Guo, Jianping and Hodge, Martin and Hoffmann, Steve and Nestle, Frank and Pitzalis, Costantino and Raychaudhuri, Soumya and Yamamoto, Kazuhiko and Li, Zhanguo and Klareskog, Lars}
}
@article {1541730,
	title = {Advances in genetics toward identifying pathogenic cell states of rheumatoid arthritis},
	journal = {Immunological Reviews},
	volume = {294},
	number = {1},
	year = {2020},
	pages = {188-204},
	abstract = {Rheumatoid arthritis (RA) risk has a large genetic component (~60\%) that is still not fully understood. This has hampered the design of effective treatments that could promise lifelong remission. RA is a polygenic disease with 106 known genome-wide significant associated loci and thousands of small effect causal variants. Our current understanding of RA risk has suggested cell-type-specific contexts for causal variants, implicating CD4 + effector memory T cells, as well as monocytes, B cells and stromal fibroblasts. While these cellular states and categories are still mechanistically broad, future studies may identify causal cell subpopulations. These efforts are propelled by advances in single cell profiling. Identification of causal cell subpopulations may accelerate therapeutic intervention to achieve lifelong remission.},
	url = {https://pubmed.ncbi.nlm.nih.gov/31782165/},
	author = {Amariuta, T and Luo,Y. and Knevel, R and Okada, Y and Raychaudhuri, S}
}
@article {1541726,
	title = {Synoviocyte-targeted therapy synergizes with TNF inhibition in arthritis reversal},
	journal = {Science Advances},
	volume = {6},
	number = {26},
	year = {2020},
	pages = {eaba4353},
	abstract = {Fibroblast-like synoviocytes (FLS) are joint-lining cells that promote rheumatoid arthritis (RA) pathology. Current disease-modifying antirheumatic agents (DMARDs) operate through systemic immunosuppression. FLS-targeted approaches could potentially be combined with DMARDs to improve control of RA without increasing immunosuppression. Here, we assessed the potential of immunoglobulin-like domains 1 and 2 (Ig1\&amp;2), a decoy protein that activates the receptor tyrosine phosphatase sigma (PTPRS) on FLS, for RA therapy. We report that PTPRS expression is enriched in synovial lining RA FLS and that Ig1\&amp;2 reduces migration of RA but not osteoarthritis FLS. Administration of an Fc-fusion Ig1\&amp;2 attenuated arthritis in mice without affecting innate or adaptive immunity. Furthermore, PTPRS was down-regulated in FLS by tumor necrosis factor (TNF) via a phosphatidylinositol 3-kinase{\textendash}mediated pathway, and TNF inhibition enhanced PTPRS expression in arthritic joints. Combination of ineffective doses of TNF inhibitor and Fc-Ig1\&amp;2 reversed arthritis in mice, providing an example of synergy between FLS-targeted and immunosuppressive DMARD therapies.},
	doi = {10.1126/sciadv.aba4353},
	url = {https://advances.sciencemag.org/content/advances/6/26/eaba4353.full.pdf},
	author = {Svensson, Mattias N. D. and Zoccheddu, Martina and Yang, Shen and Nygaard, Gyrid and Secchi, Christian and Doody, Karen M. and Slowikowski, Kamil and Mizoguchi, Fumitaka and Humby, Frances and Hands, Rebecca and Santelli, Eugenio and Sacchetti, Cristiano and Wakabayashi, Kuninobu and Wu, Dennis J. and Barback, Christopher and Ai, Rizi and Wang, Wei and Sims, Gary P. and Mydel, Piotr and Kasama, Tsuyoshi and Boyle, David L. and Galimi, Francesco and Vera, David and Tremblay, Michel L. and Raychaudhuri, Soumya and Brenner, Michael B. and Firestein, Gary S. and Pitzalis, Costantino and Ekwall, Anna-Karin H. and Stanford, Stephanie M. and Bottini, Nunzio}
}
@article {1541724,
	title = {Genome-wide Study Identifies Association between HLA-B * 55:01 and Self-Reported Penicillin Allergy},
	journal = {American Journal of Human Genetics},
	volume = {107},
	number = {4},
	year = {2020},
	pages = {612-621},
	abstract = {Hypersensitivity reactions to drugs are often unpredictable and can be life threatening, underscoring a need for understanding their underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. We extracted data from the electronic health records of more than 600,000 participants from the UK, Estonian, and Vanderbilt University Medical Center{\textquoteright}s BioVU biobanks to study the role of genetic variation in the occurrence of self-reported penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from these cohorts to further fine map the human leukocyte antigen (HLA) association and replicated our results in 23andMe{\textquoteright}s research cohort involving a total of 1.12 million individuals. Genome-wide meta-analysis of penicillin allergy revealed two loci, including one located in the HLA region on chromosome 6. This signal was further fine-mapped to the HLA-B*55:01 allele (OR 1.41 95\% CI 1.33-1.49, p value 2.04 {\texttimes} 10-31) and confirmed by independent replication in 23andMe{\textquoteright}s research cohort (OR 1.30 95\% CI 1.25-1.34, p value 1.00 {\texttimes} 10-47). The lead SNP was also associated with lower lymphocyte counts and in silico follow-up suggests a potential effect on T-lymphocytes at HLA-B*55:01. We also observed a significant hit in PTPN22 and the GWAS results correlated with the genetics of rheumatoid arthritis and psoriasis. We present robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.},
	url = {https://pubmed.ncbi.nlm.nih.gov/32888428/},
	author = {Krebs, K and Bovjin, J and Zheng, N and Lepamets, M and Censin, J C and Jurgenson, T and Sarg, D and Abner, E and Laisk, T and Luo,Y. and Skotte, L and Geller, F and Feenstra, B and Wang, W. and Auton, A and 23andMe Research Team and Raychaudhuri, S and Esko, T and Metspalu, A and Laur, S and Roden, D M and Wei, W-Q and Holmes, M V and Lindgren, C M and Phillips, E J and Magi, R and Milani, L and Fadista, J}
}
@article {1541722,
	title = {How COVID-19 is changing rheumatology clinical practice},
	journal = {Nature Reviews. Rheumatology},
	year = {2020},
	abstract = {The emergence of COVID-19 in early 2020 led to unprecedented changes to rheumatology clinical practice worldwide, including the closure of research laboratories, the restructuring of hospitals and the rapid transition to virtual care. As governments sought to slow and contain the spread of the disease, rheumatologists were presented with the difficult task of managing risks, to their patients as well as to themselves, while learning and implementing new systems for remote health care. Consequently, the COVID-19 pandemic led to a transformation in health infrastructures and telemedicine that could become powerful tools for rheumatologists, despite having some limitations. In this Viewpoint, five experts from different regions discuss their experiences of the pandemic, including the most challenging aspects of this unexpected transition, the advantages and limitations of virtual visits, and potential opportunities going forward.},
	url = {https://pubmed.ncbi.nlm.nih.gov/33139947/},
	author = {Bonfa, Eloisa and Gossec, Laure and Isenberg, David A and Li, Zhanguo and Raychaudhuri, Soumya}
}
@article {1541692,
	title = {HATK: HLA analysis toolkit},
	journal = {Bioinformatics},
	year = {2020},
	abstract = {Fine-mapping human leukocyte antigen (HLA) genes involved in disease susceptibility to individual alleles or amino acid residues has been challenging. Using information regarding HLA alleles obtained from HLA typing, HLA imputation or HLA inference, our software expands the alleles to amino acid sequences using the most recent IMGT/HLA database and prepares a dataset suitable for fine-mapping analysis. Our software also provides useful functionalities, such as various association tests, visualization tools and nomenclature conversion.https://github.com/WansonChoi/HATK.},
	isbn = {1367-4803},
	doi = {10.1093/bioinformatics/btaa684},
	url = {https://doi.org/10.1093/bioinformatics/btaa684},
	author = {Choi, Wanson and Luo, Yang and Raychaudhuri, Soumya and Han, Buhm}
}
@article {doi:10.1056/NEJMoa2004114,
	title = {RNA Identification of PRIME Cells Predicting Rheumatoid Arthritis Flares},
	journal = {New England Journal of Medicine},
	volume = {383},
	number = {3},
	year = {2020},
	pages = {218-228},
	abstract = {
	
		Background:  Rheumatoid arthritis, like many inflammatory diseases, is characterized by episodes of quiescence and exacerbation (flares). The molecular events leading to flares are unknown.
	

	
		Methods:  We established a clinical and technical protocol for repeated home collection of blood in patients with rheumatoid arthritis to allow for longitudinal RNA sequencing (RNA-seq). Specimens were obtained from 364 time points during eight flares over a period of 4 years in our index patient, as well as from 235 time points during flares in three additional patients. We identified transcripts that were differentially expressed before flares and compared these with data from synovial single-cell RNA-seq. Flow cytometry and sorted-blood-cell RNA-seq in additional patients were used to validate the findings.
	

	
		Results:  Consistent changes were observed in blood transcriptional profiles 1 to 2 weeks before a rheumatoid arthritis flare. B-cell activation was followed by expansion of circulating CD45-CD31-PDPN+ preinflammatory mesenchymal, or PRIME, cells in the blood from patients with rheumatoid arthritis; these cells shared features of inflammatory synovial fibroblasts. Levels of circulating PRIME cells decreased during flares in all 4 patients, and flow cytometry and sorted-cell RNA-seq confirmed the presence of PRIME cells in 19 additional patients with rheumatoid arthritis.
	

	
		Conclusions:  Longitudinal genomic analysis of rheumatoid arthritis flares revealed PRIME cells in the blood during the period before a flare and suggested a model in which these cells become activated by B cells in the weeks before a flare and subsequently migrate out of the blood into the synovium. (Funded by the National Institutes of Health and others.).
	

},
	doi = {10.1056/NEJMoa2004114},
	url = {https://doi.org/10.1056/NEJMoa2004114},
	author = {Orange, Dana E. and Yao, Vicky and Sawicka, Kirsty and Fak, John and Frank, Mayu O. and Parveen, Salina and Blachere, Nathalie E. and Hale, Caryn and Zhang, Fan and Raychaudhuri, Soumya and Troyanskaya, Olga G. and Darnell, Robert B.}
}
@article {Kneveleaay1548,
	title = {Using genetics to prioritize diagnoses for rheumatology outpatients with inflammatory arthritis},
	journal = {Science Translational Medicine},
	volume = {12},
	number = {545},
	year = {2020},
	publisher = {American Association for the Advancement of Science},
	abstract = {Multiple slowly progressing diseases initially present with inflammatory arthritis, and it can be difficult to clinically differentiate these conditions. Knevel et al. show that genetic data could be used to triage inflammatory arthritis{\textendash}causing diagnoses at a patient{\textquoteright}s first visit, improving the likelihood of a correct initial diagnosis and potentially expediting appropriate treatment. Their genetic diagnostic tool, here optimized for rheumatic disease diagnosis, could, in principle, be calibrated for other phenotypically similar diseases with different underlying genetics.It is challenging to quickly diagnose slowly progressing diseases. To prioritize multiple related diagnoses, we developed G-PROB (Genetic Probability tool) to calculate the probability of different diseases for a patient using genetic risk scores. We tested G-PROB for inflammatory arthritis{\textendash}causing diseases (rheumatoid arthritis, systemic lupus erythematosus, spondyloarthropathy, psoriatic arthritis, and gout). After validating on simulated data, we tested G-PROB in three cohorts: 1211 patients identified by International Classification of Diseases (ICD) codes within the eMERGE database, 245 patients identified through ICD codes and medical record review within the Partners Biobank, and 243 patients first presenting with unexplained inflammatory arthritis and with final diagnoses by record review within the Partners Biobank. Calibration of G-probabilities with disease status was high, with regression coefficients from 0.90 to 1.08 (1.00 is ideal). G-probabilities discriminated true diagnoses across the three cohorts with pooled areas under the curve (95\% CI) of 0.69 (0.67 to 0.71), 0.81 (0.76 to 0.84), and 0.84 (0.81 to 0.86), respectively. For all patients, at least one disease could be ruled out, and in 45\% of patients, a likely diagnosis was identified with a 64\% positive predictive value. In 35\% of cases, the clinician{\textquoteright}s initial diagnosis was incorrect. Initial clinical diagnosis explained 39\% of the variance in final disease, which improved to 51\% (P \&lt; 0.0001) after adding G-probabilities. Converting genotype information before a clinical visit into an interpretable probability value for five different inflammatory arthritides could potentially be used to improve the diagnostic efficiency of rheumatic diseases in clinical practice.},
	issn = {1946-6234},
	doi = {10.1126/scitranslmed.aay1548},
	url = {http://stm.sciencemag.org/cgi/content/full/12/545/eaay1548?ijkey=rz364g4f4uiag\&keytype=ref\&siteid=scitransmed},
	author = {Knevel, Rachel and le Cessie, Saskia and Terao, Chikashi C. and Slowikowski, Kamil and Cui, Jing and Huizinga, Tom W. J. and Costenbader, Karen H. and Katherine P. Liao and Karlson, Elizabeth W. and Raychaudhuri, Soumya}
}
@article {Ishigaki795948,
	title = {Large-scale genome-wide association study in a Japanese population identifies novel susceptibility loci across different diseases},
	journal = {Nature Genetics},
	volume = {52},
	number = {7},
	year = {2020},
	pages = {669-679},
	publisher = {Cold Spring Harbor Laboratory},
	abstract = {The overwhelming majority of participants in current genetic studies are of European ancestry1{\textendash}3, limiting our genetic understanding of complex disease in non-European populations. To address this, we aimed to elucidate polygenic disease biology in the East Asian population by conducting a genome-wide association study (GWAS) with 212,453 Japanese individuals across 42 diseases. We detected 383 independent signals in 331 loci for 30 diseases, among which 45 loci were novel (P \&lt; 5 {\texttimes} 10-8). Compared with known variants, novel variants have lower frequency in European populations but comparable frequency in East Asian populations, suggesting the advantage of this study in discovering these novel variants. Three novel signals were in linkage disequilibrium (r2 \&gt; 0.6) with missense variants which are monomorphic in European populations (1000 Genomes Project) including rs11235604(p.R220W of ATG16L2, a autophagy-related gene) associated with coronary artery disease. We further investigated enrichment of heritability within 2,868 annotations of genome-wide transcription factor occupancy, andidentified 378 significant enrichments across nine diseases (FDR \&lt; 0.05) (e.g. NF-κB for immune-related diseases). This large-scale GWAS in a Japanese population provides insights into the etiology of common complex diseases and highlights the importance of performing GWAS in non-European populations.},
	doi = {10.1101/795948},
	url = {https://pubmed.ncbi.nlm.nih.gov/32514122/},
	author = {Ishigaki, Kazuyoshi and Akiyama, Masato and Kanai, Masahiro and Takahashi, Atsushi and Kawakami, Eiryo and Sugishita, Hiroki and Sakaue, Saori and Matoba, Nana and Low, Siew-Kee and Okada, Yukinori and Terao, Chikashi and Amariuta, Tiffany and Gazal, Steven and Kochi, Yuta and Horikoshi, Momoko and Suzuki, Ken and Ito, Kaoru and Momozawa, Yukihide and Hirata, Makoto and Matsuda, Koichi and Ikeda, Masashi and Iwata, Nakao and Ikegawa, Shiro and Kou, Ikuyo and Tanaka, Toshihiro and Nakagawa, Hidewaki and Suzuki, Akari and Hirota, Tomomitsu and Tamari, Mayumi and Chayama, Kazuaki and Miki, Daiki and Mori, Masaki and Nagayama, Satoshi and Daigo, Yataro and Miki, Yoshio and Katagiri, Toyomasa and Ogawa, Osamu and Obara, Wataru and Ito, Hidemi and Yoshida, Teruhiko and Imoto, Issei and Takahashi, Takashi and Tanikawa, Chizu and Suzuki, Takao and Sinozaki, Nobuaki and Minami, Shiro and Yamaguchi, Hiroki and Asai, Satoshi and Takahashi, Yasuo and Yamaji, Ken and Takahashi, Kazuhisa and Fujioka, Tomoaki and Takata, Ryo and Yanai, Hideki and Masumoto, Akihide and Koretsune, Yukihiro and Kutsumi, Hiromu and Higashiyama, Masahiko and Murayama, Shigeo and Minegishi, Naoko and Suzuki, Kichiya and Tanno, Kozo and Shimizu, Atsushi and Yamaji, Taiki and Iwasaki, Motoki and Sawada, Norie and Uemura, Hirokazu and Tanaka, Keitaro and Naito, Mariko and Sasaki, Makoto and Wakai, Kenji and Tsugane, Shoichiro and Yamamoto, Masayuki and Yamamoto, Kazuhiko and Murakami, Yoshinori and Nakamura, Yusuke and Raychaudhuri, Soumya* and Inazawa, Johji* and Yamauchi, Toshimasa* and Kadowaki, Takashi* and Kubo, Michiaki* and Kamatani, Yoichiro*}
}
@article {1483806,
	title = {CUX1 and IκBζ (NFKBIZ) mediate the synergistic inflammatory response to TNF and IL-17A in stromal fibroblasts.},
	journal = {Proc Natl Acad Sci. },
	volume = {117},
	number = {10},
	year = {2020},
	pages = {5532-5541},
	abstract = {The role of stromal fibroblasts in chronic inflammation is unfolding. In rheumatoid arthritis, leukocyte-derived cytokines TNF and IL-17A work together, activating fibroblasts to become a dominant source of the hallmark cytokine IL-6. However, IL-17A alone has minimal effect on fibroblasts. To identify key mediators of the synergistic response to TNF and IL-17A in human synovial fibroblasts, we performed time series, dose-response, and gene-silencing transcriptomics experiments. Here we show that in combination with TNF, IL-17A selectively induces a specific set of genes mediated by factors including cut-like homeobox 1 (CUX1) and IκBζ (NFKBIZ). In the promoters of CXCL1, CXCL2, and CXCL3, we found a putative CUX1-NF-κB binding motif not found elsewhere in the genome. CUX1 and NF-κB p65 mediate transcription of these genes independent of LIFR, STAT3, STAT4, and ELF3. Transcription of NFKBIZ, encoding the atypical IκB factor IκBζ, is IL-17A dose-dependent, and IκBζ only mediates the transcriptional response to TNF and IL-17A, but not to TNF alone. In fibroblasts, IL-17A response depends on CUX1 and IκBζ to engage the NF-κB complex to produce chemoattractants for neutrophil and monocyte recruitment.},
	url = {https://www.pnas.org/content/117/10/5532.short},
	author = {Slowikowski, K$\#$ and HN Nguyen$\#$ and EH Noss and DP Simmons and F Mizoguchi and Watts, GFM and Gurish, M F and Brenner,M.B.* and Raychaudhuri, S*}
}
@article {1483798,
	title = {Fast, sensitive and accurate integration of single-cell data with Harmony},
	journal = {Nat Methods},
	volume = {16},
	number = {12},
	year = {2019},
	month = {2019 12},
	pages = {1289-1296},
	abstract = {The emerging diversity of single-cell RNA-seq datasets allows for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. However, it is challenging to analyze them together, particularly when datasets are assayed with different technologies, because biological and technical differences are interspersed. We present Harmony (https://github.com/immunogenomics/harmony), an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions. Harmony simultaneously accounts for multiple experimental and biological factors. In six analyses, we demonstrate the superior performance of Harmony to previously published algorithms while requiring fewer computational resources. Harmony enables the integration of ~10 cells on a personal computer. We apply Harmony to peripheral blood mononuclear cells from datasets with large experimental differences, five studies of pancreatic islet cells, mouse embryogenesis datasets and the integration of scRNA-seq with spatial transcriptomics data.},
	issn = {1548-7105},
	doi = {10.1038/s41592-019-0619-0},
	author = {Korsunsky, Ilya and Millard, Nghia and Fan, Jean and Slowikowski, Kamil and Zhang, Fan and Wei, Kevin and Baglaenko, Yuriy and Brenner, Michael and Po-Ru Loh and Raychaudhuri, Soumya}
}
@article {1456129,
	title = {Defining Inflammatory Cell States in Rheumatoid Arthritis Joint Synovial Tissues by Integrating Single-cell Transcriptomics and Mass Cytometry},
	journal = {Nature Immunology},
	volume = {20},
	year = {2019},
	pages = {928-942},
	abstract = {
	To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing (RNA-seq) and flow cytometry to T cells, B cells, monocytes, and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis (OA). Utilizing an integrated strategy based on canonical correlation analysis of 5,265 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics revealed cell states expanded in RA synovia: THY1(CD90)+HLA-DRAhi\&nbsp;sublining fibroblasts, IL1B+\&nbsp;pro-inflammatory monocytes, ITGAX+TBX21+autoimmune-associated B cells and PDCD1+\&nbsp;peripheral helper T (TPH) cells and follicular helper T (TFH) cells. We defined distinct subsets of CD8+\&nbsp;T cells characterized by GZMK+, GZMB+, and GNLY+\&nbsp;phenotypes. We mapped inflammatory mediators to their source cell populations; for example, we attributed IL6 expression to THY1+HLA-DRAhi\&nbsp;fibroblasts and IL1B production to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis.

},
	author = {Zhang, F.$\#$ and Wei, K$\#$ and Slowikowski, K$\#$ and Fonseka, CY$\#$ and Rao, DA$\#$ and Kelly, S and Goodman, SM and Tabechian, D and Hughes, LB and Salomon-Escoto, K and Watts, GFM and Jonsson, AH and Rangel-Moreno, J and Meednu, N and Rozo, C and Apruzzese, W and Eisenhauere, TM and Lieb, DJ and Boyle, DL and Mandelin, AM and Accelerating Medicines Partnership Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Consortium and Boyce, BF and DiCarlo, E and Gravallese, EM and Gregersen, P K and Moreland, L and Firestein, GS and Hacohen, N and Nusbaum, C. and Lederer, JA and Perlman, H and Pitzalis, C and Filer, A and Holers, VM and Bykerk, VP and Donlin, LT* and Anolik, JH* and Brenner,M.B.* and Raychaudhuri, S*}
}
@article {1456121,
	title = {IMPACT: Genomic annotation of cell-state-specific regulatory elements inferred from the epigenome of bound transcription factors},
	journal = {The American Journal of Human Genetics},
	volume = {104},
	number = {5},
	year = {2019},
	pages = {879-895},
	abstract = {Despite significant progress in annotating the genome with experimental methods, much of the regulatory noncoding genome remains poorly defined. Here we assert that regulatory elements may be characterized by leveraging local epigenomic signatures at sites where specific transcription factors (TFs) are bound. To link these two identifying features, we introduce IMPACT, a genome annotation strategy which identifies regulatory elements defined by cell-state-specific TF binding profiles, learned from 515 chromatin and sequence annotations. We validate IMPACT using multiple compelling applications. First, IMPACT predicts TF motif binding with high accuracy (average AUC 0.92, s.e. 0.03; across 8 TFs), a significant improvement (all p\&lt;6.9e-15) over intersecting motifs with open chromatin (average AUC 0.66, s.e. 0.11). Second, an IMPACT annotation trained on RNA polymerase II is more enriched for peripheral blood cis-eQTL variation (N=3,754) than sequence based annotations, such as promoters and regions around the TSS, (permutation p\&lt;1e-3, 25\% average increase in enrichment). Third, integration with rheumatoid arthritis (RA) summary statistics from European (N=38,242) and East Asian (N=22,515) populations revealed that the top 5\% of CD4+ Treg IMPACT regulatory elements capture 85.7\% (s.e. 19.4\%) of RA h2 (p\&lt;1.6e-5) and that the top 9.8\% of Treg IMPACT regulatory elements, consisting of all SNPs with a non-zero annotation value, capture 97.3\% (s.e. 18.2\%) of RA h2 (p\&lt;7.6e-7), the most comprehensive explanation for RA h2 to date. In comparison, the average RA h2 captured by compared CD4+ T histone marks is 42.3\% and by CD4+ T specifically expressed gene sets is 36.4\%. Finally, integration with RA fine-mapping data (N=27,345) revealed a significant enrichment (2.87, p\&lt;8.6e-3) of putatively causal variants across 20 RA associated loci in the top 1\% of CD4+ Treg IMPACT regulatory regions. Overall, we find that IMPACT generalizes well to other cell types in identifying complex trait associated regulatory elements.},
	author = {Amariuta, Tiffany and Luo, Yang and Gazal, Steven and Davenport, Emma Elisabeth and van de Geijn, Bryce and Ishigaki, Kazuyoshi and Westra, Harm-Jan and Teslovich, Nikola and Okada, Yukinori and Yamamoto, Kazuhiko and RACI Consortium and GARNET consortium and Price, Alkes* and Raychaudhuri, Soumya*}
}
@article {1420446,
	title = {Lymphocyte innateness is defined by underlying transcriptional states reflecting a balance between proliferation and effector functions},
	journal = {Nature Communications},
	volume = {10},
	number = {1},
	year = {2019},
	pages = {687},
	author = {Gutierrez-Arcelus, Maria and Teslovich, Nikola C. and Mola, Alex and Polidoro, R. B. and Nathan, A. and Kim, H. and Hannes, Susan K. and Slowikowski, Kamil and Watts, Gerald and Korsunsky, Ilya and Brenner, Michael B. and Raychaudhuri, Soumya* and Brennan, Patrick J.*}
}
@article {1483804,
	title = {Association of response to TNF inhibitors in rheumatoid arthritis with quantitative trait loci for and CD39},
	journal = {Ann Rheum Dis},
	volume = {78},
	number = {8},
	year = {2019},
	month = {2019 Aug},
	pages = {1055-1061},
	abstract = {OBJECTIVES: We sought to investigate whether genetic effects on response to TNF inhibitors (TNFi) in rheumatoid arthritis (RA) could be localised by considering known genetic susceptibility loci for relevant traits and to evaluate the usefulness of these genetic loci for stratifying drug response. METHODS: We studied the relation of TNFi response, quantified by change in swollen joint counts ( Δ SJC) and erythrocyte sedimentation rate ( Δ ESR) with locus-specific scores constructed from genome-wide assocation study summary statistics in 2938 genotyped individuals: 37 scores for RA; scores for 19 immune cell traits; scores for expression or methylation of 93 genes with previously reported associations between transcript level and drug response. Multivariate associations were evaluated in penalised regression models by cross-validation. RESULTS: We detected a statistically significant association between Δ SJC and the RA score at the locus (p=0.0004) and an inverse association between Δ SJC and the score for expression of CD39 on CD4 T cells (p=0.00005). A previously reported association between CD39 expression on regulatory T cells and response to methotrexate was in the opposite direction. In stratified analysis by concomitant methotrexate treatment, the inverse association was stronger in the combination therapy group and dissipated in the TNFi monotherapy group. Overall, ability to predict TNFi response from genotypic scores was limited, with models explaining less than 1\% of phenotypic variance. CONCLUSIONS: The association with the CD39 trait is difficult to interpret because patients with RA are often prescribed TNFi after failing to respond to methotrexate. The CD39 and pathways could be relevant for targeting drug therapy.},
	issn = {1468-2060},
	doi = {10.1136/annrheumdis-2018-214877},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/31036624},
	author = {Spiliopoulou, Athina and Colombo, Marco and Plant, Darren and Nair, Nisha and Cui, Jing and Coenen, Marieke Jh and Ikari, Katsunori and Yamanaka, Hisashi and Saevarsdottir, Saedis and Padyukov, Leonid and Bridges, S Louis and Kimberly, Robert P and Okada, Yukinori and van Riel, Piet L Cm and Wolbink, Gert Jan and van der Horst-Bruinsma, Irene E and de Vries, Niek and Tak, Paul P and Ohmura, Koichiro and Canh{\~a}o, Helena and Guchelaar, Henk-Jan and Huizinga, Tom W J and Criswell, Lindsey A and Raychaudhuri, Soumya and Weinblatt, Michael E and Wilson, Anthony G and Mariette, Xavier and Isaacs, John D and Morgan, Ann W and Pitzalis, Costantino and Barton, Anne and McKeigue, Paul}
}
@article {1483805,
	title = {Harmonizing Clinical Sequencing and Interpretation for the eMERGE III Network},
	journal = {Am J Hum Genet},
	volume = {105},
	number = {3},
	year = {2019},
	month = {2019 Sep 05},
	pages = {588-605},
	abstract = {The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled \&gt;25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2019.07.018},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/31447099},
	author = {eMERGE Consortium. Electronic address: agibbs@bcm.edu and eMERGE Consortium}
}
@article {1483797,
	title = {Advances in genetics toward identifying pathogenic cell states of rheumatoid arthritis},
	journal = {Immunol Rev},
	year = {2019},
	month = {2019 Nov 28},
	abstract = {Rheumatoid arthritis (RA) risk has a large genetic component (~60\%) that is still not fully understood. This has hampered the design of effective treatments that could promise lifelong remission. RA is a polygenic disease with 106 known genome-wide significant associated loci and thousands of small effect causal variants. Our current understanding of RA risk has suggested cell-type-specific contexts for causal variants, implicating CD4\&nbsp;+\&nbsp;effector memory T cells, as well as monocytes, B cells and stromal fibroblasts. While these cellular states and categories are still mechanistically broad, future studies may identify causal cell subpopulations. These efforts are propelled by advances in single cell profiling. Identification of causal cell subpopulations may accelerate therapeutic intervention to achieve lifelong remission.},
	issn = {1600-065X},
	doi = {10.1111/imr.12827},
	url = {https://www.google.com/url?sa=t\&rct=j\&q=\&esrc=s\&source=web\&cd=1\&ved=2ahUKEwjsiev3gLnoAhUzmHIEHQ-8BQYQFjAAegQIBxAB\&url=https\%3A\%2F\%2Fwww.ncbi.nlm.nih.gov\%2Fpubmed\%2F31782165\&usg=AOvVaw2kIPaJO6CWxozGWBvxLk3u},
	author = {Amariuta, Tiffany and Luo, Yang and Knevel, Rachel and Okada, Yukinori and Raychaudhuri, Soumya}
}
@article {1483802,
	title = {Cross-disorder analysis of schizophrenia and 19 immune-mediated diseases identifies shared genetic risk},
	journal = {Hum Mol Genet},
	volume = {28},
	number = {20},
	year = {2019},
	month = {2019 10 15},
	pages = {3498-3513},
	abstract = {Many immune diseases occur at different rates among people with schizophrenia compared to the general population. Here, we evaluated whether this phenomenon might be explained by shared genetic risk factors. We used data from large genome-wide association studies to compare the genetic architecture of schizophrenia to 19 immune diseases. First, we evaluated the association with schizophrenia of 581 variants previously reported to be associated with immune diseases at genome-wide significance. We identified five variants with potentially pleiotropic effects. While colocalization analyses were inconclusive, functional characterization of these variants provided the strongest evidence for a model in which genetic variation at rs1734907 modulates risk of schizophrenia and Crohn{\textquoteright}s disease via altered methylation and expression of EPHB4-a gene whose protein product guides the migration of neuronal axons in the brain and the migration of lymphocytes towards infected cells in the immune system. Next, we investigated genome-wide sharing of common variants between schizophrenia and immune diseases using cross-trait LD score regression. Of the 11 immune diseases with available genome-wide summary statistics, we observed genetic correlation between six immune diseases and schizophrenia: inflammatory bowel disease (rg\&nbsp;= 0.12 {\textpm} 0.03, P = 2.49 {\texttimes} 10-4), Crohn{\textquoteright}s disease (rg\&nbsp;= 0.097 {\textpm} 0.06, P = 3.27 {\texttimes} 10-3), ulcerative colitis (rg\&nbsp;= 0.11 {\textpm} 0.04, P = 4.05 {\texttimes} 10-3), primary biliary cirrhosis (rg\&nbsp;= 0.13 {\textpm} 0.05, P = 3.98 {\texttimes} 10-3), psoriasis (rg\&nbsp;= 0.18 {\textpm} 0.07, P = 7.78 {\texttimes} 10-3) and systemic lupus erythematosus (rg\&nbsp;= 0.13 {\textpm} 0.05, P = 3.76 {\texttimes} 10-3). With the exception of ulcerative colitis, the degree and direction of these genetic correlations were consistent with the expected phenotypic correlation based on epidemiological data. Our findings suggest shared genetic risk factors contribute to the epidemiological association of certain immune diseases and schizophrenia.},
	issn = {1460-2083},
	doi = {10.1093/hmg/ddz145},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/31211845},
	author = {Pouget, Jennie G and Schizophrenia Working Group of the Psychiatric Genomics Consortium and Han, Buhm and Wu, Yang and Mignot, Emmanuel and Ollila, Hanna M and Barker, Jonathan and Spain, Sarah and Dand, Nick and Trembath, Richard and Martin, Javier and Mayes, Maureen D and Bossini-Castillo, Lara and L{\'o}pez-Isac, Elena and Jin, Ying and Santorico, Stephanie A and Spritz, Richard A and Hakonarson, Hakon and Polychronakos, Constantin and Raychaudhuri, Soumya* and Knight, Jo*}
}
@article {1483800,
	title = {Distinct HLA Associations with Rheumatoid Arthritis Subsets Defined by Serological Subphenotype},
	journal = {Am J Hum Genet},
	volume = {105},
	number = {3},
	year = {2019},
	month = {2019 Sep 05},
	pages = {616-624},
	abstract = {Rheumatoid arthritis (RA) is the most common immune-mediated arthritis. Anti-citrullinated peptide antibodies (ACPA) are highly specific to RA and assayed with the commercial CCP2 assay. Genetic drivers of RA within the MHC are different for CCP2-positive and -negative subsets of RA, particularly at HLA-DRB1. However, aspartic acid at amino acid position 9 in HLA-B (B) increases risk to both RA subsets. Here we explore how individual serologies associated with RA drive associations within the MHC. To define MHC differences for specific ACPA serologies, we quantified a total of 19 separate ACPAs in RA-affected case subjects from four cohorts (n\&nbsp;=\&nbsp;6,805). We found a cluster of tightly co-occurring antibodies (canonical serologies, containing CCP2), along with several independently expressed antibodies (non-canonical serologies). After imputing HLA variants into 6,805 case subjects and 13,467 control subjects, we tested associations between the HLA region and RA subgroups based on the presence of canonical and/or non-canonical serologies. We examined CCP2(+) and CCP2(-) RA-affected case subjects separately. In CCP2(-) RA, we observed that the association between CCP2(-) RA and B was derived from individuals who were positive for non-canonical serologies (omnibus_p = 9.2\&nbsp;{\texttimes} 10). Similarly, we observed in CCP2(+) RA that associations between subsets of CCP2(+) RA and B were negatively correlated with the number of positive canonical serologies (p = 0.0096). These findings suggest unique genetic characteristics underlying fine-specific ACPAs, suggesting that RA may be further subdivided beyond simply seropositive and seronegative.},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2019.08.002},
	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6731376/},
	author = {Terao, Chikashi$\#$ and Brynedal, Boel$\#$ and Chen, Zuomei and Jiang, Xia and Westerlind, Helga and Hansson, Monika and Jakobsson, Per-Johan and Lundberg, Karin and Skriner, Karl and Serre, Guy and R{\"o}nnelid, Johan and Mathsson-Alm, Linda and Brink, Mikael and Dahlqvist, Solbritt Rantap{\"a}{\"a} and Padyukov, Leonid and Gregersen, Peter K and Barton, Anne and Alfredsson, Lars and Klareskog, Lars* and Raychaudhuri, Soumya*}
}
@article {1483803,
	title = {Genes with High Network Connectivity Are Enriched for Disease Heritability},
	journal = {Am J Hum Genet},
	volume = {105},
	number = {6},
	year = {2019},
	month = {2019 Dec 05},
	pages = {1302},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2019.11.009},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/31051114},
	author = {Kim, Samuel S and Dai, Chengzhen and Hormozdiari, Farhad and van de Geijn, Bryce and Gazal, Steven and Park, Yongjin and O{\textquoteright}Connor, Luke and Amariuta, Tiffany and Po-Ru Loh and Finucane, Hilary and Raychaudhuri, Soumya and Price, Alkes L}
}
@article {1483801,
	title = {Multimodal single-cell approaches shed light on T cell heterogeneity},
	journal = {Curr Opin Immunol},
	volume = {61},
	year = {2019},
	month = {2019 Dec},
	pages = {17-25},
	abstract = {Single-cell methods have revolutionized the study of T cell biology by enabling the identification and characterization of individual cells. This has led to a deeper understanding of T cell heterogeneity by generating functionally relevant measurements - like gene expression, surface markers, chromatin accessibility, T cell receptor sequences - in individual cells. While these methods are independently valuable, they can be augmented when applied jointly, either on separate cells from the same sample or on the same cells. Multimodal approaches are already being deployed to characterize T cells in diverse disease contexts and demonstrate the value of having multiple insights into a cell{\textquoteright}s function. But, these data sets pose new statistical challenges for integration and joint analysis.},
	issn = {1879-0372},
	doi = {10.1016/j.coi.2019.07.002},
	url = {https://www.sciencedirect.com/science/article/abs/pii/S0952791519300469},
	author = {Nathan, Aparna and Baglaenko, Yuriy and Fonseka, Chamith Y and Beynor, Jessica I and Raychaudhuri, Soumya}
}
@article {1456164,
	title = {Early progression to active tuberculosis is a highly heritable trait driven by 3q23 in Peruvians},
	journal = {Nature Communications},
	volume = {10},
	number = {3765},
	year = {2019},
	abstract = {Of the 1.8 billion people worldwide infected with\&nbsp;Mycobacterium tuberculosis, 5{\textendash}15\% will develop active tuberculosis (TB). Approximately half will progress to active TB within the first 18 months after infection, presumably because they fail to mount an effective initial immune response. Here, in a genome-wide genetic study of early TB progression, we genotype 4002 active TB cases and their household contacts in Peru. We quantify genetic heritability (h2ghg2) of early TB progression to be 21.2\% (standard error 0.08). This suggests TB progression has a strong genetic basis, and is comparable to traits with well-established genetic bases. We identify a novel association between early TB progression and variants located in a putative enhancer region on chromosome 3q23 (rs73226617, OR = 1.18;\&nbsp;P = 3.93 {\texttimes} 10-8). With in silico and in vitro analyses we identify rs73226617 or rs148722713 as the likely functional variant and\&nbsp;ATP1B3\&nbsp;as a potential causal target gene with monocyte specific function.},
	url = {https://doi.org/10.1038/s41467-019-11664-1},
	author = {Luo,Y. and Suliman, S and Asgari, S and Amariuta, T and Baglaenko, Y and Martinez-Bonet, M and Ishigaki, K and Gutierrez-Arcelus, M and Calderon, R and Lecca, L and Leon, S and J Jimenez and Yataco, R and Contreras, C and Galea, J and Becerra, M and Nejentsev, S and Nigrovic, P and Moody, DB and Murray, M* and Raychaudhuri, S*}
}
@article {1456160,
	title = {The immune cell landscape in kidneys of patients with lupus nephritis},
	journal = {Nature Immunology},
	volume = {20},
	number = {7},
	year = {2019},
	pages = {902{\textendash}914},
	abstract = {Lupus nephritis is a potentially fatal autoimmune disease for which the current treatment is ineffective and often toxic. To develop mechanistic hypotheses of disease, we analyzed kidney samples from patients with lupus nephritis and from healthy control subjects using single-cell RNA sequencing. Our analysis revealed 21 subsets of leukocytes active in disease, including multiple populations of myeloid cells, T cells, natural killer cells and B cells that demonstrated both pro-inflammatory responses and inflammation-resolving responses. We found evidence of local activation of B cells correlated with an age-associated B-cell signature and evidence of progressive stages of monocyte differentiation within the kidney. A clear interferon response was observed in most cells. Two chemokine receptors, CXCR4 and CX3CR1, were broadly expressed, implying a potentially central role in cell trafficking. Gene expression of immune cells in urine and kidney was highly correlated, which would suggest that urine might serve as a surrogate for kidney biopsies.},
	url = {https://www.nature.com/articles/s41590-019-0398-x},
	author = {Arazi, A and Rao, DA and Berthier, CC and Davidson, A and Liu, Y. and Hoover, PJ and Chicoine, A and Eisenhaure, TM and Jonsson, AH and Li, S and Lieb, DJ and Zhang, F. and Slowikowski, K and Browne, EP and Norma, A and Sutherby, D and Steelman, S and Smilek, DE and Tosta, P and Apruzzese, W and Massarotti, E and Dall{\textquoteright}Era, M and Park, M and Kamen, DL and Furie, RA and Payan-Schober, F and Pendergraft, WF and McInnes, EA and Buyon, JP and Petri, MA and Putterman, C and Kalunian, KC and Woodle, ES and Lederer, JA and Hildeman, DA and Nusbaum, C. and Raychaudhuri, S and Kretzler, M and Anolik, JH and Brenner,M.B. and Wofsy, D and Hacohen, N and Diamond, B and Accelerating Medicines Partnership in SLE network}
}
@article {1456156,
	title = {Tubular cell and keratinocyte single-cell transcriptomics applied to lupus nephritis reveal type I IFN and fibrosis relevant pathways},
	journal = {Nature Immunology},
	volume = {20},
	number = {7},
	year = {2019},
	pages = {915-927},
	abstract = {The molecular and cellular processes that lead to renal damage and to the heterogeneity of lupus nephritis (LN) are not well understood. We applied single-cell RNA sequencing (scRNA-seq) to renal biopsies from patients with LN and evaluated skin biopsies as a potential source of diagnostic and prognostic markers of renal disease. Type I interferon (IFN)-response signatures in tubular cells and keratinocytes distinguished patients with LN from healthy control subjects. Moreover, a high IFN-response signature and fibrotic signature in tubular cells were each associated with failure to respond to treatment. Analysis of tubular cells from patients with proliferative, membranous and mixed LN indicated pathways relevant to inflammation and fibrosis, which offer insight into their histologic differences. In summary, we applied scRNA-seq to LN to deconstruct its heterogeneity and identify novel targets for personalized approaches to therapy.},
	url = {https://www.nature.com/articles/s41590-019-0386-1},
	author = {Der, E and Suryawanshi, H and Morozov, P and Kustagi, M and Goilav, B and Ranabathou, S and Izmirly, P and Clancy, R and Belmont, HM and Koenigsberg, M and Mockrzycki, M and Rominieki, H and Graham, JA and Rocca, JP and Bornkamp, N and Jordan, N and Schulte, E and M. Wu and Pullman, J and Slowikowski, K and Raychaudhuri, S and Guthridge, J and James, J and Buyon, J and Tuschl, T and Putterman, C and Accelerating Medicines Partnership Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Consortium}
}
@article {1456127,
	title = {Distinct fibroblast subsets drive inflammation and damage in arthritis},
	journal = {Nature},
	volume = {570},
	year = {2019},
	pages = {246-251},
	abstract = {The identification of lymphocyte subsets with non-overlapping effector functions has been pivotal to the development of targeted therapies in immune mediated inflammatory diseases (IMIDs). However it remains unclear whether fibroblast subclasses with non-overlapping functions also exist and are responsible for the wide variety of tissue driven processes observed in IMIDs such as inflammation and damage. Here we identify and describe the biology of distinct subsets of fibroblasts responsible for mediating either inflammation or tissue damage in arthritis. We show that deletion of FAPα+ synovial cells suppressed both inflammation and bone erosions in murine models of resolving and persistent arthritis. Single cell transcriptional analysis identified two distinct fibroblast subsets: FAPα+ THY1+ immune effector fibroblasts located in the synovial sub-lining, and FAPα+ THY1- destructive fibroblasts restricted to the synovial lining. When adoptively transferred into the joint, FAP α+ THY1- fibroblasts selectively mediate bone and cartilage damage with little effect on inflammation whereas transfer of FAP α+ THY1+ fibroblasts resulted in a more severe and persistent inflammatory arthritis, with minimal effect on bone and cartilage. Our findings describing anatomically discrete, functionally distinct fibroblast subsets with non-overlapping functions have important implications for cell based therapies aimed at modulating inflammation and tissue damage.},
	url = {https://doi.org/10.1101/374330},
	author = {Croft, AP and Campos, J and Jansen, K and Turner, JD and Marshall, J and Attar, M and Savary, L and Wehmeyer, C and Naylor, AJ and Kemble, S and Begum, J and Durholz, K and Perlman, H and Barone, F and McGettrick, HM and Fearon, DT and Wei, K and Raychaudhuri, S and Korsunsky, I and Brenner,M.B. and Coles, M and Sansom, SN and Filer, A and Buckley, CD}
}
@article {1456126,
	title = {Benchmarker: An Unbiased, Association-Data-Driven Strategy to Evaluate Gene Prioritization Algorithms},
	journal = {American Journal of Human Genetics},
	volume = {104},
	number = {6},
	year = {2019},
	pages = {1025-1039},
	abstract = {Genome-wide association studies\&nbsp;(GWASs) are valuable for understanding human biology, but associated loci typically contain multiple associated variants and genes. Thus, algorithms that prioritize likely causal genes and variants for a given phenotype can provide biological interpretations of association data. However, a critical, currently missing capability is to objectively compare performance of such algorithms. Typical comparisons rely on {\textquotedblleft}gold standard{\textquotedblright} genes harboring causal coding variants, but such gold standards may be biased and incomplete. To address this issue, we developed Benchmarker, an unbiased, data-driven benchmarking method that compares performance of similarity-based prioritization strategies to each other (and to random chance) by leave-one-chromosome-out cross-validation\&nbsp;with stratified\&nbsp;linkage disequilibrium\&nbsp;(LD) score regression. We first applied Benchmarker to 20 well-powered GWASs and compared gene prioritization based on strategies employing three different data sources, including annotated gene sets and gene expression; genes prioritized based on gene sets had higher per-SNP\&nbsp;heritability\&nbsp;than those prioritized based on gene expression. Additionally, in a direct comparison of three methods, DEPICT and MAGMA outperformed NetWAS. We also evaluated combinations of methods; our results indicated that combining data sources and algorithms can help prioritize higher-quality genes for follow-up. Benchmarker provides an unbiased approach to evaluate any similarity-based method that provides genome-wide prioritization of genes, variants, or gene sets and can determine the best such method for any particular GWAS. Our method addresses an important unmet need for rigorous tool assessment and can assist in mapping\&nbsp;genetic associations\&nbsp;to causal function.},
	url = {https://doi.org/10.1016/j.ajhg.2019.03.027},
	author = {Fine, Rebecca S and Pers, Tune H and Amariuta, Tiffany and Raychaudhuri, Soumya and Hirschhorn, Joel N}
}
@article {1456125,
	title = {Macrophages tailor their function according to the signals found in tissue microenvironments, assuming a wide spectrum of phenotypes. A detailed understanding of macrophage phenotypes in human tissues is limited. Using single-cell RNA sequencing, we defin},
	journal = {Science Translational Medicine},
	volume = {11},
	number = {491},
	year = {2019},
	pages = {eaau8587},
	abstract = {Macrophages tailor their function according to the signals found in tissue microenvironments, assuming a wide spectrum of phenotypes. A detailed understanding of macrophage phenotypes in human tissues is limited. Using single-cell RNA sequencing, we defined distinct macrophage subsets in the joints of patients with the autoimmune disease rheumatoid arthritis (RA), which affects ~1\% of the population. The subset we refer to as HBEGF $^{+}$ inflammatory macrophages is enriched in RA tissues and is shaped by resident fibroblasts and the cytokine tumor necrosis factor (TNF). These macrophages promoted fibroblast invasiveness in an epidermal growth factor receptor{\textendash}dependent manner, indicating that intercellular cross-talk in this inflamed setting reshapes both cell types and contributes to fibroblast-mediated joint destruction. In an ex vivo synovial tissue assay, most medications used to treat RA patients targeted HBEGF $^{+}$ inflammatory macrophages; however, in some cases, medication redirected them into a state that is not expected to resolve inflammation. These data highlight how advances in our understanding of chronically inflamed human tissues and the effects of medications therein can be achieved by studies on local macrophage phenotypes and intercellular interactions.},
	url = {https://stm.sciencemag.org/content/11/491/eaau8587},
	author = {Kuo, D and Ding, J and Cohn, IS and Zhang, F. and Wei, K and Rao, DA and Rozo, C and Sohki, UK and Shanaj, S and Oliver, DJ and Echeverria, AP and DiCarlo, EF and Brenner,M.B. and Bykerk, VP and Goodman, SM and Raychaudhuri, S and Ratsch, G and Ivashkiv, LB and Donlin, LT}
}
@article {1420443,
	title = {The eMERGE genotype set of 83,717 subjects imputed to ~40\&thinsp;million variants genome wide and association with the herpes zoster medical record phenotype},
	journal = {Genetic Epidemiology},
	volume = {43},
	number = {1},
	year = {2019},
	pages = {63-81},
	abstract = {The Electronic Medical Records and Genomics (eMERGE) network is a network of medical centers with electronic medical records linked to existing biorepository samples for genomic discovery and genomic medicine research. The network sought to unify the genetic results from 78 Illumina and Affymetrix genotype array batches from 12 contributing medical centers for joint association analysis of 83,717 human participants. In this report, we describe the imputation of eMERGE results and methods to create the unified imputed merged set of genome-wide variant genotype data. We imputed the data using the Michigan Imputation Server, which provides a missing single-nucleotide variant genotype imputation service using the minimac3 imputation algorithm with the Haplotype Reference Consortium genotype reference set. We describe the quality control and filtering steps used in the generation of this data set and suggest generalizable quality thresholds for imputation and phenotype association studies. To test the merged imputed genotype set, we replicated a previously reported chromosome 6 HLA-B herpes zoster (shingles) association and discovered a novel zoster-associated loci in an epigenetic binding site near the terminus of chromosome 3 (3p29).\&nbsp;},
	url = {https://www.google.com/url?sa=t\&rct=j\&q=\&esrc=s\&source=web\&cd=1\&cad=rja\&uact=8\&ved=2ahUKEwjinfvThrnoAhUQmHIEHSP1BLYQFjAAegQIBRAB\&url=https\%3A\%2F\%2Fonlinelibrary.wiley.com\%2Fdoi\%2Fabs\%2F10.1002\%2Fgepi.22167\&usg=AOvVaw3whXj2z0nT3xRTLdGr2lp6},
	author = {Stanaway, Ian B. and Hall, Taryn O. and Rosenthal, Elisabeth A. and Palmer, Melody and Naranbhai, Vivek and Knevel, Rachel and Namjou-Khales, Bahram and Carroll, Robert J. and Kiryluk, Krzysztof and Gordon, Adam S. and Linder, Jodell and Howell, Kayla Marie and Mapes, Brandy M. and Lin, Frederick T.J. and Joo, Yoonjung Yoonie and Hayes, M. Geoffrey and Gharavi, Ali G. and Sarah A. Pendergrass and Marylyn D. Ritchie and deAndrade, Mariza and Croteau-Chonka, Damien C. and Raychaudhuri, Soumya and Weiss, Scott T. and Lebo, Matt and Amr, Sami S. and Carrell, David and Larson, Eric B. and Chute, Christopher G. and Rasmussen-Torvik, Laura Jarmila and Roy-Puckelwartz, Megan J. and Sleiman, Patrick and Hakonarson, Hakon and Li, Ronglin and Karlson, Elizabeth W. and Peterson, Josh F. and Kullp, Iftikhar J. and Chisholm, Rex and Denny, Joshua Charles and Jarvik, Gail P. and The eMERGE Network and Crosslin, David R.}
}
@article {1420435,
	title = {Discovering in vivo cytokine eQTL interactions from a lupus clinical trial},
	journal = {Genome Biology},
	volume = {19},
	number = {1},
	year = {2018},
	pages = {168},
	abstract = {BACKGROUND:\&nbsp;Cytokines are critical to human disease and are attractive therapeutic targets given their widespread influence on gene regulation and transcription. Defining the downstream regulatory mechanisms influenced by cytokines is central to defining drug and disease mechanisms. One promising strategy is to use interactions between expression quantitative trait loci (eQTLs) and cytokine levels to define target genes and mechanisms.RESULTS:\&nbsp;In a clinical trial for anti-IL-6 in patients with systemic lupus erythematosus, we measure interferon (IFN) status, anti-IL-6 drug exposure, and whole blood genome-wide gene expression at three time points. We show that repeat transcriptomic measurements increases the number of cis eQTLs identified compared to using a single time point. We observe a statistically significant enrichment of in vivo eQTL interactions with IFN status and anti-IL-6 drug exposure and find many novel interactions that have not been previously described. Finally, we find transcription factor binding motifs interrupted by eQTL interaction SNPs, which point to key regulatory mediators of these environmental stimuli and therefore potential therapeutic targets for autoimmune diseases. In particular, genes with IFN interactions are enriched for ISRE binding site motifs, while those with anti-IL-6 interactions are enriched for IRF4 motifs.CONCLUSIONS:\&nbsp;This study highlights the potential to exploit clinical trial data to discover in vivo eQTL interactions with therapeutically relevant environmental variables.},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/30340504},
	author = {Davenport, Emma Elisabeth and Amariuta, Tiffany and Gutierrez-Arcelus, Maria and Slowikowski, Kamil and Westra, Harm-Jan and Luo, Yang and Shen, Ciyue and Rao, Deepak A. and Zhang, Ying and Pearson, Stephen and von Schack, David and Beebe, Jean S. and Bing, Nan and John, Sally and Vincent, Michael S. and Zhang, Baohong and Raychaudhuri, Soumya}
}
@article {1420432,
	title = {Mixed Effects Association of Single Cells Identifies an Expanded Th1-Skewed Cytotoxic Effector CD4+ T Cell Subset in Rheumatoid Arthritis.},
	journal = {Science Translational Medicine},
	volume = {10},
	number = {463},
	year = {2018},
	abstract = {High dimensional single-cell analyses have dramatically improved the ability to resolve complex mixtures of cells from human disease samples; however, identifying disease-associated cell types or cell states in patient samples remains challenging due to technical and inter-individual variation. Here we present Mixed effects modeling of Associations of Single Cells (MASC), a novel reverse single cell association strategy for testing whether case-control status influences the membership of single cells in any of multiple cellular subsets while accounting for technical confounds and biological variation. Applying MASC to mass cytometry analyses of CD4+ T cells from blood of rheumatoid arthritis (RA) patients and controls revealed a significantly expanded population of CD4+ T cells, identified as CD27- HLA-DR+ effector memory cells, in RA patients (OR = 1.7; p = 0.0011). The frequency of CD27- HLA-DR+ cells was similarly elevated in blood samples from a second RA patient cohort, and CD27- HLA-DR+ cell frequency decreased in RA patients who respond to immunosuppressive therapy. Compared to peripheral blood, synovial fluid and synovial tissue samples from RA patients contained ~5-fold higher frequencies of CD27- HLA-DR+ cells, which comprised ~10\% of synovial CD4+ T cells. We find that CD27- HLA-DR+ cells are abundant producers of IFN-γ and also express perforin and granzyme A at elevated levels. Thus MASC identified the expansion of a unique Th1 skewed effector T cell population with cytotoxic capacity in RA. We propose that MASC is a broadly applicable method to identify disease-associated cell populations in high-dimensional single cell data.},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/30333237},
	author = {Fonseka, Chamith Y$\#$ and Rao, Deepak A.$\#$ and Teslovich, Nikola C. and Hannes, Susan K. and Slowikowski, Kamil and Gurish, Michael F. and Donlin, Laura T. and Weinblatt, Michael E. and Massarotti, Elena M. and Coblyn, Jonathan S. and Helfgott, Simon M. and Todd, Derrick J. and Bykerk, Vivian P. and Karlson, Elizabeth W. and Ermann, Joerg and Lee, Yvonne C. and Brenner, Michael B. and Raychaudhuri, Soumya}
}
@article {1420429,
	title = {Fine-mapping and functional studies highlight potential causal variants for rheumatoid arthritis and type 1 diabetes},
	journal = {Nature Genetics},
	volume = {50},
	number = {10},
	year = {2018},
	pages = {1366-1374},
	abstract = {To define potentially causal variants for autoimmune disease, we fine-mapped1,2\&nbsp;76 rheumatoid arthritis (11,475 cases, 15,870 controls)3\&nbsp;and type 1 diabetes loci (9,334 cases, 11,111 controls)4. After sequencing 799 1-kilobase regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89\% of common variants. We defined credible sets of <=5 causal variants at 5 rheumatoid arthritis and 10 type 1 diabetes loci. We identified potentially causal missense variants at DNASE1L3, PTPN22, SH2B3, and TYK2, and noncoding variants at MEG3, CD28{\textendash}CTLA4, and IL2RA. We also identified potential candidate causal variants at SIRPG and TNFAIP3. Using functional assays, we confirmed allele-specific protein binding and differential enhancer activity for three variants: the CD28{\textendash}CTLA4 rs117701653 SNP, MEG3 rs34552516 indel, and TNFAIP3 rs35926684 indel.},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Fine-mapping+and+functional+studies+highlight+potential+causal+variants+for+rheumatoid+arthritis+and+type+1+diabetes},
	author = {Westra, Harm-Jan$\#$ and Mart{\'\i}nez-Bonet, Marta$\#$ and Onengut-Gumuscu, Suna and Lee, Anette and Luo, Yang and Teslovich, Nikola and Worthington, Jane and Martin, Javier and Huizinga, Tom and Klareskog, Lars and Rantap{\"a}{\"a}-Dahlqvist, Solbritt and Chen, Wei-Min and Quinlan, Aaron and Todd, John A. and Eyre, Steve and Nigrovic, Peter A. and Gregersen, Peter K. and Rich, Stephen S. and Raychaudhuri, Soumya}
}
@article {1420412,
	title = {Functionally distinct disease-associated fibroblast subsets in rheumatoid arthritis},
	journal = {Nature Communications},
	volume = {9},
	number = {789},
	year = {2018},
	abstract = {Fibroblasts mediate normal tissue matrix remodeling, but they can cause fibrosis or tissue destruction following chronic inflammation. In rheumatoid arthritis (RA), synovial fibroblasts expand, degrade cartilage, and drive joint inflammation. Little is known about fibroblast heterogeneity or if aberrations in fibroblast subsets relate to disease pathology. Here, we used an integrative strategy, including bulk transcriptomics on targeted subpopulations and unbiased single-cell transcriptomics, to analyze fibroblasts from synovial tissues. We identify 7 phenotypic fibroblast subsets with distinct surface protein phenotypes, and these collapsed into 3 subsets based on transcriptomics data. One subset expressing PDPN, THY1, but lacking CD34 was 3-fold expanded in RA relative to osteoarthritis (P=0.007); most of these cells expressed CDH11. The subsets were found to differ in expression of cytokines and matrix metalloproteinases, localization in synovial microanatomy, and in response to TNF. Our approach provides a template to identify pathogenic stromal cellular subsets in complex diseases.},
	url = {https://www.nature.com/articles/s41467-018-02892-y},
	author = {Mizoguchi, Fumitaka$\#$ and Slowikowski, Kamil$\#$ and Marshall, Jennifer L. and Wei, Kevin and Rao, Deepak A. and Chang, Sook Kyung and Nguyen, Hung N. and Noss, Erika H. and Turner, Jason D. and Earp, Brandon E. and Blazar, Philip E. and John Wright and Simmons, Barry P. and Donlin, Laura T. and Kalliolias, George D. and Goodman, Susan M. and Bykerk, Vivan P. and Ivashkiv, Lionel B. and Lederer, James A. and Hacohen, Nir and Nigrovic, Peter A. and Filer, Andrew and Buckley, Christopher D. and Raychaudhuri, Soumya* and Brenner, Michael*}
}
@article {1423279,
	title = {Functional genomics of stromal cells in chronic inflammatory diseases.},
	journal = {Current Opinion in Rheumatology},
	volume = {30},
	number = {1},
	year = {2018},
	pages = {65-71},
	abstract = {PURPOSE OF REVIEW:\&nbsp;Stroma is a broad term referring to the connective tissue matrix in which other cells reside. It is composed of diverse cell types with functions such as extracellular matrix maintenance, blood and lymph vessel development, and effector cell recruitment. The tissue microenvironment is determined by the molecular characteristics and relative abundances of different stromal cells such as fibroblasts, endothelial cells, pericytes, and mesenchymal precursor cells. Stromal cell heterogeneity is explained by embryonic developmental lineage, stages of differentiation to other cell types, and activation states. Interaction between immune and stromal cell types is critical to wound healing, cancer, and a wide range of inflammatory diseases. Here, we review recent studies of inflammatory diseases that use functional genomics and single-cell technologies to identify and characterize stromal cell types associated with pathogenesis.RECENT FINDINGS:\&nbsp;High dimensional strategies using mRNA sequencing, mass cytometry, and fluorescence activated cell-sorting with fresh primary tissue samples are producing detailed views of what is happening in diseased tissue in rheumatoid arthritis, inflammatory bowel disease, and cancer. Fibroblasts positive for CD90 (Thy-1) are enriched in the synovium of rheumatoid arthritis patients. Single-cell RNA-seq studies will lead to more discoveries about the stroma in the near future.SUMMARY:\&nbsp;Stromal cells form the microenvironment of inflamed and diseased tissues. Functional genomics is producing an increasingly detailed view of subsets of stromal cells with pathogenic functions in rheumatic diseases and cancer. Future genomics studies will discover disease mechanisms by perturbing molecular pathways with chemokines and therapies known to affect patient outcomes. Functional genomics studies with large sample sizes of patient tissues will identify patient subsets with different disease phenotypes or treatment responses.},
	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5890939/},
	author = {Slowikowski, Kamil and Wei, Kevin and Brenner, Michael B. and Raychaudhuri, Soumya}
}
@article {1423277,
	title = {An Integrated Clinical Program and Crowdsourcing Strategy for Genomic Sequencing and Mendelian Disease Gene Discovery.},
	journal = {npj Genomic Medicine},
	volume = {3},
	year = {2018},
	pages = {21},
	abstract = {Despite major progress in defining the genetic basis of Mendelian disorders, the molecular etiology of many cases remains unknown. Patients with these undiagnosed disorders often have complex presentations and require treatment by multiple health care specialists. Here, we describe an integrated clinical diagnostic and research program using whole-exome and whole-genome sequencing (WES/WGS) for Mendelian disease gene discovery. This program employs specific case ascertainment parameters, a WES/WGS computational analysis pipeline that is optimized for Mendelian disease gene discovery with variant callers tuned to specific inheritance modes, an interdisciplinary crowdsourcing strategy for genomic sequence analysis, matchmaking for additional cases, and integration of the findings regarding gene causality with the clinical management plan. The interdisciplinary gene discovery team includes clinical, computational, and experimental biomedical specialists who interact to identify the genetic etiology of the disease, and when so warranted, to devise improved or novel treatments for affected patients. This program effectively integrates the clinical and research missions of an academic medical center and affords both diagnostic and therapeutic options for patients suffering from genetic disease. It may therefore be germane to other academic medical institutions engaged in implementing genomic medicine programs.},
	url = {https://www.nature.com/articles/s41525-018-0060-9},
	author = {Haghighi, Alireza and Krier, Joel B. and T{\'o}th-Petr{\'o}czy, Agnes and Cassa, Christopher A. and Frank, Natasha Y. and Carmichael, Nikkola and Fieg, Eizabeth and Bjonnes, Andrew C. and Mohanty, Anwoy Kumar and Briere, Lauren C. and Lincoln, Sharon A. and Lucia, Stephanie and Gupta, Vandana and S{\"o}ylemez, Onuralp and Sutti, Sheila and Kooshesh, Kameron and Qiu, Haiyan and Fay, Christopher J. and Perroni, Victoria and Valerius, Jennifer and Hanna, Meredith and Frank, Alexander and Ouahed, Jodie D. and Snapper, Scott B. and Pantazi, Angeliki and Chopra, Sameer S. and Leshchiner, Ignaty and Stitziel, Nathan O. and Feldweg, Anna M. and Mannstadt, Michael and Loscalzo, Joseph and Sweetser, David A. and Liao, Eric and Stoler, JOan Marilyn and Bearce nowak, Catherine and Sanchez-Lara, Pedro A. and Klein, Ophir D. and Perry, Hazel and Patsopoulos, Nikolaos A. and Raychaudhuri, Soumya and Wolfram Goessling and Green, Robert C. and Seidman, Christine E. and Calum A. MacRae and Sunyaev, Shamil and Maas, Richard L. and Vuzman, Dana}
}
@article {1423272,
	title = {Review: Genetics and the Classification of Arthritis in Adults and Children.},
	journal = {Arthritis Rheumatology},
	volume = {7},
	number = {1},
	year = {2018},
	pages = {7-17},
	abstract = {Current classification of primary inflammatory arthritis begins from the assumption that adults and children are different. No form of juvenile idiopathic arthritis bears the same name as an adult arthritis, a nomenclature gap with implications for both clinical care and research. Recent genetic data have raised questions regarding this adult/pediatric divide, revealing instead broad patterns that span the age spectrum. Combining these genetic patterns with demographic and clinical data, we propose that inflammatory arthritis can be segregated into 4 main clusters, largely irrespective of pediatric or adult onset: seropositive, seronegative (likely including a distinct group that usually begins in early childhood), spondyloarthritis, and systemic. Each of these broad clusters is internally heterogeneous, highlighting the need for further study to resolve etiologically discrete entities. Eliminating divisions based on arbitrary age cutoffs will enhance opportunities for collaboration between adult and pediatric rheumatologists, thereby helping to promote the understanding and treatment of arthritis.},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/29024575},
	author = {Nigrovic, Peter A. and Raychaudhuri, Soumya and Thompson, Susan D.}
}
@article {1420437,
	title = {Imputation-based analysis of MICA alleles in the susceptibility to ankylosing spondylitis},
	journal = {Annals of the Rheumatic Diseases},
	volume = {77},
	number = {11},
	year = {2018},
	pages = {1691-1692},
	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6716791/},
	author = {Cortes, Adrian and Gladman, Dafna and Raychaudhuri, Soumya and Cui, Jing and Wheeler, Lawrie and Brown, Matthew A.}
}
@article {1420428,
	title = {High-throughput identification of noncoding functional SNPs via type IIS enzyme restriction},
	journal = {Nature Genetics},
	volume = {50},
	number = {8},
	year = {2018},
	pages = {1180-1188},
	abstract = {Genome-wide association studies (GWAS) have identified many disease-associated noncoding variants, but cannot distinguish functional single-nucleotide polymorphisms (fSNPs) from others that reside incidentally within risk loci. To address this challenge, we developed an unbiased high-throughput screen that employs type IIS enzymatic restriction to identify fSNPs that allelically modulate the binding of regulatory proteins. We coupled this approach, termed SNP-seq, with flanking restriction enhanced pulldown (FREP) to identify regulation of\&nbsp;CD40\&nbsp;by three disease-associated fSNPs via four regulatory proteins, RBPJ, RSRC2 and FUBP-1/TRAP150. Applying this approach across 27 loci associated with juvenile idiopathic arthritis, we identified 148 candidate fSNPs, including two that regulate\&nbsp;STAT4\&nbsp;via the regulatory proteins SATB2 and H1.2. Together, these findings establish the utility of tandem SNP-seq/FREP to bridge the gap between GWAS and disease mechanism.},
	url = {https://www.nature.com/articles/s41588-018-0159-z},
	author = {Li, Gang and Mart{\'\i}nez-Bonet, Marta and Wu, Di and Yang, Yu and Cui, Jing and Nguyen, Hung N. and Cunin, Pierre and Levescot, Ana{\"\i}s and Bai, Ming and Westra, Harm-Jan and Okada, Yukinori and Brenner, Michael B and Raychaudhuri, Soumya and Hendrickson, Eric A. and Maas, Richard L. and Nigrovic, Peter A.}
}
@article {1420427,
	title = {Methods for high-dimensonal analysis of cells dissociated from cyropreserved synovial tissue},
	journal = {Arthritis Research \& Therapy},
	volume = {20},
	number = {1},
	year = {2018},
	pages = {139},
	abstract = {Detailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple highdimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples. Methods: Multiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10\% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq. Results: Upon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ~ 30 arthroplasty and ~ 20 biopsy samples yielded a consensus digestion protocol using 100 μg/ml of LiberaseTM TL enzyme preparation. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished diverse fibroblast phenotypes, distinct populations of memory B cells and antibody-secreting cells, and multiple CD4 and CD8 T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified.},
	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042350/},
	author = {Donlin, Laura T. and Rao, Deepak A. and Wei, Kevin and Slowikowski, Kamil and McGeachy, Mandy J. and Turner, Jason D. and Meednu, Nida and Mizoguchi, Fumitaka and Gutierrez-Arcelus, Maria and Lieb, David J. and Keegan, Joshua and Muskat, Kaylin and Hillman, Joshua and Rozo, Cristina and Ricker, Edd and Eisenhaure, Thomas M and Li, Shuqiang and Browne, Edward P. and Chicoine, Adam and Sutherby, Danielle and Noma, Akiko and Accelerating Medicines Partnership RA/SLE Network and Nusbaum, Chad and Kelly, Stephen and Pernis, Alessandra B. and Ivashkiv, Lionel B. and Goodman, Susan M. and Robinson, William H. and Utz, Paul J. and Lederer, James A. and Gravallese, Ellen M. and Boyce, Brendan F. and Hacohen, Nir and Pitzalis, Costantino and Gregersen, Peter K. and Firestein, Gary S. and Raychaudhuri, Soumya and Moreland, Larry W. and Holers, V. Michael and Bykerk, Vivian and Filer, Andrew and Boyle, David L. and Brenner, Michael B and Anolik, Jennifer H.}
}
@article {1420418,
	title = {Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types},
	journal = {Nature Genetics},
	volume = {50},
	number = {4},
	year = {2018},
	pages = {621-629},
	abstract = {Genetics can provide a systematic approach to discovering the tissues and cell types relevant for a complex disease or trait. Identifying these tissues and cell types is critical for following up on non-coding allelic function, developing ex-vivo models, and identifying therapeutic targets. Here, we analyze gene expression data from several sources, including the GTEx and PsychENCODE consortia, together with genome-wide association study (GWAS) summary statistics for 48 diseases and traits with an average sample size of 169,331, to identify disease-relevant tissues and cell types. We develop and apply an approach that uses stratified LD score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We detect tissue-specific enrichments at FDR \&lt; 5\% for 34 diseases and traits across a broad range of tissues that recapitulate known biology. In our analysis of traits with observed central nervous system enrichment, we detect an enrichment of neurons over other brain cell types for several brain-related traits, enrichment of inhibitory over excitatory neurons for bipolar disorder but excitatory over inhibitory neurons for schizophrenia and body mass index, and enrichments in the cortex for schizophrenia and in the striatum for migraine. In our analysis of traits with observed immunological enrichment, we identify enrichments of T cells for asthma and eczema, B cells for primary biliary cirrhosis, and myeloid cells for Alzheimer{\textquoteright}s disease, which we validated with independent chromatin data. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signal.},
	url = {https://www.google.com/url?sa=t\&rct=j\&q=\&esrc=s\&source=web\&cd=2\&cad=rja\&uact=8\&ved=2ahUKEwio96Snh7noAhV5mHIEHa6vD9MQFjABegQIBBAB\&url=https\%3A\%2F\%2Fwww.nature.com\%2Farticles\%2Fs41588-018-0081-4\&usg=AOvVaw1QxY1EEuloiWaTNE02ij3N},
	author = {Finucane, Hilary and Reshef, Yakir and Anttila, Verneri and Slowikowski, Kamil and Gusev, Alexander and Byrnes, Andrea and Gazal, Steven and Po-Ru Loh and Lareau, Caleb and Shoresh, Noam and Genovese, Giulio and Saunders, Apriar and Macosko, Evan and Pollack, Samuela and The Brainstorm Consortium and Perry, John R.B. and Buenrostro, Jason D. and Bradley E. Bernstein and Raychaudhuri, Soumya and McCarroll, Steven and Neale, Benjamin and Price, Alkes}
}
@article {1109691,
	title = {A rare coding allele in IFIH1 is protective for psoriatic arthritis},
	journal = {Ann Rheum Dis},
	volume = {76},
	number = {7},
	year = {2017},
	month = {2017 Jul},
	pages = {1321-1324},
	abstract = {OBJECTIVES: Psoriatic arthritis (PsA) is an inflammatory arthritis associated with psoriasis. While many common risk alleles have been reported for association with PsA as well as psoriasis, few rare coding alleles have yet been identified. METHODS: To identify rare coding variation associated with PsA risk or protection, we genotyped 41 267 variants with the exome chip and investigated association within an initial cohort of 1980 PsA cases and 5913 controls. Genotype data for an independent cohort of 2234 PsA cases and 5708 controls was also made available, allowing for a meta-analysis to be performed with the discovery dataset. RESULTS: We identified an association with the rare variant rs35667974 (p=2.39x10(-6), OR=0.47), encoding an Ile923Val amino acid change in the IFIH1 gene protein product. The association was reproduced in our independent cohort, which reached a high level of significance on meta-analysis with the discovery and replication datasets (p=4.67x10(-10)). We identified a strong association with IFIH1 when performing multiple-variant analysis (p=6.77x10(-6)), and found evidence of independent effects between the rare allele and the common PsA variant at the same locus. CONCLUSION: For the first time, we report a rare coding allele in IFIH1 to be protective for PsA. This rare allele has also been identified to have the same direction of effect on type I diabetes and psoriasis. While this association further supports existing evidence for IFIH1 as a causal gene for PsA, mechanistic studies will need to be pursued to confirm that IFIH1 is indeed causal.},
	issn = {1468-2060},
	doi = {10.1136/annrheumdis-2016-210592},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=A+rare+coding+allele+in+IFIH1+is+protective+for+psoriatic+arthritis},
	author = {Budu-Aggrey, Ashley and Bowes, John and Stuart, Philip E and Zawistowski, Matthew and Tsoi, Lam C and Nair, Rajan and Jadon, Deepak Rohit and McHugh, Neil and Korendowych, Eleanor and Elder, James T and Barton, Anne and Raychaudhuri, Soumya}
}
@article {1001641,
	title = {Pathologically expanded peripheral T helper cell subset drives B cells in rheumatoid arthritis},
	journal = {Nature},
	volume = {542},
	number = {7639},
	year = {2017},
	month = {2017 02 01},
	pages = {110-114},
	abstract = {CD4(+) T cells are central mediators of autoimmune pathology; however, defining their key effector functions in specific autoimmune diseases remains challenging. Pathogenic CD4(+) T cells within affected tissues may be identified by expression of markers of recent activation. Here we use mass cytometry to analyse activated T cells in joint tissue from patients with rheumatoid arthritis, a chronic immune-mediated arthritis that affects up to 1\% of the population. This approach revealed a markedly expanded population of PD-1(hi)CXCR5(-)CD4(+) T cells in synovium of patients with rheumatoid arthritis. However, these cells are not exhausted, despite high PD-1 expression. Rather, using multidimensional cytometry, transcriptomics, and functional assays, we define a population of PD-1(hi)CXCR5(-) {\textquoteright}peripheral helper{\textquoteright} T (TPH) cells that express factors enabling B-cell help, including IL-21, CXCL13, ICOS, and MAF. Like PD-1(hi)CXCR5(+) T follicular helper cells, TPH cells induce plasma cell differentiation in vitro through IL-21 secretion and SLAMF5 interaction (refs 3, 4). However, global transcriptomics highlight differences between TPH cells and T follicular helper cells, including altered expression of BCL6 and BLIMP1 and unique expression of chemokine receptors that direct migration to inflamed sites, such as CCR2, CX3CR1, and CCR5, in TPH cells. TPH cells appear to be uniquely poised to promote B-cell responses and antibody production within pathologically inflamed non-lymphoid tissues.},
	keywords = {Arthritis, Rheumatoid, B-Lymphocytes, Cell Differentiation, Cell Movement, Chemokine CXCL13, Gene Expression Profiling, Humans, Inducible T-Cell Co-Stimulator Protein, Interleukins, Macrophage-Activating Factors, Programmed Cell Death 1 Receptor, Proto-Oncogene Proteins c-bcl-6, Receptors, Chemokine, Receptors, CXCR5, Repressor Proteins, Signaling Lymphocytic Activation Molecule Family, Synovial Fluid, T-Lymphocytes, Helper-Inducer},
	issn = {1476-4687},
	doi = {10.1038/nature20810},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Pathologically+expanded+peripheral+T+helper+cell+subset+drives+B+cells+in+rheumatoid+arthritis},
	author = {Rao, Deepak A and Gurish, Michael F and Marshall, Jennifer L and Slowikowski, Kamil and Fonseka, Chamith Y and Liu, Yanyan and Donlin, Laura T and Henderson, Lauren A and Wei, Kevin and Mizoguchi, Fumitaka and Teslovich, Nikola C and Weinblatt, Michael E and Massarotti, Elena M and Coblyn, Jonathan S and Helfgott, Simon M and Lee, Yvonne C and Todd, Derrick J and Bykerk, Vivian P and Goodman, Susan M and Pernis, Alessandra B and Ivashkiv, Lionel B and Karlson, Elizabeth W and Nigrovic, Peter A and Filer, Andrew and Buckley, Christopher D and Lederer, James A and Raychaudhuri, Soumya and Brenner, Michael B}
}
@article {1001516,
	title = {Brief Report: The Role of Rare Protein-Coding Variants in Anti-Tumor Necrosis Factor Treatment Response in Rheumatoid Arthritis},
	journal = {Arthritis Rheumatol},
	volume = {69},
	number = {4},
	year = {2017},
	month = {2017 Apr},
	pages = {735-741},
	abstract = {OBJECTIVE: In many rheumatoid arthritis (RA) patients, disease is controlled with anti-tumor necrosis factor (anti-TNF) biologic therapies. However, in a significant number of patients, the disease fails to respond to anti-TNF therapy. We undertook the present study to examine the hypothesis that rare and low-frequency genetic variants might influence response to anti-TNF treatment. METHODS: We sequenced the coding region of 750 genes in 1,094 RA patients of European ancestry who were treated with anti-TNF. After quality control, 690 genes were included in the analysis. We applied single-variant association and gene-based association tests to identify variants associated with anti-TNF treatment response. In addition, given the key mechanistic role of TNF, we performed gene set analyses of 27 TNF pathway genes. RESULTS: We identified 14,420 functional variants, of which 6,934 were predicted as nonsynonymous 2,136 of which were further predicted to be "damaging." Despite the fact that the study was well powered, no single variant or gene showed study-wide significant association with change in the outcome measures disease activity or European League Against Rheumatism response. Intriguingly, we observed 3 genes, of 27 with nominal signals of association (P \&lt; 0.05), that were involved in the TNF signaling pathway. However, when we performed a rigorous gene set enrichment analysis based on association P value ranking, we observed no evidence of enrichment of association at genes involved in the TNF pathway (Penrichment  = 0.15, based on phenotype permutations). CONCLUSION: Our findings suggest that rare and low-frequency protein-coding variants in TNF signaling pathway genes or other genes do not contribute substantially to anti-TNF treatment response in patients with RA.},
	issn = {2326-5205},
	doi = {10.1002/art.39966},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Brief+Report\%3A+The+Role+of+Rare+Protein-Coding+Variants+in+Anti-Tumor+Necrosis+Factor+Treatment+Response+in+Rheumatoid+Arthritis},
	author = {Cui, Jing and Diogo, Dorothee and Stahl, Eli A and Canhao, Helena and Mariette, Xavier and Greenberg, Jeffrey D and Okada, Yukinori and Pappas, Dimitrios A and Fulton, Robert S and Tak, Paul P and Nurmohamed, Michael T and Lee, Annette and Larson, David E and Kurreeman, Fina and Deluca, Tracie L and O{\textquoteright}Laughlin, Michelle and Fronick, Catrina C and Fulton, Lucinda L and Mardis, Elaine R and van der Horst-Bruinsma, Irene E and Wolbink, Gert-Jan and Gregersen, Peter K and Kremer, Joel M and Crusius, J Bart A and de Vries, Niek and Huizinga, Tom W J and Fonseca, Jo{\~a}o Eurico and Miceli-Richard, Corinne and Karlson, Elizabeth W and Coenen, Marieke Jh and Barton, Anne and Plenge, Robert M and Raychaudhuri, Soumya}
}
@article {1423271,
	title = {Leveraging blood and tissue CD4+ T cell heterogeneity at the single cell level to identify mechanisms of disease in rheumatoid arthritis.},
	journal = {Current Opinion in Immunology},
	volume = {49},
	year = {2017},
	pages = {27-36},
	abstract = {CD4+ T cells have been long known to play an important role in the pathogenesis of rheumatoid arthritis (RA), but the specific cell populations and states that drive the disease have been challenging to identify with low dimensional single cell data and bulk assays. The advent of high dimensional single cell technologies-like single cell RNA-seq or mass cytometry-has offered promise to defining key populations, but brings new methodological and statistical challenges. Recent single cell profiling studies have revealed a broad diversity of cell types among CD4+ T cells, identifying novel populations that are expanded or altered in RA. Here, we will review recent findings on CD4+ T cell heterogeneity and RA that have come from single cell profiling studies and discuss the best practices for conducting these studies.},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Leveraging+blood+and+tissue+CD4\%2B+T+cell+heterogeneity+at+the+single+cell+level+to+identify+mechanisms+of+disease+in+rheumatoid+arthritis.},
	author = {Fonseka, Chamith Y. and Rao, Deepak A. and Raychaudhuri, Soumya}
}
@article {1423268,
	title = {Molecular basis for increased susceptibility of Indigenous North Americans to seropositive rheumatoid arthritis.},
	journal = {Annals of Rheumatic Diseases},
	volume = {76},
	number = {11},
	year = {2017},
	pages = {1915-1923},
	abstract = {OBJECTIVE:\&nbsp;The pathogenetic mechanisms by which\&nbsp;HLA-DRB1\&nbsp;alleles are associated with anticitrullinated peptide antibody (ACPA)-positive rheumatoid arthritis (RA) are incompletely understood. RA high-risk\&nbsp;HLA-DRB1\&nbsp;alleles are known to share a common motif, the {\textquoteright}shared susceptibility epitope (SE){\textquoteright}. Here, the electropositive P4 pocket of HLA-DRB1 accommodates self-peptide residues containing citrulline but not arginine. HLA-DRB1 His/Phe13β stratifies with ACPA-positive RA, while His13βSer polymorphisms stratify with ACPA-negative RA and RA protection. Indigenous North American (INA) populations have high risk of early-onset ACPA-positive RA, whereby HLA-DRB1*04:04 and HLA-DRB1*14:02 are implicated as risk factors for RA in INA. However, HLA-DRB1*14:02 has a His13βSer polymorphism. Therefore, we aimed to verify this association and determine its molecular mechanism.METHODS:\&nbsp;HLA genotype was compared in 344 INA patients with RA and 352 controls. Structures of HLA-DRB1*1402-class II loaded with vimentin-64Arg59-71, vimentin-64Cit59-71\&nbsp;and fibrinogen β-74Cit69-81\&nbsp;were solved using X-ray crystallography. Vimentin-64Cit59-71-specific and vimentin59-71-specific CD4+ T cells were characterised by flow cytometry using peptide-histocompatibility leukocyte antigen (pHLA) tetramers. After sorting of antigen-specific T cells, TCRα and β-chains were analysed using multiplex, nested PCR and sequencing.RESULTS:\&nbsp;ACPA+\&nbsp;RA in INA was independently associated with\&nbsp;HLA-DRB1*14:02. Consequent to the His13βSer polymorphism and altered P4 pocket of HLA-DRB1*14:02, both citrulline and arginine were accommodated in opposite orientations. Oligoclonal autoreactive CD4+ effector T cells reactive with both citrulline and arginine forms of vimentin59-71\&nbsp;were observed in patients with HLA-DRB1*14:02+\&nbsp;RA and at-risk ACPA-\&nbsp;first-degree relatives. HLA-DRB1*14:02-vimentin59-71-specific and HLA-DRB1*14:02-vimentin-64Cit59-71-specific CD4+ memory T cells were phenotypically distinct populations.CONCLUSION:\&nbsp;HLA-DRB1*14:02 broadens the capacity for citrullinated and native self-peptide presentation and T cell expansion, increasing risk of ACPA+ RA.},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/28801345},
	author = {Scally, Stephen and Law, Soi Cheng and Ting, Yi Tian and Van Heemst, Jurgen and Sokolove, Jeremy and Deutsch, Aaron J. and Clemens, E. Bridie and Moustakas, Antonis K. and Papadopoulos, George K. and van der Woude, Diane and Smolik, Irene and Hitchon, Carol A. and Robinson, David B. and Ferucci, Elizabeth D. and Bernstein, Charles N. and Meng, Xiaobo and Anaparti, Vidyanand and Huizinga, Tom and Kedzierska, Katherine and Reid, Hugh and Raychauhduri, Soumya and Toes, Ren{\'e} E. and Rossjohn, Jamie and El-Gabalawy, Hani and Thomas, Ranjeny}
}
@article {1423267,
	title = {Fine-mapping the MHC locus in juvenile idiopathic arthritis (JIA) reveals genetic heterogeneity corresponding to distinct adult inflammatory arthritic diseases.},
	journal = {Annals of Rheumatic Diseases},
	volume = {76},
	number = {4},
	year = {2017},
	pages = {765-772},
	abstract = {OBJECTIVES:\&nbsp;Juvenile idiopathic arthritis (JIA) is a heterogeneous group of diseases, comprising seven categories. Genetic data could potentially be used to help redefine JIA categories and improve the current classification system. The human leucocyte antigen (HLA) region is strongly associated with JIA. Fine-mapping of the region was performed to look for similarities and differences in HLA associations between the JIA categories and define correspondences with adult inflammatory arthritides.METHODS:\&nbsp;Dense genotype data from the HLA region, from the Immunochip array for 5043 JIA cases and 14 390 controls, were used to impute single-nucleotide polymorphisms, HLA classical alleles and amino acids. Bivariate analysis was performed to investigate genetic correlation between the JIA categories. Conditional analysis was used to identify additional effects within the region. Comparison of the findings with those in adult inflammatory arthritic diseases was performed.RESULTS:\&nbsp;We identified category-specific associations and have demonstrated for the first time that rheumatoid factor (RF)-negative polyarticular JIA and oligoarticular JIA are genetically similar in their HLA associations. We also observe that each JIA category potentially has an adult counterpart. The RF-positive polyarthritis association at HLA-DRB1 amino acid at position 13 mirrors the association in adult seropositive rheumatoid arthritis (RA). Interestingly, the combined oligoarthritis and RF-negative polyarthritis dataset shares the same association with adult seronegative RA.CONCLUSIONS:\&nbsp;The findings suggest the value of using genetic data in helping to classify the categories of this heterogeneous disease. Mapping JIA categories to adult counterparts could enable shared knowledge of disease pathogenesis and aetiology and facilitate transition from paediatric to adult services.},
	url = {https://www.google.com/url?sa=t\&rct=j\&q=\&esrc=s\&source=web\&cd=1\&cad=rja\&uact=8\&ved=2ahUKEwid96Hdg7noAhWMlHIEHTrgDM4QFjAAegQIAhAB\&url=https\%3A\%2F\%2Fwww.ncbi.nlm.nih.gov\%2Fpubmed\%2F27998952\&usg=AOvVaw04xoZPD2GH05m86-ZtCQ-q},
	author = {Hinks, Anne and Bowes, John and Cobb, Joanna E. and Ainsworth, Hannah C. and Marlon, Miranda C. and Comeau, M. E. and Sudman, Marc and Han, B. and Becker, M. L. and Bohnsack, John F and de Bakker, P I W and Haas, Johannes-Peter and Hazen, M. and Lovell, D. J. and Nigrovic, Peter and Nordai, Ellen and Punnaro, M. and Rosenberg, A. M. and Rygg, Marite and Smith, Samantha Louise and Wise, Carol A. and Videm, V. and Wedderburn, Lucy R. and Yarwood, Annie and Yeung, Rae S. M. and Prahalad, S. and Langefeld, Carl and Raychaudhuri, Soumya and Thompson, Susan D. and Thomson, W.}
}
@article {1423266,
	title = {Genetic landscape of interactive effects of HLA-DRB1 alleles on susceptibility to ACPA(+) rheumatoid arthritis and ACPA levels in Japanese population},
	journal = {Journal of Medical Genetics},
	volume = {54},
	number = {12},
	year = {2017},
	pages = {853-858},
	abstract = {BACKGROUND:\&nbsp;HLA-DRB1\&nbsp;is the strongest susceptibility gene to rheumatoid arthritis (RA).\&nbsp;HLA-DRB1\&nbsp;alleles showed significant non-additive and interactive effects on susceptibility to RA in the European population, but these effects on RA susceptibility should vary between populations due to the difference in allelic distribution. Furthermore, non-additive or interactive effects on the phenotypes of RA are not fully known. We evaluated the non-additive and interactive effects of\&nbsp;HLA-DRB1\&nbsp;alleles on RA susceptibility and anticitrullinated protein/peptide antibody (ACPA) levels in Japanese patients.METHODS:\&nbsp;A total of 5581 ACPA(+) RA and 19 170 controls were genotyped or imputed for\&nbsp;HLA-DRB1\&nbsp;alleles. Logistic regression analysis was performed for both allelic non-additive effects and interactive effects of allelic combinations. The significant levels were set by Bonferroni{\textquoteright}s correction. A total of 4371 ACPA(+) RA were analysed for ACPA levels.RESULTS:\&nbsp;We obtained evidence of non-additive and interactive effects of\&nbsp;HLA-DRB1\&nbsp;on ACPA(+) RA susceptibility (p=2.5{\texttimes}10-5 and 1.5{\texttimes}10-17, respectively). Multiple\&nbsp;HLA-DRB1\&nbsp;alleles including\&nbsp;HLA-DRB1*04:05, the most common susceptibility allele in the Japanese, showed significant non-additive effects (p<=0.0043). We identified multiple allelic combinations with significant interactive effects including a common combination with the European population as well as novel combinations. Additional variance of ACPA(+) RA susceptibility could be explained substantially by heterozygote dominance or interactive effects. We did not find evidence of non-additive and interactive effects on levels of ACPA.CONCLUSION:\&nbsp;HLA allelic non-additive and interactive effects on ACPA(+) RA susceptibility were observed in the Japanese population. The allelic non-additive and interactive effects depend on allelic distribution in populations.},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/29025870},
	author = {Terao, Chikashi and Okada, Yukinori and Ikari, Katsunori and Kochi, Yuta and Suzuki, Akari and Ohmura, Koichiro and Matsuo, Keitaro and Taniguchi, Atsuo and Kubo, Michiaki and Raychaudhuri, Soumya and Yamamoto, Kazuhiko and Yamanaka, Hisashi and Kamatani, Yoichiro and Mimori, Tsuneyo and Matsuda, Fumihiko}
}
@article {1109686,
	title = {Genetic association study of exfoliation syndrome identifies a protective rare variant at LOXL1 and five new susceptibility loci},
	journal = {Nat Genet},
	volume = {49},
	number = {7},
	year = {2017},
	month = {2017 Jul},
	pages = {993-1004},
	abstract = {Exfoliation syndrome (XFS) is the most common known risk factor for secondary glaucoma and a major cause of blindness worldwide. Variants in two genes, LOXL1 and CACNA1A, have previously been associated with XFS. To further elucidate the genetic basis of XFS, we collected a global sample of XFS cases to refine the association at LOXL1, which previously showed inconsistent results across populations, and to identify new variants associated with XFS. We identified a rare protective allele at LOXL1 (p.Phe407, odds ratio (OR) = 25, P = 2.9 {\texttimes} 10(-14)) through deep resequencing of XFS cases and controls from nine countries. A genome-wide association study (GWAS) of XFS cases and controls from 24 countries followed by replication in 18 countries identified seven genome-wide significant loci (P \&lt; 5 {\texttimes} 10(-8)). We identified association signals at 13q12 (POMP), 11q23.3 (TMEM136), 6p21 (AGPAT1), 3p24 (RBMS3) and 5q23 (near SEMA6A). These findings provide biological insights into the pathology of XFS and highlight a potential role for naturally occurring rare LOXL1 variants in disease biology.},
	issn = {1546-1718},
	doi = {10.1038/ng.3875},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Genetic+association+study+of+exfoliation+syndrome+identifies+a+protective+rare+variant+at+LOXL1+and+five+new+susceptibility+loci},
	author = {Aung, Tin and Ozaki, Mineo and Lee, Mei Chin and Schl{\"o}tzer-Schrehardt, Ursula and Thorleifsson, Gudmar and Mizoguchi, Takanori and Igo, Robert P and Haripriya, Aravind and Williams, Susan E and Astakhov, Yury S and Orr, Andrew C and Burdon, Kathryn P and Nakano, Satoko and Mori, Kazuhiko and Abu-Amero, Khaled and Hauser, Michael and Li, Zheng and Prakadeeswari, Gopalakrishnan and Bailey, Jessica N Cooke and Cherecheanu, Alina Popa and Kang, Jae H and Nelson, Sarah and Hayashi, Ken and Manabe, Shin-Ichi and Kazama, Shigeyasu and Zarnowski, Tomasz and Inoue, Kenji and Irkec, Murat and Coca-Prados, Miguel and Sugiyama, Kazuhisa and J{\"a}rvel{\"a}, Irma and Schlottmann, Patricio and Lerner, S Fabian and Lamari, Hasnaa and Nilg{\"u}n, Yildirim and Bikbov, Mukharram and Park, Ki Ho and Cha, Soon Cheol and Yamashiro, Kenji and Zenteno, Juan C and Jonas, Jost B and Kumar, Rajesh S and Perera, Shamira A and Chan, Anita S Y and Kobakhidze, Nino and George, Ronnie and Vijaya, Lingam and Do, Tan and Edward, Deepak P and de Juan Marcos, Lourdes and Pakravan, Mohammad and Moghimi, Sasan and Ideta, Ryuichi and Bach-Holm, Daniella and Kappelgaard, Per and Wirostko, Barbara and Thomas, Samuel and Gaston, Daniel and Bedard, Karen and Greer, Wenda L and Yang, Zhenglin and Chen, Xueyi and Huang, Lulin and Sang, Jinghong and Jia, Hongyan and Jia, Liyun and Qiao, Chunyan and Zhang, Hui and Liu, Xuyang and Zhao, Bowen and Wang, Ya-Xing and Xu, Liang and Leruez, St{\'e}phanie and Reynier, Pascal and Chichua, George and Tabagari, Sergo and Uebe, Steffen and Zenkel, Matthias and Berner, Daniel and Mossb{\"o}ck, Georg and Weisschuh, Nicole and Hoja, Ursula and Welge-Luessen, Ulrich-Christoph and Mardin, Christian and Founti, Panayiota and Chatzikyriakidou, Anthi and Pappas, Theofanis and Anastasopoulos, Eleftherios and Lambropoulos, Alexandros and Ghosh, Arkasubhra and Shetty, Rohit and Porporato, Natalia and Saravanan, Vijayan and Venkatesh, Rengaraj and Shivkumar, Chandrashekaran and Kalpana, Narendran and Sarangapani, Sripriya and Kanavi, Mozhgan R and Beni, Afsaneh Naderi and Yazdani, Shahin and Lashay, Alireza and Naderifar, Homa and Khatibi, Nassim and Fea, Antonio and Lavia, Carlo and Dallorto, Laura and Rolle, Teresa and Frezzotti, Paolo and Paoli, Daniela and Salvi, Erika and Manunta, Paolo and Mori, Yosai and Miyata, Kazunori and Higashide, Tomomi and Chihara, Etsuo and Ishiko, Satoshi and Yoshida, Akitoshi and Yanagi, Masahide and Kiuchi, Yoshiaki and Ohashi, Tsutomu and Sakurai, Toshiya and Sugimoto, Takako and Chuman, Hideki and Aihara, Makoto and Inatani, Masaru and Miyake, Masahiro and Gotoh, Norimoto and Matsuda, Fumihiko and Yoshimura, Nagahisa and Ikeda, Yoko and Ueno, Morio and Sotozono, Chie and Jeoung, Jin Wook and Sagong, Min and Park, Kyu Hyung and Ahn, Jeeyun and Cruz-Aguilar, Marisa and Ezzouhairi, Sidi M and Rafei, Abderrahman and Chong, Yaan Fun and Ng, Xiao Yu and Goh, Shuang Ru and Chen, Yueming and Yong, Victor H K and Khan, Muhammad Imran and Olawoye, Olusola O and Ashaye, Adeyinka O and Ugbede, Idakwo and Onakoya, Adeola and Kizor-Akaraiwe, Nkiru and Teekhasaenee, Chaiwat and Suwan, Yanin and Supakontanasan, Wasu and Okeke, Suhanya and Uche, Nkechi J and Asimadu, Ifeoma and Ayub, Humaira and Akhtar, Farah and Kosior-Jarecka, Ewa and Lukasik, Urszula and Lischinsky, Ignacio and Castro, Vania and Grossmann, Rodolfo Perez and Megevand, Gordana Sunaric and Roy, Sylvain and Dervan, Edward and Silke, Eoin and Rao, Aparna and Sahay, Priti and Fornero, Pablo and Cuello, Osvaldo and Sivori, Delia and Zompa, Tamara and Mills, Richard A and Souzeau, Emmanuelle and Mitchell, Paul and Wang, Jie Jin and Hewitt, Alex W and Coote, Michael and Crowston, Jonathan G and Astakhov, Sergei Y and Akopov, Eugeny L and Emelyanov, Anton and Vysochinskaya, Vera and Kazakbaeva, Gyulli and Fayzrakhmanov, Rinat and Al-Obeidan, Saleh A and Owaidhah, Ohoud and Aljasim, Leyla Ali and Chowbay, Balram and Foo, Jia Nee and Soh, Raphael Q and Sim, Kar Seng and Xie, Zhicheng and Cheong, Augustine W O and Mok, Shi Qi and Soo, Hui Meng and Chen, Xiao Yin and Peh, Su Qin and Heng, Khai Koon and Husain, Rahat and Ho, Su-Ling and Hillmer, Axel M and Cheng, Ching-Yu and Escudero-Dom{\'\i}nguez, Francisco A and Gonz{\'a}lez-Sarmiento, Rogelio and Martinon-Torres, Frederico and Salas, Antonio and Pathanapitoon, Kessara and Hansapinyo, Linda and Wanichwecharugruang, Boonsong and Kitnarong, Naris and Sakuntabhai, Anavaj and Nguyn, Hip X and Nguyn, Giang T T and Nguyn, Tr{\`\i}nh V and Zenz, Werner and Binder, Alexander and Klobassa, Daniela S and Hibberd, Martin L and Davila, Sonia and Herms, Stefan and N{\"o}then, Markus M and Moebus, Susanne and Rautenbach, Robyn M and Ziskind, Ari and Carmichael, Trevor R and Ramsay, Michele and {\'A}lvarez, Lydia and Garc{\'\i}a, Montserrat and Gonz{\'a}lez-Iglesias, H{\'e}ctor and Rodr{\'\i}guez-Calvo, Pedro P and Cueto, Luis Fern{\'a}ndez-Vega and Oguz, {\c C}ilingir and Tamcelik, Nevbahar and Atalay, Eray and Batu, Bilge and Aktas, Dilek and Kas{\i}m, Burcu and Wilson, M Roy and Coleman, Anne L and Liu, Yutao and Challa, Pratap and Herndon, Leon and Kuchtey, Rachel W and Kuchtey, John and Curtin, Karen and Chaya, Craig J and Crandall, Alan and Zangwill, Linda M and Wong, Tien Yin and Nakano, Masakazu and Kinoshita, Shigeru and den Hollander, Anneke I and Vesti, Eija and Fingert, John H and Lee, Richard K and Sit, Arthur J and Shingleton, Bradford J and Wang, Ningli and Cusi, Daniele and Qamar, Raheel and Kraft, Peter and Pericak-Vance, Margaret A and Raychaudhuri, Soumya and Heegaard, Steffen and Kivel{\"a}, Tero and Reis, Andr{\'e} and Kruse, Friedrich E and Weinreb, Robert N and Pasquale, Louis R and Haines, Jonathan L and Thorsteinsdottir, Unnur and Jonasson, Fridbert and Allingham, R Rand and Milea, Dan and Ritch, Robert and Kubota, Toshiaki and Tashiro, Kei and Vithana, Eranga N and Micheal, Shazia and Topouzis, Fotis and Craig, Jamie E and Dubina, Michael and Sundaresan, Periasamy and Stefansson, Kari and Wiggs, Janey L and Pasutto, Francesca and Khor, Chiea Chuen}
}
@article {1109671,
	title = {Investigating methotrexate toxicity within a randomized double-blinded, placebo-controlled trial: Rationale and design of the Cardiovascular Inflammation Reduction Trial-Adverse Events (CIRT-AE) Study},
	journal = {Semin Arthritis Rheum},
	year = {2017},
	month = {2017 Feb 10},
	abstract = {BACKGROUND: The role of low dose methotrexate (LDM) in potential serious toxicities remains unclear despite its common use. Prior observational studies investigating LDM toxicity compared LDM to other active drugs. Prior placebo-controlled clinical trials of LDM in inflammatory conditions were not large enough to investigate toxicity. The Cardiovascular Inflammation Reduction Trial (CIRT) is an ongoing NIH-funded, randomized, double-blind, placebo-controlled trial of LDM in the secondary prevention of cardiovascular disease. We describe here the rationale and design of the CIRT-Adverse Events (CIRT-AE) ancillary study which aims to investigate adverse events within CIRT. DESIGN: CIRT will randomize up to 7000 participants with cardiovascular disease and no systemic rheumatic disease to either LDM (target dose: 15-20mg/week) or placebo for an average follow-up period of 3-5 years; subjects in both treatment arms receive folic acid 1mg daily for 6 days each week. The primary endpoints of CIRT include recurrent cardio vascular events, incident diabetes, and all-cause mortality, and the ancillary CIRT-AE study has been designed to adjudicate other clinically important adverse events including hepatic, gastrointestinal, respiratory, hematologic, infectious, mucocutaneous, oncologic, renal, neurologic, and musculoskeletal outcomes. Methotrexate polyglutamate levels and genome-wide single nucleotide polymorphisms will be examined for association with adverse events. SUMMARY: CIRT-AE will comprehensively evaluate potential LDM toxicities among subjects with cardiovascular disease within the context of a large, ongoing, double-blind, placebo-controlled trial. This information may lead to a personalized approach to monitoring LDM in clinical practice.},
	issn = {1532-866X},
	doi = {10.1016/j.semarthrit.2017.02.003},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Investigating+methotrexate+toxicity+within+a+randomized+double-blinded\%2C+placebo-controlled+trial\%3A+Rationale+and+design+of+the+Cardiovascular+Inflammation+Reduction+Trial-Adverse+Events+(CIRT-AE)+Study},
	author = {Sparks, Jeffrey A and Barbhaiya, Medha and Karlson, Elizabeth W and Ritter, Susan Y and Raychaudhuri, Soumya and Corrigan, Cassandra C and Lu, Fengxin and Selhub, Jacob and Chasman, Daniel I and Paynter, Nina P and Ridker, Paul M and Solomon, Daniel H}
}
@article {1109676,
	title = {Phenome-wide scanning identifies multiple diseases and disease severity phenotypes associated with HLA variants},
	journal = {Sci Transl Med},
	volume = {9},
	number = {389},
	year = {2017},
	month = {2017 May 10},
	abstract = {Although many phenotypes have been associated with variants in human leukocyte antigen (HLA) genes, the full phenotypic impact of HLA variants across all diseases is unknown. We imputed HLA genomic variation from two populations of 28,839 and 8431 European ancestry individuals and tested association of HLA variation with 1368 phenotypes. A total of 104 four-digit and 92 two-digit HLA allele phenotype associations were significant in both discovery and replication cohorts, the strongest being HLA-DQB1*03:02 and type 1 diabetes. Four previously unidentified associations were identified across the spectrum of disease with two- and four-digit HLA alleles and 10 with nonsynonymous variants. Some conditions associated with multiple HLA variants and stronger associations with more severe disease manifestations were identified. A comprehensive, publicly available catalog of clinical phenotypes associated with HLA variation is provided. Examining HLA variant disease associations in this large data set allows comprehensive definition of disease associations to drive further mechanistic insights.},
	issn = {1946-6242},
	doi = {10.1126/scitranslmed.aai8708},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Phenome-wide+scanning+identifies+multiple+diseases+and+disease+severity+phenotypes+associated+with+HLA+variants},
	author = {Karnes, Jason H and Bastarache, Lisa and Shaffer, Christian M and Gaudieri, Silvana and Xu, Yaomin and Glazer, Andrew M and Mosley, Jonathan D and Zhao, Shilin and Raychaudhuri, Soumya and Mallal, Simon and Ye, Zhan and Mayer, John G and Brilliant, Murray H and Hebbring, Scott J and Roden, Dan M and Phillips, Elizabeth J and Denny, Joshua C}
}
@article {1109681,
	title = {Transethnic meta-analysis identifies GSDMA and PRDM1 as susceptibility genes to systemic sclerosis},
	journal = {Ann Rheum Dis},
	volume = {76},
	number = {6},
	year = {2017},
	month = {2017 Jun},
	pages = {1150-1158},
	abstract = {OBJECTIVES: Systemic sclerosis (SSc) is an autoimmune disease characterised by skin and systemic fibrosis culminating in organ damage. Previous genetic studies including genome-wide association studies (GWAS) have identified 12 susceptibility loci satisfying genome-wide significance. Transethnic meta-analyses have successfully expanded the list of susceptibility genes and deepened biological insights for other autoimmune diseases. METHODS: We performed transethnic meta-analysis of GWAS in the Japanese and European populations, followed by a two-staged replication study comprising a total of 4436 cases and 14 751 controls. Associations between significant single nuclear polymorphisms (SNPs) and neighbouring genes were evaluated. Enrichment analysis of H3K4Me3, a representative histone mark for active promoter was conducted with an expanded list of SSc susceptibility genes. RESULTS: We identified two significant SNP in two loci, GSDMA and PRDM1, both of which are related to immune functions and associated with other autoimmune diseases (p=1.4{\texttimes}10(-10) and 6.6{\texttimes}10(-10), respectively). GSDMA also showed a significant association with limited cutaneous SSc. We also replicated the associations of previously reported loci including a non-GWAS locus, TNFAIP3. PRDM1 encodes BLIMP1, a transcription factor regulating T-cell proliferation and plasma cell differentiation. The top SNP in GSDMA was a missense variant and correlated with gene expression of neighbouring genes, and this could explain the association in this locus. We found different human leukocyte antigen (HLA) association patterns between the two populations. Enrichment analysis suggested the importance of CD4-na{\"\i}ve primary T cell. CONCLUSIONS: GSDMA and PRDM1 are associated with SSc. These findings provide enhanced insight into the genetic and biological basis of SSc.},
	issn = {1468-2060},
	doi = {10.1136/annrheumdis-2016-210645},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Transethnic+meta-analysis+identifies+GSDMA+and+PRDM1+as+susceptibility+genes+to+systemic+sclerosis},
	author = {Terao, Chikashi and Kawaguchi, Takahisa and Dieude, Philippe and Varga, John and Kuwana, Masataka and Hudson, Marie and Kawaguchi, Yasushi and Matucci-Cerinic, Marco and Ohmura, Koichiro and Riemekasten, Gabriela and Kawasaki, Aya and Airo, Paolo and Horita, Tetsuya and Oka, Akira and Hachulla, Eric and Yoshifuji, Hajime and Caramaschi, Paola and Hunzelmann, Nicolas and Baron, Murray and Atsumi, Tatsuya and Hassoun, Paul and Torii, Takeshi and Takahashi, Meiko and Tabara, Yasuharu and Shimizu, Masakazu and Tochimoto, Akiko and Ayuzawa, Naho and Yanagida, Hidetoshi and Furukawa, Hiroshi and Tohma, Shigeto and Hasegawa, Minoru and Fujimoto, Manabu and Ishikawa, Osamu and Yamamoto, Toshiyuki and Goto, Daisuke and Asano, Yoshihide and Jinnin, Masatoshi and Endo, Hirahito and Takahashi, Hiroki and Takehara, Kazuhiko and Sato, Shinichi and Ihn, Hironobu and Raychaudhuri, Soumya and Liao, Katherine and Gregersen, Peter and Tsuchiya, Naoyuki and Riccieri, Valeria and Melchers, Inga and Valentini, Gabriele and Cauvet, Anne and Martinez, Maria and Mimori, Tsuneyo and Matsuda, Fumihiko and Allanore, Yannick}
}
@article {1001531,
	title = {Autoimmune diseases - connecting risk alleles with molecular traits of the immune system},
	journal = {Nat Rev Genet},
	volume = {17},
	number = {3},
	year = {2016},
	month = {2016 Mar},
	pages = {160-74},
	abstract = {Genome-wide strategies have driven the discovery of more than 300 susceptibility loci for autoimmune diseases. However, for almost all loci, understanding of the mechanisms leading to autoimmunity remains limited, and most variants that are likely to be causal are in non-coding regions of the genome. A critical next step will be to identify the in vivo and ex vivo immunophenotypes that are affected by risk variants. To do this, key cell types and cell states that are implicated in autoimmune diseases will need to be defined. Functional genomic annotations from these cell types and states can then be used to resolve candidate genes and causal variants. Together with longitudinal studies, this approach may yield pivotal insights into how autoimmunity is triggered.},
	keywords = {Alleles, Autoimmune Diseases, Autoimmunity, Chromosome Mapping, Epigenesis, Genetic, Genetic Loci, Genetic Predisposition to Disease, Genetic Variation, Genomics, Humans, Immune System, Immunophenotyping, Models, Molecular, Phenotype, Prevalence, Risk},
	issn = {1471-0064},
	doi = {10.1038/nrg.2015.33},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Autoimmune+diseases+-+connecting+risk+alleles+with+molecular+traits+of+the+immune+system},
	author = {Gutierrez-Arcelus, Maria and Rich, Stephen S and Raychaudhuri, Soumya}
}
@article {1001526,
	title = {A general framework for meta-analyzing dependent studies with overlapping subjects in association mapping},
	journal = {Hum Mol Genet},
	volume = {25},
	number = {9},
	year = {2016},
	month = {2016 May 01},
	pages = {1857-66},
	abstract = {Meta-analysis strategies have become critical to augment power of genome-wide association studies (GWAS). To reduce genotyping or sequencing cost, many studies today utilize shared controls, and these individuals can inadvertently overlap among multiple studies. If these overlapping individuals are not taken into account in meta-analysis, they can induce spurious associations. In this article, we propose a general framework for adjusting association statistics to account for overlapping subjects within a meta-analysis. The key idea of our method is to transform the covariance structure of the data, so it can be used in downstream analyses. As a result, the strategy is very flexible and allows a wide range of meta-analysis methods, such as the random effects model, to account for overlapping subjects. Using simulations and real datasets, we demonstrate that our method has utility in meta-analyses of GWAS, as well as in a multi-tissue mouse expression quantitative trait loci (eQTL) study where our method increases the number of discovered eQTL by up to 19\% compared with existing methods.},
	issn = {1460-2083},
	doi = {10.1093/hmg/ddw049},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=A+general+framework+for+meta-analyzing+dependent+studies+with+overlapping+subjects+in+association+mapping},
	author = {Han, Buhm and Duong, Dat and Sul, Jae Hoon and de Bakker, Paul I W and Eskin, Eleazar and Raychaudhuri, Soumya}
}
@article {1001521,
	title = {A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases},
	journal = {Nat Genet},
	volume = {48},
	number = {7},
	year = {2016},
	month = {2016 Jul},
	pages = {803-10},
	abstract = {There is growing evidence of shared risk alleles for complex traits (pleiotropy), including autoimmune and neuropsychiatric diseases. This might be due to sharing among all individuals (whole-group pleiotropy) or a subset of individuals in a genetically heterogeneous cohort (subgroup heterogeneity). Here we describe the use of a well-powered statistic, BUHMBOX, to distinguish between those two situations using genotype data. We observed a shared genetic basis for 11 autoimmune diseases and type 1 diabetes (T1D; P \&lt; 1 {\texttimes} 10(-4)) and for 11 autoimmune diseases and rheumatoid arthritis (RA; P \&lt; 1 {\texttimes} 10(-3)). This sharing was not explained by subgroup heterogeneity (corrected PBUHMBOX \&gt; 0.2; 6,670 T1D cases and 7,279 RA cases). Genetic sharing between seronegative and seropostive RA (P \&lt; 1 {\texttimes} 10(-9)) had significant evidence of subgroup heterogeneity, suggesting a subgroup of seropositive-like cases within seronegative cases (PBUHMBOX = 0.008; 2,406 seronegative RA cases). We also observed a shared genetic basis for major depressive disorder (MDD) and schizophrenia (P \&lt; 1 {\texttimes} 10(-4)) that was not explained by subgroup heterogeneity (PBUHMBOX = 0.28; 9,238 MDD cases).},
	issn = {1546-1718},
	doi = {10.1038/ng.3572},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=A+method+to+decipher+pleiotropy+by+detecting+underlying+heterogeneity+driven+by+hidden+subgroups+applied+to+autoimmune+and+neuropsychiatric+diseases},
	author = {Han, Buhm$\#$ and Pouget, Jennie G$\#$ and Slowikowski, Kamil and Stahl, Eli and Lee, Cue Hyunkyu and Diogo, Dorothee and Hu, Xinli and Park, Yu Rang and Kim, Eunji and Gregersen, Peter K and Dahlqvist, Solbritt Rantap{\"a}{\"a} and Worthington, Jane and Martin, Javier and Eyre, Steve and Klareskog, Lars and Huizinga, Tom and Chen, Wei-Min and Onengut-Gumuscu, Suna and Rich, Stephen S and Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium and Wray, Naomi R and Raychaudhuri, Soumya}
}
@article {1109666,
	title = {Genome-Wide Association Studies Suggest Limited Immune Gene Enrichment in Schizophrenia Compared to 5 Autoimmune Diseases},
	journal = {Schizophr Bull},
	volume = {42},
	number = {5},
	year = {2016},
	month = {2016 Sep},
	pages = {1176-84},
	abstract = {There has been intense debate over the immunological basis of schizophrenia, and the potential utility of adjunct immunotherapies. The major histocompatibility complex is consistently the most powerful region of association in genome-wide association studies (GWASs) of schizophrenia and has been interpreted as strong genetic evidence supporting the immune hypothesis. However, global pathway analyses provide inconsistent evidence of immune involvement in schizophrenia, and it remains unclear whether genetic data support an immune etiology per se. Here we empirically test the hypothesis that variation in immune genes contributes to schizophrenia. We show that there is no enrichment of immune loci outside of the MHC region in the largest genetic study of schizophrenia conducted to date, in contrast to 5 diseases of known immune origin. Among 108 regions of the genome previously associated with schizophrenia, we identify 6 immune candidates (DPP4, HSPD1, EGR1, CLU, ESAM, NFATC3) encoding proteins with alternative, nonimmune roles in the brain. While our findings do not refute evidence that has accumulated in support of the immune hypothesis, they suggest that genetically mediated alterations in immune function may not play a major role in schizophrenia susceptibility. Instead, there may be a role for pleiotropic effects of a small number of immune genes that also regulate brain development and plasticity. Whether immune alterations drive schizophrenia progression is an important question to be addressed by future research, especially in light of the growing interest in applying immunotherapies in schizophrenia.},
	issn = {1745-1701},
	doi = {10.1093/schbul/sbw059},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Genome-Wide+Association+Studies+Suggest+Limited+Immune+Gene+Enrichment+in+Schizophrenia+Compared+to+5+Autoimmune+Diseases},
	author = {Pouget, Jennie G and Gon{\c c}alves, Vanessa F and Schizophrenia Working Group of the Psychiatric Genomics Consortium and Spain, Sarah L and Finucane, Hilary K and Raychaudhuri, Soumya and Kennedy, James L and Knight, Jo}
}
@article {1001696,
	title = {An argument for early genomic sequencing in atypical cases: a WISP3 variant leads to diagnosis of progressive pseudorheumatoid arthropathy of childhood},
	journal = {Rheumatology (Oxford)},
	volume = {55},
	number = {3},
	year = {2016},
	month = {2016 Mar},
	pages = {586-9},
	keywords = {Adult, CCN Intercellular Signaling Proteins, Early Diagnosis, Genetic Variation, Genomics, Humans, Joint Diseases, Male, Needs Assessment, Risk Assessment, Severity of Illness Index, Time Factors},
	issn = {1462-0332},
	doi = {10.1093/rheumatology/kev367},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=An+argument+for+early+genomic+sequencing+in+atypical+cases\%3A+a+WISP3+variant+leads+to+diagnosis+of+progressive+pseudorheumatoid+arthropathy+of+childhood},
	author = {Cassa, Christopher A and Smith, Stacy E and Docken, William and Hoffman, Erin and McLaughlin, Heather and Chun, Sung and Leshchiner, Ignaty and Miraoui, Hichem and Raychaudhuri, Soumya and Frank, Natasha Y and Wilson, Brian J and Sunyaev, Shamil R. and Maas, Richard L and Brigham Genomic Medicine and Vuzman, Dana}
}
@article {1001691,
	title = {Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation},
	journal = {Nat Commun},
	volume = {7},
	year = {2016},
	month = {2016 Apr 07},
	pages = {10979},
	abstract = {Although genome-wide association studies have identified over 100 risk loci that explain \~{}33\% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.},
	keywords = {Acetylation, African Americans, Atlases as Topic, Cell Line, Tumor, Epigenesis, Genetic, European Continental Ancestry Group, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Histones, Humans, Inheritance Patterns, Linkage Disequilibrium, Male, Polymorphism, Single Nucleotide, Prostatic Neoplasms},
	issn = {2041-1723},
	doi = {10.1038/ncomms10979},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Atlas+of+prostate+cancer+heritability+in+European+and+African-American+men+pinpoints+tissue-specific+regulation},
	author = {Gusev, Alexander and Shi, Huwenbo and Kichaev, Gleb and Pomerantz, Mark and Li, Fugen and Long, Henry W and Ingles, Sue A and Kittles, Rick A and Strom, Sara S and Rybicki, Benjamin A and Nemesure, Barbara and Isaacs, William B and Zheng, Wei and Pettaway, Curtis A and Yeboah, Edward D and Tettey, Yao and Biritwum, Richard B and Adjei, Andrew A and Tay, Evelyn and Truelove, Ann and Niwa, Shelley and Chokkalingam, Anand P and John, Esther M and Murphy, Adam B and Signorello, Lisa B and Carpten, John and Leske, M Cristina and Wu, Suh-Yuh and Hennis, Anslem J M and Neslund-Dudas, Christine and Hsing, Ann W and Chu, Lisa and Goodman, Phyllis J and Klein, Eric A and Witte, John S and Casey, Graham and Kaggwa, Sam and Cook, Michael B and Stram, Daniel O and Blot, William J and Eeles, Rosalind A and Easton, Douglas and Kote-Jarai, Zsofia and Al Olama, Ali Amin and Benlloch, Sara and Muir, Kenneth and Giles, Graham G and Southey, Melissa C and Fitzgerald, Liesel M and Gronberg, Henrik and Wiklund, Fredrik and Aly, Markus and Henderson, Brian E and Schleutker, Johanna and Wahlfors, Tiina and Tammela, Teuvo L J and Nordestgaard, B{\o}rge G and Key, Tim J and Travis, Ruth C and Neal, David E and Donovan, Jenny L and Hamdy, Freddie C and Pharoah, Paul and Pashayan, Nora and Khaw, Kay-Tee and Stanford, Janet L and Thibodeau, Stephen N and McDonnell, Shannon K and Schaid, Daniel J and Maier, Christiane and Vogel, Walther and Luedeke, Manuel and Herkommer, Kathleen and Kibel, Adam S and Cybulski, Cezary and Wokolorczyk, Dominika and Kluzniak, Wojciech and Cannon-Albright, Lisa and Teerlink, Craig and Brenner, Hermann and Dieffenbach, Aida K and Arndt, Volker and Park, Jong Y and Sellers, Thomas A and Lin, Hui-Yi and Slavov, Chavdar and Kaneva, Radka and Mitev, Vanio and Batra, Jyotsna and Spurdle, Amanda and Clements, Judith A and Teixeira, Manuel R and Pandha, Hardev and Michael, Agnieszka and Paulo, Paula and Maia, Sofia and Kierzek, Andrzej and PRACTICAL consortium and Conti, David V and Albanes, Demetrius and Berg, Christine and Berndt, Sonja I and Campa, Daniele and Crawford, E David and Diver, W Ryan and Gapstur, Susan M and Gaziano, J Michael and Giovannucci, Edward and Hoover, Robert and Hunter, David J and Johansson, Mattias and Kraft, Peter and Le Marchand, Loic and Lindstr{\"o}m, Sara and Navarro, Carmen and Overvad, Kim and Riboli, Elio and Siddiq, Afshan and Stevens, Victoria L and Trichopoulos, Dimitrios and Paolo Vineis and Yeager, Meredith and Trynka, Gosia and Raychaudhuri, Soumya and Schumacher, Frederick R and Price, Alkes L and Freedman, Matthew L and Haiman, Christopher A and Pasaniuc, Bogdan}
}
@article {1001706,
	title = {Familial aggregation of arthritis-related diseases in seropositive and seronegative rheumatoid arthritis: a register-based case-control study in Sweden},
	journal = {Ann Rheum Dis},
	volume = {75},
	number = {1},
	year = {2016},
	month = {2016 Jan},
	pages = {183-9},
	abstract = {OBJECTIVES: Our objective was to estimate the risk of developing rheumatoid arthritis (RA) associated with a family history of non-RA arthritis-related diseases. This familial co-aggregation is of clinical interest since it is often encountered when assessing family history of RA specifically, but also informative on the genetic overlap between these diseases. Since anticitrullinated peptide antibodies/rheumatoid factor (RF)-positive and RF-negative RA have both specific and shared genetic factors, the familial co-aggregation was assessed separately for seropositive and seronegative disease. METHODS: Nested case-control study in prospectively recorded Swedish total population data. The Multi-Generation Register identified first-degree relatives. RA and arthritis-related diseases were ascertained through the nationwide patient register. RA serology was based on International Classification of Diseases tenth revision coded diagnoses, mainly reflecting RF. Familial risks were calculated using conditional logistic regression. Results were replicated using the Swedish rheumatology register. RESULTS: Familial co-aggregation was found between RA and every studied arthritis-related disease, but the magnitude varied widely, from juvenile idiopathic arthritis (JIA) (seropositive RA OR=3.98 (3.01 to 5.26); seronegative RA OR=5.70 (3.47 to 9.36)) to osteoarthritis (seropositive RA OR=1.03 (1.00 to 1.06); seronegative RA OR=1.05 (1.00 to 1.09)). The familial co-aggregation pattern of non-RA arthritis-related diseases was overall similar for seropositive and seronegative RA. Among those with family history of RA, relatives{\textquoteright} other arthritis-related diseases conferred little or no additional risk. CONCLUSIONS: Although family history of several arthritis-related diseases may be useful to predict RA (eg, lupus and JIA), others (eg, osteoarthritis and arthralgia) are less useful. Seropositive and seronegative RA had rather similar familial co-aggregation patterns with arthritis-related diseases, suggesting that the two RA subsets are similar in the genetic factors that overlap with these diseases.},
	keywords = {Adult, Arthritis, Arthritis, Rheumatoid, Autoantibodies, Case-Control Studies, Female, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Peptides, Cyclic, Registries, Rheumatoid Factor, Risk Assessment, Sweden},
	issn = {1468-2060},
	doi = {10.1136/annrheumdis-2014-206133},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Familial+aggregation+of+arthritis-related+diseases+in+seropositive+and+seronegative+rheumatoid+arthritis\%3A+a+register-based+case-control+study+in+Sweden},
	author = {Frisell, Thomas and Hellgren, Karin and Alfredsson, Lars and Raychaudhuri, Soumya and Klareskog, Lars and Askling, Johan}
}
@article {1001711,
	title = {Functional implications of disease-specific variants in loci jointly associated with coeliac disease and rheumatoid arthritis},
	journal = {Hum Mol Genet},
	volume = {25},
	number = {1},
	year = {2016},
	month = {2016 Jan 01},
	pages = {180-90},
	abstract = {Hundreds of genomic loci have been associated with a significant number of immune-mediated diseases, and a large proportion of these associated loci are shared among traits. Both the molecular mechanisms by which these loci confer disease susceptibility and the extent to which shared loci are implicated in a common pathogenesis are unknown. We therefore sought to dissect the functional components at loci shared between two autoimmune diseases: coeliac disease (CeD) and rheumatoid arthritis (RA). We used a cohort of 12 381 CeD cases and 7827 controls, and another cohort of 13 819 RA cases and 12 897 controls, all genotyped with the Immunochip platform. In the joint analysis, we replicated 19 previously identified loci shared by CeD and RA and discovered five new non-HLA loci shared by CeD and RA. Our fine-mapping results indicate that in nine of 24 shared loci the associated variants are distinct in the two diseases. Using cell-type-specific histone markers, we observed that loci which pointed to the same variants in both diseases were enriched for marks of promoters active in CD14+ and CD34+ immune cells (P \&lt; 0.001), while loci pointing to distinct variants in one of the two diseases showed enrichment for marks of more specialized cell types, like CD4+ regulatory T cells in CeD (P \&lt; 0.0001) compared with Th17 and CD15+ in RA (P = 0.0029).},
	keywords = {Arthritis, Rheumatoid, CD4-Positive T-Lymphocytes, Celiac Disease, Chromosome Mapping, Cohort Studies, Genetic Association Studies, Humans, Quantitative Trait Loci},
	issn = {1460-2083},
	doi = {10.1093/hmg/ddv455},
	url = { https://www.ncbi.nlm.nih.gov/pubmed/?term=Functional+implications+of+disease-specific+variants+in+loci+jointly+associated+with+coeliac+disease+and+rheumatoid+arthritis},
	author = {Gutierrez-Achury, Javier and Zorro, Maria Magdalena and Rica{\~n}o-Ponce, Isis and Zhernakova, Daria V and Coeliac Disease Immunochip Consortium, RACI Consortium and Diogo, Doroth{\'e}e and Raychaudhuri, Soumya and Franke, Lude and Trynka, Gosia and Wijmenga, Cisca and Zhernakova, Alexandra}
}
@article {1001701,
	title = {Loci associated with N-glycosylation of human IgG are not associated with rheumatoid arthritis: a Mendelian randomisation study},
	journal = {Ann Rheum Dis},
	volume = {75},
	number = {1},
	year = {2016},
	month = {2016 Jan},
	pages = {317-20},
	abstract = {OBJECTIVES: A recent study identified 16 genetic variants associated with N-glycosylation of human IgG. Several of the genomic regions where these single nucleotide polymorphisms (SNPs) reside have also been associated with autoimmune disease (AID) susceptibility, suggesting there may be pleiotropy (genetic sharing) between loci controlling both N-glycosylation and AIDs. We investigated this by testing variants associated with levels of IgG N-glycosylation for association with rheumatoid arthritis (RA) susceptibility using a Mendelian randomisation study, and testing a subset of these variants in a less well-powered study of treatment response and severity. METHODS: SNPs showing association with IgG N-glycosylation were analysed for association with RA susceptibility in 14 361 RA cases and 43 923 controls. Five SNPs were tested for association with response to anti-tumour necrosis factor (TNF) therapy in 1081 RA patient samples and for association with radiological disease severity in 342 patients. RESULTS: Only one SNP (rs9296009) associated with N-glycosylation showed an association (p=6.92{\texttimes}10(-266)) with RA susceptibility, although this was due to linkage disequilibrium with causal human leukocyte antigen (HLA) variants. Four regions of the genome harboured SNPs associated with both traits (shared loci); although statistical analysis indicated that the associations observed for the two traits are independent. No SNPs showed association with response to anti-TNF therapy. One SNP rs12342831 was modestly associated with Larsen score (p=0.05). CONCLUSIONS: In a large, well-powered cohort of RA patients, we show SNPs driving levels of N-glycosylation have no association with RA susceptibility, indicating colocalisation of associated SNPs are not necessarily indicative of a shared genetic background or a role for glycosylation in disease susceptibility.},
	keywords = {Arthritis, Rheumatoid, Biological Products, Case-Control Studies, Genetic Loci, Genetic Predisposition to Disease, Glycosylation, Humans, Immunoglobulin G, Linkage Disequilibrium, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, Severity of Illness Index, Treatment Outcome, Tumor Necrosis Factor-alpha},
	issn = {1468-2060},
	doi = {10.1136/annrheumdis-2014-207210},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/26386125},
	author = {Yarwood, Annie and Viatte, Sebastien and Okada, Yukinori and Plenge, Robert and Yamamoto, Kazuhiko and BRAGGSS, RACI and Barton, Anne and Symmons, Deborah and Raychaudhuri, Soumya and Klareskog, Lars and Gregersen, Peter and Worthington, Jane and Eyre, Steve}
}
@article {1001656,
	title = {52 Genetic Loci Influencing Myocardial Mass},
	journal = {J Am Coll Cardiol},
	volume = {68},
	number = {13},
	year = {2016},
	month = {2016 Sep 27},
	pages = {1435-1448},
	abstract = {BACKGROUND: Myocardial mass is a key determinant of cardiac muscle function and hypertrophy. Myocardial depolarization leading to cardiac muscle contraction is reflected by the amplitude and duration of the QRS complex on the electrocardiogram (ECG). Abnormal QRS amplitude or duration reflect changes in myocardial mass and conduction, and are associated with increased risk of heart failure and death. OBJECTIVES: This meta-analysis sought to gain insights into the genetic determinants of myocardial mass. METHODS: We carried out a genome-wide association meta-analysis of 4 QRS traits in up to 73,518 individuals of European ancestry, followed by extensive biological and functional assessment. RESULTS: We identified 52 genomic loci, of which 32 are novel, that are reliably associated with 1 or more QRS phenotypes at p\&nbsp;\&lt; 1\&nbsp;{\texttimes} 10(-8). These loci are enriched in regions of open chromatin, histone modifications, and transcription factor binding, suggesting that they represent regions of the genome that are actively transcribed in the human heart. Pathway analyses provided evidence that these loci play a role in cardiac hypertrophy. We further highlighted 67\&nbsp;candidate genes at the identified loci that are preferentially expressed in cardiac tissue and associated with cardiac abnormalities in Drosophila melanogaster and Mus musculus. We validated the regulatory function of a novel variant in the SCN5A/SCN10A locus in\&nbsp;vitro and in\&nbsp;vivo. CONCLUSIONS: Taken together, our findings provide new insights into genes and biological pathways controlling myocardial mass and may help identify novel therapeutic targets.},
	keywords = {Animals, Cardiomegaly, Genetic Loci, Genome-Wide Association Study, Humans},
	issn = {1558-3597},
	doi = {10.1016/j.jacc.2016.07.729},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/27659466},
	author = {van der Harst, Pim and van Setten, Jessica and Verweij, Niek and Vogler, Georg and Franke, Lude and Maurano, Matthew T and Wang, Xinchen and Mateo Leach, Irene and Eijgelsheim, Mark and Sotoodehnia, Nona and Hayward, Caroline and Sorice, Rossella and Meirelles, Osorio and Lyytik{\"a}inen, Leo-Pekka and Pola{\v s}ek, Ozren and Tanaka, Toshiko and Arking, Dan E and Ulivi, Sheila and Trompet, Stella and M{\"u}ller-Nurasyid, Martina and Smith, Albert V and D{\"o}rr, Marcus and Kerr, Kathleen F and Magnani, Jared W and del Greco M, Fabiola and Zhang, Weihua and Nolte, Ilja M and Silva, Claudia T and Padmanabhan, Sandosh and Tragante, Vinicius and Esko, T{\~o}nu and Abecasis, Gon{\c c}alo R and Adriaens, Michiel E and Andersen, Karl and Barnett, Phil and Bis, Joshua C and Bodmer, Rolf and Buckley, Brendan M and Campbell, Harry and Cannon, Megan V and Chakravarti, Aravinda and Chen, Lin Y and Delitala, Alessandro and Devereux, Richard B and Doevendans, Pieter A and Dominiczak, Anna F and Ferrucci, Luigi and Ford, Ian and Gieger, Christian and Harris, Tamara B and Haugen, Eric and Heinig, Matthias and Hernandez, Dena G and Hillege, Hans L and Hirschhorn, Joel N and Hofman, Albert and Hubner, Norbert and Hwang, Shih-Jen and Iorio, Annamaria and K{\"a}h{\"o}nen, Mika and Kellis, Manolis and Kolcic, Ivana and Kooner, Ishminder K and Kooner, Jaspal S and Kors, Jan A and Lakatta, Edward G and Lage, Kasper and Launer, Lenore J and Levy, Daniel and Lundby, Alicia and Macfarlane, Peter W and May, Dalit and Meitinger, Thomas and Metspalu, Andres and Nappo, Stefania and Naitza, Silvia and Neph, Shane and Nord, Alex S and Nutile, Teresa and Okin, Peter M and Olsen, Jesper V and Oostra, Ben A and Penninger, Josef M and Pennacchio, Len A and Pers, Tune H and Perz, Siegfried and Peters, Annette and Pinto, Yigal M and Pfeufer, Arne and Pilia, Maria Grazia and Pramstaller, Peter P and Prins, Bram P and Raitakari, Olli T and Raychaudhuri, Soumya and Rice, Ken M and Rossin, Elizabeth J and Rotter, Jerome I and Schafer, Sebastian and Schlessinger, David and Schmidt, Carsten O and Sehmi, Jobanpreet and Sillj{\'e}, Herman H W and Sinagra, Gianfranco and Sinner, Moritz F and Slowikowski, Kamil and Soliman, Elsayed Z and Spector, Timothy D and Spiering, Wilko and Stamatoyannopoulos, John A and Stolk, Ronald P and Strauch, Konstantin and Tan, Sian-Tsung and Tarasov, Kirill V and Trinh, Bosco and Uitterlinden, Andre G and van den Boogaard, Malou and van Duijn, Cornelia M and van Gilst, Wiek H and Viikari, Jorma S and Visscher, Peter M and Vitart, Veronique and V{\"o}lker, Uwe and Waldenberger, Melanie and Weichenberger, Christian X and Westra, Harm-Jan and Wijmenga, Cisca and Wolffenbuttel, Bruce H and Yang, Jian and Bezzina, Connie R and Munroe, Patricia B and Snieder, Harold and Wright, Alan F and Rudan, Igor and Boyer, Laurie A and Asselbergs, Folkert W and van Veldhuisen, Dirk J and Stricker, Bruno H and Psaty, Bruce M and Ciullo, Marina and Sanna, Serena and Lehtim{\"a}ki, Terho and Wilson, James F and Bandinelli, Stefania and Alonso, Alvaro and Gasparini, Paolo and Jukema, J Wouter and K{\"a}{\"a}b, Stefan and Gudnason, Vilmundur and Felix, Stephan B and Heckbert, Susan R and de Boer, Rudolf A and Newton-Cheh, Christopher and Hicks, Andrew A and Chambers, John C and Jamshidi, Yalda and Visel, Axel and Christoffels, Vincent M and Isaacs, Aaron and Samani, Nilesh J and de Bakker, Paul I W}
}
@article {1001686,
	title = {Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci},
	journal = {Nat Genet},
	volume = {48},
	number = {5},
	year = {2016},
	month = {2016 May},
	pages = {510-8},
	abstract = {We simultaneously investigated the genetic landscape of ankylosing spondylitis, Crohn{\textquoteright}s disease, psoriasis, primary sclerosing cholangitis and ulcerative colitis to investigate pleiotropy and the relationship between these clinically related diseases. Using high-density genotype data from more than 86,000 individuals of European ancestry, we identified 244 independent multidisease signals, including 27 new genome-wide significant susceptibility loci and 3 unreported shared risk loci. Complex pleiotropy was supported when contrasting multidisease signals with expression data sets from human, rat and mouse together with epigenetic and expressed enhancer profiles. The comorbidities among the five immune diseases were best explained by biological pleiotropy rather than heterogeneity (a subgroup of cases genetically identical to those with another disease, possibly owing to diagnostic misclassification, molecular subtypes or excessive comorbidity). In particular, the strong comorbidity between primary sclerosing cholangitis and inflammatory bowel disease is likely the result of a unique disease, which is genetically distinct from classical inflammatory bowel disease phenotypes.},
	keywords = {Bayes Theorem, Cholangitis, Sclerosing, Chronic Disease, Colitis, Ulcerative, Comorbidity, Crohn Disease, Genetic Heterogeneity, Genetic Pleiotropy, Genetic Variation, Genome-Wide Association Study, Genotype, Humans, Inflammation, Psoriasis, Quantitative Trait Loci, Spondylitis, Ankylosing},
	issn = {1546-1718},
	doi = {10.1038/ng.3528},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Analysis+of+five+chronic+inflammatory+diseases+identifies+27+new+associations+and+highlights+disease-specific+patterns+at+shared+loci},
	author = {Ellinghaus, David and Jostins, Luke and Spain, Sarah L and Cortes, Adrian and Bethune, J{\"o}rn and Han, Buhm and Park, Yu Rang and Raychaudhuri, Soumya and Pouget, Jennie G and H{\"u}benthal, Matthias and Folseraas, Trine and Wang, Yunpeng and Esko, Tonu and Metspalu, Andres and Westra, Harm-Jan and Franke, Lude and Pers, Tune H and Weersma, Rinse K and Collij, Valerie and D{\textquoteright}Amato, Mauro and Halfvarson, Jonas and Jensen, Anders Boeck and Lieb, Wolfgang and Degenhardt, Franziska and Forstner, Andreas J and Hofmann, Andrea and International IBD Genetics Consortium (IIBDGC) and International Genetics of Ankylosing Spondylitis Consortium (IGAS) and International PSC Study Group (IPSCSG) and Genetic Analysis of Psoriasis Consortium (GAPC) and Psoriasis Association Genetics Extension (PAGE) and Schreiber, Stefan and Mrowietz, Ulrich and Juran, Brian D and Lazaridis, Konstantinos N and Brunak, S{\o}ren and Dale, Anders M and Trembath, Richard C and Weidinger, Stephan and Weichenthal, Michael and Ellinghaus, Eva and Elder, James T and Barker, Jonathan N W N and Andreassen, Ole A and McGovern, Dermot P and Karlsen, Tom H and Barrett, Jeffrey C and Parkes, Miles and Brown, Matthew A and Franke, Andre}
}
@article {1001676,
	title = {Contribution of a Non-classical HLA Gene, HLA-DOA, to the Risk of Rheumatoid Arthritis},
	journal = {Am J Hum Genet},
	volume = {99},
	number = {2},
	year = {2016},
	month = {2016 Aug 04},
	pages = {366-74},
	abstract = {Despite the progress in human leukocyte antigen (HLA) causal variant mapping, independent localization of major histocompatibility complex (MHC) risk from classical HLA genes is challenging. Here, we conducted a large-scale MHC fine-mapping analysis of rheumatoid arthritis (RA) in a Japanese population (6,244 RA cases and 23,731 controls) population by using HLA imputation, followed by a multi-ethnic validation study including east Asian and European populations (n = 7,097 and 23,149, respectively). Our study identified an independent risk of a synonymous mutation at HLA-DOA, a non-classical HLA gene, on anti-citrullinated protein autoantibody (ACPA)-positive RA risk (p = 1.4\&nbsp;{\texttimes} 10(-9)), which demonstrated a cis-expression quantitative trait loci (cis-eQTL) effect on HLA-DOA expression. Trans-ethnic comparison revealed different linkage disequilibrium (LD) patterns in HLA-DOA and HLA-DRB1, explaining the observed HLA-DOA variant risk heterogeneity among ethnicities, which was most evident in the Japanese population. Although previous HLA fine-mapping studies have identified amino acid polymorphisms of the classical HLA genes as driving genetic susceptibility to disease, our study additionally identifies the dosage contribution of a non-classical HLA gene to disease etiology. Our study contributes to the\&nbsp;understanding of HLA immunology in human diseases and suggests the value of incorporating additional ancestry in MHC fine-mapping.},
	keywords = {Arthritis, Rheumatoid, Asian Continental Ancestry Group, Autoantibodies, Citrulline, Ethnic Groups, Europe, European Continental Ancestry Group, Genetic Predisposition to Disease, Genome-Wide Association Study, HLA-D Antigens, HLA-DRB1 Chains, Humans, Japan, Linkage Disequilibrium, Phenotype, Polymorphism, Single Nucleotide},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2016.06.019},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Contribution+of+a+Non-classical+HLA+Gene\%2C+HLA-DOA\%2C+to+the+Risk+of+Rheumatoid+Arthritis},
	author = {Okada, Yukinori and Suzuki, Akari and Ikari, Katsunori and Terao, Chikashi and Kochi, Yuta and Ohmura, Koichiro and Higasa, Koichiro and Akiyama, Masato and Ashikawa, Kyota and Kanai, Masahiro and Hirata, Jun and Suita, Naomasa and Teo, Yik-Ying and Xu, Huji and Bae, Sang-Cheol and Takahashi, Atsushi and Momozawa, Yukihide and Matsuda, Koichi and Momohara, Shigeki and Taniguchi, Atsuo and Yamada, Ryo and Mimori, Tsuneyo and Kubo, Michiaki and Brown, Matthew A and Raychaudhuri, Soumya and Matsuda, Fumihiko and Yamanaka, Hisashi and Kamatani, Yoichiro and Yamamoto, Kazuhiko}
}
@article {1001651,
	title = {Fine-mapping the MHC locus in juvenile idiopathic arthritis (JIA) reveals genetic heterogeneity corresponding to distinct adult inflammatory arthritic diseases},
	journal = {Ann Rheum Dis},
	volume = {76},
	number = {4},
	year = {2016},
	month = {2016 Apr},
	pages = {765-772},
	abstract = {OBJECTIVES: Juvenile idiopathic arthritis (JIA) is a heterogeneous group of diseases, comprising seven categories. Genetic data could potentially be used to help redefine JIA categories and improve the current classification system. The human leucocyte antigen (HLA) region is strongly associated with JIA. Fine-mapping of the region was performed to look for similarities and differences in HLA associations between the JIA categories and define correspondences with adult inflammatory arthritides. METHODS: Dense genotype data from the HLA region, from the Immunochip array for 5043 JIA cases and 14 390 controls, were used to impute single-nucleotide polymorphisms, HLA classical alleles and amino acids. Bivariate analysis was performed to investigate genetic correlation between the JIA categories. Conditional analysis was used to identify additional effects within the region. Comparison of the findings with those in adult inflammatory arthritic diseases was performed. RESULTS: We identified category-specific associations and have demonstrated for the first time that rheumatoid factor (RF)-negative polyarticular JIA and oligoarticular JIA are genetically similar in their HLA associations. We also observe that each JIA category potentially has an adult counterpart. The RF-positive polyarthritis association at HLA-DRB1 amino acid at position 13 mirrors the association in adult seropositive rheumatoid arthritis (RA). Interestingly, the combined oligoarthritis and RF-negative polyarthritis dataset shares the same association with adult seronegative RA. CONCLUSIONS: The findings suggest the value of using genetic data in helping to classify the categories of this heterogeneous disease. Mapping JIA categories to adult counterparts could enable shared knowledge of disease pathogenesis and aetiology and facilitate transition from paediatric to adult services.},
	keywords = {Adult, Alleles, Amino Acids, Arthritis, Juvenile, Arthritis, Rheumatoid, Case-Control Studies, Child, Genotype, HLA Antigens, HLA-DRB1 Chains, Humans, Major Histocompatibility Complex, Polymorphism, Single Nucleotide, Rheumatoid Factor},
	issn = {1468-2060},
	doi = {10.1136/annrheumdis-2016-210025},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Fine-mapping+the+MHC+locus+in+juvenile+idiopathic+arthritis+(JIA)+reveals+genetic+heterogeneity+corresponding+to+distinct+adult+inflammatory+arthritic+diseases},
	author = {Hinks, A and Bowes, J and Cobb, J and Ainsworth, H C and Marion, M C and Comeau, M E and Sudman, M and Han, B and Juvenile Arthritis Consortium for Immunochip and Becker, M L and Bohnsack, J F and de Bakker, P I W and Haas, J P and Hazen, M and Lovell, D J and Nigrovic, P A and Nordal, E and Punnaro, M and Rosenberg, A M and Rygg, M and Smith, S L and Wise, C A and Videm, V and Wedderburn, L R and Yarwood, A and Yeung, R S M and Prahalad, S and Langefeld, C D and Raychaudhuri, S and Thompson, S D and Thomson, W}
}
@article {1001661,
	title = {Genetic risk of extranodal natural killer T-cell lymphoma: a genome-wide association study},
	journal = {Lancet Oncol},
	volume = {17},
	number = {9},
	year = {2016},
	month = {2016 Sep},
	pages = {1240-7},
	abstract = {BACKGROUND: Extranodal natural killer T-cell lymphoma (NKTCL), nasal type, is a rare and aggressive malignancy that occurs predominantly in Asian and Latin American populations. Although Epstein-Barr virus infection is a known risk factor, other risk factors and the pathogenesis of NKTCL are not well understood. We aimed to identify common genetic variants affecting individual risk of NKTCL. METHODS: We did a genome-wide association study of 189 patients with extranodal NKTCL, nasal type (WHO classification criteria; cases) and 957 controls from Guangdong province, southern China. We validated our findings in four independent case-control series, including 75 cases from Guangdong province and 296 controls from Hong Kong, 65 cases and 983 controls from Guangdong province, 125 cases and 1110 controls from Beijing (northern China), and 60 cases and 2476 controls from Singapore. We used imputation and conditional logistic regression analyses to fine-map the associations. We also did a meta-analysis of the replication series and of the entire dataset. FINDINGS: Associations exceeding the genome-wide significance threshold (p\&lt;5 {\texttimes} 10(-8)) were seen at 51 single-nucleotide polymorphisms (SNPs) mapping to the class II MHC region on chromosome 6, with rs9277378 (located in HLA-DPB1) having the strongest association with NKTCL susceptibility (p=4{\textperiodcentered}21 {\texttimes} 10(-19), odds ratio [OR] 1{\textperiodcentered}84 [95\% CI 1{\textperiodcentered}61-2{\textperiodcentered}11] in meta-analysis of entire dataset). Imputation-based fine-mapping across the class II MHC region suggests that four aminoacid residues (Gly84-Gly85-Pro86-Met87) in near-complete linkage disequilibrium at the edge of the peptide-binding groove of HLA-DPB1 could account for most of the association between the rs9277378*A risk allele and NKTCL susceptibility (OR 2{\textperiodcentered}38, p value for haplotype 2{\textperiodcentered}32 {\texttimes} 10(-14)). This association is distinct from MHC associations with Epstein-Barr virus infection. INTERPRETATION: To our knowledge, this is the first time that a genetic variant conferring an NKTCL risk is noted at genome-wide significance. This finding underlines the importance of HLA-DP antigen presentation in the pathogenesis of NKTCL. FUNDING: Top-Notch Young Talents Program of China, Special Support Program of Guangdong, Specialized Research Fund for the Doctoral Program of Higher Education (20110171120099), Program for New Century Excellent Talents in University (NCET-11-0529), National Medical Research Council of Singapore (TCR12DEC005), Tanoto Foundation Professorship in Medical Oncology, New Century Foundation Limited, Ling Foundation, Singapore National Cancer Centre Research Fund, and the US National Institutes of Health (1R01AR062886, 5U01GM092691-04, and 1R01AR063759-01A1).},
	keywords = {Adult, Aged, Biomarkers, Tumor, Case-Control Studies, China, Female, Follow-Up Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Lymphoma, Extranodal NK-T-Cell, Male, Middle Aged, Neoplasm Staging, Polymorphism, Single Nucleotide, Prognosis, Risk Factors, Young Adult},
	issn = {1474-5488},
	doi = {10.1016/S1470-2045(16)30148-6},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/31879220},
	author = {Li, Zheng and Xia, Yi and Feng, Li-Na and Chen, Jie-Rong and Li, Hong-Min and Cui, Jing and Cai, Qing-Qing and Sim, Kar Seng and Nairism{\"a}gi, Maarja-Liisa and Laurensia, Yurike and Meah, Wee Yang and Liu, Wen-Sheng and Guo, Yun-Miao and Chen, Li-Zhen and Feng, Qi-Sheng and Pang, Chi Pui and Chen, Li Jia and Chew, Soo Hong and Ebstein, Richard P and Foo, Jia Nee and Liu, Jianjun and Ha, Jeslin and Khoo, Lay Poh and Chin, Suk Teng and Zeng, Yi-Xin and Aung, Tin and Chowbay, Balram and Diong, Colin Phipps and Zhang, Fen and Liu, Yan-Hui and Tang, Tiffany and Tao, Miriam and Quek, Richard and Mohamad, Farid and Tan, Soo Yong and Teh, Bin Tean and Ng, Siok Bian and Chng, Wee Joo and Ong, Choon Kiat and Okada, Yukinori and Raychaudhuri, Soumya and Lim, Soon Thye and Tan, Wen and Peng, Rou-Jun and Khor, Chiea Chuen and Bei, Jin-Xin}
}
@article {1001681,
	title = {Investigating the Causal Relationship of C-Reactive Protein with 32 Complex Somatic and Psychiatric Outcomes: A Large-Scale Cross-Consortium Mendelian Randomization Study},
	journal = {PLoS Med},
	volume = {13},
	number = {6},
	year = {2016},
	month = {2016 Jun},
	pages = {e1001976},
	abstract = {BACKGROUND: C-reactive protein (CRP) is associated with immune, cardiometabolic, and psychiatric traits and diseases. Yet it is inconclusive whether these associations are causal. METHODS AND FINDINGS: We performed Mendelian randomization (MR) analyses using two genetic risk scores (GRSs) as instrumental variables (IVs). The first GRS consisted of four single nucleotide polymorphisms (SNPs) in the CRP gene (GRSCRP), and the second consisted of 18 SNPs that were significantly associated with CRP levels in the largest genome-wide association study (GWAS) to date (GRSGWAS). To optimize power, we used summary statistics from GWAS consortia and tested the association of these two GRSs with 32 complex somatic and psychiatric outcomes, with up to 123,865 participants per outcome from populations of European ancestry. We performed heterogeneity tests to disentangle the pleiotropic effect of IVs. A Bonferroni-corrected significance level of less than 0.0016 was considered statistically significant. An observed p-value equal to or less than 0.05 was considered nominally significant evidence for a potential causal association, yet to be confirmed. The strengths (F-statistics) of the IVs were 31.92-3,761.29 and 82.32-9,403.21 for GRSCRP and GRSGWAS, respectively. CRP GRSGWAS showed a statistically significant protective relationship of a 10\% genetically elevated CRP level with the risk of schizophrenia (odds ratio [OR] 0.86 [95\% CI 0.79-0.94]; p \&lt; 0.001). We validated this finding with individual-level genotype data from the schizophrenia GWAS (OR 0.96 [95\% CI 0.94-0.98]; p \&lt; 1.72 {\texttimes} 10-6). Further, we found that a standardized CRP polygenic risk score (CRPPRS) at p-value thresholds of 1 {\texttimes} 10-4, 0.001, 0.01, 0.05, and 0.1 using individual-level data also showed a protective effect (OR \&lt; 1.00) against schizophrenia; the first CRPPRS (built of SNPs with p \&lt; 1 {\texttimes} 10-4) showed a statistically significant (p \&lt; 2.45 {\texttimes} 10-4) protective effect with an OR of 0.97 (95\% CI 0.95-0.99). The CRP GRSGWAS showed that a 10\% increase in genetically determined CRP level was significantly associated with coronary artery disease (OR 0.88 [95\% CI 0.84-0.94]; p \&lt; 2.4 {\texttimes} 10-5) and was nominally associated with the risk of inflammatory bowel disease (OR 0.85 [95\% CI 0.74-0.98]; p \&lt; 0.03), Crohn disease (OR 0.81 [95\% CI 0.70-0.94]; p \&lt; 0.005), psoriatic arthritis (OR 1.36 [95\% CI 1.00-1.84]; p \&lt; 0.049), knee osteoarthritis (OR 1.17 [95\% CI 1.01-1.36]; p \&lt; 0.04), and bipolar disorder (OR 1.21 [95\% CI 1.05-1.40]; p \&lt; 0.007) and with an increase of 0.72 (95\% CI 0.11-1.34; p \&lt; 0.02) mm Hg in systolic blood pressure, 0.45 (95\% CI 0.06-0.84; p \&lt; 0.02) mm Hg in diastolic blood pressure, 0.01 ml/min/1.73 m2 (95\% CI 0.003-0.02; p \&lt; 0.005) in estimated glomerular filtration rate from serum creatinine, 0.01 g/dl (95\% CI 0.0004-0.02; p \&lt; 0.04) in serum albumin level, and 0.03 g/dl (95\% CI 0.008-0.05; p \&lt; 0.009) in serum protein level. However, after adjustment for heterogeneity, neither GRS showed a significant effect of CRP level (at p \&lt; 0.0016) on any of these outcomes, including coronary artery disease, nor on the other 20 complex outcomes studied. Our study has two potential limitations: the limited variance explained by our genetic instruments modeling CRP levels in blood and the unobserved bias introduced by the use of summary statistics in our MR analyses. CONCLUSIONS: Genetically elevated CRP levels showed a significant potentially protective causal relationship with risk of schizophrenia. We observed nominal evidence at an observed p \&lt; 0.05 using either GRSCRP or GRSGWAS-with persistence after correction for heterogeneity-for a causal relationship of elevated CRP levels with psoriatic osteoarthritis, rheumatoid arthritis, knee osteoarthritis, systolic blood pressure, diastolic blood pressure, serum albumin, and bipolar disorder. These associations remain yet to be confirmed. We cannot verify any causal effect of CRP level on any of the other common somatic and neuropsychiatric outcomes investigated in the present study. This implies that interventions that lower CRP level are unlikely to result in decreased risk for the majority of common complex outcomes.},
	issn = {1549-1676},
	doi = {10.1371/journal.pmed.1001976},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Investigating+the+Causal+Relationship+of+C-Reactive+Protein+with+32+Complex+Somatic+and+Psychiatric+Outcomes\%3A+A+Large-Scale+Cross-Consortium+Mendelian+Randomization+Study},
	author = {Prins, Bram P and Abbasi, Ali and Wong, Anson and Vaez, Ahmad and Nolte, Ilja and Franceschini, Nora and Stuart, Philip E and Guterriez Achury, Javier and Mistry, Vanisha and Bradfield, Jonathan P and Valdes, Ana M and Bras, Jose and Shatunov, Aleksey and PAGE Consortium and International Stroke Genetics Consortium and Systemic Sclerosis consortium and Treat OA consortium and DIAGRAM Consortium and CARDIoGRAMplusC4D Consortium and ALS consortium and International Parkinson{\textquoteright}s Disease Genomics Consortium and Autism Spectrum Disorder Working Group of the Psychiatric Genomics Consortium and CKDGen consortium and GERAD1 Consortium and International Consortium for Blood Pressure and Schizophrenia Working Group of the Psychiatric Genomics Consortium and Inflammation Working Group of the CHARGE Consortium and Lu, Chen and Han, Buhm and Raychaudhuri, Soumya and Bevan, Steve and Mayes, Maureen D and Tsoi, Lam C and Evangelou, Evangelos and Nair, Rajan P and Grant, Struan F A and Polychronakos, Constantin and Radstake, Timothy R D and van Heel, David A and Dunstan, Melanie L and Wood, Nicholas W and Ammar Al-Chalabi and Dehghan, Abbas and Hakonarson, Hakon and Markus, Hugh S and Elder, James T and Knight, Jo and Arking, Dan E and Spector, Timothy D and Koeleman, Bobby P C and van Duijn, Cornelia M and Martin, Javier and Morris, Andrew P and Weersma, Rinse K and Wijmenga, Cisca and Munroe, Patricia B and Perry, John R B and Pouget, Jennie G and Jamshidi, Yalda and Snieder, Harold and Alizadeh, Behrooz Z}
}
@article {1001671,
	title = {Mapping rare, deleterious mutations in Factor H: Association with early onset, drusen burden, and lower antigenic levels in familial AMD},
	journal = {Sci Rep},
	volume = {6},
	year = {2016},
	month = {2016 Aug 30},
	pages = {31531},
	abstract = {The genetic architecture of age-related macular degeneration (AMD) involves numerous genetic variants, both common and rare, in the coding region of complement factor H (CFH). While these variants explain high disease burden in some families, they fail to explain the pathology in all. We selected families whose AMD was unexplained by known variants and performed whole exome sequencing to probe for other rare, highly penetrant variants. We identified four rare loss-of-function variants in CFH associated with AMD. Missense variant CFH 1:196646753 (C192F) segregated perfectly within a family characterized by advanced AMD and drusen temporal to the macula. Two families, each comprising a pair of affected siblings with extensive extramacular drusen, carried essential splice site variant CFH 1:196648924 (IVS6+1G\&gt;A) or missense variant rs139360826 (R175P). In a fourth family, missense variant rs121913058 (R127H) was associated with AMD. Most carriers had early onset bilateral advanced AMD and extramacular drusen. Carriers tended to have low serum Factor H levels, especially carriers of the splice variant. One missense variant (R127H) has been previously shown not to be secreted. The two other missense variants were produced recombinantly: compared to wild type, one (R175P) had no functional activity and the other (C192F) had decreased secretion.},
	issn = {2045-2322},
	doi = {10.1038/srep31531},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Mapping+rare\%2C+deleterious+mutations+in+Factor+H\%3A+Association+with+early+onset\%2C+drusen+burden\%2C+and+lower+antigenic+levels+in+familial+AMD},
	author = {Wagner, Erin K and Raychaudhuri, Soumya and Villalonga, Mercedes B and Java, Anuja and Triebwasser, Michael P and Daly, Mark J and Atkinson, John P and Seddon, Johanna M}
}
@article {1001646,
	title = {Protective coding variants in CFH and PELI3 and a variant near CTRB1 are associated with age-related macular degeneration},
	journal = {Hum Mol Genet},
	volume = {25},
	number = {23},
	year = {2016},
	month = {2016 Dec 01},
	pages = {5276-5285},
	abstract = {Although numerous common age-related macular degeneration (AMD) alleles have been discovered using genome-wide association studies, substantial disease heritability remains unexplained. We sought to identify additional common and rare variants associated with advanced AMD. A total of 4,332 cases and 25,268 controls of European ancestry from three different populations were genotyped using the Illumina Infinium HumanExome BeadChip. We performed meta-analyses to identify associations with common variants, and single variant and gene-based burden tests to identify rare variants. Two protective, low-frequency, non-synonymous variants were significantly associated with a decrease in AMD risk: A307V in PELI3 (odds ratio [OR] = 0.14, P = 4.3 {\texttimes} 10-10) and N1050Y in CFH (OR = 0.76, P = 6.2 {\texttimes} 10-12). The new variants have a large effect size, similar to some rare mutations we reported previously in a targeted sequencing study, which remain significant in this analysis: CFH R1210C (OR = 18.82, P = 3.5 {\texttimes} 10-07), C3 K155Q (OR = 3.27, P = 1.5 {\texttimes} 10-10) and C9 P167S (OR = 2.04, P = 2.8 {\texttimes} 10-07). We also identified a strong protective signal for a common variant (rs8056814) near CTRB1 associated with a decrease in AMD risk (logistic regression: OR = 0.71, P = 1.8 {\texttimes} 10-07). Suggestive protective loci were identified in the COL4A3 and APOH genes. Our results support the involvement of common and low-frequency protective variants in this vision-threatening condition. This study expands the roles of the innate immune pathway as well as the extracellular matrix and high-density lipoprotein pathways in the aetiology of AMD.},
	issn = {1460-2083},
	doi = {10.1093/hmg/ddw336},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Protective+coding+variants+in+CFH+and+PELI3+and+a+variant+near+CTRB1+are+associated+with+age-related+macular+degeneration},
	author = {Yu, Yi and Wagner, Erin K and Souied, Eric H and Seitsonen, Sanna and Immonen, Ilkka J and H{\"a}pp{\"o}l{\"a}, Paavo and Raychaudhuri, Soumya and Daly, Mark J and Seddon, Johanna M}
}
@article {1001666,
	title = {Recent Advances in Defining the Genetic Basis of Rheumatoid Arthritis},
	journal = {Annu Rev Genomics Hum Genet},
	volume = {17},
	year = {2016},
	month = {2016 Aug 31},
	pages = {273-301},
	abstract = {Rheumatoid arthritis (RA) is the most common inflammatory arthritis and exhibits genetic overlap with other autoimmune and inflammatory disorders. Although predominant associations with the HLA-DRB1 locus have been known for decades, recent data have revealed additional insight into the likely causative variants within HLA-DRB1 as well as within other HLA loci that contribute to disease risk. In addition, more than 100 common variants in non-HLA loci have been implicated in disease susceptibility. Genetic factors are involved not only in the development of RA, but also with various disease subphenotypes, including production and circulating levels of autoantibodies and joint destruction. The major current challenge is to integrate these new data into a precise understanding of disease pathogenesis, including the critical cell types and molecular networks involved as well as interactions with environmental factors. We predict that delineating the functional effects of genetic variants is likely to drive new diagnostic and therapeutic approaches to the disease.},
	issn = {1545-293X},
	doi = {10.1146/annurev-genom-090314-045919},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Recent+Advances+in+Defining+the+Genetic+Basis+of+Rheumatoid+Arthritis},
	author = {Terao, Chikashi and Raychaudhuri, Soumya and Gregersen, Peter K}
}
@article {1001771,
	title = {Association of HLA-DRB1 haplotypes with rheumatoid arthritis severity, mortality, and treatment response},
	journal = {JAMA},
	volume = {313},
	number = {16},
	year = {2015},
	month = {2015 Apr 28},
	pages = {1645-56},
	abstract = {IMPORTANCE: Advances have been made in identifying genetic susceptibility loci for autoimmune diseases, but evidence is needed regarding their association with prognosis and treatment response. OBJECTIVE: To assess whether specific HLA-DRB1 haplotypes associated with rheumatoid arthritis (RA) susceptibility are also associated with radiological severity, mortality, and response to tumor necrosis factor (TNF) inhibitor drugs. DESIGN, SETTING, AND PARTICIPANTS: The Norfolk Arthritis Register (NOAR; 1691 patients and 2811 radiographs; recruitment: 1989-2008; 2008 as final follow-up) was used as a discovery cohort and the Early Rheumatoid Arthritis Study (421 patients and 3758 radiographs; recruitment: 1986-1999; 2005 as final follow-up) as an independent replication cohort for studies of radiographic outcome. Mortality studies were performed in the NOAR cohort (2432 patients; recruitment: 1990-2007; 2011 as final follow-up) and studies of treatment response in the Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate cohort (1846 patients enrolled at initiation of TNF inhibitor; recruitment: 2006-2010; 2011 as final follow-up). Longitudinal statistical modeling was performed to integrate multiple radiograph records per patient over time. All patients were from the United Kingdom and had self-reported white ancestry. EXPOSURES: Sixteen HLA-DRB1 haplotypes defined by amino acids at positions 11, 71, and 74. MAIN OUTCOMES AND MEASURES: Radiological outcome using the Larsen score (range: 0 [none] to 200 [severe joint damage]) and erosions of the hands and feet on radiographs, all-cause mortality, and treatment response measured by change in Disease Activity Score based on 28 joint counts and European League Against Rheumatism (EULAR) response. RESULTS: Patients with RA and valine at position 11 of HLA-DRB1 had the strongest association with radiological damage (OR, 1.75 [95\% CI, 1.51-2.05], P = 4.6E-13). By year 5, the percentages of patients with erosions of the hands and feet were 48\% of noncarriers (150/314) of valine at position 11, 61\% of heterozygote carriers (130/213), and 74\% of homozygote carriers (43/58). Valine at position 11 also was associated with higher all-cause mortality in patients with inflammatory polyarthritis (hazard ratio, 1.16 [95\% CI, 1.03-1.31], P = .01) (noncarriers: 319 deaths in 1398 patients over 17,196 person-years, mortality rate of 1.9\% per year; carriers: 324 deaths in 1116 patients in 13,208 person-years, mortality rate of 2.5\% per year) and with better EULAR response to TNF inhibitor therapy (OR, 1.14 [95\% CI, 1.01-1.30], P = .04) (noncarriers: 78\% [439/561 patients] with moderate or good EULAR response; heterozygote carriers: 81\% [698/866]; and homozygote carriers: 86\% [277/322]). The risk hierarchy defined by HLA-DRB1 haplotypes was correlated between disease susceptibility, severity, and mortality, but inversely correlated with TNF inhibitor treatment response. CONCLUSIONS AND RELEVANCE: Among patients with RA, the HLA-DRB1 locus, which is associated with disease susceptibility, was also associated with radiological severity, mortality, and treatment response. Replication of these findings in other cohorts is needed as a next step in evaluating the role of HLA-DRB1 haplotype analysis for management of RA.},
	keywords = {Adult, Aged, Alleles, Antirheumatic Agents, Arthritis, Rheumatoid, Cohort Studies, European Continental Ancestry Group, Female, Foot, Genotype, Hand, Haplotypes, Heterozygote, HLA-DRB1 Chains, Humans, Male, Middle Aged, Prognosis, Registries, Severity of Illness Index, Treatment Outcome, Tumor Necrosis Factor-alpha, United Kingdom},
	issn = {1538-3598},
	doi = {10.1001/jama.2015.3435},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Association+of+HLA-DRB1+haplotypes+with+rheumatoid+arthritis+severity\%2C+mortality\%2C+and+treatment+response},
	author = {Viatte, Sebastien and Plant, Darren and Han, Buhm and Fu, Bo and Yarwood, Annie and Thomson, Wendy and Symmons, Deborah P M and Worthington, Jane and Young, Adam and Hyrich, Kimme L and Morgan, Ann W and Wilson, Anthony G and Isaacs, John D and Raychaudhuri, Soumya and Barton, Anne}
}
@article {1001551,
	title = {Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait Loci},
	journal = {Am J Hum Genet},
	volume = {97},
	number = {1},
	year = {2015},
	month = {2015 Jul 02},
	pages = {139-52},
	abstract = {Identifying genomic annotations that differentiate causal from trait-associated variants is essential to fine mapping disease loci. Although many studies have identified non-coding functional annotations that overlap disease-associated variants, these annotations often colocalize, complicating the ability to use these annotations for fine mapping causal variation. We developed a statistical approach (Genomic Annotation Shifter [GoShifter]) to assess whether enriched annotations are able to prioritize causal variation. GoShifter defines the null distribution of an annotation overlapping an allele by locally shifting annotations; this approach is less sensitive to biases arising from local genomic structure than commonly used enrichment methods that depend on SNP matching. Local shifting also allows GoShifter to identify independent causal effects from colocalizing annotations. Using GoShifter, we confirmed that variants in expression quantitative trail loci drive gene-expression changes though DNase-I hypersensitive sites (DHSs) near transcription start sites and independently through 3{\textquoteright} UTR regulation. We also showed that (1) 15\%-36\% of trait-associated loci map to DHSs independently of other annotations; (2) loci associated with breast cancer and rheumatoid arthritis harbor potentially causal variants near the summits of histone marks rather than full peak bodies; (3) variants associated with height are highly enriched in embryonic stem cell DHSs; and (4) we can effectively prioritize causal variation at specific loci.},
	keywords = {Arthritis, Rheumatoid, Breast Neoplasms, Gene Expression Regulation, Genetic Variation, Genome, Human, Histones, Humans, Molecular Sequence Annotation, Quantitative Trait Loci},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2015.05.016},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/26140449},
	author = {Trynka, Gosia and Westra, Harm-Jan and Slowikowski, Kamil and Hu, Xinli and Xu, Han and Stranger, Barbara E and Klein, Robert J and Han, Buhm and Raychaudhuri, Soumya}
}
@article {1001536,
	title = {Widespread non-additive and interaction effects within HLA loci modulate the risk of autoimmune diseases},
	journal = {Nat Genet},
	volume = {47},
	number = {9},
	year = {2015},
	month = {2015 Sep},
	pages = {1085-90},
	abstract = {Human leukocyte antigen (HLA) genes confer substantial risk for autoimmune diseases on a log-additive scale. Here we speculated that differences in autoantigen-binding repertoires between a heterozygote{\textquoteright}s two expressed HLA variants might result in additional non-additive risk effects. We tested the non-additive disease contributions of classical HLA alleles in patients and matched controls for five common autoimmune diseases: rheumatoid arthritis (ncases = 5,337), type 1 diabetes (T1D; ncases = 5,567), psoriasis vulgaris (ncases = 3,089), idiopathic achalasia (ncases = 727) and celiac disease (ncases = 11,115). In four of the five diseases, we observed highly significant, non-additive dominance effects (rheumatoid arthritis, P = 2.5 {\texttimes} 10(-12); T1D, P = 2.4 {\texttimes} 10(-10); psoriasis, P = 5.9 {\texttimes} 10(-6); celiac disease, P = 1.2 {\texttimes} 10(-87)). In three of these diseases, the non-additive dominance effects were explained by interactions between specific classical HLA alleles (rheumatoid arthritis, P = 1.8 {\texttimes} 10(-3); T1D, P = 8.6 {\texttimes} 10(-27); celiac disease, P = 6.0 {\texttimes} 10(-100)). These interactions generally increased disease risk and explained moderate but significant fractions of phenotypic variance (rheumatoid arthritis, 1.4\%; T1D, 4.0\%; celiac disease, 4.1\%) beyond a simple additive model.},
	keywords = {Autoimmune Diseases, Case-Control Studies, Epistasis, Genetic, Genetic Association Studies, Genetic Loci, Genetic Predisposition to Disease, Haplotypes, Histocompatibility Antigens Class I, HLA-C Antigens, HLA-D Antigens, Humans, Polymorphism, Single Nucleotide, Risk Factors},
	issn = {1546-1718},
	doi = {10.1038/ng.3379},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Widespread+non-additive+and+interaction+effects+within+HLA+loci+modulate+the+risk+of+autoimmune+diseases},
	author = {Lenz, Tobias L.$\#$ and Deutsch, Aaron J$\#$ and Han, Buhm and Hu, Xinli and Okada, Yukinori and Eyre, Stephen and Knapp, Michael and Zhernakova, Alexandra and Huizinga, Tom W J and Abecasis, Gon{\c c}alo and Becker, Jessica and Boeckxstaens, Guy E and Chen, Wei-Min and Franke, Andre and Gladman, Dafna D and Gockel, Ines and Gutierrez-Achury, Javier and Martin, Javier and Nair, Rajan P and N{\"o}then, Markus M and Onengut-Gumuscu, Suna and Rahman, Proton and Rantap{\"a}{\"a}-Dahlqvist, Solbritt and Stuart, Philip E and Tsoi, Lam C and van Heel, David A and Worthington, Jane and Wouters, Mira M and Klareskog, Lars and Elder, James T and Gregersen, Peter K and Schumacher, Johannes and Rich, Stephen S and Wijmenga, Cisca and Sunyaev, Shamil R. and de Bakker, Paul I W* and Raychaudhuri, Soumya*}
}
@article {1769651,
	title = {Additive and interaction effects at three amino acid positions in HLA-DQ and HLA-DR molecules drive type 1 diabetes risk},
	journal = {Nat Genet},
	volume = {47},
	number = {8},
	year = {2015},
	month = {2015 Aug},
	pages = {898-905},
	abstract = {Variation in the human leukocyte antigen (HLA) genes accounts for one-half of the genetic risk in type 1 diabetes (T1D). Amino acid changes in the HLA-DR and HLA-DQ molecules mediate most of the risk, but extensive linkage disequilibrium complicates the localization of independent effects. Using 18,832 case-control samples, we localized the signal to 3 amino acid positions in HLA-DQ and HLA-DR. HLA-DQβ1 position 57 (previously known; P = 1 {\texttimes} 10(-1,355)) by itself explained 15.2\% of the total phenotypic variance. Independent effects at HLA-DRβ1 positions 13 (P = 1 {\texttimes} 10(-721)) and 71 (P = 1 {\texttimes} 10(-95)) increased the proportion of variance explained to 26.9\%. The three positions together explained 90\% of the phenotypic variance in the HLA-DRB1-HLA-DQA1-HLA-DQB1 locus. Additionally, we observed significant interactions for 11 of 21 pairs of common HLA-DRB1-HLA-DQA1-HLA-DQB1 haplotypes (P = 1.6 {\texttimes} 10(-64)). HLA-DRβ1 positions 13 and 71 implicate the P4 pocket in the antigen-binding groove, thus pointing to another critical protein structure for T1D risk, in addition to the HLA-DQ P9 pocket.},
	keywords = {Algorithms, Amino Acids, Case-Control Studies, Diabetes Mellitus, Type 1, Epistasis, Genetic, Female, Genotype, Haplotypes, HLA-DQ alpha-Chains, HLA-DQ beta-Chains, HLA-DRB1 Chains, Humans, Logistic Models, Male, Models, Genetic, Phenotype, Polymorphism, Single Nucleotide, Risk Factors},
	issn = {1546-1718},
	doi = {10.1038/ng.3353},
	author = {Hu, Xinli$\#$ and Deutsch, Aaron J$\#$ and Lenz, Tobias L. and Onengut-Gumuscu, Suna and Han, Buhm and Chen, Wei-Min and Howson, Joanna M M and Todd, John A and de Bakker, Paul I W and Rich, Stephen S and Raychaudhuri, Soumya}
}
@article {1109641,
	title = {Association of valine and leucine at HLA-DRB1 position 11 with radiographic progression in rheumatoid arthritis, independent of the shared epitope alleles but not independent of anti-citrullinated protein antibodies},
	journal = {Arthritis Rheumatol},
	volume = {67},
	number = {4},
	year = {2015},
	month = {2015 Apr},
	pages = {877-86},
	abstract = {OBJECTIVE: For decades it has been known that the HLA-DRB1 shared epitope (SE) alleles are associated with an increased risk of development and progression of rheumatoid arthritis (RA). Recently, the following variations in the peptide-binding grooves of HLA molecules that predispose to RA development have been identified: Val and Leu at HLA-DRB1 position 11, Asp at HLA-B position 9, and Phe at HLA-DPB1 position 9. This study was undertaken to investigate whether these variants are also associated with radiographic progression in RA, independent of SE and anti-citrullinated protein antibody (ACPA) status. METHODS: A total of 4,911 radiograph sets from 1,878 RA patients included in the Leiden Early Arthritis Clinic (The Netherlands), Ume{\r a} (Sweden), Hospital Clinico San Carlos-Rheumatoid Arthritis (Spain), and National Data Bank for Rheumatic Diseases (US) cohorts were studied. HLA was imputed using single-nucleotide polymorphism data from an Immunochip, and the amino acids listed above were tested in relation to radiographic progression per cohort using an additive model. Results from the 4 cohorts were combined in inverse-variance weighted meta-analyses using a fixed-effects model. Analyses were conditioned on SE and ACPA status. RESULTS: Val and Leu at HLA-DRB1 position 11 were associated with more radiographic progression (meta-analysis P = 5.11 {\texttimes} 10(-7)); this effect was independent of SE status (meta-analysis P = 0.022) but not independent of ACPA status. Phe at HLA-DPB1 position 9 was associated with more severe radiographic progression (meta-analysis P = 0.024), though not independent of SE status. Asp at HLA-B position 9 was not associated with radiographic progression. CONCLUSION: Val and Leu at HLA-DRB1 position 11 conferred a risk of a higher rate of radiographic progression independent of SE status but not independent of ACPA status. These findings support the relevance of these amino acids at position 11.},
	keywords = {Adult, Aged, Alleles, Arthritis, Rheumatoid, Disease Progression, Epitopes, Female, Foot Joints, Gene Frequency, Hand Joints, HLA-DRB1 Chains, Humans, Male, Middle Aged, Peptides, Cyclic, Radiography},
	issn = {2326-5205},
	doi = {10.1002/art.39018},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Association+of+valine+and+leucine+at+HLA-DRB1+position+11+with+radiographic+progression+in+rheumatoid+arthritis\%2C+independent+of+the+shared+epitope+alleles+but+not+independent+of+anti-citrullinated+protein+antibo},
	author = {van Steenbergen, H W and Raychaudhuri, S and Rodr{\'\i}guez-Rodr{\'\i}guez, L and Rantap{\"a}{\"a}-Dahlqvist, S and Berglin, E and Toes, R E M and Huizinga, T W J and Fern{\'a}ndez-Guti{\'e}rrez, B and Gregersen, P K and van der Helm-van Mil, A H M}
}
@article {1109646,
	title = {Development of phenotype algorithms using electronic medical records and incorporating natural language processing},
	journal = {BMJ},
	volume = {350},
	year = {2015},
	month = {2015 Apr 24},
	pages = {h1885},
	keywords = {Algorithms, Electronic Health Records, Humans, Information Storage and Retrieval, Interdisciplinary Communication, Natural Language Processing, Phenotype, Translational Medical Research},
	issn = {1756-1833},
	doi = {10.1136/bmj.h1885},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/25911572},
	author = {Liao, Katherine P and Cai, Tianxi and Savova, Guergana K and Murphy, Shawn N and Karlson, Elizabeth W and Ananthakrishnan, Ashwin N and Gainer, Vivian S and Shaw, Stanley Y and Xia, Zongqi and Szolovits, Peter and Churchill, Susanne and Kohane, Isaac}
}
@article {1109661,
	title = {New data and an old puzzle: the negative association between schizophrenia and rheumatoid arthritis},
	journal = {Int J Epidemiol},
	volume = {44},
	number = {5},
	year = {2015},
	month = {2015 Oct},
	pages = {1706-21},
	abstract = {BACKGROUND: A long-standing epidemiological puzzle is the reduced rate of rheumatoid arthritis (RA) in those with schizophrenia (SZ) and vice versa. Traditional epidemiological approaches to determine if this negative association is underpinned by genetic factors would test for reduced rates of one disorder in relatives of the other, but sufficiently powered data sets are difficult to achieve. The genomics era presents an alternative paradigm for investigating the genetic relationship between two uncommon disorders. METHODS: We use genome-wide common single nucleotide polymorphism (SNP) data from independently collected SZ and RA case-control cohorts to estimate the SNP correlation between the disorders. We test a genotype X environment (GxE) hypothesis for SZ with environment defined as winter- vs summer-born. RESULTS: We estimate a small but significant negative SNP-genetic correlation between SZ and RA (-0.046, s.e. 0.026, P = 0.036). The negative correlation was stronger for the SNP set attributed to coding or regulatory regions (-0.174, s.e. 0.071, P = 0.0075). Our analyses led us to hypothesize a gene-environment interaction for SZ in the form of immune challenge. We used month of birth as a proxy for environmental immune challenge and estimated the genetic correlation between winter-born and non-winter born SZ to be significantly less than 1 for coding/regulatory region SNPs (0.56, s.e. 0.14, P = 0.00090). CONCLUSIONS: Our results are consistent with epidemiological observations of a negative relationship between SZ and RA reflecting, at least in part, genetic factors. Results of the month of birth analysis are consistent with pleiotropic effects of genetic variants dependent on environmental context.},
	keywords = {Adolescent, Adult, Arthritis, Rheumatoid, Cohort Studies, Cross-Sectional Studies, Female, Gene-Environment Interaction, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Schizophrenia, Young Adult},
	issn = {1464-3685},
	doi = {10.1093/ije/dyv136},
	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4881824/},
	author = {Lee, S Hong and Byrne, Enda M and Hultman, Christina M and K{\"a}hler, Anna and Vinkhuyzen, Anna A E and Ripke, Stephan and Andreassen, Ole A and Frisell, Thomas and Gusev, Alexander and Hu, Xinli and Karlsson, Robert and Mantzioris, Vasilis X and McGrath, John J and Mehta, Divya and Stahl, Eli A and Zhao, Qiongyi and Kendler, Kenneth S and Sullivan, Patrick F and Price, Alkes L and O{\textquoteright}Donovan, Michael and Okada, Yukinori and Mowry, Bryan J and Raychaudhuri, Soumya and Wray, Naomi R and Schizophrenia Working Group of the Psychiatric Genomics Consortium and Rheumatoid Arthritis Consortium International and Schizophrenia Working Group of the Psychiatric Genomics Consortium Authors and Byerley, William and Cahn, Wiepke and Cantor, Rita M and Cichon, Sven and Cormican, Paul and Curtis, David and Djurovic, Srdjan and Escott-Price, Valentina and Gejman, Pablo V and Georgieva, Lyudmila and Giegling, Ina and Hansen, Thomas F and Ingason, Andr{\'e}s and Kim, Yunjung and Konte, Bettina and Lee, Phil H and McIntosh, Andrew and McQuillin, Andrew and Morris, Derek W and N{\"o}then, Markus M and O{\textquoteright}Dushlaine, Colm and Olincy, Ann and Olsen, Line and Pato, Carlos N and Pato, Michele T and Pickard, Benjamin S and Posthuma, Danielle and Rasmussen, Henrik B and Rietschel, Marcella and Rujescu, Dan and Schulze, Thomas G and Silverman, Jeremy M and Thirumalai, Srinivasa and Werge, Thomas and Schizophrenia Working Group of the Psychiatric Genomics Consortium Collaborators and Agartz, Ingrid and Amin, Farooq and Azevedo, Maria H and Bass, Nicholas and Black, Donald W and Blackwood, Douglas H R and Bruggeman, Richard and Buccola, Nancy G and Choudhury, Khalid and Cloninger, C Robert and Corvin, Aiden and Craddock, Nicholas and Daly, Mark J and Datta, Susmita and Donohoe, Gary J and Duan, Jubao and Dudbridge, Frank and Fanous, Ayman and Freedman, Robert and Freimer, Nelson B and Friedl, Marion and Gill, Michael and Gurling, Hugh and De Haan, Lieuwe and Hamshere, Marian L and Hartmann, Annette M and Holmans, Peter A and Kahn, Ren{\'e} S and Keller, Matthew C and Kenny, Elaine and Kirov, George K and Krabbendam, Lydia and Krasucki, Robert and Lawrence, Jacob and Lencz, Todd and Levinson, Douglas F and Lieberman, Jeffrey A and Lin, Dan-Yu and Linszen, Don H and Magnusson, Patrik K E and Maier, Wolfgang and Malhotra, Anil K and Mattheisen, Manuel and Mattingsdal, Morten and McCarroll, Steven A and Medeiros, Helena and Melle, Ingrid and Milanova, Vihra and Myin-Germeys, Inez and Neale, Benjamin M and Ophoff, Roel A and Owen, Michael J and Pimm, Jonathan and Purcell, Shaun M and Puri, Vinay and Quested, Digby J and Rossin, Lizzy and Ruderfer, Douglas and Sanders, Alan R and Shi, Jianxin and Sklar, Pamela and St Clair, David and Stroup, T Scott and van Os, Jim and Visscher, Peter M and Wiersma, Durk and Zammit, Stanley and Rheumatoid Arthritis Consortium International Authors and Bridges, S Louis and Choi, Hyon K and Coenen, Marieke Jh and de Vries, Niek and Dieud, Philippe and Greenberg, Jeffrey D and Huizinga, Tom W J and Padyukov, Leonid and Siminovitch, Katherine A and Tak, Paul P and Worthington, Jane and Rheumatoid Arthritis Consortium International Collaborators and De Jager, Philip L and Denny, Joshua C and Gregersen, Peter K and Klareskog, Lars and Mariette, Xavier and Plenge, Robert M and van Laar, Mart and van Riel, Piet}
}
@article {1109656,
	title = {Rare Variants in the Functional Domains of Complement Factor H Are Associated With Age-Related Macular Degeneration},
	journal = {Invest Ophthalmol Vis Sci},
	volume = {56},
	number = {11},
	year = {2015},
	month = {2015 Oct},
	pages = {6873-8},
	abstract = {PURPOSE: Age-related macular degeneration (AMD) has a substantial genetic risk component, as evidenced by the risk from common genetic variants uncovered in the first genome-wide association studies. More recently, it has become apparent that rare genetic variants also play an independent role in AMD risk. We sought to determine if rare variants in complement factor H (CFH) played a role in AMD risk. METHODS: We had previously collected DNA from a large population of patients with advanced age-related macular degeneration (A-AMD) and controls for targeted deep sequencing of candidate AMD risk genes. In this analysis, we tested for an increased burden of rare variants in CFH in 1665 cases and 752 controls from this cohort. RESULTS: We identified 65 missense, nonsense, or splice-site mutations with a minor allele frequency <= 1\%. Rare variants with minor allele frequency <= 1\% (odds ratio [OR] = 1.5, P = 4.4 {\texttimes} 10$^{-}${\texttwosuperior}), 0.5\% (OR = 1.6, P = 2.6 {\texttimes} 10$^{-}${\texttwosuperior}), and all singletons (OR = 2.3, P = 3.3 {\texttimes} 10$^{-}${\texttwosuperior}) were enriched in A-AMD cases. Moreover, we observed loss-of-function rare variants (nonsense, splice-site, and loss of a conserved cysteine) in 10 cases and serum levels of FH were decreased in all 5 with an available sample (haploinsufficiency). Further, rare variants in the major functional domains of CFH were increased in cases (OR = 3.2; P = 1.4 {\texttimes} 10$^{-}${\textthreesuperior}) and the magnitude of the effect correlated with the disruptive nature of the variant, location in an active site, and inversely with minor allele frequency. CONCLUSIONS: In this large A-AMD cohort, rare variants in the CFH gene were enriched and tended to be located in functional sites or led to low serum levels. These data, combined with those indicating a similar, but even more striking, increase in rare variants found in CFI, strongly implicate complement activation in A-AMD etiopathogenesis as CFH and CFI interact to inhibit the alternative pathway.},
	keywords = {Aged, Codon, Nonsense, Complement Factor H, Gene Frequency, Genetic Association Studies, Genetic Predisposition to Disease, Genetic Variation, Humans, Macular Degeneration, Mutation, Missense, Polymorphism, Single Nucleotide, Risk Factors},
	issn = {1552-5783},
	doi = {10.1167/iovs.15-17432},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/26501415},
	author = {Triebwasser, Michael P and Roberson, Elisha D O and Yu, Yi and Schramm, Elizabeth C and Wagner, Erin K and Raychaudhuri, Soumya and Seddon, Johanna M and Atkinson, John P}
}
@article {1109651,
	title = {Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources},
	journal = {J Am Med Inform Assoc},
	volume = {22},
	number = {5},
	year = {2015},
	month = {2015 Sep},
	pages = {993-1000},
	abstract = {OBJECTIVE: Analysis of narrative (text) data from electronic health records (EHRs) can improve population-scale phenotyping for clinical and genetic research. Currently, selection of text features for phenotyping algorithms is slow and laborious, requiring extensive and iterative involvement by domain experts. This paper introduces a method to develop phenotyping algorithms in an unbiased manner by automatically extracting and selecting informative features, which can be comparable to expert-curated ones in classification accuracy. MATERIALS AND METHODS: Comprehensive medical concepts were collected from publicly available knowledge sources in an automated, unbiased fashion. Natural language processing (NLP) revealed the occurrence patterns of these concepts in EHR narrative notes, which enabled selection of informative features for phenotype classification. When combined with additional codified features, a penalized logistic regression model was trained to classify the target phenotype. RESULTS: The authors applied our method to develop algorithms to identify patients with rheumatoid arthritis and coronary artery disease cases among those with rheumatoid arthritis from a large multi-institutional EHR. The area under the receiver operating characteristic curves (AUC) for classifying RA and CAD using models trained with automated features were 0.951 and 0.929, respectively, compared to the AUCs of 0.938 and 0.929 by models trained with expert-curated features. DISCUSSION: Models trained with NLP text features selected through an unbiased, automated procedure achieved comparable or slightly higher accuracy than those trained with expert-curated features. The majority of the selected model features were interpretable. CONCLUSION: The proposed automated feature extraction method, generating highly accurate phenotyping algorithms with improved efficiency, is a significant step toward high-throughput phenotyping.},
	keywords = {Algorithms, Arthritis, Rheumatoid, Electronic Health Records, Humans, Information Storage and Retrieval, Natural Language Processing, Unified Medical Language System},
	issn = {1527-974X},
	doi = {10.1093/jamia/ocv034},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Toward+high-throughput+phenotyping\%3A+unbiased+automated+feature+extraction+and+selection+from+knowledge+sources},
	author = {Yu, Sheng and Liao, Katherine P and Shaw, Stanley Y and Gainer, Vivian S and Churchill, Susanne E and Szolovits, Peter and Murphy, Shawn N and Kohane, Isaac S and Cai, Tianxi}
}
@article {1001791,
	title = {A weighted genetic risk score using all known susceptibility variants to estimate rheumatoid arthritis risk},
	journal = {Ann Rheum Dis},
	volume = {74},
	number = {1},
	year = {2015},
	month = {2015 Jan},
	pages = {170-6},
	abstract = {BACKGROUND: There is currently great interest in the incorporation of genetic susceptibility loci into screening models to identify individuals at high risk of disease. Here, we present the first risk prediction model including all 46 known genetic loci associated with rheumatoid arthritis (RA). METHODS: A weighted genetic risk score (wGRS) was created using 45 RA non-human leucocyte antigen (HLA) susceptibility loci, imputed amino acids at HLA-DRB1 (11, 71 and 74), HLA-DPB1 (position 9) HLA-B (position 9) and gender. The wGRS was tested in 11 366 RA cases and 15 489 healthy controls. The risk of developing RA was estimated using logistic regression by dividing the wGRS into quintiles. The ability of the wGRS to discriminate between cases and controls was assessed by receiver operator characteristic analysis and discrimination improvement tests. RESULTS: Individuals in the highest risk group showed significantly increased odds of developing anti-cyclic citrullinated peptide-positive RA compared to the lowest risk group (OR 27.13, 95\% CI 23.70 to 31.05). The wGRS was validated in an independent cohort that showed similar results (area under the curve 0.78, OR 18.00, 95\% CI 13.67 to 23.71). Comparison of the full wGRS with a wGRS in which HLA amino acids were replaced by a HLA tag single-nucleotide polymorphism showed a significant loss of sensitivity and specificity. CONCLUSIONS: Our study suggests that in RA, even when using all known genetic susceptibility variants, prediction performance remains modest; while this is insufficiently accurate for general population screening, it may prove of more use in targeted studies. Our study has also highlighted the importance of including HLA variation in risk prediction models.},
	keywords = {Arthritis, Rheumatoid, Female, Genetic Predisposition to Disease, HLA-B Antigens, HLA-DP beta-Chains, HLA-DRB1 Chains, Humans, Logistic Models, Male, Peptides, Cyclic, Polymorphism, Single Nucleotide, Risk Assessment, Sex Factors},
	issn = {1468-2060},
	doi = {10.1136/annrheumdis-2013-204133},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=A+weighted+genetic+risk+score+using+all+known+susceptibility+variants+to+estimate+rheumatoid+arthritis+risk},
	author = {Yarwood, Annie and Han, Buhm and Raychaudhuri, Soumya and Bowes, John and Lunt, Mark and Pappas, Dimitrios A and Kremer, Joel and Greenberg, Jeffrey D and Plenge, Robert and Rheumatoid Arthritis Consortium International (RACI) and Worthington, Jane and Barton, Anne and Eyre, Steve}
}
@article {1001761,
	title = {Accurate and fast multiple-testing correction in eQTL studies},
	journal = {Am J Hum Genet},
	volume = {96},
	number = {6},
	year = {2015},
	month = {2015 Jun 04},
	pages = {857-68},
	abstract = {In studies of expression quantitative trait loci (eQTLs), it is of increasing interest to identify eGenes, the genes whose expression levels are associated with variation at a particular genetic variant. Detecting eGenes is important for follow-up analyses and prioritization because genes are the main entities in biological processes. To detect eGenes, one typically focuses on the genetic variant with the minimum p value among all variants in cis with a gene and corrects for multiple testing to obtain a gene-level p value. For performing multiple-testing correction, a permutation test is widely used. Because of growing sample sizes of eQTL studies, however, the permutation test has become a computational bottleneck in eQTL studies. In this paper, we propose an efficient approach for correcting for multiple testing and assess eGene p values by utilizing a multivariate normal distribution. Our approach properly takes into account the linkage-disequilibrium structure among variants, and its time complexity is independent of sample size. By applying our small-sample correction techniques, our method achieves high accuracy in both small and large studies. We have shown that our method consistently produces extremely accurate p values (accuracy \&gt; 98\%) for three human eQTL datasets with different sample sizes and SNP densities: the Genotype-Tissue Expression pilot dataset, the multi-region brain dataset, and the HapMap 3 dataset.},
	keywords = {Data Interpretation, Statistical, Gene Expression Regulation, Genes, Genetic Variation, Humans, Multivariate Analysis, Normal Distribution, Polymorphism, Single Nucleotide, Probability, Quantitative Trait Loci, Sample Size, Statistics, Nonparametric},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2015.04.012},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/26027500},
	author = {Sul, Jae Hoon and Raj, Towfique and de Jong, Simone and de Bakker, Paul I W and Raychaudhuri, Soumya and Ophoff, Roel A and Stranger, Barbara E and Eskin, Eleazar and Han, Buhm}
}
@article {1001786,
	title = {Biological interpretation of genome-wide association studies using predicted gene functions},
	journal = {Nat Commun},
	volume = {6},
	year = {2015},
	month = {2015 Jan 19},
	pages = {5890},
	abstract = {The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.},
	keywords = {Genome-Wide Association Study, Software},
	issn = {2041-1723},
	doi = {10.1038/ncomms6890},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/25597830},
	author = {Pers, Tune H and Karjalainen, Juha M and Chan, Yingleong and Westra, Harm-Jan and Wood, Andrew R and Yang, Jian and Lui, Julian C and Vedantam, Sailaja and Gustafsson, Stefan and Esko, Tonu and Frayling, Tim and Speliotes, Elizabeth K and Genetic Investigation of ANthropometric Traits (GIANT) Consortium and Boehnke, Michael and Raychaudhuri, Soumya and Fehrmann, Rudolf S N and Hirschhorn, Joel N and Franke, Lude}
}
@article {1001756,
	title = {Do Genetic Susceptibility Variants Associate with Disease Severity in Early Active Rheumatoid Arthritis?},
	journal = {J Rheumatol},
	volume = {42},
	number = {7},
	year = {2015},
	month = {2015 Jul},
	pages = {1131-40},
	abstract = {OBJECTIVE: Genetic variants affect both the development and severity of rheumatoid arthritis (RA). Recent studies have expanded the number of RA susceptibility variants. We tested the hypothesis that these associated with disease severity in a clinical trial cohort of patients with early, active RA. METHODS: We evaluated 524 patients with RA enrolled in the Combination Anti-Rheumatic Drugs in Early RA (CARDERA) trials. We tested validated susceptibility variants - 69 single-nucleotide polymorphisms (SNP), 15 HLA-DRB1 alleles, and amino acid polymorphisms in 6 HLA molecule positions - for their associations with progression in Larsen scoring, 28-joint Disease Activity Scores, and Health Assessment Questionnaire (HAQ) scores over 2 years using linear mixed-effects and latent growth curve models. RESULTS: HLA variants were associated with joint destruction. The *04:01 SNP (rs660895, p = 0.0003), *04:01 allele (p = 0.0002), and HLA-DRβ1 amino acids histidine at position 13 (p = 0.0005) and valine at position 11 (p = 0.0012) significantly associated with radiological progression. This association was only significant in anticitrullinated protein antibody (ACPA)-positive patients, suggesting that while their effects were not mediated by ACPA, they only predicted joint damage in ACPA-positive RA. Non-HLA variants did not associate with radiograph damage (assessed individually and cumulatively as a weighted genetic risk score). Two SNP - rs11889341 (STAT4, p = 0.0001) and rs653178 (SH2B3-PTPN11, p = 0.0004) - associated with HAQ scores over 6-24 months. CONCLUSION: HLA susceptibility variants play an important role in determining radiological progression in early, active ACPA-positive RA. Genome-wide and HLA-wide analyses across large populations are required to better characterize the genetic architecture of radiological progression in RA.},
	keywords = {Adult, Alleles, Antirheumatic Agents, Arthritis, Rheumatoid, Disease Progression, Female, Genetic Association Studies, Genetic Predisposition to Disease, Genotype, HLA-DRB1 Chains, Humans, Male, Middle Aged, Models, Theoretical, Polymorphism, Single Nucleotide, Severity of Illness Index},
	issn = {0315-162X},
	doi = {10.3899/jrheum.141211},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/25979711},
	author = {Scott, Ian C and Rijsdijk, Fr{\"u}hling and Walker, Jemma and Quist, Jelmar and Spain, Sarah L and Tan, Rachael and Steer, Sophia and Okada, Yukinori and Raychaudhuri, Soumya and Cope, Andrew P and Lewis, Cathryn M}
}
@article {1001766,
	title = {Fine mapping in the MHC region accounts for 18\% additional genetic risk for celiac disease},
	journal = {Nat Genet},
	volume = {47},
	number = {6},
	year = {2015},
	month = {2015 Jun},
	pages = {577-8},
	abstract = {Although dietary gluten is the trigger for celiac disease, risk is strongly influenced by genetic variation in the major histocompatibility complex (MHC) region. We fine mapped the MHC association signal to identify additional risk factors independent of the HLA-DQA1 and HLA-DQB1 alleles and observed five new associations that account for 18\% of the genetic risk. Taking these new loci together with the 57 known non-MHC loci, genetic variation can now explain up to 48\% of celiac disease heritability.},
	keywords = {Case-Control Studies, Celiac Disease, Chromosome Mapping, Genetic Association Studies, Genetic Predisposition to Disease, Haplotypes, HLA-DQ alpha-Chains, HLA-DQ beta-Chains, Humans, Risk, Risk Factors},
	issn = {1546-1718},
	doi = {10.1038/ng.3268},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Fine+mapping+in+the+MHC+region+accounts+for+18\%25+additional+genetic+risk+for+celiac+disease},
	author = {Gutierrez-Achury, Javier and Zhernakova, Alexandra and Pulit, Sara L and Trynka, Gosia and Hunt, Karen A and Romanos, Jihane and Raychaudhuri, Soumya and van Heel, David A and Wijmenga, Cisca and de Bakker, Paul I W}
}
@article {1001781,
	title = {High-density genotyping of immune loci in Koreans and Europeans identifies eight new rheumatoid arthritis risk loci},
	journal = {Ann Rheum Dis},
	volume = {74},
	number = {3},
	year = {2015},
	month = {2015 Mar},
	pages = {e13},
	abstract = {OBJECTIVE: A highly polygenic aetiology and high degree of allele-sharing between ancestries have been well elucidated in genetic studies of rheumatoid arthritis. Recently, the high-density genotyping array Immunochip for immune disease loci identified 14 new rheumatoid arthritis risk loci among individuals of European ancestry. Here, we aimed to identify new rheumatoid arthritis risk loci using Korean-specific Immunochip data. METHODS: We analysed Korean rheumatoid arthritis case-control samples using the Immunochip and genome-wide association studies (GWAS) array to search for new risk alleles of rheumatoid arthritis with anticitrullinated peptide antibodies. To increase power, we performed a meta-analysis of Korean data with previously published European Immunochip and GWAS data for a total sample size of 9299 Korean and 45,790 European case-control samples. RESULTS: We identified eight new rheumatoid arthritis susceptibility loci (TNFSF4, LBH, EOMES, ETS1-FLI1, COG6, RAD51B, UBASH3A and SYNGR1) that passed a genome-wide significance threshold (p\&lt;5{\texttimes}10(-8)), with evidence for three independent risk alleles at 1q25/TNFSF4. The risk alleles from the seven new loci except for the TNFSF4 locus (monomorphic in Koreans), together with risk alleles from previously established RA risk loci, exhibited a high correlation of effect sizes between ancestries. Further, we refined the number of single nucleotide polymorphisms (SNPs) that represent potentially causal variants through a trans-ethnic comparison of densely genotyped SNPs. CONCLUSIONS: This study demonstrates the advantage of dense-mapping and trans-ancestral analysis for identification of potentially causal SNPs. In addition, our findings support the importance of T cells in the pathogenesis and the fact of frequent overlap of risk loci among diverse autoimmune diseases.},
	keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Alleles, Arthritis, Rheumatoid, Asian Continental Ancestry Group, Case-Control Studies, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Republic of Korea, Young Adult},
	issn = {1468-2060},
	doi = {10.1136/annrheumdis-2013-204749},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=High-density+genotyping+of+immune+loci+in+Koreans+and+Europeans+identifies+eight+new+rheumatoid+arthritis+risk+loci},
	author = {Kim, Kwangwoo and Bang, So-Young and Lee, Hye-Soon and Cho, Soo-Kyung and Choi, Chan-Bum and Sung, Yoon-Kyoung and Kim, Tae-Hwan and Jun, Jae-Bum and Yoo, Dae Hyun and Kang, Young Mo and Kim, Seong-Kyu and Suh, Chang-Hee and Shim, Seung-Cheol and Lee, Shin-Seok and Lee, Jisoo and Chung, Won Tae and Choe, Jung-Yoon and Shin, Hyoung Doo and Lee, Jong-Young and Han, Bok-Ghee and Nath, Swapan K and Eyre, Steve and Bowes, John and Pappas, Dimitrios A and Kremer, Joel M and Gonzalez-Gay, Miguel A and Rodriguez-Rodriguez, Luis and {\"A}rlestig, Lisbeth and Okada, Yukinori and Diogo, Doroth{\'e}e and Liao, Katherine P and Karlson, Elizabeth W and Raychaudhuri, Soumya and Rantap{\"a}{\"a}-Dahlqvist, Solbritt and Martin, Javier and Klareskog, Lars and Padyukov, Leonid and Gregersen, Peter K and Worthington, Jane and Greenberg, Jeffrey D and Plenge, Robert M and Bae, Sang-Cheol}
}
@article {1001741,
	title = {Interactions between amino acid-defined major histocompatibility complex class II variants and smoking in seropositive rheumatoid arthritis},
	journal = {Arthritis Rheumatol},
	volume = {67},
	number = {10},
	year = {2015},
	month = {2015 Oct},
	pages = {2611-23},
	abstract = {OBJECTIVE: To define the interaction between cigarette smoking and HLA polymorphisms in seropositive rheumatoid arthritis (RA), in the context of a recently identified amino acid-based HLA model for RA susceptibility. METHODS: We imputed Immunochip data on HLA amino acids and classical alleles from 3 case-control studies (the Swedish Epidemiological Investigation of Rheumatoid Arthritis [EIRA] study [1,654 cases and 1,934 controls], the Nurses{\textquoteright} Health Study [NHS] [229 cases and 360 controls], and the Korean RA Cohort Study [1,390 cases and 735 controls]). We examined the interaction effects of heavy smoking (\&gt;10 pack-years) and the genetic risk score (GRS) of multiple RA-associated amino acid positions (positions 11, 13, 71, and 74 in HLA-DRβ1, position 9 in HLA-B, and position 9 in HLA-DPβ1), as well as the interaction effects of heavy smoking and the GRS of HLA-DRβ1 4-amino acid haplotypes (assessed via attributable proportion due to interaction [AP] using the additive interaction model). RESULTS: Heavy smoking and all investigated HLA amino acid positions and haplotypes were associated with RA susceptibility in the 3 populations. In the interaction analysis, we found a significant deviation from the expected additive joint effect between heavy smoking and the HLA-DRβ1 4-amino acid haplotype (AP 0.416, 0.467, and 0.796, in the EIRA, NHS, and Korean studies, respectively). We further identified the key interacting variants as being located at HLA-DRβ1 amino acid positions 11 and 13 but not at any of the other RA risk-associated amino acid positions. For residues in positions 11 and 13, there were similar patterns between RA risk effects and interaction effects. CONCLUSION: Our findings of significant gene-environment interaction effects indicate that a physical interaction between citrullinated autoantigens produced by smoking and HLA-DR molecules is characterized by the HLA-DRβ1 4-amino acid haplotype, primarily by positions 11 and 13.},
	keywords = {Adult, Alleles, Amino Acids, Case-Control Studies, Female, Genes, MHC Class II, Genetic Predisposition to Disease, Genetic Variation, Haplotypes, HLA-B Antigens, HLA-DP beta-Chains, HLA-DRB1 Chains, Humans, Male, Middle Aged, Models, Genetic, Rheumatic Fever, Risk Factors, Smoking},
	issn = {2326-5205},
	doi = {10.1002/art.39228},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Interactions+between+amino+acid-defined+major+histocompatibility+complex+class+II+variants+and+smoking+in+seropositive+rheumatoid+arthritis},
	author = {Kim, Kwangwoo and Jiang, Xia and Cui, Jing and Lu, Bing and Costenbader, Karen H and Sparks, Jeffrey A and Bang, So-Young and Lee, Hye-Soon and Okada, Yukinori and Raychaudhuri, Soumya and Alfredsson, Lars and Bae, Sang-Cheol and Klareskog, Lars and Karlson, Elizabeth W}
}
@article {1001751,
	title = {Rare genetic variants in the CFI gene are associated with advanced age-related macular degeneration and commonly result in reduced serum factor I levels},
	journal = {Hum Mol Genet},
	volume = {24},
	number = {13},
	year = {2015},
	month = {2015 Jul 01},
	pages = {3861-70},
	abstract = {To assess a potential diagnostic and therapeutic biomarker for age-related macular degeneration (AMD), we sequenced the complement factor I gene (CFI) in 2266 individuals with AMD and 1400 without, identifying 231 individuals with rare genetic variants. We evaluated the functional impact by measuring circulating serum factor I (FI) protein levels in individuals with and without rare CFI variants. The burden of very rare (frequency \&lt;1/1000) variants in CFI was strongly associated with disease (P = 1.1 {\texttimes} 10(-8)). In addition, we examined eight coding variants with counts >=5 and saw evidence for association with AMD in three variants. Individuals with advanced AMD carrying a rare CFI variant had lower mean FI compared with non-AMD subjects carrying a variant (P \&lt; 0.001). Further new evidence that FI levels drive AMD risk comes from analyses showing individuals with a CFI rare variant and low FI were more likely to have advanced AMD (P = 5.6 {\texttimes} 10(-5)). Controlling for covariates, low FI increased the risk of advanced AMD among those with a variant compared with individuals without advanced AMD with a rare CFI variant (OR 13.6, P = 1.6 {\texttimes} 10(-4)), and also compared with control individuals without a rare CFI variant (OR 19.0, P = 1.1 {\texttimes} 10(-5)). Thus, low FI levels are strongly associated with rare CFI variants and AMD. Enhancing FI activity may be therapeutic and measuring FI provides a screening tool for identifying patients who are most likely to benefit from complement inhibitory therapy.},
	keywords = {Complement Factor I, Female, Fibrinogen, Genetic Variation, Humans, Macular Degeneration, Male},
	issn = {1460-2083},
	doi = {10.1093/hmg/ddv091},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Rare+genetic+variants+in+the+CFI+gene+are+associated+with+advanced+age-related+macular+degeneration+and+commonly+result+in+reduced+serum+factor+I+levels},
	author = {Kavanagh, David and Yu, Yi and Schramm, Elizabeth C and Triebwasser, Michael and Wagner, Erin K and Raychaudhuri, Soumya and Daly, Mark J and Atkinson, John P and Seddon, Johanna M}
}
@article {1001746,
	title = {Tissue-Specific Enrichment of Lymphoma Risk Loci in Regulatory Elements},
	journal = {PLoS One},
	volume = {10},
	number = {9},
	year = {2015},
	month = {2015},
	pages = {e0139360},
	abstract = {Though numerous polymorphisms have been associated with risk of developing lymphoma, how these variants function to promote tumorigenesis is poorly understood. Here, we report that lymphoma risk SNPs, especially in the non-Hodgkin{\textquoteright}s lymphoma subtype chronic lymphocytic leukemia, are significantly enriched for co-localization with epigenetic marks of active gene regulation. These enrichments were seen in a lymphoid-specific manner for numerous ENCODE datasets, including DNase-hypersensitivity as well as multiple segmentation-defined enhancer regions. Furthermore, we identify putatively functional SNPs that are both in regulatory elements in lymphocytes and are associated with gene expression changes in blood. We developed an algorithm, UES, that uses a Monte Carlo simulation approach to calculate the enrichment of previously identified risk SNPs in various functional elements. This multiscale approach integrating multiple datasets helps disentangle the underlying biology of lymphoma, and more broadly, is generally applicable to GWAS results from other diseases as well.},
	keywords = {Algorithms, Genetic Loci, Genome, Human, Genome-Wide Association Study, Humans, Leukemia, Lymphocytic, Chronic, B-Cell, Linkage Disequilibrium, Monte Carlo Method, Organ Specificity, Polymorphism, Single Nucleotide, Regulatory Elements, Transcriptional, Risk Factors},
	issn = {1932-6203},
	doi = {10.1371/journal.pone.0139360},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Tissue-Specific+Enrichment+of+Lymphoma+Risk+Loci+in+Regulatory+Elements},
	author = {Hayes, James E and Trynka, Gosia and Vijai, Joseph and Offit, Kenneth and Raychaudhuri, Soumya and Klein, Robert J}
}
@article {1001776,
	title = {TYK2 protein-coding variants protect against rheumatoid arthritis and autoimmunity, with no evidence of major pleiotropic effects on non-autoimmune complex traits},
	journal = {PLoS One},
	volume = {10},
	number = {4},
	year = {2015},
	month = {2015},
	pages = {e0122271},
	abstract = {Despite the success of genome-wide association studies (GWAS) in detecting a large number of loci for complex phenotypes such as rheumatoid arthritis (RA) susceptibility, the lack of information on the causal genes leaves important challenges to interpret GWAS results in the context of the disease biology. Here, we genetically fine-map the RA risk locus at 19p13 to define causal variants, and explore the pleiotropic effects of these same variants in other complex traits. First, we combined Immunochip dense genotyping (n = 23,092 case/control samples), Exomechip genotyping (n = 18,409 case/control samples) and targeted exon-sequencing (n = 2,236 case/controls samples) to demonstrate that three protein-coding variants in TYK2 (tyrosine kinase 2) independently protect against RA: P1104A (rs34536443, OR = 0.66, P = 2.3 x 10(-21)), A928V (rs35018800, OR = 0.53, P = 1.2 x 10(-9)), and I684S (rs12720356, OR = 0.86, P = 4.6 x 10(-7)). Second, we show that the same three TYK2 variants protect against systemic lupus erythematosus (SLE, Pomnibus = 6 x 10(-18)), and provide suggestive evidence that two of the TYK2 variants (P1104A and A928V) may also protect against inflammatory bowel disease (IBD; P(omnibus) = 0.005). Finally, in a phenome-wide association study (PheWAS) assessing \&gt;500 phenotypes using electronic medical records (EMR) in \&gt;29,000 subjects, we found no convincing evidence for association of P1104A and A928V with complex phenotypes other than autoimmune diseases such as RA, SLE and IBD. Together, our results demonstrate the role of TYK2 in the pathogenesis of RA, SLE and IBD, and provide supporting evidence for TYK2 as a promising drug target for the treatment of autoimmune diseases.},
	keywords = {Arthritis, Rheumatoid, Autoimmunity, Cell Adhesion Molecules, Electronic Health Records, Exons, Genetic Loci, Genetic Pleiotropy, Genetic Predisposition to Disease, Humans, Polymorphism, Single Nucleotide, TYK2 Kinase},
	issn = {1932-6203},
	doi = {10.1371/journal.pone.0122271},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=TYK2+protein-coding+variants+protect+against+rheumatoid+arthritis+and+autoimmunity\%2C+with+no+evidence+of+major+pleiotropic+effects+on+non-autoimmune+complex+traits},
	author = {Diogo, Doroth{\'e}e and Bastarache, Lisa and Liao, Katherine P and Graham, Robert R and Fulton, Robert S and Greenberg, Jeffrey D and Eyre, Steve and Bowes, John and Cui, Jing and Lee, Annette and Pappas, Dimitrios A and Kremer, Joel M and Barton, Anne and Coenen, Marieke Jh and Franke, Barbara and Kiemeney, Lambertus A and Mariette, Xavier and Richard-Miceli, Corrine and Canh{\~a}o, Helena and Fonseca, Jo{\~a}o E and de Vries, Niek and Tak, Paul P and Crusius, J Bart A and Nurmohamed, Michael T and Kurreeman, Fina and Mikuls, Ted R and Okada, Yukinori and Stahl, Eli A and Larson, David E and Deluca, Tracie L and O{\textquoteright}Laughlin, Michelle and Fronick, Catrina C and Fulton, Lucinda L and Kosoy, Roman and Ransom, Michael and Bhangale, Tushar R and Ortmann, Ward and Cagan, Andrew and Gainer, Vivian and Karlson, Elizabeth W and Kohane, Isaac and Murphy, Shawn N and Martin, Javier and Zhernakova, Alexandra and Klareskog, Lars and Padyukov, Leonid and Worthington, Jane and Mardis, Elaine R and Seldin, Michael F and Gregersen, Peter K and Behrens, Timothy and Raychaudhuri, Soumya and Denny, Joshua C and Plenge, Robert M}
}
@article {1001736,
	title = {Disproportionate Contributions of Select Genomic Compartments and Cell Types to Genetic Risk for Coronary Artery Disease},
	journal = {PLoS Genet},
	volume = {11},
	number = {10},
	year = {2015},
	month = {2015 Oct},
	pages = {e1005622},
	abstract = {Large genome-wide association studies (GWAS) have identified many genetic loci associated with risk for myocardial infarction (MI) and coronary artery disease (CAD). Concurrently, efforts such as the National Institutes of Health (NIH) Roadmap Epigenomics Project and the Encyclopedia of DNA Elements (ENCODE) Consortium have provided unprecedented data on functional elements of the human genome. In the present study, we systematically investigate the biological link between genetic variants associated with this complex disease and their impacts on gene function. First, we examined the heritability of MI/CAD according to genomic compartments. We observed that single nucleotide polymorphisms (SNPs) residing within nearby regulatory regions show significant polygenicity and contribute between 59-71\% of the heritability for MI/CAD. Second, we showed that the polygenicity and heritability explained by these SNPs are enriched in histone modification marks in specific cell types. Third, we found that a statistically higher number of 45 MI/CAD-associated SNPs that have been identified from large-scale GWAS studies reside within certain functional elements of the genome, particularly in active enhancer and promoter regions. Finally, we observed significant heterogeneity of this signal across cell types, with strong signals observed within adipose nuclei, as well as brain and spleen cell types. These results suggest that the genetic etiology of MI/CAD is largely explained by tissue-specific regulatory perturbation within the human genome.},
	keywords = {Coronary Artery Disease, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Polymorphism, Single Nucleotide, Regulatory Sequences, Nucleic Acid, Risk Factors},
	issn = {1553-7404},
	doi = {10.1371/journal.pgen.1005622},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Disproportionate+Contributions+of+Select+Genomic+Compartments+and+Cell+Types+to+Genetic+Risk+for+Coronary+Artery+Disease},
	author = {Won, Hong-Hee and Natarajan, Pradeep and Dobbyn, Amanda and Jordan, Daniel M and Roussos, Panos and Lage, Kasper and Raychaudhuri, Soumya and Stahl, Eli and Do, Ron}
}
@article {1001716,
	title = {HLA-DRB1*11 and variants of the MHC class II locus are strong risk factors for systemic juvenile idiopathic arthritis},
	journal = {Proc Natl Acad Sci U S A},
	volume = {112},
	number = {52},
	year = {2015},
	month = {2015 Dec 29},
	pages = {15970-5},
	abstract = {Systemic juvenile idiopathic arthritis (sJIA) is an often severe, potentially life-threatening childhood inflammatory disease, the pathophysiology of which is poorly understood. To determine whether genetic variation within the MHC locus on chromosome 6 influences sJIA susceptibility, we performed an association study of 982 children with sJIA and 8,010 healthy control subjects from nine countries. Using meta-analysis of directly observed and imputed SNP genotypes and imputed classic HLA types, we identified the MHC locus as a bona fide susceptibility locus with effects on sJIA risk that transcended geographically defined strata. The strongest sJIA-associated SNP, rs151043342 [P = 2.8 {\texttimes} 10(-17), odds ratio (OR) 2.6 (2.1, 3.3)], was part of a cluster of 482 sJIA-associated SNPs that spanned a 400-kb region and included the class II HLA region. Conditional analysis controlling for the effect of rs151043342 found that rs12722051 independently influenced sJIA risk [P = 1.0 {\texttimes} 10(-5), OR 0.7 (0.6, 0.8)]. Meta-analysis of imputed classic HLA-type associations in six study populations of Western European ancestry revealed that HLA-DRB1*11 and its defining amino acid residue, glutamate 58, were strongly associated with sJIA [P = 2.7 {\texttimes} 10(-16), OR 2.3 (1.9, 2.8)], as was the HLA-DRB1*11-HLA-DQA1*05-HLA-DQB1*03 haplotype [6.4 {\texttimes} 10(-17), OR 2.3 (1.9, 2.9)]. By examining the MHC locus in the largest collection of sJIA patients assembled to date, this study solidifies the relationship between the class II HLA region and sJIA, implicating adaptive immune molecules in the pathogenesis of sJIA.},
	keywords = {Arthritis, Juvenile, Child, Gene Frequency, Genetic Predisposition to Disease, Genotype, Haplotypes, Histocompatibility Antigens Class II, HLA-DRB1 Chains, Humans, Linkage Disequilibrium, Meta-Analysis as Topic, Odds Ratio, Polymorphism, Single Nucleotide, Risk Factors},
	issn = {1091-6490},
	doi = {10.1073/pnas.1520779112},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=HLA-DRB1*11+and+variants+of+the+MHC+class+II+locus+are+strong+risk+factors+for+systemic+juvenile+idiopathic+arthritis},
	author = {Ombrello, Michael J and Remmers, Elaine F and Tachmazidou, Ioanna and Grom, Alexei and Foell, Dirk and Haas, Johannes-Peter and Martini, Alberto and Gattorno, Marco and {\"O}zen, Seza and Prahalad, Sampath and Zeft, Andrew S and Bohnsack, John F and Mellins, Elizabeth D and Ilowite, Norman T and Russo, Ricardo and Len, Claudio and Hilario, Maria Odete E and Oliveira, Sheila and Yeung, Rae S M and Rosenberg, Alan and Wedderburn, Lucy R and Anton, Jordi and Schwarz, Tobias and Hinks, Anne and Bilginer, Yelda and Park, Jane and Cobb, Joanna and Satorius, Colleen L and Han, Buhm and Baskin, Elizabeth and Signa, Sara and Duerr, Richard H and Achkar, J P and Kamboh, M Ilyas and Kaufman, Kenneth M and Kottyan, Leah C and Pinto, Dalila and Scherer, Stephen W and Alarc{\'o}n-Riquelme, Marta E and Docampo, Elisa and Xavier Estivill and G{\"u}l, Ahmet and British Society of Pediatric and Adolescent Rheumatology (BSPAR) Study Group and Childhood Arthritis Prospective Study (CAPS) Group and Randomized Placebo Phase Study of Rilonacept in sJIA (RAPPORT) Investigators and Sparks-Childhood Arthritis Response to Medication Study (CHARMS) Group and Biologically Based Outcome Predictors in JIA (BBOP) Group and de Bakker, Paul I W and Raychaudhuri, Soumya and Langefeld, Carl D and Thompson, Susan and Zeggini, Eleftheria and Thomson, Wendy and Kastner, Daniel L and Woo, Patricia and International Childhood Arthritis Genetics (INCHARGE) Consortium}
}
@article {1001731,
	title = {Partitioning heritability by functional annotation using genome-wide association summary statistics},
	journal = {Nat Genet},
	volume = {47},
	number = {11},
	year = {2015},
	month = {2015 Nov},
	pages = {1228-35},
	abstract = {Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here we analyze a broad set of functional elements, including cell type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes and leverages genome-wide information. Our findings include a large enrichment of heritability in conserved regions across many traits, a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers and many cell type-specific enrichments, including significant enrichment of central nervous system cell types in the heritability of body mass index, age at menarche, educational attainment and smoking behavior.},
	keywords = {Algorithms, Computer Simulation, Disease, Female, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Histones, Humans, Inheritance Patterns, Lysine, Male, Methylation, Models, Genetic, Polymorphism, Single Nucleotide},
	issn = {1546-1718},
	doi = {10.1038/ng.3404},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Partitioning+heritability+by+functional+annotation+using+genome-wide+association+summary+statistics},
	author = {Finucane, Hilary K and Bulik-Sullivan, Brendan and Gusev, Alexander and Trynka, Gosia and Reshef, Yakir and Po-Ru Loh and Anttila, Verneri and Xu, Han and Zang, Chongzhi and Farh, Kyle and Ripke, Stephan and Day, Felix R and ReproGen Consortium and Schizophrenia Working Group of the Psychiatric Genomics Consortium and RACI Consortium and Purcell, Shaun and Stahl, Eli and Lindstrom, Sara and Perry, John R B and Okada, Yukinori and Raychaudhuri, Soumya and Daly, Mark J and Patterson, Nick and Neale, Benjamin M and Price, Alkes L}
}
@article {1001726,
	title = {Polymorphisms of large effect explain the majority of the host genetic contribution to variation of HIV-1 virus load},
	journal = {Proc Natl Acad Sci U S A},
	volume = {112},
	number = {47},
	year = {2015},
	month = {2015 Nov 24},
	pages = {14658-63},
	abstract = {Previous genome-wide association studies (GWAS) of HIV-1-infected populations have been underpowered to detect common variants with moderate impact on disease outcome and have not assessed the phenotypic variance explained by genome-wide additive effects. By combining the majority of available genome-wide genotyping data in HIV-infected populations, we tested for association between \~{}8 million variants and viral load (HIV RNA copies per milliliter of plasma) in 6,315 individuals of European ancestry. The strongest signal of association was observed in the HLA class I region that was fully explained by independent effects mapping to five variable amino acid positions in the peptide binding grooves of the HLA-B and HLA-A proteins. We observed a second genome-wide significant association signal in the chemokine (C-C motif) receptor (CCR) gene cluster on chromosome 3. Conditional analysis showed that this signal could not be fully attributed to the known protective CCR5Δ32 allele and the risk P1 haplotype, suggesting further causal variants in this region. Heritability analysis demonstrated that common human genetic variation-mostly in the HLA and CCR5 regions-explains 25\% of the variability in viral load. This study suggests that analyses in non-European populations and of variant classes not assessed by GWAS should be priorities for the field going forward.},
	keywords = {Adult, Alleles, Amino Acids, Chromosomes, Human, Pair 3, Genetic Predisposition to Disease, Genome-Wide Association Study, HIV-1, HLA-B Antigens, Host-Pathogen Interactions, Humans, Inheritance Patterns, Physical Chromosome Mapping, Polymorphism, Single Nucleotide, Receptors, CCR5, Viral Load},
	issn = {1091-6490},
	doi = {10.1073/pnas.1514867112},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Polymorphisms+of+large+effect+explain+the+majority+of+the+host+genetic+contribution+to+variation+of+HIV-1+virus+load},
	author = {McLaren, Paul J and Coulonges, Cedric and Bartha, Istv{\'a}n and Lenz, Tobias L. and Deutsch, Aaron J and Bashirova, Arman and Buchbinder, Susan and Carrington, Mary N and Cossarizza, Andrea and Dalmau, Judith and De Luca, Andrea and Goedert, James J and Gurdasani, Deepti and Haas, David W and Herbeck, Joshua T and Johnson, Eric O and Kirk, Gregory D and Lambotte, Olivier and Luo, Ma and Mallal, Simon and van Manen, Dani{\"e}lle and Martinez-Picado, Javier and Meyer, Laurence and Miro, Jos{\'e} M and Mullins, James I and Obel, Niels and Poli, Guido and Sandhu, Manjinder S and Schuitemaker, Hanneke and Shea, Patrick R and Theodorou, Ioannis and Walker, Bruce D and Weintrob, Amy C and Winkler, Cheryl A and Wolinsky, Steven M and Raychaudhuri, Soumya and Goldstein, David B and Telenti, Amalio and de Bakker, Paul I W and Zagury, Jean-Fran{\c c}ois and Fellay, Jacques}
}
@article {1001721,
	title = {Rheumatoid Factor Is Associated With the Distribution of Hand Joint Destruction in Rheumatoid Arthritis},
	journal = {Arthritis Rheumatol},
	volume = {67},
	number = {12},
	year = {2015},
	month = {2015 Dec},
	pages = {3113-23},
	abstract = {OBJECTIVE: Rheumatoid arthritis (RA) is a chronic disease leading to joint destruction. Although many studies have addressed factors potentially correlated with the speed of joint destruction, less attention has been paid to the distribution of joint destruction in patients with RA. In this study, destruction of the hand bones in patients with RA was classified into 2 anatomic subgroups, the fingers and the non-fingers, with the aim of analyzing which factors are associated with destruction of the finger joints. METHODS: A total of 1,215 Japanese patients with RA were recruited from 2 different populations. The degree of joint destruction was assessed using the total modified Sharp/van der Heijde score (SHS) of radiographic joint damage. The SHS score of joint damage in the finger joints was used as the dependent variable, and the SHS score in the non-finger joints was used as a covariate. Age, sex, disease duration, smoking, C-reactive protein level, treatment for RA, and positivity for and levels of anti-citrullinated protein antibodies and rheumatoid factor (RF) were evaluated as candidate correlates. Overall effect sizes were assessed in a meta-analysis. In addition, associations observed in the Japanese patients were compared to those in a cohort of 157 Dutch RA patients in the BeSt study (a randomized, controlled trial involving 4 different strictly specified treatment strategies for early RA). RESULTS: Not surprisingly, disease duration in Japanese patients with RA was associated with the finger SHS score (P <= 0.00037). Both positivity for and levels of RF showed significant associations with the finger SHS score after adjustment for covariates (P = 0.0022 and P = 8.1 {\texttimes} 10(-7) , respectively). These associations were also true in relation to the time-averaged finger SHS score. An association between RF positivity and the finger SHS score was also observed in Dutch patients with RA in the BeSt study (P = 0.049). CONCLUSION: Positivity for and levels of RF are associated with finger joint destruction independent of non-finger joint destruction and other covariates. Our findings suggest that there are different mechanisms of joint destruction operating in the finger joints of patients with RA.},
	keywords = {Adult, Aged, Antirheumatic Agents, Arthritis, Rheumatoid, Asian Continental Ancestry Group, Autoantibodies, Cohort Studies, Disease Progression, European Continental Ancestry Group, Female, Finger Joint, Foot Joints, Hand Joints, HLA-DRB1 Chains, Humans, Japan, Linear Models, Male, Methotrexate, Middle Aged, Netherlands, Peptides, Cyclic, Radiography, Rheumatoid Factor, Severity of Illness Index},
	issn = {2326-5205},
	doi = {10.1002/art.39306},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/26245322},
	author = {Terao, Chikashi and Yamakawa, Noriyuki and Yano, Koichiro and Markusse, Iris M and Ikari, Katsunori and Yoshida, Shinji and Furu, Moritoshi and Hashimoto, Motomu and Ito, Hiromu and Fujii, Takao and Ohmura, Koichiro and Murakami, Kosaku and Takahashi, Meiko and Hamaguchi, Masahide and Tabara, Yasuharu and Taniguchi, Atsuo and Momohara, Shigeki and Raychaudhuri, Soumya and Allaart, Cornelia F and Yamanaka, Hisashi and Mimori, Tsuneyo and Matsuda, Fumihiko}
}
@article {1001541,
	title = {Immune cell profiling to guide therapeutic decisions in rheumatic diseases},
	journal = {Nat Rev Rheumatol},
	volume = {11},
	number = {9},
	year = {2015},
	month = {2015 Sep},
	pages = {541-51},
	abstract = {Biomarkers are needed to guide treatment decisions for patients with rheumatic diseases. Although the phenotypic and functional analysis of immune cells is an appealing strategy for understanding immune-mediated disease processes, immune cell profiling currently has no role in clinical rheumatology. New technologies, including mass cytometry, gene expression profiling by RNA sequencing (RNA-seq) and multiplexed functional assays, enable the analysis of immune cell function with unprecedented detail and promise not only a deeper understanding of pathogenesis, but also the discovery of novel biomarkers. The large and complex data sets generated by these technologies--big data--require specialized approaches for analysis and visualization of results. Standardization of assays and definition of the range of normal values are additional challenges when translating these novel approaches into clinical practice. In this Review, we discuss technological advances in the high-dimensional analysis of immune cells and consider how these developments might support the discovery of predictive biomarkers to benefit the practice of rheumatology and improve patient care.},
	keywords = {B-Lymphocytes, Cells, Cultured, Genome-Wide Association Study, Humans, Rheumatic Diseases, T-Lymphocytes},
	issn = {1759-4804},
	doi = {10.1038/nrrheum.2015.71},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Immune+cell+profiling+to+guide+therapeutic+decisions+in+rheumatic+diseases},
	author = {Ermann, Joerg and Rao, Deepak A and Teslovich, Nikola C and Brenner, Michael B and Raychaudhuri, Soumya}
}
@article {1109626,
	title = {Common genetic variants modulate pathogen-sensing responses in human dendritic cells},
	journal = {Science},
	volume = {343},
	number = {6175},
	year = {2014},
	month = {2014 Mar 07},
	pages = {1246980},
	abstract = {Little is known about how human genetic variation affects the responses to environmental stimuli in the context of complex diseases. Experimental and computational approaches were applied to determine the effects of genetic variation on the induction of pathogen-responsive genes in human dendritic cells. We identified 121 common genetic variants associated in cis with variation in expression responses to Escherichia coli lipopolysaccharide, influenza, or interferon-β (IFN-β). We localized and validated causal variants to binding sites of pathogen-activated STAT (signal transducer and activator of transcription) and IRF (IFN-regulatory factor) transcription factors. We also identified a common variant in IRF7 that is associated in trans with type I IFN induction in response to influenza infection. Our results reveal common alleles that explain interindividual variation in pathogen sensing and provide functional annotation for genetic variants that alter susceptibility to inflammatory diseases.},
	keywords = {Adult, Autoimmune Diseases, Communicable Diseases, Dendritic Cells, Escherichia coli, Female, Gene-Environment Interaction, Genetic Loci, Genome-Wide Association Study, HEK293 Cells, Host-Pathogen Interactions, Humans, Influenza A virus, Interferon Regulatory Factor-7, Interferon-beta, Lipopolysaccharides, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, STAT Transcription Factors, Transcriptome, Young Adult},
	issn = {1095-9203},
	doi = {10.1126/science.1246980},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Common+genetic+variants+modulate+pathogen-sensing+responses+in+human+dendritic+cells},
	author = {Lee, Mark N and Ye, Chun and Villani, Alexandra-Chlo{\'e} and Raj, Towfique and Li, Weibo and Eisenhaure, Thomas M and Imboywa, Selina H and Chipendo, Portia I and Ran, F Ann and Slowikowski, Kamil and Ward, Lucas D and Raddassi, Khadir and McCabe, Cristin and Lee, Michelle H and Frohlich, Irene Y and Hafler, David A and Kellis, Manolis and Raychaudhuri, Soumya and Zhang, Feng and Stranger, Barbara E and Benoist, Christophe O and De Jager, Philip L and Regev, Aviv and Hacohen, Nir}
}
@article {1109621,
	title = {Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility},
	journal = {Nat Genet},
	volume = {46},
	number = {3},
	year = {2014},
	month = {2014 Mar},
	pages = {234-44},
	abstract = {To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.},
	keywords = {Alleles, Asian Continental Ancestry Group, Case-Control Studies, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Genetic Predisposition to Disease, Genome-Wide Association Study, Hispanic Americans, Humans, Polymorphism, Single Nucleotide, Risk Factors},
	issn = {1546-1718},
	doi = {10.1038/ng.2897},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Genome-wide+trans-ancestry+meta-analysis+provides+insight+into+the+genetic+architecture+of+type+2+diabetes+susceptibility},
	author = {DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium and Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium and South Asian Type 2 Diabetes (SAT2D) Consortium and Mexican American Type 2 Diabetes (MAT2D) Consortium and Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium and Mahajan, Anubha and Go, Min Jin and Zhang, Weihua and Below, Jennifer E and Gaulton, Kyle J and Ferreira, Teresa and Horikoshi, Momoko and Johnson, Andrew D and Ng, Maggie C Y and Prokopenko, Inga and Saleheen, Danish and Wang, Xu and Zeggini, Eleftheria and Abecasis, Goncalo R and Adair, Linda S and Almgren, Peter and Atalay, Mustafa and Aung, Tin and Baldassarre, Damiano and Balkau, Beverley and Bao, Yuqian and Barnett, Anthony H and Barroso, Ines and Basit, Abdul and Been, Latonya F and Beilby, John and Bell, Graeme I and Benediktsson, Rafn and Bergman, Richard N and Boehm, Bernhard O and Boerwinkle, Eric and Bonnycastle, Lori L and Burtt, No{\"e}l and Cai, Qiuyin and Campbell, Harry and Carey, Jason and Cauchi, Stephane and Caulfield, Mark and Chan, Juliana C N and Chang, Li-Ching and Chang, Tien-Jyun and Chang, Yi-Cheng and Charpentier, Guillaume and Chen, Chien-Hsiun and Chen, Han and Chen, Yuan-Tsong and Chia, Kee-Seng and Chidambaram, Manickam and Chines, Peter S and Cho, Nam H and Cho, Young Min and Chuang, Lee-Ming and Collins, Francis S and Cornelis, Marylin C and Couper, David J and Crenshaw, Andrew T and van Dam, Rob M and Danesh, John and Das, Debashish and de Faire, Ulf and Dedoussis, George and Deloukas, Panos and Dimas, Antigone S and Dina, Christian and Doney, Alex S and Donnelly, Peter J and Dorkhan, Mozhgan and van Duijn, Cornelia and Dupuis, Jos{\'e}e and Edkins, Sarah and Elliott, Paul and Emilsson, Valur and Erbel, Raimund and Eriksson, Johan G and Escobedo, Jorge and Esko, Tonu and Eury, Elodie and Florez, Jose C and Fontanillas, Pierre and Forouhi, Nita G and Forsen, Tom and Fox, Caroline and Fraser, Ross M and Frayling, Timothy M and Froguel, Philippe and Frossard, Philippe and Gao, Yutang and Gertow, Karl and Gieger, Christian and Gigante, Bruna and Grallert, Harald and Grant, George B and Grrop, Leif C and Groves, Chrisropher J and Grundberg, Elin and Guiducci, Candace and Hamsten, Anders and Han, Bok-Ghee and Hara, Kazuo and Hassanali, Neelam and Hattersley, Andrew T and Hayward, Caroline and Hedman, Asa K and Herder, Christian and Hofman, Albert and Holmen, Oddgeir L and Hovingh, Kees and Hreidarsson, Astradur B and Hu, Cheng and Hu, Frank B and Hui, Jennie and Humphries, Steve E and Hunt, Sarah E and Hunter, David J and Hveem, Kristian and Hydrie, Zafar I and Ikegami, Hiroshi and Illig, Thomas and Ingelsson, Erik and Islam, Muhammed and Isomaa, Bo and Jackson, Anne U and Jafar, Tazeen and James, Alan and Jia, Weiping and J{\"o}ckel, Karl-Heinz and Jonsson, Anna and Jowett, Jeremy B M and Kadowaki, Takashi and Kang, Hyun Min and Kanoni, Stavroula and Kao, Wen Hong L and Kathiresan, Sekar and Kato, Norihiro and Katulanda, Prasad and Keinanen-Kiukaanniemi, Kirkka M and Kelly, Ann M and Khan, Hassan and Khaw, Kay-Tee and Khor, Chiea-Chuen and Kim, Hyung-Lae and Kim, Sangsoo and Kim, Young Jin and Kinnunen, Leena and Klopp, Norman and Kong, Augustine and Korpi-Hy{\"o}v{\"a}lti, Eeva and Kowlessur, Sudhir and Kraft, Peter and Kravic, Jasmina and Kristensen, Malene M and Krithika, S and Kumar, Ashish and Kumate, Jesus and Kuusisto, Johanna and Kwak, Soo Heon and Laakso, Markku and Lagou, Vasiliki and Lakka, Timo A and Langenberg, Claudia and Langford, Cordelia and Robert Lawrence and Leander, Karin and Lee, Jen-Mai and Lee, Nanette R and Li, Man and Li, Xinzhong and Li, Yun and Liang, Junbin and Liju, Samuel and Lim, Wei-Yen and Lind, Lars and Lindgren, Cecilia M and Lindholm, Eero and Liu, Ching-Ti and Liu, Jianjun and Lobbens, St{\'e}phane and Long, Jirong and Loos, Ruth J F and Lu, Wei and Luan, Jian{\textquoteright}an and Lyssenko, Valeriya and Ma, Ronald C W and Maeda, Shiro and M{\"a}gi, Reedik and M{\"a}nnisto, Satu and Matthews, David R and Meigs, James B and Melander, Olle and Metspalu, Andres and Meyer, Julia and Mirza, Ghazala and Mihailov, Evelin and Moebus, Susanne and Mohan, Viswanathan and Mohlke, Karen L and Morris, Andrew D and M{\"u}hleisen, Thomas W and M{\"u}ller-Nurasyid, Martina and Musk, Bill and Nakamura, Jiro and Nakashima, Eitaro and Navarro, Pau and Ng, Peng-Keat and Nica, Alexandra C and Nilsson, Peter M and Nj{\o}lstad, Inger and N{\"o}then, Markus M and Ohnaka, Keizo and Ong, Twee Hee and Owen, Katharine R and Palmer, Colin N A and Pankow, James S and Park, Kyong Soo and Parkin, Melissa and Pechlivanis, Sonali and Pedersen, Nancy L and Peltonen, Leena and Perry, John R B and Peters, Annette and Pinidiyapathirage, Janini M and Platou, Carl G and Potter, Simon and Price, Jackie F and Qi, Lu and Radha, Venkatesan and Rallidis, Loukianos and Rasheed, Asif and Rathman, Wolfgang and Rauramaa, Rainer and Raychaudhuri, Soumya and Rayner, N William and Rees, Simon D and Rehnberg, Emil and Ripatti, Samuli and Robertson, Neil and Roden, Michael and Rossin, Elizabeth J and Rudan, Igor and Rybin, Denis and Saaristo, Timo E and Salomaa, Veikko and Saltevo, Juha and Samuel, Maria and Sanghera, Dharambir K and Saramies, Jouko and Scott, James and Scott, Laura J and Scott, Robert A and Segr{\`e}, Ayellet V and Sehmi, Joban and Sennblad, Bengt and Shah, Nabi and Shah, Sonia and Shera, A Samad and Ou Shu, Xiao and Shuldiner, Alan R and Sigur{\dj}sson, Gunnar and Sijbrands, Eric and Silveira, Angela and Sim, Xueling and Sivapalaratnam, Suthesh and Small, Kerrin S and So, Wing Yee and Stan{\v c}{\'a}kov{\'a}, Alena and Stefansson, Kari and Steinbach, Gerald and Steinthorsdottir, Valgerdur and Stirrups, Kathleen and Strawbridge, Rona J and Stringham, Heather M and Sun, Qi and Suo, Chen and Syv{\"a}nen, Ann-Christine and Takayanagi, Ryoichi and Takeuchi, Fumihiko and Tay, Wan Ting and Teslovich, Tanya M and Thorand, Barbara and Thorleifsson, Gudmar and Thorsteinsdottir, Unnur and Tikkanen, Emmi and Trakalo, Joseph and Tremoli, Elena and Trip, Mieke D and Tsai, Fuu Jen and Tuomi, Tiinamaija and Tuomilehto, Jaakko and Uitterlinden, Andre G and Valladares-Salgado, Adan and Vedantam, Sailaja and Veglia, Fabrizio and Voight, Benjamin F and Wang, Congrong and Wareham, Nicholas J and Wennauer, Roman and Wickremasinghe, Ananda R and Wilsgaard, Tom and Wilson, James F and Wiltshire, Steven and Winckler, Wendy and Wong, Tien Yin and Wood, Andrew R and Wu, Jer-Yuarn and Wu, Ying and Yamamoto, Ken and Yamauchi, Toshimasa and Yang, Mingyu and Yengo, Loic and Yokota, Mitsuhiro and Young, Robin and Zabaneh, Delilah and Zhang, Fan and Zhang, Rong and Zheng, Wei and Zimmet, Paul Z and Altshuler, David and Bowden, Donald W and Cho, Yoon Shin and Cox, Nancy J and Cruz, Miguel and Hanis, Craig L and Kooner, Jaspal and Lee, Jong-Young and Seielstad, Mark and Teo, Yik Ying and Boehnke, Michael and Parra, Esteban J and Chambers, Jonh C and Tai, E Shyong and McCarthy, Mark I and Morris, Andrew P}
}
@article {1109636,
	title = {HLA-DRB1-associated rheumatoid arthritis risk at multiple levels in African Americans: hierarchical classification systems, amino acid positions, and residues},
	journal = {Arthritis Rheumatol},
	volume = {66},
	number = {12},
	year = {2014},
	month = {2014 Dec},
	pages = {3274-82},
	abstract = {OBJECTIVE: To evaluate HLA-DRB1 genetic risk of rheumatoid arthritis (RA) in African Americans by 3 validated allele classification systems and by amino acid position and residue, and to compare genetic risk between African American and European ancestries. METHODS: Four-digit HLA-DRB1 genotyping was performed on 561 autoantibody-positive African American cases and 776 African American controls. Association analysis was performed on Tezenas du Montcel (TdM), de Vries (DV), and Mattey classification system alleles and separately by amino acid position and individual residues. RESULTS: TdM S2 and S3P alleles were associated with RA (odds ratio [95\% confidence interval] 2.8 [2.0-3.9] and 2.1 [1.7-2.7], respectively). The DV (P = 3.2 {\texttimes} 10(-12)) and Mattey (P = 6.5 {\texttimes} 10(-13)) system alleles were both protective in African Americans. Amino acid position 11 (permutation P \&lt; 0.00001) accounted for nearly all variability explained by HLA-DRB1, although conditional analysis demonstrated that position 57 was also significant (0.01 <= permutation P <= 0.05). The valine and aspartic acid residues at position 11 conferred the highest risk of RA in African Americans. CONCLUSION: With some exceptions, the genetic risk conferred by HLA-DRB1 in African Americans is similar to that in individuals of European ancestry at multiple levels: classification system (e.g., TdM), amino acid position (e.g., 11), and residue (Val11). Unlike that reported for individuals of European ancestry, amino acid position 57 was associated with RA in African Americans, but positions 71 and 74 were not. Asp11 (odds ratio 1 in European ancestry) corresponds to the 4-digit classical allele *09:01, which is also a risk allele for RA in Koreans.},
	keywords = {Adult, African Americans, Alleles, Amino Acid Motifs, Amino Acids, Arthritis, Rheumatoid, Case-Control Studies, Epitopes, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, HLA-DRB1 Chains, Humans, Male, Middle Aged, Odds Ratio},
	issn = {2326-5205},
	doi = {10.1002/art.38855},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=HLA-DRB1-associated+rheumatoid+arthritis+risk+at+multiple+levels+in+African+Americans\%3A+hierarchical+classification+systems\%2C+amino+acid+positions\%2C+and+residues},
	author = {Reynolds, Richard J and Ahmed, Altan F and Danila, Maria I and Hughes, Laura B and Consortium for the Longitudinal Evaluation of African Americans with Early Rheumatoid Arthritis Investigators and Gregersen, Peter K and Raychaudhuri, Soumya and Plenge, Robert M and Bridges, S Louis}
}
@article {1109616,
	title = {The influence of polygenic risk scores on heritability of anti-CCP level in RA},
	journal = {Genes Immun},
	volume = {15},
	number = {2},
	year = {2014},
	month = {2014 Mar},
	pages = {107-14},
	abstract = {The objective of this study was to study genetic factors that influence quantitative anticyclic citrullinated peptide (anti-CCP) antibody levels in RA patients. We carried out a genome-wide association study (GWAS) meta-analysis using 1975 anti-CCP+ RA patients from three large cohorts, the Brigham Rheumatoid Arthritis Sequential Study (BRASS), North American Rheumatoid Arthritis Consortium (NARAC) and the Epidemiological Investigation of RA (EIRA). We also carried out a genome-wide complex trait analysis (GCTA) to estimate the heritability of anti-CCP levels. GWAS-meta-analysis showed that anti-CCP levels were most strongly associated with the human leukocyte antigen (HLA) region with a P-value of 2 {\texttimes} 10(-11) for rs1980493. There were 112 SNPs in this region that exceeded the genome-wide significance threshold of 5 {\texttimes} 10(-8), and all were in linkage disequilibrium (LD) with the HLA- DRB1*03 allele with LD r(2) in the range of 0.25-0.88. Suggestive novel associations outside of the HLA region were also observed for rs8063248 (near the GP2 gene) with a P-value of 3 {\texttimes} 10(-7). None of the known RA risk alleles (\~{}52 loci) were associated with anti-CCP level. Heritability analysis estimated that 44\% of anti-CCP variation was attributable to genetic factors captured by GWAS variants. In summary, anti-CCP level is a heritable trait, and HLA-DR3 and GP2 are associated with lower anti-CCP levels.},
	keywords = {Arthritis, Rheumatoid, Autoantibodies, Case-Control Studies, Cohort Studies, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, GPI-Linked Proteins, HLA-DR3 Antigen, HLA-DRB1 Chains, Humans, Linkage Disequilibrium, Male, Middle Aged, Models, Genetic, Peptides, Cyclic, Polymorphism, Single Nucleotide, Prospective Studies},
	issn = {1476-5470},
	doi = {10.1038/gene.2013.68},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=The+influence+of+polygenic+risk+scores+on+heritability+of+anti-CCP+level+in+RA},
	author = {Cui, J and Taylor, K E and Lee, Y C and K{\"a}llberg, H and Weinblatt, M E and Coblyn, J S and Klareskog, L and Criswell, L A and Gregersen, P K and Shadick, N A and Plenge, R M and Karlson, EW}
}
@article {1109631,
	title = {An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge},
	journal = {Genome Biol},
	volume = {15},
	number = {3},
	year = {2014},
	month = {2014 Mar 25},
	pages = {R53},
	abstract = {BACKGROUND: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.},
	keywords = {Child, Databases, Genetic, Female, Financing, Organized, Genetic Testing, Genomics, Heart Defects, Congenital, Humans, Male, Myopathies, Structural, Congenital, Peer Review, Research, Sequence Analysis, DNA},
	issn = {1474-760X},
	doi = {10.1186/gb-2014-15-3-r53},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=An+international+effort+towards+developing+standards+for+best+practices+in+analysis\%2C+interpretation+and+reporting+of+clinical+genome+sequencing+results+in+the+CLARITY+Challenge},
	author = {Brownstein, Catherine A and Beggs, Alan H and Homer, Nils and Merriman, Barry and Yu, Timothy W and Flannery, Katherine C and DeChene, Elizabeth T and Towne, Meghan C and Savage, Sarah K and Price, Emily N and Holm, Ingrid A and Luquette, Lovelace J and Lyon, Elaine and Majzoub, Joseph and Neupert, Peter and McCallie, David and Szolovits, Peter and Willard, Huntington F and Mendelsohn, Nancy J and Temme, Renee and Finkel, Richard S and Yum, Sabrina W and Medne, Livija and Sunyaev, Shamil R. and Adzhubey, Ivan and Cassa, Christopher A and de Bakker, Paul I W and Duzkale, Hatice and Dworzy{\'n}ski, Piotr and Fairbrother, William and Francioli, Laurent and Funke, Birgit H and Giovanni, Monica A and Handsaker, Robert E and Lage, Kasper and Lebo, Matthew S and Lek, Monkol and Leshchiner, Ignaty and MacArthur, Daniel G and McLaughlin, Heather M and Murray, Michael F and Pers, Tune H and Polak, Paz P and Raychaudhuri, Soumya and Rehm, Heidi L and Soemedi, Rachel and Stitziel, Nathan O and Vestecka, Sara and Supper, Jochen and Gugenmus, Claudia and Klocke, Bernward and Hahn, Alexander and Schubach, Max and Menzel, Mortiz and Biskup, Saskia and Freisinger, Peter and Deng, Mario and Braun, Martin and Perner, Sven and Smith, Richard J H and Andorf, Janeen L and Huang, Jian and Ryckman, Kelli and Sheffield, Val C and Stone, Edwin M and Bair, Thomas and Black-Ziegelbein, E Ann and Braun, Terry A and Darbro, Benjamin and DeLuca, Adam P and Kolbe, Diana L and Scheetz, Todd E and Shearer, Aiden E and Sompallae, Rama and Kai Wang and Bassuk, Alexander G and Edens, Erik and Mathews, Katherine and Moore, Steven A and Shchelochkov, Oleg A and Trapane, Pamela and Bossler, Aaron and Campbell, Colleen A and Heusel, Jonathan W and Kwitek, Anne and Maga, Tara and Panzer, Karin and Wassink, Thomas and Van Daele, Douglas and Azaiez, Hela and Booth, Kevin and Meyer, Nic and Segal, Michael M and Williams, Marc S and Tromp, Gerard and White, Peter and Corsmeier, Donald and Fitzgerald-Butt, Sara and Herman, Gail and Lamb-Thrush, Devon and McBride, Kim L and Newsom, David and Pierson, Christopher R and Rakowsky, Alexander T and Maver, Ale{\v s} and Lovre{\v c}i{\'c}, Luca and Palanda{\v c}i{\'c}, Anja and Peterlin, Borut and Torkamani, Ali and Wedell, Anna and Huss, Mikael and Alexeyenko, Andrey and Lindvall, Jessica M and Magnusson, M{\r a}ns and Nilsson, Daniel and Stranneheim, Henrik and Taylan, Fulya and Gilissen, Christian and Hoischen, Alexander and van Bon, Bregje and Yntema, Helger and Nelen, Marcel and Zhang, Weidong and Sager, Jason and Zhang, Lu and Blair, Kathryn and Kural, Deniz and Cariaso, Michael and Lennon, Greg G and Javed, Asif and Agrawal, Saloni and Ng, Pauline C and Sandhu, Komal S and Krishna, Shuba and Veeramachaneni, Vamsi and Isakov, Ofer and Halperin, Eran and Friedman, Eitan and Shomron, Noam and Glusman, Gustavo and Roach, Jared C and Caballero, Juan and Cox, Hannah C and Mauldin, Denise and Ament, Seth A and Rowen, Lee and Richards, Daniel R and San Lucas, F Anthony and Gonzalez-Garay, Manuel L and Caskey, C Thomas and Bai, Yu and Huang, Ying and Fang, Fang and Zhang, Yan and Wang, Zhengyuan and Barrera, Jorge and Garcia-Lobo, Juan M and Gonz{\'a}lez-Lamu{\~n}o, Domingo and Llorca, Javier and Rodriguez, Maria C and Varela, Ignacio and Reese, Martin G and De La Vega, Francisco M and Kiruluta, Edward and Cargill, Michele and Hart, Reece K and Sorenson, Jon M and Lyon, Gholson J and Stevenson, David A and Bray, Bruce E and Moore, Barry M and Eilbeck, Karen and Yandell, Mark and Zhao, Hongyu and Hou, Lin and Chen, Xiaowei and Yan, Xiting and Chen, Mengjie and Li, Cong and Yang, Can and Gunel, Murat and Li, Peining and Kong, Yong and Alexander, Austin C and Albertyn, Zayed I and Boycott, Kym M and Bulman, Dennis E and Gordon, Paul M K and Innes, A Micheil and Knoppers, Bartha M and Majewski, Jacek and Marshall, Christian R and Parboosingh, Jillian S and Sawyer, Sarah L and Samuels, Mark E and Schwartzentruber, Jeremy and Kohane, Isaac S and Margulies, David M}
}
@article {1001856,
	title = {Fast pairwise IBD association testing in genome-wide association studies},
	journal = {Bioinformatics},
	volume = {30},
	number = {2},
	year = {2014},
	month = {2014 Jan 15},
	pages = {206-13},
	abstract = {MOTIVATION: Recently, investigators have proposed state-of-the-art Identity-by-descent (IBD) mapping methods to detect IBD segments between purportedly unrelated individuals. The IBD information can then be used for association testing in genetic association studies. One approach for this IBD association testing strategy is to test for excessive IBD between pairs of cases ({\textquoteright}pairwise method{\textquoteright}). However, this approach is inefficient because it requires a large number of permutations. Moreover, a limited number of permutations define a lower bound for P-values, which makes fine-mapping of associated regions difficult because, in practice, a much larger genomic region is implicated than the region that is actually associated. RESULTS: In this article, we introduce a new pairwise method {\textquoteright}Fast-Pairwise{\textquoteright}. Fast-Pairwise uses importance sampling to improve efficiency and enable approximation of extremely small P-values. Fast-Pairwise method takes only days to complete a genome-wide scan. In the application to the WTCCC type 1 diabetes data, Fast-Pairwise successfully fine-maps a known human leukocyte antigen gene that is known to cause the disease. AVAILABILITY: Fast-Pairwise is publicly available at: http://genetics.cs.ucla.edu/graphibd.},
	keywords = {Algorithms, Case-Control Studies, Chromosome Mapping, Computer Simulation, Diabetes Mellitus, Type 1, Genome, Human, Genome-Wide Association Study, HLA Antigens, Humans, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable},
	issn = {1367-4811},
	doi = {10.1093/bioinformatics/btt609},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Fast+pairwise+IBD+association+testing+in+genome-wide+association+studies},
	author = {Han, Buhm and Kang, Eun Yong and Raychaudhuri, Soumya and de Bakker, Paul I W and Eskin, Eleazar}
}
@article {1001846,
	title = {Genetics of rheumatoid arthritis contributes to biology and drug discovery},
	journal = {Nature},
	volume = {506},
	number = {7488},
	year = {2014},
	month = {2014 Feb 20},
	pages = {376-81},
	abstract = {A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA). Here we performed a genome-wide association study meta-analysis in a total of \&gt;100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating \~{}10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2 - 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation, cis-acting expression quantitative trait loci and pathway analyses--as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes--to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.},
	keywords = {Alleles, Animals, Arthritis, Rheumatoid, Asian Continental Ancestry Group, Case-Control Studies, Computational Biology, Drug Discovery, Drug Repositioning, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Hematologic Neoplasms, Humans, Male, Mice, Mice, Knockout, Molecular Targeted Therapy, Polymorphism, Single Nucleotide},
	issn = {1476-4687},
	doi = {10.1038/nature12873},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/24390342},
	author = {Okada, Yukinori and Wu, Di and Trynka, Gosia and Raj, Towfique and Terao, Chikashi and Ikari, Katsunori and Kochi, Yuta and Ohmura, Koichiro and Suzuki, Akari and Yoshida, Shinji and Graham, Robert R and Manoharan, Arun and Ortmann, Ward and Bhangale, Tushar and Denny, Joshua C and Carroll, Robert J and Eyler, Anne E and Greenberg, Jeffrey D and Kremer, Joel M and Pappas, Dimitrios A and Jiang, Lei and Yin, Jian and Ye, Lingying and Su, Ding-Feng and Yang, Jian and Xie, Gang and Keystone, Ed and Westra, Harm-Jan and Esko, T{\~o}nu and Metspalu, Andres and Zhou, Xuezhong and Gupta, Namrata and Mirel, Daniel and Stahl, Eli A and Diogo, Doroth{\'e}e and Cui, Jing and Liao, Katherine and Guo, Michael H and Myouzen, Keiko and Kawaguchi, Takahisa and Coenen, Marieke Jh and van Riel, Piet L C M and van de Laar, Mart A F J and Guchelaar, Henk-Jan and Huizinga, Tom W J and Dieud{\'e}, Philippe and Mariette, Xavier and Bridges, S Louis and Zhernakova, Alexandra and Toes, Rene E M and Tak, Paul P and Miceli-Richard, Corinne and Bang, So-Young and Lee, Hye-Soon and Martin, Javier and Gonzalez-Gay, Miguel A and Rodriguez-Rodriguez, Luis and Rantap{\"a}{\"a}-Dahlqvist, Solbritt and Arlestig, Lisbeth and Choi, Hyon K and Kamatani, Yoichiro and Galan, Pilar and Lathrop, Mark and RACI Consortium and GARNET consortium and Eyre, Steve and Bowes, John and Barton, Anne and de Vries, Niek and Moreland, Larry W and Criswell, Lindsey A and Karlson, Elizabeth W and Taniguchi, Atsuo and Yamada, Ryo and Kubo, Michiaki and Liu, Jun S and Bae, Sang-Cheol and Worthington, Jane and Padyukov, Leonid and Klareskog, Lars and Gregersen, Peter K and Raychaudhuri, Soumya and Stranger, Barbara E and De Jager, Philip L and Franke, Lude and Visscher, Peter M and Brown, Matthew A and Yamanaka, Hisashi and Mimori, Tsuneyo and Takahashi, Atsushi and Xu, Huji and Behrens, Timothy W and Siminovitch, Katherine A and Momohara, Shigeki and Matsuda, Fumihiko and Yamamoto, Kazuhiko and Plenge, Robert M}
}
@article {1001851,
	title = {Integration of sequence data from a Consanguineous family with genetic data from an outbred population identifies PLB1 as a candidate rheumatoid arthritis risk gene},
	journal = {PLoS One},
	volume = {9},
	number = {2},
	year = {2014},
	month = {2014},
	pages = {e87645},
	abstract = {Integrating genetic data from families with highly penetrant forms of disease together with genetic data from outbred populations represents a promising strategy to uncover the complete frequency spectrum of risk alleles for complex traits such as rheumatoid arthritis (RA). Here, we demonstrate that rare, low-frequency and common alleles at one gene locus, phospholipase B1 (PLB1), might contribute to risk of RA in a 4-generation consanguineous pedigree (Middle Eastern ancestry) and also in unrelated individuals from the general population (European ancestry). Through identity-by-descent (IBD) mapping and whole-exome sequencing, we identified a non-synonymous c.2263G\&gt;C (p.G755R) mutation at the PLB1 gene on 2q23, which significantly co-segregated with RA in family members with a dominant mode of inheritance (P = 0.009). We further evaluated PLB1 variants and risk of RA using a GWAS meta-analysis of 8,875 RA cases and 29,367 controls of European ancestry. We identified significant contributions of two independent non-coding variants near PLB1 with risk of RA (rs116018341 [MAF = 0.042] and rs116541814 [MAF = 0.021], combined P = 3.2 {\texttimes} 10(-6)). Finally, we performed deep exon sequencing of PLB1 in 1,088 RA cases and 1,088 controls (European ancestry), and identified suggestive dispersion of rare protein-coding variant frequencies between cases and controls (P = 0.049 for C-alpha test and P = 0.055 for SKAT). Together, these data suggest that PLB1 is a candidate risk gene for RA. Future studies to characterize the full spectrum of genetic risk in the PLB1 genetic locus are warranted.},
	keywords = {Arthritis, Rheumatoid, Base Sequence, Cohort Studies, Consanguinity, European Continental Ancestry Group, Exome, Exons, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotyping Techniques, High-Throughput Nucleotide Sequencing, Humans, Lysophospholipase, Male, Meta-Analysis as Topic, Mutation, Pedigree, Polymorphism, Single Nucleotide, Reproducibility of Results, Risk Factors},
	issn = {1932-6203},
	doi = {10.1371/journal.pone.0087645},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Integration+of+sequence+data+from+a+Consanguineous+family+with+genetic+data+from+an+outbred+population+identifies+PLB1+as+a+candidate+rheumatoid+arthritis+risk+gene},
	author = {Okada, Yukinori and Diogo, Dorothee and Greenberg, Jeffrey D and Mouassess, Faten and Achkar, Walid A L and Fulton, Robert S and Denny, Joshua C and Gupta, Namrata and Mirel, Daniel and Gabriel, Stacy and Li, Gang and Kremer, Joel M and Pappas, Dimitrios A and Carroll, Robert J and Eyler, Anne E and Trynka, Gosia and Stahl, Eli A and Cui, Jing and Saxena, Richa and Coenen, Marieke Jh and Guchelaar, Henk-Jan and Huizinga, Tom W J and Dieud{\'e}, Philippe and Mariette, Xavier and Barton, Anne and Canh{\~a}o, Helena and Fonseca, Jo{\~a}o E and de Vries, Niek and Tak, Paul P and Moreland, Larry W and Bridges, S Louis and Miceli-Richard, Corinne and Choi, Hyon K and Kamatani, Yoichiro and Galan, Pilar and Lathrop, Mark and Raj, Towfique and De Jager, Philip L and Raychaudhuri, Soumya and Worthington, Jane and Padyukov, Leonid and Klareskog, Lars and Siminovitch, Katherine A and Gregersen, Peter K and Mardis, Elaine R and Arayssi, Thurayya and Kazkaz, Layla A and Plenge, Robert M}
}
@article {1001841,
	title = {Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes},
	journal = {Science},
	volume = {344},
	number = {6183},
	year = {2014},
	month = {2014 May 02},
	pages = {519-23},
	abstract = {To extend our understanding of the genetic basis of human immune function and dysfunction, we performed an expression quantitative trait locus (eQTL) study of purified CD4(+) T cells and monocytes, representing adaptive and innate immunity, in a multi-ethnic cohort of 461 healthy individuals. Context-specific cis- and trans-eQTLs were identified, and cross-population mapping allowed, in some cases, putative functional assignment of candidate causal regulatory variants for disease-associated loci. We note an over-representation of T cell-specific eQTLs among susceptibility alleles for autoimmune diseases and of monocyte-specific eQTLs among Alzheimer{\textquoteright}s and Parkinson{\textquoteright}s disease variants. This polarization implicates specific immune cell types in these diseases and points to the need to identify the cell-autonomous effects of disease susceptibility variants.},
	keywords = {Adaptive Immunity, Alleles, Alzheimer Disease, Autoimmune Diseases, Autoimmunity, CD4-Positive T-Lymphocytes, Ethnic Groups, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Immunity, Innate, Monocytes, Multiple Sclerosis, Neurodegenerative Diseases, Parkinson Disease, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Rheumatic Fever, Transcriptome},
	issn = {1095-9203},
	doi = {10.1126/science.1249547},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Polarization+of+the+effects+of+autoimmune+and+neurodegenerative+risk+alleles+in+leukocytes},
	author = {Raj, Towfique and Rothamel, Katie and Mostafavi, Sara and Ye, Chun and Lee, Mark N and Replogle, Joseph M and Feng, Ting and Lee, Michelle and Asinovski, Natasha and Frohlich, Irene and Imboywa, Selina and Von Korff, Alina and Okada, Yukinori and Patsopoulos, Nikolaos A and Davis, Scott and McCabe, Cristin and Paik, Hyun-il and Srivastava, Gyan P and Raychaudhuri, Soumya and Hafler, David A and Koller, Daphne and Regev, Aviv and Hacohen, Nir and Mathis, Diane and Benoist, Christophe and Stranger, Barbara E and De Jager, Philip L}
}
@article {1001836,
	title = {Association between low density lipoprotein and rheumatoid arthritis genetic factors with low density lipoprotein levels in rheumatoid arthritis and non-rheumatoid arthritis controls},
	journal = {Ann Rheum Dis},
	volume = {73},
	number = {6},
	year = {2014},
	month = {2014 Jun},
	pages = {1170-5},
	abstract = {OBJECTIVES: While genetic determinants of low density lipoprotein (LDL) cholesterol levels are well characterised in the general population, they are understudied in rheumatoid arthritis (RA). Our objective was to determine the association of established LDL and RA genetic alleles with LDL levels in RA cases compared with non-RA controls. METHODS: Using data from electronic medical records, we linked validated RA cases and non-RA controls to discarded blood samples. For each individual, we extracted data on: first LDL measurement, age, gender and year of LDL measurement. We genotyped subjects for 11 LDL and 44 non-HLA RA alleles, and calculated RA and LDL genetic risk scores (GRS). We tested the association between each GRS and LDL level using multivariate linear regression models adjusted for age, gender, year of LDL measurement and RA status. RESULTS: Among 567 RA cases and 979 controls, 80\% were female and mean age at the first LDL measurement was 55 years. RA cases had significantly lower mean LDL levels than controls (117.2 vs 125.6 mg/dl, respectively, p\&lt;0.0001). Each unit increase in LDL GRS was associated with 0.8 mg/dl higher LDL levels in both RA cases and controls (p=3.0{\texttimes}10(-7)). Each unit increase in RA GRS was associated with 4.3 mg/dl lower LDL levels in both groups (p=0.01). CONCLUSIONS: LDL alleles were associated with higher LDL levels in RA. RA alleles were associated with lower LDL levels in both RA cases and controls. As RA cases carry more RA alleles, these findings suggest a genetic basis for epidemiological observations of lower LDL levels in RA.},
	keywords = {Adult, Aged, Arthritis, Rheumatoid, Case-Control Studies, Dyslipidemias, Female, Genetic Predisposition to Disease, Genotype, Humans, Lipoproteins, LDL, Male, Middle Aged, Polymorphism, Single Nucleotide},
	issn = {1468-2060},
	doi = {10.1136/annrheumdis-2012-203202},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Association+between+low+density+lipoprotein+and+rheumatoid+arthritis+genetic+factors+with+low+density+lipoprotein+levels+in+rheumatoid+arthritis+and+non-rheumatoid+arthritis+controls},
	author = {Liao, Katherine P and Diogo, Doroth{\'e}e and Cui, Jing and Cai, Tianxi and Okada, Yukinori and Gainer, Vivian S and Murphy, Shawn N and Gupta, Namrata and Mirel, Daniel and Ananthakrishnan, Ashwin N and Szolovits, Peter and Shaw, Stanley Y and Raychaudhuri, Soumya and Churchill, Susanne and Kohane, Isaac and Karlson, Elizabeth W and Plenge, Robert M}
}
@article {1001831,
	title = {Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization},
	journal = {Nat Genet},
	volume = {46},
	number = {8},
	year = {2014},
	month = {2014 Aug},
	pages = {826-36},
	abstract = {The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain \~{}8-10\% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD.},
	keywords = {Adult, Aged, Arrhythmias, Cardiac, Calcium Signaling, Death, Sudden, Cardiac, Electrocardiography, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Heart Ventricles, Humans, Long QT Syndrome, Male, Middle Aged, Myocardium, Polymorphism, Single Nucleotide},
	issn = {1546-1718},
	doi = {10.1038/ng.3014},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Genetic+association+study+of+QT+interval+highlights+role+for+calcium+signaling+pathways+in+myocardial+repolarization},
	author = {Arking, Dan E and Pulit, Sara L and Crotti, Lia and van der Harst, Pim and Munroe, Patricia B and Koopmann, Tamara T and Sotoodehnia, Nona and Rossin, Elizabeth J and Morley, Michael and Wang, Xinchen and Johnson, Andrew D and Lundby, Alicia and Gudbjartsson, Dan{\'\i}el F and Noseworthy, Peter A and Eijgelsheim, Mark and Bradford, Yuki and Tarasov, Kirill V and D{\"o}rr, Marcus and M{\"u}ller-Nurasyid, Martina and Lahtinen, Annukka M and Nolte, Ilja M and Smith, Albert Vernon and Bis, Joshua C and Isaacs, Aaron and Newhouse, Stephen J and Evans, Daniel S and Post, Wendy S and Waggott, Daryl and Lyytik{\"a}inen, Leo-Pekka and Hicks, Andrew A and Eisele, Lewin and Ellinghaus, David and Hayward, Caroline and Navarro, Pau and Ulivi, Sheila and Tanaka, Toshiko and Tester, David J and Chatel, St{\'e}phanie and Gustafsson, Stefan and Kumari, Meena and Morris, Richard W and Naluai, {\r A}sa T and Padmanabhan, Sandosh and Kluttig, Alexander and Strohmer, Bernhard and Panayiotou, Andrie G and Torres, Maria and Knoflach, Michael and Hubacek, Jaroslav A and Slowikowski, Kamil and Raychaudhuri, Soumya and Kumar, Runjun D and Harris, Tamara B and Launer, Lenore J and Shuldiner, Alan R and Alonso, Alvaro and Bader, Joel S and Ehret, Georg and Huang, Hailiang and Kao, W H Linda and Strait, James B and Macfarlane, Peter W and Brown, Morris and Caulfield, Mark J and Samani, Nilesh J and Kronenberg, Florian and Willeit, Johann and CARe Consortium and COGENT Consortium and Smith, J Gustav and Greiser, Karin H and Meyer Zu Schwabedissen, Henriette and Werdan, Karl and Carella, Massimo and Zelante, Leopoldo and Heckbert, Susan R and Psaty, Bruce M and Rotter, Jerome I and Kolcic, Ivana and Pola{\v s}ek, Ozren and Wright, Alan F and Griffin, Maura and Daly, Mark J and DCCT/EDIC and Arnar, David O and H{\'o}lm, Hilma and Thorsteinsdottir, Unnur and eMERGE Consortium and Denny, Joshua C and Roden, Dan M and Zuvich, Rebecca L and Emilsson, Valur and Plump, Andrew S and Larson, Martin G and O{\textquoteright}Donnell, Christopher J and Yin, Xiaoyan and Bobbo, Marco and D{\textquoteright}Adamo, Adamo P and Iorio, Annamaria and Sinagra, Gianfranco and Carracedo, Angel and Cummings, Steven R and Nalls, Michael A and Jula, Antti and Kontula, Kimmo K and Marjamaa, Annukka and Oikarinen, Lasse and Perola, Markus and Porthan, Kimmo and Erbel, Raimund and Hoffmann, Per and J{\"o}ckel, Karl-Heinz and K{\"a}lsch, Hagen and N{\"o}then, Markus M and HRGEN Consortium and den Hoed, Marcel and Loos, Ruth J F and Thelle, Dag S and Gieger, Christian and Meitinger, Thomas and Perz, Siegfried and Peters, Annette and Prucha, Hanna and Sinner, Moritz F and Waldenberger, Melanie and de Boer, Rudolf A and Franke, Lude and van der Vleuten, Pieter A and Beckmann, Britt Maria and Martens, Eimo and Bardai, Abdennasser and Hofman, Nynke and Wilde, Arthur A M and Behr, Elijah R and Dalageorgou, Chrysoula and Giudicessi, John R and Medeiros-Domingo, Argelia and Barc, Julien and Kyndt, Florence and Probst, Vincent and Ghidoni, Alice and Insolia, Roberto and Hamilton, Robert M and Scherer, Stephen W and Brandimarto, Jeffrey and Margulies, Kenneth and Moravec, Christine E and del Greco M, Fabiola and Fuchsberger, Christian and O{\textquoteright}Connell, Jeffrey R and Lee, Wai K and Watt, Graham C M and Campbell, Harry and Wild, Sarah H and El Mokhtari, Nour E and Frey, Norbert and Asselbergs, Folkert W and Mateo Leach, Irene and Navis, Gerjan and van den Berg, Maarten P and van Veldhuisen, Dirk J and Kellis, Manolis and Krijthe, Bouwe P and Franco, Oscar H and Hofman, Albert and Kors, Jan A and Uitterlinden, Andr{\'e} G and Witteman, Jacqueline C M and Kedenko, Lyudmyla and Lamina, Claudia and Oostra, Ben A and Abecasis, Gon{\c c}alo R and Lakatta, Edward G and Mulas, Antonella and Orr{\'u}, Marco and Schlessinger, David and Uda, Manuela and Markus, Marcello R P and V{\"o}lker, Uwe and Snieder, Harold and Spector, Timothy D and {\"A}rnl{\"o}v, Johan and Lind, Lars and Sundstr{\"o}m, Johan and Syv{\"a}nen, Ann-Christine and Kivimaki, Mika and K{\"a}h{\"o}nen, Mika and Mononen, Nina and Raitakari, Olli T and Viikari, Jorma S and Adamkova, Vera and Kiechl, Stefan and Brion, Maria and Nicolaides, Andrew N and Paulweber, Bernhard and Haerting, Johannes and Dominiczak, Anna F and Nyberg, Fredrik and Whincup, Peter H and Hingorani, Aroon D and Schott, Jean-Jacques and Bezzina, Connie R and Ingelsson, Erik and Ferrucci, Luigi and Gasparini, Paolo and Wilson, James F and Rudan, Igor and Franke, Andre and M{\"u}hleisen, Thomas W and Pramstaller, Peter P and Lehtim{\"a}ki, Terho J and Paterson, Andrew D and Parsa, Afshin and Liu, Yongmei and van Duijn, Cornelia M and Siscovick, David S and Gudnason, Vilmundur and Jamshidi, Yalda and Salomaa, Veikko and Felix, Stephan B and Sanna, Serena and Ritchie, Marylyn D and Stricker, Bruno H and Stefansson, Kari and Boyer, Laurie A and Cappola, Thomas P and Olsen, Jesper V and Lage, Kasper and Schwartz, Peter J and K{\"a}{\"a}b, Stefan and Chakravarti, Aravinda and Ackerman, Michael J and Pfeufer, Arne and de Bakker, Paul I W and Newton-Cheh, Christopher}
}
@article {1001821,
	title = {Genetic variants in the complement system predisposing to age-related macular degeneration: a review},
	journal = {Mol Immunol},
	volume = {61},
	number = {2},
	year = {2014},
	month = {2014 Oct},
	pages = {118-25},
	abstract = {Age-related macular degeneration (AMD) is a major cause of visual impairment in the western world. It is characterized by the presence of lipoproteinaceous deposits (drusen) in the inner layers of the retina. Immunohistochemistry studies identified deposition of complement proteins in the drusen as well as in the choroid. In the last decade, genetic studies have linked both common and rare variants in genes of the complement system to increased risk of development of AMD. Here, we review the variants described to date and discuss the functional implications of dysregulation of the alternative pathway of complement in AMD.},
	keywords = {Complement System Proteins, Genetic Predisposition to Disease, Genetic Variation, Humans, Macular Degeneration},
	issn = {1872-9142},
	doi = {10.1016/j.molimm.2014.06.032},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Genetic+variants+in+the+complement+system+predisposing+to+age-related+macular+degeneration\%3A+a+review},
	author = {Schramm, Elizabeth C and Clark, Simon J and Triebwasser, Michael P and Raychaudhuri, Soumya and Seddon, Johanna M and Atkinson, John P}
}
@article {1001811,
	title = {A novel test for recessive contributions to complex diseases implicates Bardet-Biedl syndrome gene BBS10 in idiopathic type 2 diabetes and obesity},
	journal = {Am J Hum Genet},
	volume = {95},
	number = {5},
	year = {2014},
	month = {2014 Nov 06},
	pages = {509-20},
	abstract = {Rare-variant association studies in common, complex diseases are customarily conducted under an additive risk model in both single-variant and burden testing. Here, we describe a method to improve detection of rare recessive variants in complex diseases termed RAFT (recessive-allele-frequency-based test). We found that RAFT outperforms existing approaches when the variant influences disease risk in a recessive manner on simulated data. We then applied our method to 1,791 Finnish individuals with type 2 diabetes (T2D) and 2,657 matched control subjects. In BBS10, we discovered a rare variant (c.1189A\&gt;G [p.Ile397Val]; rs202042386) that confers risk of T2D in a recessive state (p = 1.38\&nbsp;{\texttimes} 10(-6)) and would be missed by conventional methods. Testing of this variant in an established in\&nbsp;vivo zebrafish model confirmed the variant to be pathogenic. Taken together, these data suggest that RAFT can effectively reveal rare recessive contributions to complex diseases overlooked by conventional association tests.},
	keywords = {Animals, Diabetes Mellitus, Type 2, Finland, Gene Frequency, Genes, Recessive, Genetic Predisposition to Disease, Genome-Wide Association Study, Group II Chaperonins, Humans, Likelihood Functions, Models, Genetic, Obesity, Odds Ratio, Zebrafish},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2014.09.015},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=A+novel+test+for+recessive+contributions+to+complex+diseases+implicates+Bardet-Biedl+syndrome+gene+BBS10+in+idiopathic+type+2+diabetes+and+obesity},
	author = {Lim, Elaine T and Liu, Yangfan P and Chan, Yingleong and Tiinamaija, Tuomi and K{\"a}r{\"a}j{\"a}m{\"a}ki, AnnMari and Madsen, Erik and Go-T2D Consortium and Altshuler, David M and Raychaudhuri, Soumya and Groop, Leif and Flannick, Jason and Hirschhorn, Joel N and Katsanis, Nicholas and Daly, Mark J}
}
@article {1001806,
	title = {Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases},
	journal = {Am J Hum Genet},
	volume = {95},
	number = {5},
	year = {2014},
	month = {2014 Nov 06},
	pages = {535-52},
	abstract = {Regulatory and coding variants are known to be enriched with associations identified by genome-wide association studies (GWASs) of complex disease, but their contributions to trait heritability are currently unknown. We applied variance-component methods to imputed genotype data for 11 common diseases to partition the heritability explained by genotyped SNPs (hg(2)) across functional categories (while accounting for shared variance due to linkage disequilibrium). Extensive simulations showed that in contrast to current estimates from GWAS summary statistics, the variance-component approach partitions heritability accurately under a wide range of complex-disease architectures. Across the 11 diseases DNaseI hypersensitivity sites (DHSs) from 217 cell types spanned 16\% of imputed SNPs (and 24\% of genotyped SNPs) but explained an average of 79\% (SE = 8\%) of hg(2) from imputed SNPs (5.1{\texttimes} enrichment; p = 3.7\&nbsp;{\texttimes} 10(-17)) and 38\% (SE = 4\%) of hg(2) from genotyped SNPs (1.6{\texttimes} enrichment, p = 1.0\&nbsp;{\texttimes} 10(-4)). Further enrichment was observed at enhancer DHSs and cell-type-specific DHSs. In contrast, coding variants, which span 1\% of the genome, explained \&lt;10\% of hg(2) despite having the highest enrichment. We replicated these findings but found no significant contribution from rare coding variants in independent schizophrenia cohorts genotyped on GWAS and exome chips. Our results highlight the value of analyzing components of heritability to unravel the functional architecture of common disease.},
	keywords = {Computer Simulation, Genetic Diseases, Inborn, Genetic Variation, Genome-Wide Association Study, Humans, Inheritance Patterns, Models, Genetic, Open Reading Frames, Regulatory Elements, Transcriptional},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2014.10.004},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Partitioning+heritability+of+regulatory+and+cell-type-specific+variants+across+11+common+diseases},
	author = {Gusev, Alexander and Lee, S Hong and Trynka, Gosia and Finucane, Hilary and Vilhj{\'a}lmsson, Bjarni J and Xu, Han and Zang, Chongzhi and Ripke, Stephan and Bulik-Sullivan, Brendan and Stahl, Eli and Schizophrenia Working Group of the Psychiatric Genomics Consortium and SWE-SCZ Consortium and K{\"a}hler, Anna K and Hultman, Christina M and Purcell, Shaun M and McCarroll, Steven A and Daly, Mark and Pasaniuc, Bogdan and Sullivan, Patrick F and Neale, Benjamin M and Wray, Naomi R and Raychaudhuri, Soumya and Price, Alkes L and Schizophrenia Working Group of the Psychiatric Genomics Consortium and SWE-SCZ Consortium}
}
@article {1001826,
	title = {Predicting HLA alleles from high-resolution SNP data in three Southeast Asian populations},
	journal = {Hum Mol Genet},
	volume = {23},
	number = {16},
	year = {2014},
	month = {2014 Aug 15},
	pages = {4443-51},
	abstract = {The major histocompatibility complex (MHC) containing the classical human leukocyte antigen (HLA) Class I and Class II genes is among the most polymorphic and diverse regions in the human genome. Despite the clinical importance of identifying the HLA types, very few databases jointly characterize densely genotyped single nucleotide polymorphisms (SNPs) and HLA alleles in the same samples. To date, the HapMap presents the only public resource that provides a SNP reference panel for predicting HLA alleles, constructed with four collections of individuals of north-western European, northern Han Chinese, cosmopolitan Japanese and Yoruba Nigerian ancestry. Owing to complex patterns of linkage disequilibrium in this region, it is unclear whether the HapMap reference panels can be appropriately utilized for other populations. Here, we describe a public resource for the Singapore Genome Variation Project with: (i) dense genotyping across \~{} 9000 SNPs in the MHC; (ii) four-digit HLA typing for eight Class I and Class II loci, in 96 southern Han Chinese, 89 Southeast Asian Malays and 83 Tamil Indians. This resource provides population estimates of the frequencies of HLA alleles at these eight loci in the three population groups, particularly for HLA-DPA1 and HLA-DPB1 that were not assayed in HapMap. Comparing between population-specific reference panels and a cosmopolitan panel created from all four HapMap populations, we demonstrate that more accurate imputation is obtained with population-specific panels than with the cosmopolitan panel, especially for the Malays and Indians but even when imputing between northern and southern Han Chinese. As with SNP imputation, common HLA alleles were imputed with greater accuracy than low-frequency variants.},
	keywords = {Alleles, Asian Continental Ancestry Group, Genetic Loci, HLA Antigens, HLA-DP alpha-Chains, HLA-DP beta-Chains, Humans, Major Histocompatibility Complex, Polymorphism, Single Nucleotide},
	issn = {1460-2083},
	doi = {10.1093/hmg/ddu149},
	author = {Pillai, Nisha Esakimuthu and Okada, Yukinori and Saw, Woei-Yuh and Ong, Rick Twee-Hee and Wang, Xu and Tantoso, Erwin and Xu, Wenting and Peterson, Trevor A and Bielawny, Thomas and Ali, Mohammad and Tay, Koon-Yong and Poh, Wan-Ting and Tan, Linda Wei-Lin and Koo, Seok-Hwee and Lim, Wei-Yen and Soong, Richie and Wenk, Markus and Raychaudhuri, Soumya and Little, Peter and Plummer, Francis A and Lee, Edmund J D and Chia, Kee-Seng and Luo, Ma and de Bakker, Paul I W and Teo, Yik-Ying}
}
@article {1001801,
	title = {A role for noncoding variation in schizophrenia},
	journal = {Cell Rep},
	volume = {9},
	number = {4},
	year = {2014},
	month = {2014 Nov 20},
	pages = {1417-29},
	abstract = {A large portion of common variant loci associated with genetic risk for schizophrenia reside within noncoding sequence of unknown function. Here, we demonstrate promoter and enhancer enrichment in schizophrenia variants associated with expression quantitative trait loci (eQTL). The enrichment is greater when functional annotations derived from the human brain are used relative to peripheral tissues. Regulatory trait concordance analysis ranked genes within schizophrenia genome-wide significant loci for a potential functional role, based on colocalization of a risk SNP, eQTL, and regulatory element sequence. We identified potential physical interactions of noncontiguous proximal and distal regulatory elements. This was verified in prefrontal cortex and -induced pluripotent stem cell-derived neurons for the L-type calcium channel (CACNA1C) risk locus. Our findings point to a functional link between schizophrenia-associated noncoding SNPs and 3D genome architecture associated with chromosomal loopings and transcriptional regulation in the brain.},
	keywords = {Arthritis, Rheumatoid, Calcium Channels, L-Type, Databases, Genetic, DNA, Intergenic, Enhancer Elements, Genetic, Gene Expression Regulation, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Molecular Sequence Annotation, Organ Specificity, Polymorphism, Single Nucleotide, Promoter Regions, Genetic, Protein Binding, Risk Factors, Schizophrenia},
	issn = {2211-1247},
	doi = {10.1016/j.celrep.2014.10.015},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/25453756},
	author = {Roussos, Panos and Mitchell, Amanda C and Voloudakis, Georgios and Fullard, John F and Pothula, Venu M and Tsang, Jonathan and Stahl, Eli A and Georgakopoulos, Anastasios and Ruderfer, Douglas M and Charney, Alexander and Okada, Yukinori and Siminovitch, Katherine A and Worthington, Jane and Padyukov, Leonid and Klareskog, Lars and Gregersen, Peter K and Plenge, Robert M and Raychaudhuri, Soumya and Fromer, Menachem and Purcell, Shaun M and Brennand, Kristen J and Robakis, Nikolaos K and Schadt, Eric E and Akbarian, Schahram and Sklar, Pamela}
}
@article {1001796,
	title = {Variation at HLA-DRB1 is associated with resistance to enteric fever},
	journal = {Nat Genet},
	volume = {46},
	number = {12},
	year = {2014},
	month = {2014 Dec},
	pages = {1333-6},
	abstract = {Enteric fever affects more than 25 million people annually and results from systemic infection with Salmonella enterica serovar Typhi or Paratyphi pathovars A, B or C(1). We conducted a genome-wide association study of 432 individuals with blood culture-confirmed enteric fever and 2,011 controls from Vietnam. We observed strong association at rs7765379 (odds ratio (OR) for the minor allele = 0.18, P = 4.5 {\texttimes} 10(-10)), a marker mapping to the HLA class II region, in proximity to HLA-DQB1 and HLA-DRB1. We replicated this association in 595 enteric fever cases and 386 controls from Nepal and also in a second independent collection of 151 cases and 668 controls from Vietnam. Imputation-based fine-mapping across the extended MHC region showed that the classical HLA-DRB1*04:05 allele (OR = 0.14, P = 2.60 {\texttimes} 10(-11)) could entirely explain the association at rs7765379, thus implicating HLA-DRB1 as a major contributor to resistance against enteric fever, presumably through antigen presentation.},
	keywords = {Alleles, Antigen Presentation, Biomarkers, Chromosome Mapping, Genetic Markers, Genetic Predisposition to Disease, Genotype, HLA-DRB1 Chains, Humans, Models, Statistical, Nepal, Odds Ratio, Polymorphism, Single Nucleotide, Principal Component Analysis, Regression Analysis, Typhoid Fever, Vietnam},
	issn = {1546-1718},
	doi = {10.1038/ng.3143},
	author = {Dunstan, Sarah J and Hue, Nguyen Thi and Han, Buhm and Li, Zheng and Tram, Trinh Thi Bich and Sim, Kar Seng and Parry, Christopher M and Chinh, Nguyen Tran and Vinh, Ha and Lan, Nguyen Phu Huong and Thieu, Nga Tran Vu and Vinh, Phat Voong and Koirala, Samir and Dongol, Sabina and Arjyal, Amit and Karkey, Abhilasha and Shilpakar, Olita and Dolecek, Christiane and Foo, Jia Nee and Phuong, Le Thi and Lanh, Mai Ngoc and Do, Tan and Aung, Tin and Hon, Do Nu and Teo, Yik Ying and Hibberd, Martin L and Anders, Katherine L and Okada, Yukinori and Raychaudhuri, Soumya and Simmons, Cameron P and Baker, Stephen and de Bakker, Paul I W and Basnyat, Buddha and Hien, Tran Tinh and Farrar, Jeremy J and Khor, Chiea Chuen}
}
@article {1001816,
	title = {Whole-exome sequencing identifies rare, functional CFH variants in families with macular degeneration},
	journal = {Hum Mol Genet},
	volume = {23},
	number = {19},
	year = {2014},
	month = {2014 Oct 01},
	pages = {5283-93},
	abstract = {We sequenced the whole exome of 35 cases and 7 controls from 9 age-related macular degeneration (AMD) families in whom known common genetic risk alleles could not explain their high disease burden and/or their early-onset advanced disease. Two families harbored novel rare mutations in CFH (R53C and D90G). R53C segregates perfectly with AMD in 11 cases (heterozygous) and 1 elderly control (reference allele) (LOD = 5.07, P = 6.7 {\texttimes} 10(-7)). In an independent cohort, 4 out of 1676 cases but none of the 745 examined controls or 4300 NHBLI Exome Sequencing Project (ESP) samples carried the R53C mutation (P = 0.0039). In another family of six siblings, D90G similarly segregated with AMD in five cases and one control (LOD = 1.22, P = 0.009). No other sample in our large cohort or the ESP had this mutation. Functional studies demonstrated that R53C decreased the ability of FH to perform decay accelerating activity. D90G exhibited a decrease in cofactor-mediated inactivation. Both of these changes would lead to a loss of regulatory activity, resulting in excessive alternative pathway activation. This study represents an initial application of the whole-exome strategy to families with early-onset AMD. It successfully identified high impact alleles leading to clearer functional insight into AMD etiopathogenesis.},
	keywords = {Alleles, Complement C3b, Complement Factor H, Exome, Female, Gene Frequency, Genetic Variation, High-Throughput Nucleotide Sequencing, Humans, Kinetics, Lod Score, Macular Degeneration, Male, Models, Molecular, Pedigree, Polymorphism, Single Nucleotide, Protein Binding, Protein Conformation},
	issn = {1460-2083},
	doi = {10.1093/hmg/ddu226},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Whole-exome+sequencing+identifies+rare\%2C+functional+CFH+variants+in+families+with+macular+degeneration},
	author = {Yu, Yi and Triebwasser, Michael P and Wong, Edwin K S and Schramm, Elizabeth C and Thomas, Brett and Reynolds, Robyn and Mardis, Elaine R and Atkinson, John P and Daly, Mark and Raychaudhuri, Soumya and Kavanagh, David and Seddon, Johanna M}
}
@article {1001566,
	title = {Fine mapping major histocompatibility complex associations in psoriasis and its clinical subtypes},
	journal = {Am J Hum Genet},
	volume = {95},
	number = {2},
	year = {2014},
	month = {2014 Aug 07},
	pages = {162-72},
	abstract = {Psoriasis vulgaris (PsV) risk is strongly associated with variation within the major histocompatibility complex (MHC) region, but its genetic architecture has yet to be fully elucidated. Here, we conducted a large-scale fine-mapping study of PsV risk in the MHC region in 9,247 PsV-affected individuals and 13,589 controls of European descent by imputing class I and II human leukocyte antigen (HLA) genes from SNP genotype data. In addition, we imputed sequence variants for MICA, an MHC HLA-like gene that has been associated with PsV, to evaluate association at that locus as well. We observed that HLA-C(*)06:02 demonstrated the lowest p value for overall PsV risk (p = 1.7 {\texttimes} 10(-364)). Stepwise analysis revealed multiple HLA-C(*)06:02-independent risk variants in both class I and class II HLA genes for PsV susceptibility (HLA-C(*)12:03, HLA-B amino acid positions 67 and 9, HLA-A amino acid position 95, and HLA-DQα1 amino acid position 53; p \&lt; 5.0 {\texttimes} 10(-8)), but no apparent risk conferred by MICA. We further evaluated risk of two major clinical subtypes of PsV, psoriatic arthritis (PsA; n = 3,038) and cutaneous psoriasis (PsC; n = 3,098). We found that risk heterogeneity between PsA and PsC might be driven by HLA-B amino acid position 45 (Pomnibus = 2.2 {\texttimes} 10(-11)), indicating that different genetic factors underlie the overall risk of PsV and the risk of specific PsV subphenotypes. Our study illustrates the value of high-resolution HLA and MICA imputation for fine mapping causal variants in the MHC.},
	keywords = {Amino Acid Sequence, Arthritis, Psoriatic, Base Sequence, Chromosome Mapping, Genetic Association Studies, Genetic Predisposition to Disease, Genotype, Histocompatibility Antigens Class I, Histocompatibility Antigens Class II, HLA-B Antigens, HLA-C Antigens, Humans, Major Histocompatibility Complex, Polymorphism, Single Nucleotide, Psoriasis},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2014.07.002},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Fine+mapping+major+histocompatibility+complex+associations+in+psoriasis+and+its+clinical+subtypes},
	author = {Okada, Yukinori and Han, Buhm and Tsoi, Lam C and Stuart, Philip E and Ellinghaus, Eva and Tejasvi, Trilokraj and Chandran, Vinod and Pellett, Fawnda and Pollock, Remy and Bowcock, Anne M and Krueger, Gerald G and Weichenthal, Michael and Voorhees, John J and Rahman, Proton and Gregersen, Peter K and Franke, Andre and Nair, Rajan P and Abecasis, Gon{\c c}alo R and Gladman, Dafna D and Elder, James T and de Bakker, Paul I W and Raychaudhuri, Soumya}
}
@article {1001576,
	title = {Fine mapping seronegative and seropositive rheumatoid arthritis to shared and distinct HLA alleles by adjusting for the effects of heterogeneity},
	journal = {Am J Hum Genet},
	volume = {94},
	number = {4},
	year = {2014},
	month = {2014 Apr 03},
	pages = {522-32},
	abstract = {Despite progress in defining human leukocyte antigen (HLA) alleles for anti-citrullinated-protein-autoantibody-positive (ACPA(+)) rheumatoid arthritis (RA), identifying HLA alleles for ACPA-negative (ACPA(-)) RA has been challenging because of clinical heterogeneity within clinical cohorts. We imputed 8,961 classical HLA alleles, amino acids, and SNPs from Immunochip data in a discovery set of 2,406 ACPA(-) RA case and 13,930 control individuals. We developed a statistical approach to identify and adjust for clinical heterogeneity within ACPA(-) RA and observed independent associations for serine and leucine at position 11 in HLA-DRβ1 (p = 1.4 {\texttimes} 10(-13), odds ratio [OR] = 1.30) and for aspartate at position 9 in HLA-B (p = 2.7 {\texttimes} 10(-12), OR = 1.39) within the peptide binding grooves. These amino acid positions induced associations at HLA-DRB1(*)03 (encoding serine at 11) and HLA-B(*)08 (encoding aspartate at 9). We validated these findings in an independent set of 427 ACPA(-) case subjects, carefully phenotyped with a highly sensitive ACPA assay, and 1,691 control subjects (HLA-DRβ1 Ser11+Leu11: p = 5.8 {\texttimes} 10(-4), OR = 1.28; HLA-B Asp9: p = 2.6 {\texttimes} 10(-3), OR = 1.34). Although both amino acid sites drove risk of ACPA(+) and ACPA(-) disease, the effects of individual residues at HLA-DRβ1 position 11 were distinct (p \&lt; 2.9 {\texttimes} 10(-107)). We also identified an association with ACPA(+) RA at HLA-A position 77 (p = 2.7 {\texttimes} 10(-8), OR = 0.85) in 7,279 ACPA(+) RA case and 15,870 control subjects. These results contribute to mounting evidence that ACPA(+) and ACPA(-) RA are genetically distinct and potentially have separate autoantigens contributing to pathogenesis. We expect that our approach might have broad applications in analyzing clinical conditions with heterogeneity at both major histocompatibility complex (MHC) and non-MHC regions.},
	keywords = {Alleles, Arthritis, Rheumatoid, Case-Control Studies, Genetic Heterogeneity, HLA Antigens, Humans},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2014.02.013},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Fine+mapping+seronegative+and+seropositive+rheumatoid+arthritis+to+shared+and+distinct+HLA+alleles+by+adjusting+for+the+effects+of+heterogeneity},
	author = {Han, Buhm and Diogo, Doroth{\'e}e and Eyre, Steve and Kallberg, Henrik and Zhernakova, Alexandra and Bowes, John and Padyukov, Leonid and Okada, Yukinori and Gonz{\'a}lez-Gay, Miguel A and Rantap{\"a}{\"a}-Dahlqvist, Solbritt and Martin, Javier and Huizinga, Tom W J and Plenge, Robert M and Worthington, Jane and Gregersen, Peter K and Klareskog, Lars and de Bakker, Paul I W and Raychaudhuri, Soumya}
}
@article {1001571,
	title = {Regulation of gene expression in autoimmune disease loci and the genetic basis of proliferation in CD4+ effector memory T cells},
	journal = {PLoS Genet},
	volume = {10},
	number = {6},
	year = {2014},
	month = {2014 Jun},
	pages = {e1004404},
	abstract = {Genome-wide association studies (GWAS) and subsequent dense-genotyping of associated loci identified over a hundred single-nucleotide polymorphism (SNP) variants associated with the risk of rheumatoid arthritis (RA), type 1 diabetes (T1D), and celiac disease (CeD). Immunological and genetic studies suggest a role for CD4-positive effector memory T (CD+ TEM) cells in the pathogenesis of these diseases. To elucidate mechanisms of autoimmune disease alleles, we investigated molecular phenotypes in CD4+ effector memory T cells potentially affected by these variants. In a cohort of genotyped healthy individuals, we isolated high purity CD4+ TEM cells from peripheral blood, then assayed relative abundance, proliferation upon T cell receptor (TCR) stimulation, and the transcription of 215 genes within disease loci before and after stimulation. We identified 46 genes regulated by cis-acting expression quantitative trait loci (eQTL), the majority of which we detected in stimulated cells. Eleven of the 46 genes with eQTLs were previously undetected in peripheral blood mononuclear cells. Of 96 risk alleles of RA, T1D, and/or CeD in densely genotyped loci, eleven overlapped cis-eQTLs, of which five alleles completely explained the respective signals. A non-coding variant, rs389862A, increased proliferative response (p=4.75 {\texttimes} 10-8). In addition, baseline expression of seventeen genes in resting cells reliably predicted proliferative response after TCR stimulation. Strikingly, however, there was no evidence that risk alleles modulated CD4+ TEM abundance or proliferation. Our study underscores the power of examining molecular phenotypes in relevant cells and conditions for understanding pathogenic mechanisms of disease variants.},
	keywords = {Arthritis, Rheumatoid, Autoimmune Diseases, CD4-Positive T-Lymphocytes, Celiac Disease, Cell Proliferation, Diabetes Mellitus, Type 1, Gene Expression Regulation, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Receptors, Antigen, T-Cell},
	issn = {1553-7404},
	doi = {10.1371/journal.pgen.1004404},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Regulation+of+gene+expression+in+autoimmune+disease+loci+and+the+genetic+basis+of+proliferation+in+CD4\%2B+effector+memory+T+cells},
	author = {Hu, Xinli and Kim, Hyun and Raj, Towfique and Brennan, Patrick J and Trynka, Gosia and Teslovich, Nikola and Slowikowski, Kamil and Chen, Wei-Min and Onengut, Suna and Baecher-Allan, Clare and De Jager, Philip L and Rich, Stephen S and Stranger, Barbara E and Brenner, Michael B and Raychaudhuri, Soumya}
}
@article {1001556,
	title = {Risk for ACPA-positive rheumatoid arthritis is driven by shared HLA amino acid polymorphisms in Asian and European populations},
	journal = {Hum Mol Genet},
	volume = {23},
	number = {25},
	year = {2014},
	month = {2014 Dec 20},
	pages = {6916-26},
	abstract = {Previous studies have emphasized ethnically heterogeneous human leukocyte antigen (HLA) classical allele associations to rheumatoid arthritis (RA) risk. We fine-mapped RA risk alleles within the major histocompatibility complex (MHC) in 2782 seropositive RA cases and 4315 controls of Asian descent. We applied imputation to determine genotypes for eight class I and II HLA genes to Asian populations for the first time using a newly constructed pan-Asian reference panel. First, we empirically measured high imputation accuracy in Asian samples. Then we observed the most significant association in HLA-DRβ1 at amino acid position 13, located outside the classical shared epitope (Pomnibus = 6.9 {\texttimes} 10(-135)). The individual residues at position 13 have relative effects that are consistent with published effects in European populations (His \&gt; Phe \&gt; Arg \&gt; Tyr ≅ Gly \&gt; Ser)--but the observed effects in Asians are generally smaller. Applying stepwise conditional analysis, we identified additional independent associations at positions 57 (conditional Pomnibus = 2.2 {\texttimes} 10(-33)) and 74 (conditional Pomnibus = 1.1 {\texttimes} 10(-8)). Outside of HLA-DRβ1, we observed independent effects for amino acid polymorphisms within HLA-B (Asp9, conditional P = 3.8 {\texttimes} 10(-6)) and HLA-DPβ1 (Phe9, conditional P = 3.0 {\texttimes} 10(-5)) concordant with European populations. Our trans-ethnic HLA fine-mapping study reveals that (i) a common set of amino acid residues confer shared effects in European and Asian populations and (ii) these same effects can explain ethnically heterogeneous classical allelic associations (e.g. HLA-DRB1*09:01) due to allele frequency differences between populations. Our study illustrates the value of high-resolution imputation for fine-mapping causal variants in the MHC.},
	keywords = {Alleles, Amino Acids, Arthritis, Rheumatoid, Asian Continental Ancestry Group, Autoantibodies, Chromosome Mapping, Citrulline, Epitopes, European Continental Ancestry Group, Gene Expression, Gene Frequency, HLA-B Antigens, HLA-DP beta-Chains, HLA-DRB1 Chains, Humans, Polymorphism, Genetic, Risk},
	issn = {1460-2083},
	doi = {10.1093/hmg/ddu387},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Risk+for+ACPA-positive+rheumatoid+arthritis+is+driven+by+shared+HLA+amino+acid+polymorphisms+in+Asian+and+European+populations},
	author = {Okada, Yukinori and Kim, Kwangwoo and Han, Buhm and Pillai, Nisha E and Ong, Rick T-H and Saw, Woei-Yuh and Luo, Ma and Jiang, Lei and Yin, Jian and Bang, So-Young and Lee, Hye-Soon and Brown, Matthew A and Bae, Sang-Cheol and Xu, Huji and Teo, Yik-Ying and de Bakker, Paul I W and Raychaudhuri, Soumya}
}
@article {1001561,
	title = {SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci},
	journal = {Bioinformatics},
	volume = {30},
	number = {17},
	year = {2014},
	month = {2014 Sep 01},
	pages = {2496-7},
	abstract = {UNLABELLED: We created a fast, robust and general C+ + implementation of a single-nucleotide polymorphism (SNP) set enrichment algorithm to identify cell types, tissues and pathways affected by risk loci. It tests trait-associated genomic loci for enrichment of specificity to conditions (cell types, tissues and pathways). We use a non-parametric statistical approach to compute empirical P-values by comparison with null SNP sets. As a proof of concept, we present novel applications of our method to four sets of genome-wide significant SNPs associated with red blood cell count, multiple sclerosis, celiac disease and HDL cholesterol. AVAILABILITY AND IMPLEMENTATION: http://broadinstitute.org/mpg/snpsea. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.},
	keywords = {Algorithms, Erythroid Cells, Genetic Loci, Genomics, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Risk},
	issn = {1367-4811},
	doi = {10.1093/bioinformatics/btu326},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=SNPsea\%3A+an+algorithm+to+identify+cell+types\%2C+tissues+and+pathways+affected+by+risk+loci},
	author = {Slowikowski, Kamil and Hu, Xinli and Raychaudhuri, Soumya}
}
@article {1109611,
	title = {Applying active learning to high-throughput phenotyping algorithms for electronic health records data},
	journal = {J Am Med Inform Assoc},
	volume = {20},
	number = {e2},
	year = {2013},
	month = {2013 Dec},
	pages = {e253-9},
	abstract = {OBJECTIVES: Generalizable, high-throughput phenotyping methods based on supervised machine learning (ML) algorithms could significantly accelerate the use of electronic health records data for clinical and translational research. However, they often require large numbers of annotated samples, which are costly and time-consuming to review. We investigated the use of active learning (AL) in ML-based phenotyping algorithms. METHODS: We integrated an uncertainty sampling AL approach with support vector machines-based phenotyping algorithms and evaluated its performance using three annotated disease cohorts including rheumatoid arthritis (RA), colorectal cancer (CRC), and venous thromboembolism (VTE). We investigated performance using two types of feature sets: unrefined features, which contained at least all clinical concepts extracted from notes and billing codes; and a smaller set of refined features selected by domain experts. The performance of the AL was compared with a passive learning (PL) approach based on random sampling. RESULTS: Our evaluation showed that AL outperformed PL on three phenotyping tasks. When unrefined features were used in the RA and CRC tasks, AL reduced the number of annotated samples required to achieve an area under the curve (AUC) score of 0.95 by 68\% and 23\%, respectively. AL also achieved a reduction of 68\% for VTE with an optimal AUC of 0.70 using refined features. As expected, refined features improved the performance of phenotyping classifiers and required fewer annotated samples. CONCLUSIONS: This study demonstrated that AL can be useful in ML-based phenotyping methods. Moreover, AL and feature engineering based on domain knowledge could be combined to develop efficient and generalizable phenotyping methods.},
	keywords = {Algorithms, Artificial Intelligence, Electronic Health Records, Genetic Association Studies, Humans, Phenotype, Support Vector Machine},
	issn = {1527-974X},
	doi = {10.1136/amiajnl-2013-001945},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Applying+active+learning+to+high-throughput+phenotyping+algorithms+for+electronic+health+records+data},
	author = {Chen, Yukun and Carroll, Robert J and Hinz, Eugenia R McPeek and Shah, Anushi and Eyler, Anne E and Denny, Joshua C and Xu, Hua}
}
@article {1109591,
	title = {Association of granulomatosis with polyangiitis (Wegener{\textquoteright}s) with HLA-DPB1*04 and SEMA6A gene variants: evidence from genome-wide analysis},
	journal = {Arthritis Rheum},
	volume = {65},
	number = {9},
	year = {2013},
	month = {2013 Sep},
	pages = {2457-68},
	abstract = {OBJECTIVE: To identify genetic determinants of granulomatosis with polyangiitis (Wegener{\textquoteright}s) (GPA). METHODS: We carried out a genome-wide association study (GWAS) of 492 GPA cases and 1,506 healthy controls (white subjects of European descent), followed by replication analysis of the most strongly associated signals in an independent cohort of 528 GPA cases and 1,228 controls. RESULTS: Genome-wide significant associations were identified in 32 single-nucleotide polymorphic (SNP) markers across the HLA region, the majority of which were located in the HLA-DPB1 and HLA-DPA1 genes encoding the class II major histocompatibility complex (MHC) DPβ chain 1 and DPα chain 1 proteins, respectively. Peak association signals in these 2 genes, emanating from SNPs rs9277554 (for DPβ chain 1) and rs9277341 (DPα chain 1) were strongly replicated in an independent cohort (in the combined analysis of the initial cohort and the replication cohort, P = 1.92 {\texttimes} 10(-50) and 2.18 {\texttimes} 10(-39) , respectively). Imputation of classic HLA alleles and conditional analyses revealed that the SNP association signal was fully accounted for by the classic HLA-DPB1*04 allele. An independent single SNP, rs26595, near SEMA6A (the gene for semaphorin 6A) on chromosome 5, was also associated with GPA, reaching genome-wide significance in a combined analysis of the GWAS and replication cohorts (P = 2.09 {\texttimes} 10(-8) ). CONCLUSION: We identified the SEMA6A and HLA-DP loci as significant contributors to risk for GPA, with the HLA-DPB1*04 allele almost completely accounting for the MHC association. These two associations confirm the critical role of immunogenetic factors in the development of GPA.},
	keywords = {Adult, Alleles, Female, Gene Frequency, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Granulomatosis with Polyangiitis, Haplotypes, HLA-DP beta-Chains, Humans, Major Histocompatibility Complex, Male, Polymorphism, Single Nucleotide, Semaphorins},
	issn = {1529-0131},
	doi = {10.1002/art.38036},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Association+of+granulomatosis+with+polyangiitis+(Wegener\%27s)+with+HLA-DPB1*04+and+SEMA6A+gene+variants\%3A+evidence+from+genome-wide+analysis},
	author = {Xie, Gang and Roshandel, Delnaz and Sherva, Richard and Monach, Paul A and Lu, Emily Yue and Kung, Tabitha and Carrington, Keisha and Zhang, Steven S and Pulit, Sara L and Ripke, Stephan and Carette, Simon and Dellaripa, Paul F and Edberg, Jeffrey C and Hoffman, Gary S and Khalidi, Nader and Langford, Carol A and Mahr, Alfred D and St Clair, E William and Seo, Philip and Specks, Ulrich and Spiera, Robert F and Stone, John H and Ytterberg, Steven R and Raychaudhuri, Soumya and de Bakker, Paul I W and Farrer, Lindsay A and Amos, Christopher I and Merkel, Peter A and Siminovitch, Katherine A}
}
@article {1109576,
	title = {Associations of autoantibodies, autoimmune risk alleles, and clinical diagnoses from the electronic medical records in rheumatoid arthritis cases and non-rheumatoid arthritis controls},
	journal = {Arthritis Rheum},
	volume = {65},
	number = {3},
	year = {2013},
	month = {2013 Mar},
	pages = {571-81},
	abstract = {OBJECTIVE: The significance of non-rheumatoid arthritis (RA) autoantibodies in patients with RA is unclear. The aim of this study was to assess associations of autoantibodies with autoimmune risk alleles and with clinical diagnoses from the electronic medical records (EMRs) among RA cases and non-RA controls. METHODS: Data on 1,290 RA cases and 1,236 non-RA controls of European genetic ancestry were obtained from the EMRs of 2 large academic centers. The levels of anti-citrullinated protein antibodies (ACPAs), antinuclear antibodies (ANAs), anti-tissue transglutaminase antibodies (AGTAs), and anti-thyroid peroxidase (anti-TPO) antibodies were measured. All subjects were genotyped for autoimmune risk alleles, and the association between number of autoimmune risk alleles present and number of types of autoantibodies present was studied. A phenome-wide association study (PheWAS) was conducted to study potential associations between autoantibodies and clinical diagnoses among RA cases and non-RA controls. RESULTS: The mean ages were 60.7 years in RA cases and 64.6 years in non-RA controls. The proportion of female subjects was 79\% in each group. The prevalence of ACPAs and ANAs was higher in RA cases compared to controls (each P \&lt; 0.0001); there were no differences in the prevalence of anti-TPO antibodies and AGTAs. Carriage of higher numbers of autoimmune risk alleles was associated with increasing numbers of autoantibody types in RA cases (P = 2.1 {\texttimes} 10(-5)) and non-RA controls (P = 5.0 {\texttimes} 10(-3)). From the PheWAS, the presence of ANAs was significantly associated with a diagnosis of Sj{\"o}gren{\textquoteright}s/sicca syndrome in RA cases. CONCLUSION: The increased frequency of autoantibodies in RA cases and non-RA controls was associated with the number of autoimmune risk alleles carried by an individual. PheWAS of EMR data, with linkage to laboratory data obtained from blood samples, provide a novel method to test for the clinical significance of biomarkers in disease.},
	keywords = {Aged, Antibodies, Antinuclear, Arthritis, Rheumatoid, Autoantibodies, Electronic Health Records, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genotype, GTP-Binding Proteins, Humans, Hypothyroidism, Iodide Peroxidase, Male, Middle Aged, Peptides, Cyclic, Risk Factors, Seroepidemiologic Studies, Sjogren{\textquoteright}s Syndrome, Thyroiditis, Transglutaminases},
	issn = {1529-0131},
	doi = {10.1002/art.37801},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Associations+of+autoantibodies\%2C+autoimmune+risk+alleles\%2C+and+clinical+diagnoses+from+the+electronic+medical+records+in+rheumatoid+arthritis+cases+and+non-rheumatoid+arthritis+controls},
	author = {Liao, Katherine P and Kurreeman, Fina and Li, Gang and Duclos, Grant and Murphy, Shawn and Guzman, Raul and Cai, Tianxi and Gupta, Namrata and Gainer, Vivian and Schur, Peter and Cui, Jing and Denny, Joshua C and Szolovits, Peter and Churchill, Susanne and Kohane, Isaac and Karlson, Elizabeth W and Plenge, Robert M}
}
@article {1109566,
	title = {Automatic prediction of rheumatoid arthritis disease activity from the electronic medical records},
	journal = {PLoS One},
	volume = {8},
	number = {8},
	year = {2013},
	month = {2013},
	pages = {e69932},
	abstract = {OBJECTIVE: We aimed to mine the data in the Electronic Medical Record to automatically discover patients{\textquoteright} Rheumatoid Arthritis disease activity at discrete rheumatology clinic visits. We cast the problem as a document classification task where the feature space includes concepts from the clinical narrative and lab values as stored in the Electronic Medical Record. MATERIALS AND METHODS: The Training Set consisted of 2792 clinical notes and associated lab values. Test Set 1 included 1749 clinical notes and associated lab values. Test Set 2 included 344 clinical notes for which there were no associated lab values. The Apache clinical Text Analysis and Knowledge Extraction System was used to analyze the text and transform it into informative features to be combined with relevant lab values. RESULTS: Experiments over a range of machine learning algorithms and features were conducted. The best performing combination was linear kernel Support Vector Machines with Unified Medical Language System Concept Unique Identifier features with feature selection and lab values. The Area Under the Receiver Operating Characteristic Curve (AUC) is 0.831 (σ = 0.0317), statistically significant as compared to two baselines (AUC = 0.758, σ = 0.0291). Algorithms demonstrated superior performance on cases clinically defined as extreme categories of disease activity (Remission and High) compared to those defined as intermediate categories (Moderate and Low) and included laboratory data on inflammatory markers. CONCLUSION: Automatic Rheumatoid Arthritis disease activity discovery from Electronic Medical Record data is a learnable task approximating human performance. As a result, this approach might have several research applications, such as the identification of patients for genome-wide pharmacogenetic studies that require large sample sizes with precise definitions of disease activity and response to therapies.},
	keywords = {Antirheumatic Agents, Arthritis, Rheumatoid, Artificial Intelligence, data mining, Disease Progression, Electronic Health Records, Humans, ROC Curve, Support Vector Machine},
	issn = {1932-6203},
	doi = {10.1371/journal.pone.0069932},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Automatic+prediction+of+rheumatoid+arthritis+disease+activity+from+the+electronic+medical+records},
	author = {Lin, Chen and Karlson, Elizabeth W and Canhao, Helena and Miller, Timothy A and Dligach, Dmitriy and Chen, Pei Jun and Perez, Raul Natanael Guzman and Shen, Yuanyan and Weinblatt, Michael E and Shadick, Nancy A and Plenge, Robert M and Savova, Guergana K}
}
@article {1109586,
	title = {Crowdsourcing genetic prediction of clinical utility in the Rheumatoid Arthritis Responder Challenge},
	journal = {Nat Genet},
	volume = {45},
	number = {5},
	year = {2013},
	month = {2013 May},
	pages = {468-9},
	keywords = {Arthritis, Rheumatoid, Crowdsourcing, Humans, Models, Genetic, Predictive Value of Tests},
	issn = {1546-1718},
	doi = {10.1038/ng.2623},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Crowdsourcing+genetic+prediction+of+clinical+utility+in+the+Rheumatoid+Arthritis+Responder+Challenge},
	author = {Plenge, Robert M and Greenberg, Jeffrey D and Mangravite, Lara M and Derry, Jonathan M J and Stahl, Eli A and Coenen, Marieke Jh and Barton, Anne and Padyukov, Leonid and Klareskog, Lars and Gregersen, Peter K and Mariette, Xavier and Moreland, Larry W and Bridges, S Louis and de Vries, Niek and Huizinga, Tom W J and Guchelaar, Henk-Jan and International Rheumatoid Arthritis Consortium (INTERACT) and Friend, Stephen H and Stolovitzky, Gustavo}
}
@article {1109596,
	title = {Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs},
	journal = {Nat Genet},
	volume = {45},
	number = {9},
	year = {2013},
	month = {2013 Sep},
	pages = {984-94},
	abstract = {Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29\% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 {\textpm} 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 {\textpm} 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 {\textpm} 0.06 s.e.), and ADHD and major depressive disorder (0.32 {\textpm} 0.07 s.e.), low between schizophrenia and ASD (0.16 {\textpm} 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn{\textquoteright}s disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.},
	keywords = {Adult, Attention Deficit Disorder with Hyperactivity, Bipolar Disorder, Child, Child Development Disorders, Pervasive, Crohn Disease, Depressive Disorder, Major, Genetic Heterogeneity, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Inheritance Patterns, Mental Disorders, Polymorphism, Single Nucleotide, Schizophrenia},
	issn = {1546-1718},
	doi = {10.1038/ng.2711},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Genetic+relationship+between+five+psychiatric+disorders+estimated+from+genome-wide+SNPs},
	author = {Cross-Disorder Group of the Psychiatric Genomics Consortium and Lee, S Hong and Ripke, Stephan and Neale, Benjamin M and Faraone, Stephen V and Purcell, Shaun M and Perlis, Roy H and Mowry, Bryan J and Thapar, Anita and Goddard, Michael E and Witte, John S and Absher, Devin and Agartz, Ingrid and Akil, Huda and Amin, Farooq and Andreassen, Ole A and Anjorin, Adebayo and Anney, Richard and Anttila, Verneri and Arking, Dan E and Asherson, Philip and Azevedo, Maria H and Backlund, Lena and Badner, Judith A and Bailey, Anthony J and Banaschewski, Tobias and Barchas, Jack D and Barnes, Michael R and Barrett, Thomas B and Bass, Nicholas and Battaglia, Agatino and Bauer, Michael and Bay{\'e}s, M{\`o}nica and Bellivier, Frank and Bergen, Sarah E and Berrettini, Wade and Betancur, Catalina and Bettecken, Thomas and Biederman, Joseph and Binder, Elisabeth B and Black, Donald W and Blackwood, Douglas H R and Bloss, Cinnamon S and Boehnke, Michael and Boomsma, Dorret I and Breen, Gerome and Breuer, Ren{\'e} and Bruggeman, Richard and Cormican, Paul and Buccola, Nancy G and Buitelaar, Jan K and Bunney, William E and Buxbaum, Joseph D and Byerley, William F and Byrne, Enda M and Caesar, Sian and Cahn, Wiepke and Cantor, Rita M and Casas, Miguel and Chakravarti, Aravinda and Chambert, Kimberly and Choudhury, Khalid and Cichon, Sven and Cloninger, C Robert and Collier, David A and Cook, Edwin H and Coon, Hilary and Cormand, Bru and Corvin, Aiden and Coryell, William H and Craig, David W and Craig, Ian W and Crosbie, Jennifer and Cuccaro, Michael L and Curtis, David and Czamara, Darina and Datta, Susmita and Dawson, Geraldine and Day, Richard and De Geus, Eco J and Degenhardt, Franziska and Djurovic, Srdjan and Donohoe, Gary J and Doyle, Alysa E and Duan, Jubao and Dudbridge, Frank and Duketis, Eftichia and Ebstein, Richard P and Edenberg, Howard J and Elia, Josephine and Ennis, Sean and Etain, Bruno and Fanous, Ayman and Farmer, Anne E and Ferrier, I Nicol and Flickinger, Matthew and Fombonne, Eric and Foroud, Tatiana and Frank, Josef and Franke, Barbara and Fraser, Christine and Freedman, Robert and Freimer, Nelson B and Freitag, Christine M and Friedl, Marion and Fris{\'e}n, Louise and Gallagher, Louise and Gejman, Pablo V and Georgieva, Lyudmila and Gershon, Elliot S and Geschwind, Daniel H and Giegling, Ina and Gill, Michael and Gordon, Scott D and Gordon-Smith, Katherine and Green, Elaine K and Greenwood, Tiffany A and Grice, Dorothy E and Gross, Magdalena and Grozeva, Detelina and Guan, Weihua and Gurling, Hugh and De Haan, Lieuwe and Haines, Jonathan L and Hakonarson, Hakon and Hallmayer, Joachim and Hamilton, Steven P and Hamshere, Marian L and Hansen, Thomas F and Hartmann, Annette M and Hautzinger, Martin and Heath, Andrew C and Henders, Anjali K and Herms, Stefan and Hickie, Ian B and Hipolito, Maria and Hoefels, Susanne and Holmans, Peter A and Holsboer, Florian and Hoogendijk, Witte J and Hottenga, Jouke-Jan and Hultman, Christina M and Hus, Vanessa and Ingason, Andr{\'e}s and Ising, Marcus and Jamain, St{\'e}phane and Jones, Edward G and Jones, Ian and Jones, Lisa and Tzeng, Jung-Ying and K{\"a}hler, Anna K and Kahn, Ren{\'e} S and Kandaswamy, Radhika and Keller, Matthew C and Kennedy, James L and Kenny, Elaine and Kent, Lindsey and Kim, Yunjung and Kirov, George K and Klauck, Sabine M and Klei, Lambertus and Knowles, James A and Kohli, Martin A and Koller, Daniel L and Konte, Bettina and Korszun, Ania and Krabbendam, Lydia and Krasucki, Robert and Kuntsi, Jonna and Kwan, Phoenix and Land{\'e}n, Mikael and L{\r a}ngstr{\"o}m, Niklas and Lathrop, Mark and Lawrence, Jacob and Lawson, William B and Leboyer, Marion and Ledbetter, David H and Lee, Phil H and Lencz, Todd and Lesch, Klaus-Peter and Levinson, Douglas F and Lewis, Cathryn M and Li, Jun and Lichtenstein, Paul and Lieberman, Jeffrey A and Lin, Dan-Yu and Linszen, Don H and Liu, Chunyu and Lohoff, Falk W and Loo, Sandra K and Lord, Catherine and Lowe, Jennifer K and Lucae, Susanne and MacIntyre, Donald J and Madden, Pamela A F and Maestrini, Elena and Magnusson, Patrik K E and Mahon, Pamela B and Maier, Wolfgang and Malhotra, Anil K and Mane, Shrikant M and Martin, Christa L and Martin, Nicholas G and Mattheisen, Manuel and Matthews, Keith and Mattingsdal, Morten and McCarroll, Steven A and McGhee, Kevin A and McGough, James J and McGrath, Patrick J and McGuffin, Peter and McInnis, Melvin G and McIntosh, Andrew and McKinney, Rebecca and McLean, Alan W and McMahon, Francis J and McMahon, William M and McQuillin, Andrew and Medeiros, Helena and Medland, Sarah E and Meier, Sandra and Melle, Ingrid and Meng, Fan and Meyer, Jobst and Middeldorp, Christel M and Middleton, Lefkos and Milanova, Vihra and Miranda, Ana and Monaco, Anthony P and Montgomery, Grant W and Moran, Jennifer L and Moreno-De-Luca, Daniel and Morken, Gunnar and Morris, Derek W and Morrow, Eric M and Moskvina, Valentina and Muglia, Pierandrea and M{\"u}hleisen, Thomas W and Muir, Walter J and M{\"u}ller-Myhsok, Bertram and Murtha, Michael and Myers, Richard M and Myin-Germeys, Inez and Neale, Michael C and Nelson, Stan F and Nievergelt, Caroline M and Nikolov, Ivan and Nimgaonkar, Vishwajit and Nolen, Willem A and N{\"o}then, Markus M and Nurnberger, John I and Nwulia, Evaristus A and Nyholt, Dale R and O{\textquoteright}Dushlaine, Colm and Oades, Robert D and Olincy, Ann and Oliveira, Guiomar and Olsen, Line and Ophoff, Roel A and Osby, Urban and Owen, Michael J and Palotie, Aarno and Parr, Jeremy R and Paterson, Andrew D and Pato, Carlos N and Pato, Michele T and Penninx, Brenda W and Pergadia, Michele L and Pericak-Vance, Margaret A and Pickard, Benjamin S and Pimm, Jonathan and Piven, Joseph and Posthuma, Danielle and Potash, James B and Poustka, Fritz and Propping, Peter and Puri, Vinay and Quested, Digby J and Quinn, Emma M and Ramos-Quiroga, Josep Antoni and Rasmussen, Henrik B and Raychaudhuri, Soumya and Rehnstr{\"o}m, Karola and Reif, Andreas and Ribas{\'e}s, Marta and Rice, John P and Rietschel, Marcella and Roeder, Kathryn and Roeyers, Herbert and Rossin, Lizzy and Rothenberger, Aribert and Rouleau, Guy and Ruderfer, Douglas and Rujescu, Dan and Sanders, Alan R and Sanders, Stephan J and Santangelo, Susan L and Sergeant, Joseph A and Schachar, Russell and Schalling, Martin and Schatzberg, Alan F and Scheftner, William A and Schellenberg, Gerard D and Scherer, Stephen W and Schork, Nicholas J and Schulze, Thomas G and Schumacher, Johannes and Schwarz, Markus and Scolnick, Edward and Scott, Laura J and Shi, Jianxin and Shilling, Paul D and Shyn, Stanley I and Silverman, Jeremy M and Slager, Susan L and Smalley, Susan L and Smit, Johannes H and Smith, Erin N and Sonuga-Barke, Edmund J S and St Clair, David and State, Matthew and Steffens, Michael and Steinhausen, Hans-Christoph and Strauss, John S and Strohmaier, Jana and Stroup, T Scott and Sutcliffe, James S and Szatmari, Peter and Szelinger, Szabocls and Thirumalai, Srinivasa and Thompson, Robert C and Todorov, Alexandre A and Tozzi, Federica and Treutlein, Jens and Uhr, Manfred and van den Oord, Edwin J C G and Van Grootheest, Gerard and van Os, Jim and Vicente, Astrid M and Vieland, Veronica J and Vincent, John B and Visscher, Peter M and Walsh, Christopher A and Wassink, Thomas H and Watson, Stanley J and Weissman, Myrna M and Werge, Thomas and Wienker, Thomas F and Wijsman, Ellen M and Willemsen, Gonneke and Williams, Nigel and Willsey, A Jeremy and Witt, Stephanie H and Xu, Wei and Young, Allan H and Yu, Timothy W and Zammit, Stanley and Zandi, Peter P and Zhang, Peng and Zitman, Frans G and Z{\"o}llner, Sebastian and Devlin, Bernie and Kelsoe, John R and Sklar, Pamela and Daly, Mark J and O{\textquoteright}Donovan, Michael C and Craddock, Nicholas and Sullivan, Patrick F and Smoller, Jordan W and Kendler, Kenneth S and Wray, Naomi R and International Inflammatory Bowel Disease Genetics Consortium (IIBDGC)}
}
@article {1109581,
	title = {Genetics and epigenetics of rheumatoid arthritis},
	journal = {Nat Rev Rheumatol},
	volume = {9},
	number = {3},
	year = {2013},
	month = {2013 Mar},
	pages = {141-53},
	abstract = {Investigators have made key advances in rheumatoid arthritis (RA) genetics in the past 10 years. Although genetic studies have had limited influence on clinical practice and drug discovery, they are currently generating testable hypotheses to explain disease pathogenesis. Firstly, we review here the major advances in identifying RA genetic susceptibility markers both within and outside of the MHC. Understanding how genetic variants translate into pathogenic mechanisms and ultimately into phenotypes remains a mystery for most of the polymorphisms that confer susceptibility to RA, but functional data are emerging. Interplay between environmental and genetic factors is poorly understood and in need of further investigation. Secondly, we review current knowledge of the role of epigenetics in RA susceptibility. Differences in the epigenome could represent one of the ways in which environmental exposures translate into phenotypic outcomes. The best understood epigenetic phenomena include post-translational histone modifications and DNA methylation events, both of which have critical roles in gene regulation. Epigenetic studies in RA represent a new area of research with the potential to answer unsolved questions.},
	keywords = {Alleles, Arthritis, Rheumatoid, DNA Methylation, Epigenomics, Genetic Linkage, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Genotype, Humans, Hydrolases, Major Histocompatibility Complex, Phenotype, Polymorphism, Single Nucleotide, Protein Processing, Post-Translational, Protein Tyrosine Phosphatase, Non-Receptor Type 22},
	issn = {1759-4804},
	doi = {10.1038/nrrheum.2012.237},
	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3694322/},
	author = {Viatte, Sebastien and Plant, Darren and Raychaudhuri, Soumya}
}
@article {1109561,
	title = {Imputing amino acid polymorphisms in human leukocyte antigens},
	journal = {PLoS One},
	volume = {8},
	number = {6},
	year = {2013},
	month = {2013},
	pages = {e64683},
	abstract = {DNA sequence variation within human leukocyte antigen (HLA) genes mediate susceptibility to a wide range of human diseases. The complex genetic structure of the major histocompatibility complex (MHC) makes it difficult, however, to collect genotyping data in large cohorts. Long-range linkage disequilibrium between HLA loci and SNP markers across the major histocompatibility complex (MHC) region offers an alternative approach through imputation to interrogate HLA variation in existing GWAS data sets. Here we describe a computational strategy, SNP2HLA, to impute classical alleles and amino acid polymorphisms at class I (HLA-A, -B, -C) and class II (-DPA1, -DPB1, -DQA1, -DQB1, and -DRB1) loci. To characterize performance of SNP2HLA, we constructed two European ancestry reference panels, one based on data collected in HapMap-CEPH pedigrees (90 individuals) and another based on data collected by the Type 1 Diabetes Genetics Consortium (T1DGC, 5,225 individuals). We imputed HLA alleles in an independent data set from the British 1958 Birth Cohort (N = 918) with gold standard four-digit HLA types and SNPs genotyped using the Affymetrix GeneChip 500 K and Illumina Immunochip microarrays. We demonstrate that the sample size of the reference panel, rather than SNP density of the genotyping platform, is critical to achieve high imputation accuracy. Using the larger T1DGC reference panel, the average accuracy at four-digit resolution is 94.7\% using the low-density Affymetrix GeneChip 500 K, and 96.7\% using the high-density Illumina Immunochip. For amino acid polymorphisms within HLA genes, we achieve 98.6\% and 99.3\% accuracy using the Affymetrix GeneChip 500 K and Illumina Immunochip, respectively. Finally, we demonstrate how imputation and association testing at amino acid resolution can facilitate fine-mapping of primary MHC association signals, giving a specific example from type 1 diabetes.},
	keywords = {Alleles, Amino Acids, Chromosome Mapping, Diabetes Mellitus, Type 1, European Continental Ancestry Group, Genetic Predisposition to Disease, Genome-Wide Association Study, Haplotypes, HapMap Project, Histocompatibility Antigens Class I, Histocompatibility Antigens Class II, HLA Antigens, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide},
	issn = {1932-6203},
	doi = {10.1371/journal.pone.0064683},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/23762245},
	author = {Jia, Xiaoming and Han, Buhm and Onengut-Gumuscu, Suna and Chen, Wei-Min and Concannon, Patrick J and Rich, Stephen S and Raychaudhuri, Soumya and de Bakker, Paul I W}
}
@article {1109606,
	title = {Lipid and lipoprotein levels and trend in rheumatoid arthritis compared to the general population},
	journal = {Arthritis Care Res (Hoboken)},
	volume = {65},
	number = {12},
	year = {2013},
	month = {2013 Dec},
	pages = {2046-50},
	abstract = {OBJECTIVE: Differences in lipid levels associated with cardiovascular (CV) risk between rheumatoid arthritis (RA) patients and the general population remain unclear. Determining these differences is important in understanding the role of lipids in CV risk in RA. METHODS: We studied 2,005 RA subjects from 2 large academic medical centers. We extracted electronic medical record data on the first low-density lipoprotein (LDL) measurement, and total cholesterol and high-density lipoprotein (HDL) measurements within 1 year of the LDL measurement. Subjects with an electronic statin prescription prior to the first LDL measurement were excluded. We compared lipid levels in RA patients to recently published levels from the general US population using the t-test and stratifying by published parameters, i.e., 2007-2010, and women. We determined lipid trends using separate linear regression models for total cholesterol, LDL cholesterol, and HDL cholesterol, testing the association between year of measurement (1989-2010) and lipid level, adjusted by age and sex. Lipid trends in RA were qualitatively compared to the published general population trends. RESULTS: Women with RA had a significantly lower total cholesterol (186 versus 200 mg/dl; P = 0.002) and LDL cholesterol (105 versus 118 mg/dl; P = 0.001) compared to the general population (2007-2010). HDL cholesterol was not significantly different in the 2 groups. In the RA cohort, total cholesterol and LDL cholesterol significantly decreased each year, while HDL cholesterol increased (all with P \&lt; 0.0001), consistent with overall trends observed in a previous study. CONCLUSION: RA patients appear to have an overall lower total cholesterol and LDL cholesterol than the general population despite the general overall risk of CV disease in RA from observational studies.},
	keywords = {Arthritis, Rheumatoid, Cardiovascular Diseases, Cohort Studies, Cross-Sectional Studies, Female, Humans, Lipids, Lipoproteins, Male, Risk Factors},
	issn = {2151-4658},
	doi = {10.1002/acr.22091},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/23925980},
	author = {Liao, Katherine P and Cai, Tianxi and Gainer, Vivian S and Cagan, Andrew and Murphy, Shawn N and Liu, Chihchin and Churchill, Susanne and Shaw, Stanley Y and Kohane, Isaac and Solomon, Daniel H and Plenge, Robert M and Karlson, Elizabeth W}
}
@article {1109571,
	title = {Rare complete knockouts in humans: population distribution and significant role in autism spectrum disorders},
	journal = {Neuron},
	volume = {77},
	number = {2},
	year = {2013},
	month = {2013 Jan 23},
	pages = {235-42},
	abstract = {To characterize the role of rare complete human knockouts in autism spectrum disorders (ASDs), we identify genes with homozygous or compound heterozygous loss-of-function (LoF) variants (defined as nonsense and essential splice sites) from exome sequencing of 933 cases and 869 controls. We identify a 2-fold increase in complete knockouts of autosomal genes with low rates of LoF variation (<= 5\% frequency) in cases and estimate a 3\% contribution to ASD risk by these events, confirming this observation in an independent set of 563 probands and 4,605 controls. Outside the pseudoautosomal regions on the X chromosome, we similarly observe a significant 1.5-fold increase in rare hemizygous knockouts in males, contributing to another 2\% of ASDs in males. Taken together, these results provide compelling evidence that rare autosomal and X chromosome complete gene knockouts are important inherited risk factors for ASD.},
	keywords = {Case-Control Studies, Child Development Disorders, Pervasive, Child, Preschool, Chromosomes, Human, X, Demography, Female, Gene Deletion, Genetic Variation, Homozygote, Humans, Linkage Disequilibrium, Loss of Heterozygosity, Male, Risk Factors},
	issn = {1097-4199},
	doi = {10.1016/j.neuron.2012.12.029},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Rare+complete+knockouts+in+humans\%3A+population+distribution+and+significant+role+in+autism+spectrum+disorders},
	author = {Lim, Elaine T and Raychaudhuri, Soumya and Sanders, Stephan J and Stevens, Christine and Sabo, Aniko and MacArthur, Daniel G and Neale, Benjamin M and Kirby, Andrew and Ruderfer, Douglas M and Fromer, Menachem and Lek, Monkol and Liu, Li and Flannick, Jason and Ripke, Stephan and Nagaswamy, Uma and Muzny, Donna and Reid, Jeffrey G and Hawes, Alicia and Newsham, Irene and Wu, Yuanqing and Lewis, Lora and Dinh, Huyen and Gross, Shannon and Wang, Li-San and Lin, Chiao-Feng and Valladares, Otto and Gabriel, Stacey B and DePristo, Mark and Altshuler, David M and Purcell, Shaun M and NHLBI Exome Sequencing Project and State, Matthew W and Boerwinkle, Eric and Buxbaum, Joseph D and Cook, Edwin H and Gibbs, Richard A and Schellenberg, Gerard D and Sutcliffe, James S and Devlin, Bernie and Roeder, Kathryn and Daly, Mark J}
}
@article {1109601,
	title = {Rare variants in CFI, C3 and C9 are associated with high risk of advanced age-related macular degeneration},
	journal = {Nat Genet},
	volume = {45},
	number = {11},
	year = {2013},
	month = {2013 Nov},
	pages = {1366-70},
	abstract = {To define the role of rare variants in advanced age-related macular degeneration (AMD) risk, we sequenced the exons of 681 genes within all reported AMD loci and related pathways in 2,493 cases and controls. We first tested each gene for increased or decreased burden of rare variants in cases compared to controls. We found that 7.8\% of AMD cases compared to 2.3\% of controls are carriers of rare missense CFI variants (odds ratio (OR) = 3.6; P = 2 {\texttimes} 10(-8)). There was a predominance of dysfunctional variants in cases compared to controls. We then tested individual variants for association with disease. We observed significant association with rare missense alleles in genes other than CFI. Genotyping in 5,115 independent samples confirmed associations with AMD of an allele in C3 encoding p.Lys155Gln (replication P = 3.5 {\texttimes} 10(-5), OR = 2.8; joint P = 5.2 {\texttimes} 10(-9), OR = 3.8) and an allele in C9 encoding p.Pro167Ser (replication P = 2.4 {\texttimes} 10(-5), OR = 2.2; joint P = 6.5 {\texttimes} 10(-7), OR = 2.2). Finally, we show that the allele of C3 encoding Gln155 results in resistance to proteolytic inactivation by CFH and CFI. These results implicate loss of C3 protein regulation and excessive alternative complement activation in AMD pathogenesis, thus informing both the direction of effect and mechanistic underpinnings of this disorder.},
	keywords = {Aging, Amino Acid Substitution, Base Sequence, Complement Activation, Complement C3, Complement C9, Complement Factor I, Genetic Predisposition to Disease, Genetic Variation, Genotype, Humans, Macular Degeneration, Risk, Sequence Analysis, DNA},
	issn = {1546-1718},
	doi = {10.1038/ng.2741},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Rare+variants+in+CFI\%2C+C3+and+C9+are+associated+with+high+risk+of+advanced+age-related+macular+degeneration},
	author = {Seddon, Johanna M and Yu, Yi and Miller, Elizabeth C and Reynolds, Robyn and Tan, Perciliz L and Gowrisankar, Sivakumar and Goldstein, Jacqueline I and Triebwasser, Michael and Anderson, Holly E and Zerbib, Jennyfer and Kavanagh, David and Souied, Eric and Katsanis, Nicholas and Daly, Mark J and Atkinson, John P and Raychaudhuri, Soumya}
}
@article {1001866,
	title = {Common risk alleles for inflammatory diseases are targets of recent positive selection},
	journal = {Am J Hum Genet},
	volume = {92},
	number = {4},
	year = {2013},
	month = {2013 Apr 04},
	pages = {517-29},
	abstract = {Genome-wide association studies (GWASs) have identified hundreds of loci harboring genetic variation influencing inflammatory-disease susceptibility in humans. It has been hypothesized that present day inflammatory diseases may have arisen, in part, due to pleiotropic effects of host resistance to pathogens over the course of human history, with significant selective pressures acting to increase host resistance to pathogens. The extent to which genetic factors underlying inflammatory-disease susceptibility has been influenced by selective processes can now be quantified more comprehensively than previously possible. To understand the evolutionary forces that have shaped inflammatory-disease susceptibility and to elucidate functional pathways affected by selection, we performed a systems-based analysis to integrate (1) published GWASs for inflammatory diseases, (2) a genome-wide scan for signatures of positive selection in a population of European ancestry, (3) functional genomics data comprised of protein-protein interaction networks, and (4) a genome-wide expression quantitative trait locus (eQTL) mapping study in peripheral blood mononuclear cells (PBMCs). We demonstrate that loci for inflammatory-disease susceptibility are enriched for genomic signatures of recent positive natural selection, with selected loci forming a highly interconnected protein-protein interaction network. Further, we identify 21 loci for inflammatory-disease susceptibility that display signatures of recent positive selection, of which 13 also show evidence of cis-regulatory effects on genes within the associated locus. Thus, our integrated analyses highlight a set of susceptibility loci that might subserve a shared molecular function and has experienced selective pressure over the course of human history; today, these loci play a key role in influencing susceptibility to multiple different inflammatory diseases, in part through alterations of gene expression in immune cells.},
	keywords = {Alleles, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Haplotypes, Humans, Inflammation, Protein Interaction Maps, Quantitative Trait Loci, Risk Factors, Selection, Genetic},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2013.03.001},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Common+risk+alleles+for+inflammatory+diseases+are+targets+of+recent+positive+selection},
	author = {Raj, Towfique and Kuchroo, Manik and Replogle, Joseph M and Raychaudhuri, Soumya and Stranger, Barbara E and De Jager, Philip L}
}
@article {1001871,
	title = {Genome-wide association study and gene expression analysis identifies CD84 as a predictor of response to etanercept therapy in rheumatoid arthritis},
	journal = {PLoS Genet},
	volume = {9},
	number = {3},
	year = {2013},
	month = {2013 Mar},
	pages = {e1003394},
	abstract = {Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8 {\texttimes} 10(-8)), but not in the infliximab or adalimumab subsets (P\&gt;0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3{\textquoteright} UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1 {\texttimes} 10(-11) in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry.},
	keywords = {Adult, Aged, Alleles, Antigens, CD, Antirheumatic Agents, Arthritis, Rheumatoid, Asian Continental Ancestry Group, Biomarkers, Pharmacological, Etanercept, European Continental Ancestry Group, Female, Gene Expression Regulation, Genome-Wide Association Study, Humans, Immunoglobulin G, Male, Middle Aged, Polymorphism, Single Nucleotide, Receptors, Tumor Necrosis Factor, Signaling Lymphocytic Activation Molecule Family, Tumor Necrosis Factor-alpha},
	issn = {1553-7404},
	doi = {10.1371/journal.pgen.1003394},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Genome-wide+association+study+and+gene+expression+analysis+identifies+CD84+as+a+predictor+of+response+to+etanercept+therapy+in+rheumatoid+arthritis},
	author = {Cui, Jing and Stahl, Eli A and Saevarsdottir, Saedis and Miceli, Corinne and Diogo, Dorothee and Trynka, Gosia and Raj, Towfique and Mirkov, Ma{\v s}a Umicevic and Canhao, Helena and Ikari, Katsunori and Terao, Chikashi and Okada, Yukinori and Wedr{\'e}n, Sara and Askling, Johan and Yamanaka, Hisashi and Momohara, Shigeki and Taniguchi, Atsuo and Ohmura, Koichiro and Matsuda, Fumihiko and Mimori, Tsuneyo and Gupta, Namrata and Kuchroo, Manik and Morgan, Ann W and Isaacs, John D and Wilson, Anthony G and Hyrich, Kimme L and Herenius, Marieke and Doorenspleet, Marieke E and Tak, Paul-Peter and Crusius, J Bart A and van der Horst-Bruinsma, Irene E and Wolbink, Gert Jan and van Riel, Piet L C M and van de Laar, Mart and Guchelaar, Henk-Jan and Shadick, Nancy A and Allaart, Cornelia F and Huizinga, Tom W J and Toes, Rene E M and Kimberly, Robert P and Bridges, S Louis and Criswell, Lindsey A and Moreland, Larry W and Fonseca, Jo{\~a}o Eurico and de Vries, Niek and Stranger, Barbara E and De Jager, Philip L and Raychaudhuri, Soumya and Weinblatt, Michael E and Gregersen, Peter K and Mariette, Xavier and Barton, Anne and Padyukov, Leonid and Coenen, Marieke Jh and Karlson, Elizabeth W and Plenge, Robert M}
}
@article {1001861,
	title = {Human genetics in rheumatoid arthritis guides a high-throughput drug screen of the CD40 signaling pathway},
	journal = {PLoS Genet},
	volume = {9},
	number = {5},
	year = {2013},
	month = {2013 May},
	pages = {e1003487},
	abstract = {Although genetic and non-genetic studies in mouse and human implicate the CD40 pathway in rheumatoid arthritis (RA), there are no approved drugs that inhibit CD40 signaling for clinical care in RA or any other disease. Here, we sought to understand the biological consequences of a CD40 risk variant in RA discovered by a previous genome-wide association study (GWAS) and to perform a high-throughput drug screen for modulators of CD40 signaling based on human genetic findings. First, we fine-map the CD40 risk locus in 7,222 seropositive RA patients and 15,870 controls, together with deep sequencing of CD40 coding exons in 500 RA cases and 650 controls, to identify a single SNP that explains the entire signal of association (rs4810485, P = 1.4{\texttimes}10(-9)). Second, we demonstrate that subjects homozygous for the RA risk allele have \~{}33\% more CD40 on the surface of primary human CD19+ B lymphocytes than subjects homozygous for the non-risk allele (P = 10(-9)), a finding corroborated by expression quantitative trait loci (eQTL) analysis in peripheral blood mononuclear cells from 1,469 healthy control individuals. Third, we use retroviral shRNA infection to perturb the amount of CD40 on the surface of a human B lymphocyte cell line (BL2) and observe a direct correlation between amount of CD40 protein and phosphorylation of RelA (p65), a subunit of the NF-κB transcription factor. Finally, we develop a high-throughput NF-κB luciferase reporter assay in BL2 cells activated with trimerized CD40 ligand (tCD40L) and conduct an HTS of 1,982 chemical compounds and FDA-approved drugs. After a series of counter-screens and testing in primary human CD19+ B cells, we identify 2 novel chemical inhibitors not previously implicated in inflammation or CD40-mediated NF-κB signaling. Our study demonstrates proof-of-concept that human genetics can be used to guide the development of phenotype-based, high-throughput small-molecule screens to identify potential novel therapies in complex traits such as RA.},
	keywords = {Alleles, Animals, Antigens, CD19, Antigens, CD40, Arthritis, Rheumatoid, B-Lymphocytes, Drug Evaluation, Preclinical, Genetic Predisposition to Disease, Genome-Wide Association Study, High-Throughput Screening Assays, Humans, Mice, NF-kappa B, Quantitative Trait Loci, Signal Transduction, Small Molecule Libraries},
	issn = {1553-7404},
	doi = {10.1371/journal.pgen.1003487},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Human+genetics+in+rheumatoid+arthritis+guides+a+high-throughput+drug+screen+of+the+CD40+signaling+pathway},
	author = {Li, Gang and Diogo, Doroth{\'e}e and Wu, Di and Spoonamore, Jim and Dancik, Vlado and Franke, Lude and Kurreeman, Fina and Rossin, Elizabeth J and Duclos, Grant and Hartland, Cathy and Zhou, Xuezhong and Li, Kejie and Liu, Jun and De Jager, Philip L and Siminovitch, Katherine A and Zhernakova, Alexandra and Raychaudhuri, Soumya and Bowes, John and Eyre, Steve and Padyukov, Leonid and Gregersen, Peter K and Worthington, Jane and Rheumatoid Arthritis Consortium International (RACI) and Gupta, Namrata and Clemons, Paul A and Stahl, Eli and Tolliday, Nicola and Plenge, Robert M}
}
@article {1001881,
	title = {Quantifying missing heritability at known GWAS loci},
	journal = {PLoS Genet},
	volume = {9},
	number = {12},
	year = {2013},
	month = {2013},
	pages = {e1003993},
	abstract = {Recent work has shown that much of the missing heritability of complex traits can be resolved by estimates of heritability explained by all genotyped SNPs. However, it is currently unknown how much heritability is missing due to poor tagging or additional causal variants at known GWAS loci. Here, we use variance components to quantify the heritability explained by all SNPs at known GWAS loci in nine diseases from WTCCC1 and WTCCC2. After accounting for expectation, we observed all SNPs at known GWAS loci to explain 1.29 x more heritability than GWAS-associated SNPs on average (P=3.3 x 10$^{-}$$^{5}$). For some diseases, this increase was individually significant: 2.07 x for Multiple Sclerosis (MS) (P=6.5 x 10$^{-}$$^{9}$) and 1.48 x for Crohn{\textquoteright}s Disease (CD) (P = 1.3 x 10$^{-}${\textthreesuperior}); all analyses of autoimmune diseases excluded the well-studied MHC region. Additionally, we found that GWAS loci from other related traits also explained significant heritability. The union of all autoimmune disease loci explained 7.15 x more MS heritability than known MS SNPs (P \&lt; 1.0 x 10$^{-}${\textonesuperior}$^{6}$ and 2.20 x more CD heritability than known CD SNPs (P = 6.1 x 10$^{-}$$^{9}$), with an analogous increase for all autoimmune diseases analyzed. We also observed significant increases in an analysis of \&gt; 20,000 Rheumatoid Arthritis (RA) samples typed on ImmunoChip, with 2.37 x more heritability from all SNPs at GWAS loci (P = 2.3 x 10$^{-}$$^{6}$) and 5.33 x more heritability from all autoimmune disease loci (P \&lt; 1 x 10$^{-}${\textonesuperior}$^{6}$ compared to known RA SNPs (including those identified in this cohort). Our methods adjust for LD between SNPs, which can bias standard estimates of heritability from SNPs even if all causal variants are typed. By comparing adjusted estimates, we hypothesize that the genome-wide distribution of causal variants is enriched for low-frequency alleles, but that causal variants at known GWAS loci are skewed towards common alleles. These findings have important ramifications for fine-mapping study design and our understanding of complex disease architecture.},
	keywords = {Alleles, Arthritis, Rheumatoid, Crohn Disease, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Models, Theoretical, Multiple Sclerosis, Polymorphism, Single Nucleotide},
	issn = {1553-7404},
	doi = {10.1371/journal.pgen.1003993},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/24385918},
	author = {Gusev, Alexander and Bhatia, Gaurav and Zaitlen, Noah and Vilhjalmsson, Bjarni J and Diogo, Doroth{\'e}e and Stahl, Eli A and Gregersen, Peter K and Worthington, Jane and Klareskog, Lars and Raychaudhuri, Soumya and Plenge, Robert M and Pasaniuc, Bogdan and Price, Alkes L}
}
@article {1001876,
	title = {Rare, low-frequency, and common variants in the protein-coding sequence of biological candidate genes from GWASs contribute to risk of rheumatoid arthritis},
	journal = {Am J Hum Genet},
	volume = {92},
	number = {1},
	year = {2013},
	month = {2013 Jan 10},
	pages = {15-27},
	abstract = {The extent to which variants in the protein-coding sequence of genes contribute to risk of rheumatoid arthritis (RA) is unknown. In this study, we addressed this issue by deep exon sequencing and large-scale genotyping of 25 biological candidate genes located within RA risk loci discovered by genome-wide association studies (GWASs). First, we assessed the contribution of rare coding variants in the 25 genes to the risk of RA in a pooled sequencing study of 500 RA cases and 650 controls of European ancestry. We observed an accumulation of rare nonsynonymous variants exclusive to RA cases in IL2RA and IL2RB (burden test: p = 0.007 and p = 0.018, respectively). Next, we assessed the aggregate contribution of low-frequency and common coding variants to the risk of RA by dense genotyping of the 25 gene loci in 10,609 RA cases and 35,605 controls. We observed a strong enrichment of coding variants with a nominal signal of association with RA (p \&lt; 0.05) after adjusting for the best signal of association at the loci (p(enrichment) = 6.4 {\texttimes} 10(-4)). For one locus containing CD2, we found that a missense variant, rs699738 (c.798C\&gt;A [p.His266Gln]), and a noncoding variant, rs624988, reside on distinct haplotypes and independently contribute to the risk of RA (p = 4.6 {\texttimes} 10(-6)). Overall, our results indicate that variants (distributed across the allele-frequency spectrum) within the protein-coding portion of a subset of biological candidate genes identified by GWASs contribute to the risk of RA. Further, we have demonstrated that very large sample sizes will be required for comprehensively identifying the independent alleles contributing to the missing heritability of RA.},
	keywords = {Arthritis, Rheumatoid, Exons, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Risk Factors},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2012.11.012},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Rare\%2C+low-frequency\%2C+and+common+variants+in+the+protein-coding+sequence+of+biological+candidate+genes+from+GWASs+contribute+to+risk+of+rheumatoid+arthritis},
	author = {Diogo, Doroth{\'e}e and Kurreeman, Fina and Stahl, Eli A and Liao, Katherine P and Gupta, Namrata and Greenberg, Jeffrey D and Rivas, Manuel A and Hickey, Brendan and Flannick, Jason and Thomson, Brian and Guiducci, Candace and Ripke, Stephan and Adzhubey, Ivan and Barton, Anne and Kremer, Joel M and Alfredsson, Lars and Consortium of Rheumatology Researchers of North America and Rheumatoid Arthritis Consortium International and Sunyaev, Shamil and Martin, Javier and Zhernakova, Alexandra and Bowes, John and Eyre, Steve and Siminovitch, Katherine A and Gregersen, Peter K and Worthington, Jane and Klareskog, Lars and Padyukov, Leonid and Raychaudhuri, Soumya and Plenge, Robert M}
}
@article {1001586,
	title = {Application of user-guided automated cytometric data analysis to large-scale immunoprofiling of invariant natural killer T cells},
	journal = {Proc Natl Acad Sci U S A},
	volume = {110},
	number = {47},
	year = {2013},
	month = {2013 Nov 19},
	pages = {19030-5},
	abstract = {Defining and characterizing pathologies of the immune system requires precise and accurate quantification of abundances and functions of cellular subsets via cytometric studies. At this time, data analysis relies on manual gating, which is a major source of variability in large-scale studies. We devised an automated, user-guided method, X-Cyt, which specializes in rapidly and robustly identifying targeted populations of interest in large data sets. We first applied X-Cyt to quantify CD4(+) effector and central memory T cells in 236 samples, demonstrating high concordance with manual analysis (r = 0.91 and 0.95, respectively) and superior performance to other available methods. We then quantified the rare mucosal associated invariant T cell population in 35 samples, achieving manual concordance of 0.98. Finally we characterized the population dynamics of invariant natural killer T (iNKT) cells, a particularly rare peripheral lymphocyte, in 110 individuals by assaying 19 markers. We demonstrated that although iNKT cell numbers and marker expression are highly variable in the population, iNKT abundance correlates with sex and age, and the expression of phenotypic and functional markers correlates closely with CD4 expression.},
	keywords = {Age Factors, Antigens, CD4, Biomarkers, Flow Cytometry, Humans, Natural Killer T-Cells, Sex Factors, Software},
	issn = {1091-6490},
	doi = {10.1073/pnas.1318322110},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Application+of+user-guided+automated+cytometric+data+analysis+to+large-scale+immunoprofiling+of+invariant+natural+killer+T+cells},
	author = {Hu, Xinli and Kim, Hyun and Brennan, Patrick J and Han, Buhm and Baecher-Allan, Clare M and De Jager, Philip L and Brenner, Michael B and Raychaudhuri, Soumya}
}
@article {1001591,
	title = {Chromatin marks identify critical cell types for fine mapping complex trait variants},
	journal = {Nat Genet},
	volume = {45},
	number = {2},
	year = {2013},
	month = {2013 Feb},
	pages = {124-30},
	abstract = {If trait-associated variants alter regulatory regions, then they should fall within chromatin marks in relevant cell types. However, it is unclear which of the many marks are most useful in defining cell types associated with disease and fine mapping variants. We hypothesized that informative marks are phenotypically cell type specific; that is, SNPs associated with the same trait likely overlap marks in the same cell type. We examined 15 chromatin marks and found that those highlighting active gene regulation were phenotypically cell type specific. Trimethylation of histone H3 at lysine 4 (H3K4me3) was the most phenotypically cell type specific (P \&lt; 1 {\texttimes} 10(-6)), driven by colocalization of variants and marks rather than gene proximity (P \&lt; 0.001). H3K4me3 peaks overlapped with 37 SNPs for plasma low-density lipoprotein concentration in the liver (P \&lt; 7 {\texttimes} 10(-5)), 31 SNPs for rheumatoid arthritis within CD4(+) regulatory T cells (P = 1 {\texttimes} 10(-4)), 67 SNPs for type 2 diabetes in pancreatic islet cells (P = 0.003) and the liver (P = 0.003), and 14 SNPs for neuropsychiatric disease in neuronal tissues (P = 0.007). We show how cell type-specific H3K4me3 peaks can inform the fine mapping of associated SNPs to identify causal variation.},
	keywords = {Arthritis, Rheumatoid, Chromatin, Databases, Genetic, Diabetes Mellitus, Type 2, Genetic Markers, Histones, Humans, Nervous System Diseases, Phenotype, Polymorphism, Single Nucleotide, Software},
	issn = {1546-1718},
	doi = {10.1038/ng.2504},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Chromatin+marks+identify+critical+cell+types+for+fine+mapping+complex+trait+variants},
	author = {Trynka, Gosia and Sandor, Cynthia and Han, Buhm and Xu, Han and Stranger, Barbara E and Liu, X Shirley and Raychaudhuri, Soumya}
}
@article {1001581,
	title = {Using chromatin marks to interpret and localize genetic associations to complex human traits and diseases},
	journal = {Curr Opin Genet Dev},
	volume = {23},
	number = {6},
	year = {2013},
	month = {2013 Dec},
	pages = {635-41},
	abstract = {While studies to associate genomic variants to complex traits have gradually become increasingly productive, the molecular mechanisms that underlie these associations are rarely understood. Because only a small fraction of trait-associated variants can be linked to coding sequences, investigators have speculated that many of the underlying causal alleles influence non-coding gene regulatory sites. Recent studies have successfully identified examples of mechanisms for non-coding alleles at individual loci. Now, genome-wide chromatin assays have resulted in maps of dozens of genomic annotations of the non-coding genome across multiple different tissues, cell types and cell lines. This gives a tremendous opportunity to integrate these annotations with complex trait signals to globally interpret associated variants, and prioritize likely causal alleles. Here, we review the examples of mechanisms by which non-coding, common alleles result in phenotypes. We discuss the efforts to integrate common trait-associated variants with genomic annotations. Finally, we highlight some caveats of these approaches and outline future directions for improvement.},
	keywords = {Alleles, Chromatin, Chromosome Mapping, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Phenotype, Polymorphism, Single Nucleotide},
	issn = {1879-0380},
	doi = {10.1016/j.gde.2013.10.009},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Using+chromatin+marks+to+interpret+and+localize+genetic+associations+to+complex+human+traits+and+diseases},
	author = {Trynka, Gosia and Raychaudhuri, Soumya}
}
@article {1109546,
	title = {Classical HLA-DRB1 and DPB1 alleles account for HLA associations with primary biliary cirrhosis},
	journal = {Genes Immun},
	volume = {13},
	number = {6},
	year = {2012},
	month = {2012 Sep},
	pages = {461-8},
	abstract = {Susceptibility to primary biliary cirrhosis (PBC) is strongly associated with human leukocyte antigen (HLA)-region polymorphisms. To determine if associations can be explained by classical HLA determinants, we studied Italian, 676 cases and 1440 controls, genotyped with dense single-nucleotide polymorphisms (SNPs) for which classical HLA alleles and amino acids were imputed. Although previous genome-wide association studies and our results show stronger SNP associations near DQB1, we demonstrate that the HLA signals can be attributed to classical DRB1 and DPB1 genes. Strong support for the predominant role of DRB1 is provided by our conditional analyses. We also demonstrate an independent association of DPB1. Specific HLA-DRB1 genes (*08, *11 and *14) account for most of the DRB1 association signal. Consistent with previous studies, DRB1*08 (P=1.59 {\texttimes} 10(-11)) was the strongest predisposing allele, whereas DRB1*11 (P=1.42 {\texttimes} 10(-10)) was protective. Additionally, DRB1*14 and the DPB1 association (DPB1*03:01; P=9.18 {\texttimes} 10(-7)) were predisposing risk alleles. No signal was observed in the HLA class 1 or class 3 regions. These findings better define the association of PBC with HLA and specifically support the role of classical HLA-DRB1 and DPB1 genes and alleles in susceptibility to PBC.},
	keywords = {Case-Control Studies, European Continental Ancestry Group, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, HLA-DP beta-Chains, HLA-DRB1 Chains, Humans, Italy, Liver Cirrhosis, Biliary, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, Risk Factors},
	issn = {1476-5470},
	doi = {10.1038/gene.2012.17},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Classical+HLA-DRB1+and+DPB1+alleles+account+for+HLA+associations+with+primary+biliary+cirrhosis},
	author = {Invernizzi, P and Ransom, M and Raychaudhuri, S and Kosoy, R and Lleo, A and Shigeta, R and Franke, A and Bossa, F and Amos, C I and Gregersen, P K and Siminovitch, K A and Cusi, D and de Bakker, P I W and Podda, M and Gershwin, M E and Seldin, M F and Italian PBC Genetics Study Group}
}
@article {1109536,
	title = {A genome-wide association search for type 2 diabetes genes in African Americans},
	journal = {PLoS One},
	volume = {7},
	number = {1},
	year = {2012},
	month = {2012},
	pages = {e29202},
	abstract = {African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P\&lt;0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P\&lt;0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P\&lt;2.5{\texttimes}10(-8)). SNP rs7560163 (P = 7.0{\texttimes}10(-9), OR (95\% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P\&lt;0.05) and reached more nominal levels of significance (P\&lt;2.5{\texttimes}10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.},
	keywords = {Adult, African Americans, Aged, Case-Control Studies, Cohort Studies, Diabetes Mellitus, Type 2, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Meta-Analysis as Topic, Middle Aged, Polymorphism, Single Nucleotide, Validation Studies as Topic},
	issn = {1932-6203},
	doi = {10.1371/journal.pone.0029202},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/22238593},
	author = {Palmer, Nicholette D and McDonough, Caitrin W and Hicks, Pamela J and Roh, Bong H and Wing, Maria R and An, S Sandy and Hester, Jessica M and Cooke, Jessica N and Bostrom, Meredith A and Rudock, Megan E and Talbert, Matthew E and Lewis, Joshua P and DIAGRAM Consortium and MAGIC investigators and Ferrara, Assiamira and Lu, Lingyi and Ziegler, Julie T and Sale, Michele M and Divers, Jasmin and Shriner, Daniel and Adeyemo, Adebowale and Rotimi, Charles N and Ng, Maggie C Y and Langefeld, Carl D and Freedman, Barry I and Bowden, Donald W and Voight, Benjamin F and Scott, Laura J and Steinthorsdottir, Valgerdur and Morris, Andrew P and Dina, Christian and Welch, Ryan P and Zeggini, Eleftheria and Huth, Cornelia and Aulchenko, Yurii S and Thorleifsson, Gudmar and McCulloch, Laura J and Ferreira, Teresa and Grallert, Harald and Amin, Najaf and Wu, Guanming and Willer, Cristen J and Raychaudhuri, Soumya and McCarroll, Steve A and Langenberg, Claudia and Hofmann, Oliver M and Dupuis, Jos{\'e}e and Qi, Lu and Segr{\`e}, Ayellet V and van Hoek, Mandy and Navarro, Pau and Ardlie, Kristin and Balkau, Beverley and Benediktsson, Rafn and Bennett, Amanda J and Blagieva, Roza and Boerwinkle, Eric and Bonnycastle, Lori L and Bengtsson Bostr{\"o}m, Kristina and Bravenboer, Bert and Bumpstead, Suzannah and Burtt, No{\"e}l P and Charpentier, Guillaume and Chines, Peter S and Cornelis, Marilyn and Couper, David J and Crawford, Gabe and Doney, Alex S F and Elliott, Katherine S and Elliott, Amanda L and Erdos, Michael R and Fox, Caroline S and Franklin, Christopher S and Ganser, Martha and Gieger, Christian and Grarup, Niels and Green, Todd and Griffin, Simon and Groves, Christopher J and Guiducci, Candace and Hadjadj, Samy and Hassanali, Neelam and Herder, Christian and Isomaa, Bo and Jackson, Anne U and Johnson, Paul R V and J{\o}rgensen, Torben and Kao, Wen H L and Klopp, Norman and Kong, Augustine and Kraft, Peter and Kuusisto, Johanna and Lauritzen, Torsten and Li, Man and Lieverse, Aloysius and Lindgren, Cecilia M and Lyssenko, Valeriya and Marre, Michel and Meitinger, Thomas and Midthjell, Kristian and Morken, Mario A and Narisu, Narisu and Nilsson, Peter and Owen, Katharine R and Payne, Felicity and Perry, John R B and Petersen, Ann-Kristin and Platou, Carl and Proen{\c c}a, Christine and Prokopenko, Inga and Rathmann, Wolfgang and Rayner, N William and Robertson, Neil R and Rocheleau, Ghislain and Roden, Michael and Sampson, Michael J and Saxena, Richa and Shields, Beverley M and Shrader, Peter and Sigurdsson, Gunnar and Spars{\o}, Thomas and Strassburger, Klaus and Stringham, Heather M and Sun, Qi and Swift, Amy J and Thorand, Barbara and Tichet, Jean and Tuomi, Tiinamaija and van Dam, Rob M and van Haeften, Timon W and van Herpt, Thijs and van Vliet-Ostaptchouk, Jana V and Walters, G Bragi and Weedon, Michael N and Wijmenga, Cisca and Witteman, Jacqueline and Bergman, Richard N and Cauchi, Stephane and Collins, Francis S and Gloyn, Anna L and Gyllensten, Ulf and Hansen, Torben and Hide, Winston A and Hitman, Graham A and Hofman, Albert and Hunter, David J and Hveem, Kristian and Laakso, Markku and Mohlke, Karen L and Morris, Andrew D and Palmer, Colin N A and Pramstaller, Peter P and Rudan, Igor and Sijbrands, Eric and Stein, Lincoln D and Tuomilehto, Jaakko and Uitterlinden, Andre and Mark Walker and Wareham, Nicholas J and Watanabe, Richard M and Abecasis, Goncalo R and Boehm, Bernhard O and Campbell, Harry and Daly, Mark J and Hattersley, Andrew T and Hu, Frank B and Meigs, James B and Pankow, James S and Pedersen, Oluf and Wichmann, H-Erich and Barroso, In{\^e}s and Florez, Jose C and Frayling, Timothy M and Groop, Leif and Sladek, Rob and Thorsteinsdottir, Unnur and Wilson, James F and Illig, Thomas and Froguel, Philippe and van Duijn, Cornelia M and Stefansson, Kari and Altshuler, David and Boehnke, Michael and McCarthy, Mark I and Soranzo, Nicole and Wheeler, Eleanor and Glazer, Nicole L and Bouatia-Naji, Nabila and M{\"a}gi, Reedik and Randall, Joshua and Johnson, Toby and Elliott, Paul and Rybin, Denis and Henneman, Peter and Dehghan, Abbas and Hottenga, Jouke Jan and Song, Kijoung and Goel, Anuj and Egan, Josephine M and Lajunen, Taina and Doney, Alex and Kanoni, Stavroula and Cavalcanti-Proen{\c c}a, Christine and Kumari, Meena and Timpson, Nicholas J and Zabena, Carina and Ingelsson, Erik and An, Ping and O{\textquoteright}Connell, Jeffrey and Luan, Jian{\textquoteright}an and Elliott, Amanda and McCarroll, Steven A and Roccasecca, Rosa Maria and Pattou, Fran{\c c}ois and Sethupathy, Praveen and Ariyurek, Yavuz and Barter, Philip and Beilby, John P and Ben-Shlomo, Yoav and Bergmann, Sven and Bochud, Murielle and Bonnefond, Am{\'e}lie and Borch-Johnsen, Knut and B{\"o}ttcher, Yvonne and Brunner, Eric and Bumpstead, Suzannah J and Chen, Yii-Der Ida and Chines, Peter and Clarke, Robert and Coin, Lachlan J M and Cooper, Matthew N and Crisponi, Laura and Day, Ian N M and de Geus, Eco J C and Delplanque, Jerome and Fedson, Annette C and Fischer-Rosinsky, Antje and Forouhi, Nita G and Frants, Rune and Franzosi, Maria Grazia and Galan, Pilar and Goodarzi, Mark O and Graessler, J{\"u}rgen and Grundy, Scott and Gwilliam, Rhian and Hallmans, G{\"o}ran and Hammond, Naomi and Han, Xijing and Hartikainen, Anna-Liisa and Hayward, Caroline and Heath, Simon C and Hercberg, Serge and Hicks, Andrew A and Hillman, David R and Hingorani, Aroon D and Hui, Jennie and Hung, Joe and Jula, Antti and Kaakinen, Marika and Kaprio, Jaakko and Kesaniemi, Y Antero and Kivimaki, Mika and Knight, Beatrice and Koskinen, Seppo and Kovacs, Peter and Kyvik, Kirsten Ohm and Lathrop, G Mark and Lawlor, Debbie A and Le Bacquer, Olivier and Lecoeur, C{\'e}cile and Li, Yun and Mahley, Robert and Mangino, Massimo and Manning, Alisa K and Mart{\'\i}nez-Larrad, Mar{\'\i}a Teresa and McAteer, Jarred B and McPherson, Ruth and Meisinger, Christa and Melzer, David and Meyre, David and Mitchell, Braxton D and Mukherjee, Sutapa and Naitza, Silvia and Neville, Matthew J and Oostra, Ben A and Orr{\`u}, Marco and Pakyz, Ruth and Paolisso, Giuseppe and Pattaro, Cristian and Pearson, Daniel and Peden, John F and Pedersen, Nancy L and Perola, Markus and Pfeiffer, Andreas F H and Pichler, Irene and Polasek, Ozren and Posthuma, Danielle and Potter, Simon C and Pouta, Anneli and Province, Michael A and Psaty, Bruce M and Rayner, Nigel W and Rice, Kenneth and Ripatti, Samuli and Rivadeneira, Fernando and Rolandsson, Olov and Sandbaek, Annelli and Sandhu, Manjinder and Sanna, Serena and Sayer, Avan Aihie and Scheet, Paul and Seedorf, Udo and Sharp, Stephen J and Shields, Beverley and Sijbrands, Eric J G and Silveira, Angela and Simpson, Laila and Singleton, Andrew and Smith, Nicholas L and Sovio, Ulla and Swift, Amy and Syddall, Holly and Syv{\"a}nen, Ann-Christine and Tanaka, Toshiko and T{\"o}njes, Anke and Uitterlinden, Andr{\'e} G and van Dijk, Ko Willems and Varma, Dhiraj and Visvikis-Siest, Sophie and Vitart, Veronique and Vogelzangs, Nicole and Waeber, G{\'e}rard and Wagner, Peter J and Walley, Andrew and Ward, Kim L and Watkins, Hugh and Wild, Sarah H and Willemsen, Gonneke and Witteman, Jaqueline C M and Yarnell, John W G and Zelenika, Diana and Zethelius, Bj{\"o}rn and Zhai, Guangju and Zhao, Jing Hua and Zillikens, M Carola and Borecki, Ingrid B and Loos, Ruth J F and Meneton, Pierre and Magnusson, Patrik K E and Nathan, David M and Williams, Gordon H and Silander, Kaisa and Salomaa, Veikko and Smith, George Davey and Bornstein, Stefan R and Schwarz, Peter and Spranger, Joachim and Karpe, Fredrik and Shuldiner, Alan R and Cooper, Cyrus and Dedoussis, George V and Serrano-R{\'\i}os, Manuel and Lind, Lars and Palmer, Lyle J and Franks, Paul W and Ebrahim, Shah and Marmot, Michael and Kao, W H Linda and Pramstaller, Peter Paul and Wright, Alan F and Stumvoll, Michael and Hamsten, Anders and Buchanan, Thomas A and Valle, Timo T and Rotter, Jerome I and Siscovick, David S and Penninx, Brenda W J H and Boomsma, Dorret I and Deloukas, Panos and Spector, Timothy D and Ferrucci, Luigi and Cao, Antonio and Scuteri, Angelo and Schlessinger, David and Uda, Manuela and Ruokonen, Aimo and Jarvelin, Marjo-Riitta and Waterworth, Dawn M and Vollenweider, Peter and Peltonen, Leena and Mooser, Vincent and Sladek, Robert}
}
@article {1109551,
	title = {Heritability and genome-wide association study to assess genetic differences between advanced age-related macular degeneration subtypes},
	journal = {Ophthalmology},
	volume = {119},
	number = {9},
	year = {2012},
	month = {2012 Sep},
	pages = {1874-85},
	abstract = {PURPOSE: To investigate whether the 2 subtypes of advanced age-related macular degeneration (AMD), choroidal neovascularization (CNV), and geographic atrophy (GA) segregate separately in families and to identify which genetic variants are associated with these 2 subtypes. DESIGN: Sibling correlation study and genome-wide association study (GWAS). PARTICIPANTS: For the sibling correlation study, 209 sibling pairs with advanced AMD were included. For the GWAS, 2594 participants with advanced AMD subtypes and 4134 controls were included. Replication cohorts included 5383 advanced AMD participants and 15 240 controls. METHODS: Participants had the AMD grade assigned based on fundus photography, examination, or both. To determine heritability of advanced AMD subtypes, a sibling correlation study was performed. For the GWAS, genome-wide genotyping was conducted and 6 036 699 single nucleotide polymorphisms (SNPs) were imputed. Then, the SNPs were analyzed with a generalized linear model controlling for genotyping platform and genetic ancestry. The most significant associations were evaluated in independent cohorts. MAIN OUTCOME MEASURES: Concordance of advanced AMD subtypes in sibling pairs and associations between SNPs with GA and CNV advanced AMD subtypes. RESULTS: The difference between the observed and expected proportion of siblings concordant for the same subtype of advanced AMD was different to a statistically significant degree (P = 4.2 {\texttimes} 10(-5)), meaning that in siblings of probands with CNV or GA, the same advanced subtype is more likely to develop. In the analysis comparing participants with CNV to those with GA, a statistically significant association was observed at the ARMS2/HTRA1 locus (rs10490924; odds ratio [OR], 1.47; P = 4.3 {\texttimes} 10(-9)), which was confirmed in the replication samples (OR, 1.38; P = 7.4 {\texttimes} 10(-14) for combined discovery and replication analysis). CONCLUSIONS: Whether CNV versus GA develops in a patient with AMD is determined in part by genetic variation. In this large GWAS meta-analysis and replication analysis, the ARMS2/HTRA1 locus confers increased risk for both advanced AMD subtypes, but imparts greater risk for CNV than for GA. This locus explains a small proportion of the excess sibling correlation for advanced AMD subtype. Other loci were detected with suggestive associations that differ for advanced AMD subtypes and deserve follow-up in additional studies.},
	keywords = {Choroidal Neovascularization, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Geographic Atrophy, Humans, Macular Degeneration, Male, Polymorphism, Single Nucleotide, Proteins, Risk Factors, Serine Endopeptidases, Siblings},
	issn = {1549-4713},
	doi = {10.1016/j.ophtha.2012.03.014},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Heritability+and+genome-wide+association+study+to+assess+genetic+differences+between+advanced+age-related+macular+degeneration+subtypes},
	author = {Sobrin, Lucia and Ripke, Stephan and Yu, Yi and Fagerness, Jesen and Bhangale, Tushar R and Tan, Perciliz L and Souied, Eric H and Buitendijk, Gabri{\"e}lle H S and Merriam, Joanna E and Richardson, Andrea J and Raychaudhuri, Soumya and Reynolds, Robyn and Chin, Kimberly A and Lee, Aaron Y and Leveziel, Nicolas and Zack, Donald J and Campochiaro, Peter and Smith, R Theodore and Barile, Gaetano R and Hogg, Ruth E and Chakravarthy, Usha and Behrens, Timothy W and Uitterlinden, Andr{\'e} G and van Duijn, Cornelia M and Vingerling, Johannes R and Brantley, Milam A and Baird, Paul N and Klaver, Caroline C W and Allikmets, Rando and Katsanis, Nicholas and Graham, Robert R and Ioannidis, John P A and Daly, Mark J and Seddon, Johanna M}
}
@article {1109556,
	title = {Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease},
	journal = {Nature},
	volume = {491},
	number = {7422},
	year = {2012},
	month = {2012 Nov 01},
	pages = {119-24},
	abstract = {Crohn{\textquoteright}s disease and ulcerative colitis, the two common forms of inflammatory bowel disease (IBD), affect over 2.5 million people of European ancestry, with rising prevalence in other populations. Genome-wide association studies and subsequent meta-analyses of these two diseases as separate phenotypes have implicated previously unsuspected mechanisms, such as autophagy, in their pathogenesis and showed that some IBD loci are shared with other inflammatory diseases. Here we expand on the knowledge of relevant pathways by undertaking a meta-analysis of Crohn{\textquoteright}s disease and ulcerative colitis genome-wide association scans, followed by extensive validation of significant findings, with a combined total of more than 75,000 cases and controls. We identify 71 new associations, for a total of 163 IBD loci, that meet genome-wide significance thresholds. Most loci contribute to both phenotypes, and both directional (consistently favouring one allele over the course of human history) and balancing (favouring the retention of both alleles within populations) selection effects are evident. Many IBD loci are also implicated in other immune-mediated disorders, most notably with ankylosing spondylitis and psoriasis. We also observe considerable overlap between susceptibility loci for IBD and mycobacterial infection. Gene co-expression network analysis emphasizes this relationship, with pathways shared between host responses to mycobacteria and those predisposing to IBD.},
	keywords = {Colitis, Ulcerative, Crohn Disease, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Haplotypes, Host-Pathogen Interactions, Humans, Inflammatory Bowel Diseases, Mycobacterium, Mycobacterium Infections, Mycobacterium tuberculosis, Phenotype, Polymorphism, Single Nucleotide, Reproducibility of Results},
	issn = {1476-4687},
	doi = {10.1038/nature11582},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Host-microbe+interactions+have+shaped+the+genetic+architecture+of+inflammatory+bowel+disease},
	author = {Jostins, Luke and Ripke, Stephan and Weersma, Rinse K and Duerr, Richard H and McGovern, Dermot P and Hui, Ken Y and Lee, James C and Schumm, L Philip and Sharma, Yashoda and Anderson, Carl A and Essers, Jonah and Mitrovic, Mitja and Ning, Kaida and Cleynen, Isabelle and Theatre, Emilie and Spain, Sarah L and Raychaudhuri, Soumya and Goyette, Philippe and Wei, Zhi and Abraham, Clara and Jean-Paul Achkar and Ahmad, Tariq and Amininejad, Leila and Ananthakrishnan, Ashwin N and Andersen, Vibeke and Andrews, Jane M and Baidoo, Leonard and Balschun, Tobias and Bampton, Peter A and Bitton, Alain and Boucher, Gabrielle and Brand, Stephan and B{\"u}ning, Carsten and Cohain, Ariella and Cichon, Sven and D{\textquoteright}Amato, Mauro and De Jong, Dirk and Devaney, Kathy L and Dubinsky, Marla and Edwards, Cathryn and Ellinghaus, David and Ferguson, Lynnette R and Franchimont, Denis and Fransen, Karin and Gearry, Richard and Georges, Michel and Gieger, Christian and Glas, J{\"u}rgen and Haritunians, Talin and Hart, Ailsa and Hawkey, Chris and Hedl, Matija and Hu, Xinli and Karlsen, Tom H and Kupcinskas, Limas and Kugathasan, Subra and Latiano, Anna and Laukens, Debby and Lawrance, Ian C and Lees, Charlie W and Louis, Edouard and Mahy, Gillian and Mansfield, John and Morgan, Angharad R and Mowat, Craig and Newman, William and Palmieri, Orazio and Ponsioen, Cyriel Y and Potocnik, Uros and Prescott, Natalie J and Regueiro, Miguel and Rotter, Jerome I and Russell, Richard K and Sanderson, Jeremy D and Sans, Miquel and Satsangi, Jack and Schreiber, Stefan and Simms, Lisa A and Sventoraityte, Jurgita and Targan, Stephan R and Taylor, Kent D and Tremelling, Mark and Verspaget, Hein W and De Vos, Martine and Wijmenga, Cisca and Wilson, David C and Winkelmann, Juliane and Xavier, Ramnik J and Zeissig, Sebastian and Zhang, Bin and Zhang, Clarence K and Zhao, Hongyu and International IBD Genetics Consortium (IIBDGC) and Silverberg, Mark S and Annese, Vito and Hakonarson, Hakon and Brant, Steven R and Radford-Smith, Graham and Mathew, Christopher G and Rioux, John D and Schadt, Eric E and Daly, Mark J and Franke, Andre and Parkes, Miles and Vermeire, Severine and Barrett, Jeffrey C and Cho, Judy H}
}
@article {1109531,
	title = {Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals},
	journal = {PLoS Genet},
	volume = {8},
	number = {3},
	year = {2012},
	month = {2012},
	pages = {e1002607},
	abstract = {Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5{\texttimes}10(-8)-1.2{\texttimes}10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p\&lt;3{\texttimes}10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3{\texttimes}10(-3), n = 22,044), increased triglycerides (p = 2.6{\texttimes}10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8{\texttimes}10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4{\texttimes}10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5{\texttimes}10(-13), n = 96,748) and decreased BMI (p = 1.4{\texttimes}10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.},
	keywords = {Adiponectin, African Americans, Asian Continental Ancestry Group, Cholesterol, HDL, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Female, Gene Expression, Genetic Predisposition to Disease, Genome-Wide Association Study, Glucose Tolerance Test, Humans, Insulin Resistance, Male, Metabolic Networks and Pathways, Polymorphism, Single Nucleotide, Waist-Hip Ratio},
	issn = {1553-7404},
	doi = {10.1371/journal.pgen.1002607},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Novel+loci+for+adiponectin+levels+and+their+influence+on+type+2+diabetes+and+metabolic+traits\%3A+a+multi-ethnic+meta-analysis+of+45\%2C891+individuals},
	author = {Dastani, Zari and Hivert, Marie-France and Timpson, Nicholas and Perry, John R B and Yuan, Xin and Scott, Robert A and Henneman, Peter and Heid, Iris M and Kizer, Jorge R and Lyytik{\"a}inen, Leo-Pekka and Fuchsberger, Christian and Tanaka, Toshiko and Morris, Andrew P and Small, Kerrin and Isaacs, Aaron and Beekman, Marian and Coassin, Stefan and Lohman, Kurt and Qi, Lu and Kanoni, Stavroula and Pankow, James S and Uh, Hae-Won and Wu, Ying and Bidulescu, Aurelian and Rasmussen-Torvik, Laura J and Greenwood, Celia M T and Ladouceur, Martin and Grimsby, Jonna and Manning, Alisa K and Liu, Ching-Ti and Kooner, Jaspal and Mooser, Vincent E and Vollenweider, Peter and Kapur, Karen A and Chambers, John and Wareham, Nicholas J and Langenberg, Claudia and Frants, Rune and Willems-Vandijk, Ko and Oostra, Ben A and Willems, Sara M and Lamina, Claudia and Winkler, Thomas W and Psaty, Bruce M and Tracy, Russell P and Brody, Jennifer and Chen, Ida and Viikari, Jorma and K{\"a}h{\"o}nen, Mika and Pramstaller, Peter P and Evans, David M and St Pourcain, Beate and Sattar, Naveed and Wood, Andrew R and Bandinelli, Stefania and Carlson, Olga D and Egan, Josephine M and B{\"o}hringer, Stefan and van Heemst, Diana and Kedenko, Lyudmyla and Kristiansson, Kati and Nuotio, Marja-Liisa and Loo, Britt-Marie and Harris, Tamara and Garcia, Melissa and Kanaya, Alka and Haun, Margot and Klopp, Norman and Wichmann, H-Erich and Deloukas, Panos and Katsareli, Efi and Couper, David J and Duncan, Bruce B and Kloppenburg, Margreet and Adair, Linda S and Borja, Judith B and DIAGRAM+ Consortium and MAGIC Consortium and GLGC Investigators and MuTHER Consortium and Wilson, James G and Musani, Solomon and Guo, Xiuqing and Johnson, Toby and Semple, Robert and Teslovich, Tanya M and Allison, Matthew A and Redline, Susan and Buxbaum, Sarah G and Mohlke, Karen L and Meulenbelt, Ingrid and Ballantyne, Christie M and Dedoussis, George V and Hu, Frank B and Liu, Yongmei and Paulweber, Bernhard and Spector, Timothy D and Slagboom, P Eline and Ferrucci, Luigi and Jula, Antti and Perola, Markus and Raitakari, Olli and Florez, Jose C and Salomaa, Veikko and Eriksson, Johan G and Frayling, Timothy M and Hicks, Andrew A and Lehtim{\"a}ki, Terho and Smith, George Davey and Siscovick, David S and Kronenberg, Florian and van Duijn, Cornelia and Loos, Ruth J F and Waterworth, Dawn M and Meigs, James B and Dupuis, Josee and Richards, J Brent and Voight, Benjamin F and Scott, Laura J and Steinthorsdottir, Valgerdur and Dina, Christian and Welch, Ryan P and Zeggini, Eleftheria and Huth, Cornelia and Aulchenko, Yurii S and Thorleifsson, Gudmar and McCulloch, Laura J and Ferreira, Teresa and Grallert, Harald and Amin, Najaf and Wu, Guanming and Willer, Cristen J and Raychaudhuri, Soumya and McCarroll, Steve A and Hofmann, Oliver M and Segr{\`e}, Ayellet V and van Hoek, Mandy and Navarro, Pau and Ardlie, Kristin and Balkau, Beverley and Benediktsson, Rafn and Bennett, Amanda J and Blagieva, Roza and Boerwinkle, Eric and Bonnycastle, Lori L and Bengtsson Bostr{\"o}m, Kristina and Bravenboer, Bert and Bumpstead, Suzannah and Burtt, No{\"e}l P and Charpentier, Guillaume and Chines, Peter S and Cornelis, Marilyn and Crawford, Gabe and Doney, Alex S F and Elliott, Katherine S and Elliott, Amanda L and Erdos, Michael R and Fox, Caroline S and Franklin, Christopher S and Ganser, Martha and Gieger, Christian and Grarup, Niels and Green, Todd and Griffin, Simon and Groves, Christopher J and Guiducci, Candace and Hadjadj, Samy and Hassanali, Neelam and Herder, Christian and Isomaa, Bo and Jackson, Anne U and Johnson, Paul R V and J{\o}rgensen, Torben and Kao, Wen H L and Kong, Augustine and Kraft, Peter and Kuusisto, Johanna and Lauritzen, Torsten and Li, Man and Lieverse, Aloysius and Lindgren, Cecilia M and Lyssenko, Valeriya and Marre, Michel and Meitinger, Thomas and Midthjell, Kristian and Morken, Mario A and Narisu, Narisu and Nilsson, Peter and Owen, Katharine R and Payne, Felicity and Petersen, Ann-Kristin and Platou, Carl and Proen{\c c}a, Christine and Prokopenko, Inga and Rathmann, Wolfgang and Rayner, N William and Robertson, Neil R and Rocheleau, Ghislain and Roden, Michael and Sampson, Michael J and Saxena, Richa and Shields, Beverley M and Shrader, Peter and Sigurdsson, Gunnar and Spars{\o}, Thomas and Strassburger, Klaus and Stringham, Heather M and Sun, Qi and Swift, Amy J and Thorand, Barbara and Tichet, Jean and Tuomi, Tiinamaija and van Dam, Rob M and van Haeften, Timon W and van Herpt, Thijs and van Vliet-Ostaptchouk, Jana V and Walters, G Bragi and Weedon, Michael N and Wijmenga, Cisca and Witteman, Jacqueline and Bergman, Richard N and Cauchi, Stephane and Collins, Francis S and Gloyn, Anna L and Gyllensten, Ulf and Hansen, Torben and Hide, Winston A and Hitman, Graham A and Hofman, Albert and Hunter, David J and Hveem, Kristian and Laakso, Markku and Morris, Andrew D and Palmer, Colin N A and Rudan, Igor and Sijbrands, Eric and Stein, Lincoln D and Tuomilehto, Jaakko and Uitterlinden, Andre and Mark Walker and Watanabe, Richard M and Abecasis, Goncalo R and Boehm, Bernhard O and Campbell, Harry and Daly, Mark J and Hattersley, Andrew T and Pedersen, Oluf and Barroso, In{\^e}s and Groop, Leif and Sladek, Rob and Thorsteinsdottir, Unnur and Wilson, James F and Illig, Thomas and Froguel, Philippe and van Duijn, Cornelia M and Stefansson, Kari and Altshuler, David and Boehnke, Michael and McCarthy, Mark I and Soranzo, Nicole and Wheeler, Eleanor and Glazer, Nicole L and Bouatia-Naji, Nabila and M{\"a}gi, Reedik and Randall, Joshua and Elliott, Paul and Rybin, Denis and Dehghan, Abbas and Hottenga, Jouke Jan and Song, Kijoung and Goel, Anuj and Lajunen, Taina and Doney, Alex and Cavalcanti-Proen{\c c}a, Christine and Kumari, Meena and Timpson, Nicholas J and Zabena, Carina and Ingelsson, Erik and An, Ping and O{\textquoteright}Connell, Jeffrey and Luan, Jian{\textquoteright}an and Elliott, Amanda and McCarroll, Steven A and Roccasecca, Rosa Maria and Pattou, Fran{\c c}ois and Sethupathy, Praveen and Ariyurek, Yavuz and Barter, Philip and Beilby, John P and Ben-Shlomo, Yoav and Bergmann, Sven and Bochud, Murielle and Bonnefond, Am{\'e}lie and Borch-Johnsen, Knut and B{\"o}ttcher, Yvonne and Brunner, Eric and Bumpstead, Suzannah J and Chen, Yii-Der Ida and Chines, Peter and Clarke, Robert and Coin, Lachlan J M and Cooper, Matthew N and Crisponi, Laura and Day, Ian N M and de Geus, Eco J C and Delplanque, Jerome and Fedson, Annette C and Fischer-Rosinsky, Antje and Forouhi, Nita G and Franzosi, Maria Grazia and Galan, Pilar and Goodarzi, Mark O and Graessler, J{\"u}rgen and Grundy, Scott and Gwilliam, Rhian and Hallmans, G{\"o}ran and Hammond, Naomi and Han, Xijing and Hartikainen, Anna-Liisa and Hayward, Caroline and Heath, Simon C and Hercberg, Serge and Hillman, David R and Hingorani, Aroon D and Hui, Jennie and Hung, Joe and Kaakinen, Marika and Kaprio, Jaakko and Kesaniemi, Y Antero and Kivimaki, Mika and Knight, Beatrice and Koskinen, Seppo and Kovacs, Peter and Kyvik, Kirsten Ohm and Lathrop, G Mark and Lawlor, Debbie A and Le Bacquer, Olivier and Lecoeur, C{\'e}cile and Li, Yun and Mahley, Robert and Mangino, Massimo and Mart{\'\i}nez-Larrad, Mar{\'\i}a Teresa and McAteer, Jarred B and McPherson, Ruth and Meisinger, Christa and Melzer, David and Meyre, David and Mitchell, Braxton D and Mukherjee, Sutapa and Naitza, Silvia and Neville, Matthew J and Orr{\`u}, Marco and Pakyz, Ruth and Paolisso, Giuseppe and Pattaro, Cristian and Pearson, Daniel and Peden, John F and Pedersen, Nancy L and Pfeiffer, Andreas F H and Pichler, Irene and Polasek, Ozren and Posthuma, Danielle and Potter, Simon C and Pouta, Anneli and Province, Michael A and Rayner, Nigel W and Rice, Kenneth and Ripatti, Samuli and Rivadeneira, Fernando and Rolandsson, Olov and Sandbaek, Annelli and Sandhu, Manjinder and Sanna, Serena and Sayer, Avan Aihie and Scheet, Paul and Seedorf, Udo and Sharp, Stephen J and Shields, Beverley and Sigur{\dh}sson, Gunnar and Sijbrands, Eric J G and Silveira, Angela and Simpson, Laila and Singleton, Andrew and Smith, Nicholas L and Sovio, Ulla and Swift, Amy and Syddall, Holly and Syv{\"a}nen, Ann-Christine and T{\"o}njes, Anke and Uitterlinden, Andr{\'e} G and van Dijk, Ko Willems and Varma, Dhiraj and Visvikis-Siest, Sophie and Vitart, Veronique and Vogelzangs, Nicole and Waeber, G{\'e}rard and Wagner, Peter J and Walley, Andrew and Ward, Kim L and Watkins, Hugh and Wild, Sarah H and Willemsen, Gonneke and Witteman, Jaqueline C M and Yarnell, John W G and Zelenika, Diana and Zethelius, Bj{\"o}rn and Zhai, Guangju and Zhao, Jing Hua and Zillikens, M Carola and DIAGRAM Consortium and GIANT Consortium and Global B Pgen Consortium and Borecki, Ingrid B and Meneton, Pierre and Magnusson, Patrik K E and Nathan, David M and Williams, Gordon H and Silander, Kaisa and Bornstein, Stefan R and Schwarz, Peter and Spranger, Joachim and Karpe, Fredrik and Shuldiner, Alan R and Cooper, Cyrus and Serrano-R{\'\i}os, Manuel and Lind, Lars and Palmer, Lyle J and Hu, Frank B and Franks, Paul W and Ebrahim, Shah and Marmot, Michael and Kao, W H Linda and Pramstaller, Peter Paul and Wright, Alan F and Stumvoll, Michael and Hamsten, Anders and Procardis Consortium and Buchanan, Thomas A and Valle, Timo T and Rotter, Jerome I and Penninx, Brenda W J H and Boomsma, Dorret I and Cao, Antonio and Scuteri, Angelo and Schlessinger, David and Uda, Manuela and Ruokonen, Aimo and Jarvelin, Marjo-Riitta and Peltonen, Leena and Mooser, Vincent and Sladek, Robert and MAGIC investigators and GLGC Consortium and Kiran Musunuru and Smith, Albert V and Edmondson, Andrew C and Stylianou, Ioannis M and Koseki, Masahiro and Pirruccello, James P and Chasman, Daniel I and Johansen, Christopher T and Fouchier, Sigrid W and Peloso, Gina M and Barbalic, Maja and Ricketts, Sally L and Bis, Joshua C and Feitosa, Mary F and Orho-Melander, Marju and Melander, Olle and Li, Xiaohui and Li, Mingyao and Cho, Yoon Shin and Go, Min Jin and Kim, Young Jin and Lee, Jong-Young and Park, Taesung and Kim, Kyunga and Sim, Xueling and Ong, Rick Twee-Hee and Croteau-Chonka, Damien C and Lange, Leslie A and Smith, Joshua D and Ziegler, Andreas and Zhang, Weihua and Zee, Robert Y L and Whitfield, John B and Thompson, John R and Surakka, Ida and Spector, Tim D and Smit, Johannes H and Sinisalo, Juha and Scott, James and Saharinen, Juha and Sabatti, Chiara and Rose, Lynda M and Roberts, Robert and Rieder, Mark and Parker, Alex N and Pare, Guillaume and O{\textquoteright}Donnell, Christopher J and Nieminen, Markku S and Nickerson, Deborah A and Montgomery, Grant W and McArdle, Wendy and Masson, David and Martin, Nicholas G and Marroni, Fabio and Lucas, Gavin and Luben, Robert and Lokki, Marja-Liisa and Lettre, Guillaume and Launer, Lenore J and Lakatta, Edward G and Laaksonen, Reijo and Kyvik, Kirsten O and K{\"o}nig, Inke R and Khaw, Kay-Tee and Kaplan, Lee M and Johansson, {\r A}sa and Janssens, A Cecile J W and Igl, Wilmar and Hovingh, G Kees and Hengstenberg, Christian and Havulinna, Aki S and Hastie, Nicholas D and Harris, Tamara B and Haritunians, Talin and Hall, Alistair S and Groop, Leif C and Gonzalez, Elena and Freimer, Nelson B and Erdmann, Jeanette and Ejebe, Kenechi G and D{\"o}ring, Angela and Dominiczak, Anna F and Demissie, Serkalem and Deloukas, Panagiotis and de Faire, Ulf and Crawford, Gabriel and Chen, Yii-Der I and Caulfield, Mark J and Boekholdt, S Matthijs and Assimes, Themistocles L and Quertermous, Thomas and Seielstad, Mark and Wong, Tien Y and Tai, E-Shyong and Feranil, Alan B and Kuzawa, Christopher W and Taylor, Herman A and Gabriel, Stacey B and Holm, Hilma and Gudnason, Vilmundur and Krauss, Ronald M and Ordovas, Jose M and Munroe, Patricia B and Kooner, Jaspal S and Tall, Alan R and Hegele, Robert A and Kastelein, John J P and Schadt, Eric E and Strachan, David P and Reilly, Muredach P and Samani, Nilesh J and Schunkert, Heribert and Cupples, L Adrienne and Sandhu, Manjinder S and Ridker, Paul M and Daniel J Rader and Kathiresan, Sekar}
}
@article {1109541,
	title = {Rheumatoid arthritis. Evidence for a genetic component to disease severity in RA},
	journal = {Nat Rev Rheumatol},
	volume = {8},
	number = {6},
	year = {2012},
	month = {2012 May 31},
	pages = {312-3},
	abstract = {Rheumatoid arthritis (RA) is partly heritable; genetic and serological markers are known to confer risk of developing pathology. But given clinical heterogeneity in RA, can we predict who will develop severe disease? Substantial heritability of erosive progression rates has now been identified, but better prognostic biomarkers remain wanting.},
	keywords = {Arthritis, Rheumatoid, Disease Progression, Family Health, Genetic Predisposition to Disease, Humans, Prognosis, Quantitative Trait, Heritable, Risk Factors, Severity of Illness Index},
	issn = {1759-4804},
	doi = {10.1038/nrrheum.2012.74},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/22647779},
	author = {Stahl, Eli A and Raychaudhuri, Soumya}
}
@article {1001896,
	title = {Five amino acids in three HLA proteins explain most of the association between MHC and seropositive rheumatoid arthritis},
	journal = {Nat Genet},
	volume = {44},
	number = {3},
	year = {2012},
	month = {2012 Jan 29},
	pages = {291-6},
	abstract = {The genetic association of the major histocompatibility complex (MHC) to rheumatoid arthritis risk has commonly been attributed to alleles in HLA-DRB1. However, debate persists about the identity of the causal variants in HLA-DRB1 and the presence of independent effects elsewhere in the MHC. Using existing genome-wide SNP data in 5,018 individuals with seropositive rheumatoid arthritis (cases) and 14,974 unaffected controls, we imputed and tested classical alleles and amino acid polymorphisms in HLA-A, HLA-B, HLA-C, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1 and HLA-DRB1, as well as 3,117 SNPs across the MHC. Conditional and haplotype analyses identified that three amino acid positions (11, 71 and 74) in HLA-DRβ1 and single-amino-acid polymorphisms in HLA-B (at position 9) and HLA-DPβ1 (at position 9), which are all located in peptide-binding grooves, almost completely explain the MHC association to rheumatoid arthritis risk. This study shows how imputation of functional variation from large reference panels can help fine map association signals in the MHC.},
	keywords = {Amino Acid Substitution, Arthritis, Rheumatoid, Case-Control Studies, Genome-Wide Association Study, Haplotypes, HLA-B Antigens, HLA-DP beta-Chains, HLA-DRB1 Chains, Humans, Major Histocompatibility Complex, Models, Molecular, Polymorphism, Single Nucleotide},
	issn = {1546-1718},
	doi = {10.1038/ng.1076},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Five+amino+acids+in+three+HLA+proteins+explain+most+of+the+association+between+MHC+and+seropositive+rheumatoid+arthritis},
	author = {Raychaudhuri, Soumya and Sandor, Cynthia and Stahl, Eli A and Freudenberg, Jan and Lee, Hye-Soon and Jia, Xiaoming and Alfredsson, Lars and Padyukov, Leonid and Klareskog, Lars and Worthington, Jane and Siminovitch, Katherine A and Bae, Sang-Cheol and Plenge, Robert M and Gregersen, Peter K and de Bakker, Paul I W}
}
@article {1001891,
	title = {Use of a multiethnic approach to identify rheumatoid- arthritis-susceptibility loci, 1p36 and 17q12},
	journal = {Am J Hum Genet},
	volume = {90},
	number = {3},
	year = {2012},
	month = {2012 Mar 09},
	pages = {524-32},
	abstract = {We have previously shown that rheumatoid arthritis (RA) risk alleles overlap between different ethnic groups. Here, we utilize a multiethnic approach to show that we can effectively discover RA risk alleles. Thirteen putatively associated SNPs that had not yet exceeded genome-wide significance (p \&lt; 5 {\texttimes} 10(-8)) in our previous RA genome-wide association study (GWAS) were analyzed in independent sample sets consisting of 4,366 cases and 17,765 controls of European, African American, and East Asian ancestry. Additionally, we conducted an overall association test across all 65,833 samples (a GWAS meta-analysis plus the replication samples). Of the 13 SNPs investigated, four were significantly below the study-wide Bonferroni corrected p value threshold (p \&lt; 0.0038) in the replication samples. Two SNPs (rs3890745 at the 1p36 locus [p = 2.3 {\texttimes} 10(-12)] and rs2872507 at the 17q12 locus [p = 1.7 {\texttimes} 10(-9)]) surpassed genome-wide significance in all 16,659 RA cases and 49,174 controls combined. We used available GWAS data to fine map these two loci in Europeans and East Asians, and we found that the same allele conferred risk in both ethnic groups. A series of bioinformatic analyses identified TNFRSF14-MMEL1 at the 1p36 locus and IKZF3-ORMDL3-GSDMB at the 17q12 locus as the genes most likely associated with RA. These findings demonstrate empirically that a multiethnic approach is an effective strategy for discovering RA risk loci, and they suggest that combining GWASs across ethnic groups represents an efficient strategy for gaining statistical power.},
	keywords = {Alleles, Arthritis, Rheumatoid, Case-Control Studies, Chromosomes, Human, Pair 1, Chromosomes, Human, Pair 17, Computational Biology, Ethnic Groups, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Ikaros Transcription Factor, Linkage Disequilibrium, Membrane Proteins, Neoplasm Proteins, Neprilysin, Polymorphism, Single Nucleotide, Receptors, Tumor Necrosis Factor, Member 14},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2012.01.010},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Use+of+a+multiethnic+approach+to+identify+rheumatoid-+arthritis-susceptibility+loci\%2C+1p36+and+17q12},
	author = {Kurreeman, Fina A S and Stahl, Eli A and Okada, Yukinori and Liao, Katherine and Diogo, Doroth{\'e}e and Raychaudhuri, Soumya and Freudenberg, Jan and Kochi, Yuta and Patsopoulos, Nikolaos A and Gupta, Namrata and CLEAR investigators and Sandor, Cynthia and Bang, So-Young and Lee, Hye-Soon and Padyukov, Leonid and Suzuki, Akari and Siminovitch, Kathy and Worthington, Jane and Gregersen, Peter K and Hughes, Laura B and Reynolds, Richard J and Bridges, S Louis and Bae, Sang-Cheol and Yamamoto, Kazuhiko and Plenge, Robert M}
}
@article {1001886,
	title = {Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis},
	journal = {Nat Genet},
	volume = {44},
	number = {5},
	year = {2012},
	month = {2012 Mar 25},
	pages = {483-9},
	abstract = {The genetic architectures of common, complex diseases are largely uncharacterized. We modeled the genetic architecture underlying genome-wide association study (GWAS) data for rheumatoid arthritis and developed a new method using polygenic risk-score analyses to infer the total liability-scale variance explained by associated GWAS SNPs. Using this method, we estimated that, together, thousands of SNPs from rheumatoid arthritis GWAS explain an additional 20\% of disease risk (excluding known associated loci). We further tested this method on datasets for three additional diseases and obtained comparable estimates for celiac disease (43\% excluding the major histocompatibility complex), myocardial infarction and coronary artery disease (48\%) and type 2 diabetes (49\%). Our results are consistent with simulated genetic models in which hundreds of associated loci harbor common causal variants and a smaller number of loci harbor multiple rare causal variants. These analyses suggest that GWAS will continue to be highly productive for the discovery of additional susceptibility loci for common diseases.},
	keywords = {Arthritis, Rheumatoid, Bayes Theorem, Cardiovascular Diseases, Case-Control Studies, Celiac Disease, Diabetes Mellitus, Type 2, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Multifactorial Inheritance, Polymorphism, Single Nucleotide},
	issn = {1546-1718},
	doi = {10.1038/ng.2232},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/22446960},
	author = {Stahl, Eli A and Wegmann, Daniel and Trynka, Gosia and Gutierrez-Achury, Javier and Do, Ron and Voight, Benjamin F and Kraft, Peter and Chen, Robert and Kallberg, Henrik J and Kurreeman, Fina A S and Diabetes Genetics Replication and Meta-analysis Consortium and Myocardial Infarction Genetics Consortium and Kathiresan, Sekar and Wijmenga, Cisca and Gregersen, Peter K and Alfredsson, Lars and Siminovitch, Katherine A and Worthington, Jane and de Bakker, Paul I W and Raychaudhuri, Soumya and Plenge, Robert M}
}
@article {1109526,
	title = {Common variants near FRK/COL10A1 and VEGFA are associated with advanced age-related macular degeneration},
	journal = {Hum Mol Genet},
	volume = {20},
	number = {18},
	year = {2011},
	month = {2011 Sep 15},
	pages = {3699-709},
	abstract = {Despite significant progress in the identification of genetic loci for age-related macular degeneration (AMD), not all of the heritability has been explained. To identify variants which contribute to the remaining genetic susceptibility, we performed the largest meta-analysis of genome-wide association studies to date for advanced AMD. We imputed 6 036 699 single-nucleotide polymorphisms with the 1000 Genomes Project reference genotypes on 2594 cases and 4134 controls with follow-up replication of top signals in 5640 cases and 52 174 controls. We identified two new common susceptibility alleles, rs1999930 on 6q21-q22.3 near FRK/COL10A1 [odds ratio (OR) 0.87; P = 1.1 {\texttimes} 10(-8)] and rs4711751 on 6p12 near VEGFA (OR 1.15; P = 8.7 {\texttimes} 10(-9)). In addition to the two novel loci, 10 previously reported loci in ARMS2/HTRA1 (rs10490924), CFH (rs1061170, and rs1410996), CFB (rs641153), C3 (rs2230199), C2 (rs9332739), CFI (rs10033900), LIPC (rs10468017), TIMP3 (rs9621532) and CETP (rs3764261) were confirmed with genome-wide significant signals in this large study. Loci in the recently reported genes ABCA1 and COL8A1 were also detected with suggestive evidence of association with advanced AMD. The novel variants identified in this study suggest that angiogenesis (VEGFA) and extracellular collagen matrix (FRK/COL10A1) pathways contribute to the development of advanced AMD.},
	keywords = {Case-Control Studies, Cohort Studies, Collagen Type X, European Continental Ancestry Group, Female, Genetic Variation, Genome-Wide Association Study, Genotype, Humans, Macular Degeneration, Male, Neoplasm Proteins, Polymorphism, Single Nucleotide, Protein-Tyrosine Kinases, Vascular Endothelial Growth Factor A},
	issn = {1460-2083},
	doi = {10.1093/hmg/ddr270},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Common+variants+near+FRK\%2FCOL10A1+and+VEGFA+are+associated+with+advanced+age-related+macular+degeneration},
	author = {Yu, Yi and Bhangale, Tushar R and Fagerness, Jesen and Ripke, Stephan and Thorleifsson, Gudmar and Tan, Perciliz L and Souied, Eric H and Richardson, Andrea J and Merriam, Joanna E and Buitendijk, Gabri{\"e}lle H S and Reynolds, Robyn and Raychaudhuri, Soumya and Chin, Kimberly A and Sobrin, Lucia and Evangelou, Evangelos and Lee, Phil H and Lee, Aaron Y and Leveziel, Nicolas and Zack, Donald J and Campochiaro, Betsy and Campochiaro, Peter and Smith, R Theodore and Barile, Gaetano R and Guymer, Robyn H and Hogg, Ruth and Chakravarthy, Usha and Robman, Luba D and Gustafsson, Omar and Sigurdsson, Haraldur and Ortmann, Ward and Behrens, Timothy W and Stefansson, Kari and Uitterlinden, Andr{\'e} G and van Duijn, Cornelia M and Vingerling, Johannes R and Klaver, Caroline C W and Allikmets, Rando and Brantley, Milam A and Baird, Paul N and Katsanis, Nicholas and Thorsteinsdottir, Unnur and Ioannidis, John P A and Daly, Mark J and Graham, Robert R and Seddon, Johanna M}
}
@article {1109516,
	title = {Meta-analysis of genome-wide association studies in celiac disease and rheumatoid arthritis identifies fourteen non-HLA shared loci},
	journal = {PLoS Genet},
	volume = {7},
	number = {2},
	year = {2011},
	month = {2011 Feb},
	pages = {e1002004},
	abstract = {Epidemiology and candidate gene studies indicate a shared genetic basis for celiac disease (CD) and rheumatoid arthritis (RA), but the extent of this sharing has not been systematically explored. Previous studies demonstrate that 6 of the established non-HLA CD and RA risk loci (out of 26 loci for each disease) are shared between both diseases. We hypothesized that there are additional shared risk alleles and that combining genome-wide association study (GWAS) data from each disease would increase power to identify these shared risk alleles. We performed a meta-analysis of two published GWAS on CD (4,533 cases and 10,750 controls) and RA (5,539 cases and 17,231 controls). After genotyping the top associated SNPs in 2,169 CD cases and 2,255 controls, and 2,845 RA cases and 4,944 controls, 8 additional SNPs demonstrated P\&lt;5 {\texttimes} 10(-8) in a combined analysis of all 50,266 samples, including four SNPs that have not been previously confirmed in either disease: rs10892279 near the DDX6 gene (P(combined) =  1.2 {\texttimes} 10(-12)), rs864537 near CD247 (P(combined) =  2.2 {\texttimes} 10(-11)), rs2298428 near UBE2L3 (P(combined) =  2.5 {\texttimes} 10(-10)), and rs11203203 near UBASH3A (P(combined) =  1.1 {\texttimes} 10(-8)). We also confirmed that 4 gene loci previously established in either CD or RA are associated with the other autoimmune disease at combined P\&lt;5 {\texttimes} 10(-8) (SH2B3, 8q24, STAT4, and TRAF1-C5). From the 14 shared gene loci, 7 SNPs showed a genome-wide significant effect on expression of one or more transcripts in the linkage disequilibrium (LD) block around the SNP. These associations implicate antigen presentation and T-cell activation as a shared mechanism of disease pathogenesis and underscore the utility of cross-disease meta-analysis for identification of genetic risk factors with pleiotropic effects between two clinically distinct diseases.},
	keywords = {Alleles, Arthritis, Rheumatoid, Celiac Disease, Genetic Loci, Genome-Wide Association Study, Histocompatibility Antigens, Lymphocyte Activation, Polymorphism, Single Nucleotide, Selection, Genetic, T-Lymphocytes},
	issn = {1553-7404},
	doi = {10.1371/journal.pgen.1002004},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Meta-analysis+of+genome-wide+association+studies+in+celiac+disease+and+rheumatoid+arthritis+identifies+fourteen+non-HLA+shared+loci},
	author = {Zhernakova, Alexandra and Stahl, Eli A and Trynka, Gosia and Raychaudhuri, Soumya and Festen, Eleanora A and Franke, Lude and Westra, Harm-Jan and Fehrmann, Rudolf S N and Kurreeman, Fina A S and Thomson, Brian and Gupta, Namrata and Romanos, Jihane and McManus, Ross and Ryan, Anthony W and Turner, Graham and Brouwer, Elisabeth and Posthumus, Marcel D and Remmers, Elaine F and Tucci, Francesca and Toes, Rene and Grandone, Elvira and Mazzilli, Maria Cristina and Rybak, Anna and Cukrowska, Bozena and Coenen, Marieke Jh and Radstake, Timothy R D J and van Riel, Piet L C M and Li, Yonghong and de Bakker, Paul I W and Gregersen, Peter K and Worthington, Jane and Siminovitch, Katherine A and Klareskog, Lars and Huizinga, Tom W J and Wijmenga, Cisca and Plenge, Robert M}
}
@article {1109511,
	title = {Proteins encoded in genomic regions associated with immune-mediated disease physically interact and suggest underlying biology},
	journal = {PLoS Genet},
	volume = {7},
	number = {1},
	year = {2011},
	month = {2011 Jan 13},
	pages = {e1001273},
	abstract = {Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn{\textquoteright}s disease (CD) GWAS, we build protein-protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease.},
	keywords = {Arthritis, Rheumatoid, Crohn Disease, Diabetes Mellitus, Type 2, Gene Regulatory Networks, Genetic Loci, Genome, Genome-Wide Association Study, Humans},
	issn = {1553-7404},
	doi = {10.1371/journal.pgen.1001273},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Proteins+encoded+in+genomic+regions+associated+with+immune-mediated+disease+physically+interact+and+suggest+underlying+biology},
	author = {Rossin, Elizabeth J and Lage, Kasper and Raychaudhuri, Soumya and Xavier, Ramnik J and Tatar, Diana and Benita, Yair and International Inflammatory Bowel Disease Genetics Constortium and Cotsapas, Chris and Daly, Mark J}
}
@article {1109521,
	title = {Three ulcerative colitis susceptibility loci are associated with primary sclerosing cholangitis and indicate a role for IL2, REL, and CARD9},
	journal = {Hepatology},
	volume = {53},
	number = {6},
	year = {2011},
	month = {2011 Jun},
	pages = {1977-85},
	abstract = {UNLABELLED: Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease characterized by inflammation and fibrosis of the bile ducts. Both environmental and genetic factors contribute to its pathogenesis. To further clarify its genetic background, we investigated susceptibility loci recently identified for ulcerative colitis (UC) in a large cohort of 1,186 PSC patients and 1,748 controls. Single nucleotide polymorphisms (SNPs) tagging 13 UC susceptibility loci were initially genotyped in 854 PSC patients and 1,491 controls from Benelux (331 cases, 735 controls), Germany (265 cases, 368 controls), and Scandinavia (258 cases, 388 controls). Subsequently, a joint analysis was performed with an independent second Scandinavian cohort (332 cases, 257 controls). SNPs at chromosomes 2p16 (P-value 4.12 {\texttimes} 10(-4) ), 4q27 (P-value 4.10 {\texttimes} 10(-5) ), and 9q34 (P-value 8.41 {\texttimes} 10(-4) ) were associated with PSC in the joint analysis after correcting for multiple testing. In PSC patients without inflammatory bowel disease (IBD), SNPs at 4q27 and 9q34 were nominally associated (P \&lt; 0.05). We applied additional in silico analyses to identify likely candidate genes at PSC susceptibility loci. To identify nonrandom, evidence-based links we used GRAIL (Gene Relationships Across Implicated Loci) analysis showing interconnectivity between genes in six out of in total nine PSC-associated regions. Expression quantitative trait analysis from 1,469 Dutch and UK individuals demonstrated that five out of nine SNPs had an effect on cis-gene expression. These analyses prioritized IL2, CARD9, and REL as novel candidates. CONCLUSION: We have identified three UC susceptibility loci to be associated with PSC, harboring the putative candidate genes REL, IL2, and CARD9. These results add to the scarce knowledge on the genetic background of PSC and imply an important role for both innate and adaptive immunological factors.},
	keywords = {Alleles, CARD Signaling Adaptor Proteins, Case-Control Studies, Cholangitis, Sclerosing, Cohort Studies, Colitis, Ulcerative, Genetic Predisposition to Disease, Genotype, Germany, Humans, Interleukin-2, Netherlands, Polymorphism, Single Nucleotide, Proto-Oncogene Proteins c-rel, Quantitative Trait Loci, Scandinavian and Nordic Countries},
	issn = {1527-3350},
	doi = {10.1002/hep.24307},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Three+ulcerative+colitis+susceptibility+loci+are+associated+with+primary+sclerosing+cholangitis+and+indicate+a+role+for+IL2\%2C+REL\%2C+and+CARD9},
	author = {Janse, Marcel and Lamberts, Laetitia E and Franke, Lude and Raychaudhuri, Soumya and Ellinghaus, Eva and Muri Boberg, Kirsten and Melum, Espen and Folseraas, Trine and Schrumpf, Erik and Bergquist, Annika and Bj{\"o}rnsson, Einar and Fu, Jingyuan and Jan Westra, Harm and Groen, Harry J M and Fehrmann, Rudolf S N and Smolonska, Joanna and van den Berg, Leonard H and Ophoff, Roel A and Porte, Robert J and Weism{\"u}ller, Tobias J and Wedemeyer, Jochen and Schramm, Christoph and Sterneck, Martina and G{\"u}nther, Rainer and Braun, Felix and Vermeire, Severine and Henckaerts, Liesbet and Wijmenga, Cisca and Ponsioen, Cyriel Y and Schreiber, Stefan and Karlsen, Tom H and Franke, Andre and Weersma, Rinse K}
}
@article {1001906,
	title = {Fine mapping the TAGAP risk locus in rheumatoid arthritis},
	journal = {Genes Immun},
	volume = {12},
	number = {4},
	year = {2011},
	month = {2011 Jun},
	pages = {314-8},
	abstract = {A common allele at the TAGAP gene locus demonstrates a suggestive, but not conclusive association with risk of rheumatoid arthritis (RA). To fine map the locus, we conducted comprehensive imputation of CEU HapMap single-nucleotide polymorphisms (SNPs) in a genome-wide association study (GWAS) of 5,500 RA cases and 22,621 controls (all of European ancestry). After controlling for population stratification with principal components analysis, the strongest signal of association was to an imputed SNP, rs212389 (P=3.9 {\texttimes} 10(-8), odds ratio=0.87). This SNP remained highly significant upon conditioning on the previous RA risk variant (rs394581, P=2.2 {\texttimes} 10(-5)) or on a SNP previously associated with celiac disease and type I diabetes (rs1738074, P=1.7 {\texttimes} 10(-4)). Our study has refined the TAGAP signal of association to a single haplotype in RA, and in doing so provides conclusive statistical evidence that the TAGAP locus is associated with RA risk. Our study also underscores the utility of comprehensive imputation in large GWAS data sets to fine map disease risk alleles.},
	keywords = {Arthritis, Rheumatoid, Case-Control Studies, Genetic Loci, Genome-Wide Association Study, GTPase-Activating Proteins, Humans, Polymorphism, Single Nucleotide, Risk Factors},
	issn = {1476-5470},
	doi = {10.1038/gene.2011.8},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/21390051},
	author = {Chen, R and Stahl, E A and Kurreeman, F A S and Gregersen, P K and Siminovitch, K A and Worthington, J and Padyukov, L and Raychaudhuri, S and Plenge, R M}
}
@article {1001911,
	title = {Genetic basis of autoantibody positive and negative rheumatoid arthritis risk in a multi-ethnic cohort derived from electronic health records},
	journal = {Am J Hum Genet},
	volume = {88},
	number = {1},
	year = {2011},
	month = {2011 Jan 07},
	pages = {57-69},
	abstract = {Discovering and following up on genetic associations with complex phenotypes require large patient cohorts. This is particularly true for patient cohorts of diverse ancestry and clinically relevant subsets of disease. The ability to mine the electronic health records (EHRs) of patients followed as part of routine clinical care provides a potential opportunity to efficiently identify affected cases and unaffected controls for appropriate-sized genetic studies. Here, we demonstrate proof-of-concept that it is possible to use EHR data linked with biospecimens to establish a multi-ethnic case-control cohort for genetic research of a complex disease, rheumatoid arthritis (RA). In 1,515 EHR-derived RA cases and 1,480 controls matched for both genetic ancestry and disease-specific autoantibodies (anti-citrullinated protein antibodies [ACPA]), we demonstrate that the odds ratios and aggregate genetic risk score (GRS) of known RA risk alleles measured in individuals of European ancestry within our EHR cohort are nearly identical to those derived from a genome-wide association study (GWAS) of 5,539 autoantibody-positive RA cases and 20,169 controls. We extend this approach to other ethnic groups and identify a large overlap in the GRS among individuals of European, African, East Asian, and Hispanic ancestry. We also demonstrate that the distribution of a GRS based on 28 non-HLA risk alleles in ACPA+ cases partially overlaps with ACPA- subgroup of RA cases. Our study demonstrates that the genetic basis of rheumatoid arthritis risk is similar among cases of diverse ancestry divided into subsets based on ACPA status and emphasizes the utility of linking EHR clinical data with biospecimens for genetic studies.},
	keywords = {African Continental Ancestry Group, Arthritis, Rheumatoid, Asian Continental Ancestry Group, Autoantibodies, Case-Control Studies, Cohort Studies, Electronic Health Records, European Continental Ancestry Group, Female, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Hispanic Americans, Humans, Male, Middle Aged, Risk},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2010.12.007},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Genetic+basis+of+autoantibody+positive+and+negative+rheumatoid+arthritis+risk+in+a+multi-ethnic+cohort+derived+from+electronic+health+records},
	author = {Kurreeman, Fina and Liao, Katherine and Chibnik, Lori and Hickey, Brendan and Stahl, Eli and Gainer, Vivian and Li, Gang and Bry, Lynn and Mahan, Scott and Ardlie, Kristin and Thomson, Brian and Szolovits, Peter and Churchill, Susanne and Murphy, Shawn N and Cai, Tianxi and Raychaudhuri, Soumya and Kohane, Isaac and Karlson, Elizabeth and Plenge, Robert M}
}
@article {1001901,
	title = {A rare penetrant mutation in CFH confers high risk of age-related macular degeneration},
	journal = {Nat Genet},
	volume = {43},
	number = {12},
	year = {2011},
	month = {2011 Oct 23},
	pages = {1232-6},
	abstract = {Two common variants in the gene encoding complement factor H (CFH), the Y402H substitution (rs1061170, c.1204C\&gt;T)(1-4) and the intronic rs1410996 SNP(5,6), explain 17\% of age-related macular degeneration (AMD) liability. However, proof for the involvement of CFH, as opposed to a neighboring transcript, and knowledge of the potential mechanism of susceptibility alleles are lacking. Assuming that rare functional variants might provide mechanistic insights, we used genotype data and high-throughput sequencing to discover a rare, high-risk CFH haplotype with a c.3628C\&gt;T mutation that resulted in an R1210C substitution. This allele has been implicated previously in atypical hemolytic uremic syndrome, and it abrogates C-terminal ligand binding(7,8). Genotyping R1210C in 2,423 AMD cases and 1,122 controls demonstrated high penetrance (present in 40 cases versus 1 control, P = 7.0 {\texttimes} 10(-6)) and an association with a 6-year-earlier onset of disease (P = 2.3 {\texttimes} 10(-6)). This result suggests that loss-of-function alleles at CFH are likely to drive AMD risk. This finding represents one of the first instances in which a common complex disease variant has led to the discovery of a rare penetrant mutation.},
	keywords = {Aged, Aged, 80 and over, Case-Control Studies, Complement Factor H, Female, Genetic Predisposition to Disease, Haplotypes, Heterozygote, High-Throughput Nucleotide Sequencing, Humans, Linkage Disequilibrium, Macular Degeneration, Male, Middle Aged, Mutation, Missense, Penetrance, Polymorphism, Single Nucleotide, Principal Component Analysis, Risk Factors, Sequence Analysis, DNA},
	issn = {1546-1718},
	doi = {10.1038/ng.976},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=A+rare+penetrant+mutation+in+CFH+confers+high+risk+of+age-related+macular+degeneration},
	author = {Raychaudhuri, Soumya and Iartchouk, Oleg and Chin, Kimberly and Tan, Perciliz L and Tai, Albert K and Ripke, Stephan and Gowrisankar, Sivakumar and Vemuri, Soumya and Montgomery, Kate and Yu, Yi and Reynolds, Robyn and Zack, Donald J and Campochiaro, Betsy and Campochiaro, Peter and Katsanis, Nicholas and Daly, Mark J and Seddon, Johanna M}
}
@article {1001596,
	title = {Integrating autoimmune risk loci with gene-expression data identifies specific pathogenic immune cell subsets},
	journal = {Am J Hum Genet},
	volume = {89},
	number = {4},
	year = {2011},
	month = {2011 Oct 07},
	pages = {496-506},
	abstract = {Although genome-wide association studies have implicated many individual loci in complex diseases, identifying the exact causal alleles and the cell types within which they act remains greatly challenging. To ultimately understand disease mechanism, researchers must\&nbsp;carefully conceive functional studies in relevant pathogenic cell types to demonstrate the cellular impact of disease-associated genetic variants. This challenge is highlighted in autoimmune diseases, such as rheumatoid arthritis, where any of a broad range of immunological cell types might potentially be impacted by genetic variation to cause disease. To this end, we developed a statistical approach to identify potentially pathogenic cell types in autoimmune diseases by using a gene-expression data set of 223 murine-sorted immune cells from the Immunological Genome Consortium. We found enrichment of transitional B cell genes in systemic lupus erythematosus (p = 5.9\&nbsp;{\texttimes} 10(-6)) and epithelial-associated stimulated dendritic cell genes in Crohn disease (p = 1.6\&nbsp;{\texttimes} 10(-5)). Finally, we demonstrated enrichment of CD4+ effector memory T\&nbsp;cell genes within rheumatoid arthritis loci (p \&lt; 10(-6)). To further validate the role of CD4+ effector memory T\&nbsp;cells within rheumatoid arthritis, we identified 436 loci that were not yet known to be associated with the disease but that had a statistically suggestive association in a recent genome-wide association study (GWAS) meta-analysis (p(GWAS) \&lt; 0.001). Even among these putative loci, we noted a significant enrichment for genes specifically expressed in CD4+ effector memory T\&nbsp;cells (p = 1.25\&nbsp;{\texttimes} 10(-4)). These cell types are primary candidates for future functional studies to reveal the role of risk alleles in autoimmunity. Our approach has application in other phenotypes, outside of autoimmunity, where many loci have been discovered and high-quality cell-type-specific gene expression is available.},
	keywords = {Alleles, Animals, Arthritis, Rheumatoid, Autoimmune Diseases, CD4-Positive T-Lymphocytes, Gene Expression Profiling, Gene Expression Regulation, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Immune System, Mice, Models, Statistical, Polymorphism, Single Nucleotide, Risk},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2011.09.002},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Integrating+autoimmune+risk+loci+with+gene-expression+data+identifies+specific+pathogenic+immune+cell+subsets},
	author = {Hu, Xinli and Kim, Hyun and Stahl, Eli and Plenge, Robert and Daly, Mark and Raychaudhuri, Soumya}
}
@article {1001601,
	title = {Mapping rare and common causal alleles for complex human diseases},
	journal = {Cell},
	volume = {147},
	number = {1},
	year = {2011},
	month = {2011 Sep 30},
	pages = {57-69},
	abstract = {Advances in genotyping and sequencing technologies have revolutionized the genetics of complex disease by locating rare and common variants that influence an individual{\textquoteright}s risk for diseases, such as diabetes, cancers, and psychiatric disorders. However, to capitalize on these data for prevention and therapies requires the identification of causal alleles and a mechanistic understanding for how these variants contribute to the disease. After discussing the strategies currently used to map variants for complex diseases, this Primer explores how variants may be prioritized for follow-up functional studies and the challenges and approaches for assessing the contributions of rare and common variants to disease phenotypes.},
	keywords = {Chromatin Assembly and Disassembly, Chromosome Mapping, Disease, Genetic Predisposition to Disease, Genetic Variation, Genetics, Population, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Quantitative Trait Loci},
	issn = {1097-4172},
	doi = {10.1016/j.cell.2011.09.011},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/21962507},
	author = {Raychaudhuri, Soumya}
}
@article {1001606,
	title = {VIZ-GRAIL: visualizing functional connections across disease loci},
	journal = {Bioinformatics},
	volume = {27},
	number = {11},
	year = {2011},
	month = {2011 Jun 01},
	pages = {1589-90},
	abstract = {MOTIVATION: As disease loci are rapidly discovered, an emerging challenge is to identify common pathways and biological functionality across loci. Such pathways might point to potential disease mechanisms. One strategy is to look for functionally related or interacting genes across genetic loci. Previously, we defined a statistical strategy, Gene Relationships Across Implicated Loci (GRAIL), to identify whether pair-wise gene relationships defined using PubMed text similarity are enriched across loci. Here, we have implemented VIZ-GRAIL, a software tool to display those relationships and to depict the underlying biological patterns. RESULTS: Our tool can seamlessly interact with the GRAIL web site to obtain the results of analyses and create easy to read visual displays. To most clearly display results, VIZ-GRAIL arranges genes and genetic loci to minimize intersecting pair-wise gene connections. VIZ-GRAIL can be easily applied to other types of functional connections, beyond those from GRAIL. This method should help investigators appreciate the presence of potentially important common functions across loci. AVAILABILITY: The GRAIL algorithm is implemented online at http://www.broadinstitute.org/mpg/grail/grail.php. VIZ-GRAIL source-code is at http://www.broadinstitute.org/mpg/grail/vizgrail.html.},
	keywords = {Algorithms, Computer graphics, Disease, Genes, Genetic Loci, Software},
	issn = {1367-4811},
	doi = {10.1093/bioinformatics/btr185},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=VIZ-GRAIL\%3A+visualizing+functional+connections+across+disease+loci},
	author = {Raychaudhuri, Soumya}
}
@article {1109491,
	title = {Accurately assessing the risk of schizophrenia conferred by rare copy-number variation affecting genes with brain function},
	journal = {PLoS Genet},
	volume = {6},
	number = {9},
	year = {2010},
	month = {2010 Sep 09},
	pages = {e1001097},
	abstract = {Investigators have linked rare copy number variation (CNVs) to neuropsychiatric diseases, such as schizophrenia. One hypothesis is that CNV events cause disease by affecting genes with specific brain functions. Under these circumstances, we expect that CNV events in cases should impact brain-function genes more frequently than those events in controls. Previous publications have applied "pathway" analyses to genes within neuropsychiatric case CNVs to show enrichment for brain-functions. While such analyses have been suggestive, they often have not rigorously compared the rates of CNVs impacting genes with brain function in cases to controls, and therefore do not address important confounders such as the large size of brain genes and overall differences in rates and sizes of CNVs. To demonstrate the potential impact of confounders, we genotyped rare CNV events in 2,415 unaffected controls with Affymetrix 6.0; we then applied standard pathway analyses using four sets of brain-function genes and observed an apparently highly significant enrichment for each set. The enrichment is simply driven by the large size of brain-function genes. Instead, we propose a case-control statistical test, cnv-enrichment-test, to compare the rate of CNVs impacting specific gene sets in cases versus controls. With simulations, we demonstrate that cnv-enrichment-test is robust to case-control differences in CNV size, CNV rate, and systematic differences in gene size. Finally, we apply cnv-enrichment-test to rare CNV events published by the International Schizophrenia Consortium (ISC). This approach reveals nominal evidence of case-association in neuronal-activity and the learning gene sets, but not the other two examined gene sets. The neuronal-activity genes have been associated in a separate set of schizophrenia cases and controls; however, testing in independent samples is necessary to definitively confirm this association. Our method is implemented in the PLINK software package.},
	keywords = {Brain, Case-Control Studies, Computer Simulation, Databases, Genetic, DNA Copy Number Variations, Gene Deletion, Genes, Genetic Predisposition to Disease, Genome, Human, Humans, Models, Genetic, Risk Assessment, Schizophrenia},
	issn = {1553-7404},
	doi = {10.1371/journal.pgen.1001097},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Accurately+assessing+the+risk+of+schizophrenia+conferred+by+rare+copy-number+variation+affecting+genes+with+brain+function},
	author = {Raychaudhuri, Soumya and Korn, Joshua M and McCarroll, Steven A and International Schizophrenia Consortium and Altshuler, David and Sklar, Pamela and Purcell, Shaun and Daly, Mark J}
}
@article {1109501,
	title = {Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index},
	journal = {Nat Genet},
	volume = {42},
	number = {11},
	year = {2010},
	month = {2010 Nov},
	pages = {937-48},
	abstract = {Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and \~{} 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P \&lt; 5 {\texttimes} 10$^{-}$$^{8}$), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.},
	keywords = {Body Height, Body Mass Index, Body Size, Body Weight, Chromosome Mapping, European Continental Ancestry Group, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Obesity, Polymorphism, Single Nucleotide},
	issn = {1546-1718},
	doi = {10.1038/ng.686},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/20935630},
	author = {Speliotes, Elizabeth K and Willer, Cristen J and Berndt, Sonja I and Monda, Keri L and Thorleifsson, Gudmar and Jackson, Anne U and Lango Allen, Hana and Lindgren, Cecilia M and Luan, Jian{\textquoteright}an and M{\"a}gi, Reedik and Randall, Joshua C and Vedantam, Sailaja and Winkler, Thomas W and Qi, Lu and Workalemahu, Tsegaselassie and Heid, Iris M and Steinthorsdottir, Valgerdur and Stringham, Heather M and Weedon, Michael N and Wheeler, Eleanor and Wood, Andrew R and Ferreira, Teresa and Weyant, Robert J and Segr{\`e}, Ayellet V and Estrada, Karol and Liang, Liming and James Nemesh and Park, Ju-Hyun and Gustafsson, Stefan and Kilpel{\"a}inen, Tuomas O and Yang, Jian and Bouatia-Naji, Nabila and Esko, T{\~o}nu and Feitosa, Mary F and Kutalik, Zolt{\'a}n and Mangino, Massimo and Raychaudhuri, Soumya and Scherag, Andre and Smith, Albert Vernon and Welch, Ryan and Zhao, Jing Hua and Aben, Katja K and Absher, Devin M and Amin, Najaf and Dixon, Anna L and Fisher, Eva and Glazer, Nicole L and Goddard, Michael E and Heard-Costa, Nancy L and Hoesel, Volker and Hottenga, Jouke-Jan and Johansson, Asa and Johnson, Toby and Ketkar, Shamika and Lamina, Claudia and Li, Shengxu and Moffatt, Miriam F and Myers, Richard H and Narisu, Narisu and Perry, John R B and Peters, Marjolein J and Preuss, Michael and Ripatti, Samuli and Rivadeneira, Fernando and Sandholt, Camilla and Scott, Laura J and Timpson, Nicholas J and Tyrer, Jonathan P and van Wingerden, Sophie and Watanabe, Richard M and White, Charles C and Wiklund, Fredrik and Barlassina, Christina and Chasman, Daniel I and Cooper, Matthew N and Jansson, John-Olov and Lawrence, Robert W and Pellikka, Niina and Prokopenko, Inga and Shi, Jianxin and Thiering, Elisabeth and Alavere, Helene and Alibrandi, Maria T S and Almgren, Peter and Arnold, Alice M and Aspelund, Thor and Atwood, Larry D and Balkau, Beverley and Balmforth, Anthony J and Bennett, Amanda J and Ben-Shlomo, Yoav and Bergman, Richard N and Bergmann, Sven and Biebermann, Heike and Blakemore, Alexandra I F and Boes, Tanja and Bonnycastle, Lori L and Bornstein, Stefan R and Brown, Morris J and Buchanan, Thomas A and Busonero, Fabio and Campbell, Harry and Cappuccio, Francesco P and Cavalcanti-Proen{\c c}a, Christine and Chen, Yii-Der Ida and Chen, Chih-Mei and Chines, Peter S and Clarke, Robert and Coin, Lachlan and Connell, John and Day, Ian N M and den Heijer, Martin and Duan, Jubao and Ebrahim, Shah and Elliott, Paul and Elosua, Roberto and Eiriksdottir, Gudny and Erdos, Michael R and Eriksson, Johan G and Facheris, Maurizio F and Felix, Stephan B and Fischer-Posovszky, Pamela and Folsom, Aaron R and Friedrich, Nele and Freimer, Nelson B and Fu, Mao and Gaget, Stefan and Gejman, Pablo V and Geus, Eco J C and Gieger, Christian and Gjesing, Anette P and Goel, Anuj and Goyette, Philippe and Grallert, Harald and Gr{\"a}ssler, J{\"u}rgen and Greenawalt, Danielle M and Groves, Christopher J and Gudnason, Vilmundur and Guiducci, Candace and Hartikainen, Anna-Liisa and Hassanali, Neelam and Hall, Alistair S and Havulinna, Aki S and Hayward, Caroline and Heath, Andrew C and Hengstenberg, Christian and Hicks, Andrew A and Hinney, Anke and Hofman, Albert and Homuth, Georg and Hui, Jennie and Igl, Wilmar and Iribarren, Carlos and Isomaa, Bo and Jacobs, Kevin B and Jarick, Ivonne and Jewell, Elizabeth and John, Ulrich and J{\o}rgensen, Torben and Jousilahti, Pekka and Jula, Antti and Kaakinen, Marika and Kajantie, Eero and Kaplan, Lee M and Kathiresan, Sekar and Kettunen, Johannes and Kinnunen, Leena and Knowles, Joshua W and Kolcic, Ivana and K{\"o}nig, Inke R and Koskinen, Seppo and Kovacs, Peter and Kuusisto, Johanna and Kraft, Peter and Kval{\o}y, Kirsti and Laitinen, Jaana and Lantieri, Olivier and Lanzani, Chiara and Launer, Lenore J and Lecoeur, Cecile and Lehtim{\"a}ki, Terho and Lettre, Guillaume and Liu, Jianjun and Lokki, Marja-Liisa and Lorentzon, Mattias and Luben, Robert N and Ludwig, Barbara and MAGIC and Manunta, Paolo and Marek, Diana and Marre, Michel and Martin, Nicholas G and McArdle, Wendy L and McCarthy, Anne and McKnight, Barbara and Meitinger, Thomas and Melander, Olle and Meyre, David and Midthjell, Kristian and Montgomery, Grant W and Morken, Mario A and Morris, Andrew P and Mulic, Rosanda and Ngwa, Julius S and Nelis, Mari and Neville, Matt J and Nyholt, Dale R and O{\textquoteright}Donnell, Christopher J and O{\textquoteright}Rahilly, Stephen and Ong, Ken K and Oostra, Ben and Par{\'e}, Guillaume and Parker, Alex N and Perola, Markus and Pichler, Irene and Pietil{\"a}inen, Kirsi H and Platou, Carl G P and Polasek, Ozren and Pouta, Anneli and Rafelt, Suzanne and Raitakari, Olli and Rayner, Nigel W and Ridderstr{\r a}le, Martin and Rief, Winfried and Ruokonen, Aimo and Robertson, Neil R and Rzehak, Peter and Salomaa, Veikko and Sanders, Alan R and Sandhu, Manjinder S and Sanna, Serena and Saramies, Jouko and Savolainen, Markku J and Scherag, Susann and Schipf, Sabine and Schreiber, Stefan and Schunkert, Heribert and Silander, Kaisa and Sinisalo, Juha and Siscovick, David S and Smit, Jan H and Soranzo, Nicole and Sovio, Ulla and Stephens, Jonathan and Surakka, Ida and Swift, Amy J and Tammesoo, Mari-Liis and Tardif, Jean-Claude and Teder-Laving, Maris and Teslovich, Tanya M and Thompson, John R and Thomson, Brian and T{\"o}njes, Anke and Tuomi, Tiinamaija and van Meurs, Joyce B J and van Ommen, Gert-Jan and Vatin, Vincent and Viikari, Jorma and Visvikis-Siest, Sophie and Vitart, Veronique and Vogel, Carla I G and Voight, Benjamin F and Waite, Lindsay L and Wallaschofski, Henri and Walters, G Bragi and Widen, Elisabeth and Wiegand, Susanna and Wild, Sarah H and Willemsen, Gonneke and Witte, Daniel R and Witteman, Jacqueline C and Xu, Jianfeng and Zhang, Qunyuan and Zgaga, Lina and Ziegler, Andreas and Zitting, Paavo and Beilby, John P and Farooqi, I Sadaf and Hebebrand, Johannes and Huikuri, Heikki V and James, Alan L and K{\"a}h{\"o}nen, Mika and Levinson, Douglas F and Macciardi, Fabio and Nieminen, Markku S and Ohlsson, Claes and Palmer, Lyle J and Ridker, Paul M and Stumvoll, Michael and Beckmann, Jacques S and Boeing, Heiner and Boerwinkle, Eric and Boomsma, Dorret I and Caulfield, Mark J and Chanock, Stephen J and Collins, Francis S and Cupples, L Adrienne and Smith, George Davey and Erdmann, Jeanette and Froguel, Philippe and Gr{\"o}nberg, Henrik and Gyllensten, Ulf and Hall, Per and Hansen, Torben and Harris, Tamara B and Hattersley, Andrew T and Hayes, Richard B and Heinrich, Joachim and Hu, Frank B and Hveem, Kristian and Illig, Thomas and Jarvelin, Marjo-Riitta and Kaprio, Jaakko and Karpe, Fredrik and Khaw, Kay-Tee and Kiemeney, Lambertus A and Krude, Heiko and Laakso, Markku and Lawlor, Debbie A and Metspalu, Andres and Munroe, Patricia B and Ouwehand, Willem H and Pedersen, Oluf and Penninx, Brenda W and Peters, Annette and Pramstaller, Peter P and Quertermous, Thomas and Reinehr, Thomas and Rissanen, Aila and Rudan, Igor and Samani, Nilesh J and Schwarz, Peter E H and Shuldiner, Alan R and Spector, Timothy D and Tuomilehto, Jaakko and Uda, Manuela and Uitterlinden, Andr{\'e} and Valle, Timo T and Wabitsch, Martin and Waeber, G{\'e}rard and Wareham, Nicholas J and Watkins, Hugh and Procardis Consortium and Wilson, James F and Wright, Alan F and Zillikens, M Carola and Chatterjee, Nilanjan and McCarroll, Steven A and Purcell, Shaun and Schadt, Eric E and Visscher, Peter M and Assimes, Themistocles L and Borecki, Ingrid B and Deloukas, Panos and Fox, Caroline S and Groop, Leif C and Haritunians, Talin and Hunter, David J and Kaplan, Robert C and Mohlke, Karen L and O{\textquoteright}Connell, Jeffrey R and Peltonen, Leena and Schlessinger, David and Strachan, David P and van Duijn, Cornelia M and Wichmann, H-Erich and Frayling, Timothy M and Thorsteinsdottir, Unnur and Abecasis, Gon{\c c}alo R and Barroso, In{\^e}s and Boehnke, Michael and Stefansson, Kari and North, Kari E and McCarthy, Mark I and Hirschhorn, Joel N and Ingelsson, Erik and Loos, Ruth J F}
}
@article {1109471,
	title = {Association of CD40 with rheumatoid arthritis confirmed in a large UK case-control study},
	journal = {Ann Rheum Dis},
	volume = {69},
	number = {5},
	year = {2010},
	month = {2010 May},
	pages = {813-6},
	abstract = {OBJECTIVE: A recent meta-analysis of published genome-wide association studies (GWAS) in populations of European descent reported novel associations of markers mapping to the CD40, CCL21 and CDK6 genes with rheumatoid arthritis (RA) susceptibility while a large-scale, case-control association study in a Japanese population identified association with multiple single nucleotide polymorphisms (SNPs) in the CD244 gene. The aim of the current study was to validate these potential RA susceptibility markers in a UK population. METHODS: A total of 4 SNPs (rs4810485 in CD40, rs2812378 in CCL21, rs42041 in CDK6 and rs6682654 in CD244) were genotyped in a UK cohort comprising 3962 UK patients with RA and 3531 healthy controls using the Sequenom iPlex platform. Genotype counts in patients and controls were analysed with the chi(2) test using Stata. RESULTS: Association to the CD40 gene was robustly replicated (p=2 x 10(-4), OR 0.86, 95\% CI 0.79 to 0.93) and modest evidence was found for association with the CCL21 locus (p=0.04, OR 1.08, 95\% CI 1.01 to 1.16). However, there was no evidence for association of rs42041 (CDK6) and rs6682654 (CD244) with RA susceptibility in this UK population. Following a meta-analysis including the original data, association to CD40 was confirmed (p=7.8 x 10(-8), OR 0.87 (95\% CI 0.83 to 0.92). CONCLUSION: In this large UK cohort, strong association of the CD40 gene with susceptibility to RA was found, and weaker evidence for association with RA in the CCL21 locus.},
	keywords = {Antigens, CD40, Arthritis, Rheumatoid, Case-Control Studies, Chemokine CCL21, Cyclin-Dependent Kinase 6, Female, Gene Frequency, Genetic Markers, Genetic Predisposition to Disease, Genotype, Humans, Male, Polymorphism, Single Nucleotide},
	issn = {1468-2060},
	doi = {10.1136/ard.2009.109579},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Association+of+CD40+with+rheumatoid+arthritis+confirmed+in+a+large+UK+case-control+study},
	author = {Orozco, Gisela and Eyre, Steve and Hinks, Anne and Ke, Xiayi and Wellcome Trust Case Control consortium YEAR Consortium and Wilson, Anthony G and Bax, Deborah E and Morgan, Ann W and Emery, Paul and Steer, Sophia and Hocking, Lynne and Reid, David M and Wordsworth, Paul and Harrison, Pille and Thomson, Wendy and Barton, Anne and Worthington, Jane}
}
@article {1109486,
	title = {Associations of CFHR1-CFHR3 deletion and a CFH SNP to age-related macular degeneration are not independent},
	journal = {Nat Genet},
	volume = {42},
	number = {7},
	year = {2010},
	month = {2010 Jul},
	pages = {553-5; author reply 555-6},
	keywords = {Blood Proteins, Complement C3b Inactivator Proteins, Complement Factor H, Gene Deletion, Gene Frequency, Genetic Predisposition to Disease, Genotype, Haplotypes, Humans, Logistic Models, Macular Degeneration, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors},
	issn = {1546-1718},
	doi = {10.1038/ng0710-553},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Associations+of+CFHR1-CFHR3+deletion+and+a+CFH+SNP+to+age-related+macular+degeneration+are+not+independent},
	author = {Raychaudhuri, Soumya and Ripke, Stephan and Li, Mingyao and Neale, Benjamin M and Fagerness, Jesen and Reynolds, Robyn and Sobrin, Lucia and Swaroop, Anand and Abecasis, Gon{\c c}alo and Seddon, Johanna M and Daly, Mark J}
}
@article {1109476,
	title = {Cumulative association of 22 genetic variants with seropositive rheumatoid arthritis risk},
	journal = {Ann Rheum Dis},
	volume = {69},
	number = {6},
	year = {2010},
	month = {2010 Jun},
	pages = {1077-85},
	abstract = {BACKGROUND: Recent discoveries of risk alleles have made it possible to define genetic risk profiles for patients with rheumatoid arthritis (RA). This study examined whether a cumulative score based on 22 validated genetic risk alleles for seropositive RA would identify high-risk, asymptomatic individuals who might benefit from preventive interventions. METHODS: Eight human leucocyte antigen (HLA) alleles and 14 single-nucleotide polymorphisms representing 13 validated RA risk loci were genotyped among 289 white seropositive cases and 481 controls from the US Nurses{\textquoteright} Health Studies (NHS) and 629 white cyclic-citrullinated peptide antibody-positive cases and 623 controls from the Swedish Epidemiologic Investigation of Rheumatoid Arthritis (EIRA). A weighted genetic risk score (GRS) was created, in which the weight for each risk allele is the log of the published odds ratio (OR). Logistic regression was used to study associations with incident RA. Area under the curve (AUC) statistics were compared from a clinical-only model and clinical plus genetic model in each cohort. RESULTS: Patients with GRS \&gt;1.25 SD of the mean had a significantly higher OR of seropositive RA in both NHS (OR=2.9, 95\%CI 1.8 to 4.6) and EIRA (OR 3.4, 95\% CI 2.3 to 5.0) referent to the population average. In NHS, the AUC for a clinical model was 0.57 and for a clinical plus genetic model was 0.66, and in EIRA was 0.63 and 0.75, respectively. CONCLUSION: The combination of 22 risk alleles into a weighted GRS significantly stratifies individuals for RA risk beyond clinical risk factors alone. Given the low incidence of RA, the clinical utility of a weighted GRS is limited in the general population.},
	keywords = {Adult, Aged, Arthritis, Rheumatoid, Autoantibodies, Epidemiologic Methods, Female, Gene Frequency, Genetic Predisposition to Disease, Genotype, Humans, Male, Middle Aged, Peptides, Cyclic, Polymorphism, Single Nucleotide},
	issn = {1468-2060},
	doi = {10.1136/ard.2009.120170},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Cumulative+association+of+22+genetic+variants+with+seropositive+rheumatoid+arthritis+risk},
	author = {Karlson, Elizabeth W and Chibnik, Lori B and Kraft, Peter and Cui, Jing and Keenan, Brendan T and Ding, Bo and Raychaudhuri, Souyma and Klareskog, Lars and Alfredsson, Lars and Plenge, Robert M}
}
@article {1109466,
	title = {Genome-wide association study of advanced age-related macular degeneration identifies a role of the hepatic lipase gene (LIPC)},
	journal = {Proc Natl Acad Sci U S A},
	volume = {107},
	number = {16},
	year = {2010},
	month = {2010 Apr 20},
	pages = {7395-400},
	abstract = {Advanced age-related macular degeneration (AMD) is the leading cause of late onset blindness. We present results of a genome-wide association study of 979 advanced AMD cases and 1,709 controls using the Affymetrix 6.0 platform with replication in seven additional cohorts (totaling 5,789 unrelated cases and 4,234 unrelated controls). We also present a comprehensive analysis of copy-number variations and polymorphisms for AMD. Our discovery data implicated the association between AMD and a variant in the hepatic lipase gene (LIPC) in the high-density lipoprotein cholesterol (HDL) pathway (discovery P = 4.53e-05 for rs493258). Our LIPC association was strongest for a functional promoter variant, rs10468017, (P = 1.34e-08), that influences LIPC expression and serum HDL levels with a protective effect of the minor T allele (HDL increasing) for advanced wet and dry AMD. The association we found with LIPC was corroborated by the Michigan/Penn/Mayo genome-wide association study; the locus near the tissue inhibitor of metalloproteinase 3 was corroborated by our replication cohort for rs9621532 with P = 3.71e-09. We observed weaker associations with other HDL loci (ABCA1, P = 9.73e-04; cholesterylester transfer protein, P = 1.41e-03; FADS1-3, P = 2.69e-02). Based on a lack of consistent association between HDL increasing alleles and AMD risk, the LIPC association may not be the result of an effect on HDL levels, but it could represent a pleiotropic effect of the same functional component. Results implicate different biologic pathways than previously reported and provide new avenues for prevention and treatment of AMD.},
	keywords = {Alleles, Case-Control Studies, Cholesterol, HDL, Gene Expression Regulation, Genome-Wide Association Study, Genotype, Humans, Lipase, Lipids, Macular Degeneration, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, Reverse Transcriptase Polymerase Chain Reaction, Risk, Tissue Inhibitor of Metalloproteinase-3},
	issn = {1091-6490},
	doi = {10.1073/pnas.0912019107},
	url = {Genome-wide association study of advanced age-related macular degeneration identifies a role of the hepatic lipase gene (LIPC)},
	author = {Neale, Benjamin M and Fagerness, Jesen and Reynolds, Robyn and Sobrin, Lucia and Parker, Margaret and Raychaudhuri, Soumya and Tan, Perciliz L and Oh, Edwin C and Merriam, Joanna E and Souied, Eric and Bernstein, Paul S and Li, Binxing and Frederick, Jeanne M and Zhang, Kang and Brantley, Milam A and Lee, Aaron Y and Zack, Donald J and Campochiaro, Betsy and Campochiaro, Peter and Ripke, Stephan and Smith, R Theodore and Barile, Gaetano R and Katsanis, Nicholas and Allikmets, Rando and Daly, Mark J and Seddon, Johanna M}
}
@article {1109506,
	title = {Genome-wide meta-analysis increases to 71 the number of confirmed Crohn{\textquoteright}s disease susceptibility loci},
	journal = {Nat Genet},
	volume = {42},
	number = {12},
	year = {2010},
	month = {2010 Dec},
	pages = {1118-25},
	abstract = {We undertook a meta-analysis of six Crohn{\textquoteright}s disease genome-wide association studies (GWAS) comprising 6,333 affected individuals (cases) and 15,056 controls and followed up the top association signals in 15,694 cases, 14,026 controls and 414 parent-offspring trios. We identified 30 new susceptibility loci meeting genome-wide significance (P \&lt; 5 {\texttimes} 10$^{-}$$^{8}$). A series of in silico analyses highlighted particular genes within these loci and, together with manual curation, implicated functionally interesting candidate genes including SMAD3, ERAP2, IL10, IL2RA, TYK2, FUT2, DNMT3A, DENND1B, BACH2 and TAGAP. Combined with previously confirmed loci, these results identify 71 distinct loci with genome-wide significant evidence for association with Crohn{\textquoteright}s disease.},
	keywords = {Computational Biology, Crohn Disease, Genetic Linkage, Genetic Loci, Genetic Predisposition to Disease, Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, Reproducibility of Results},
	issn = {1546-1718},
	doi = {10.1038/ng.717},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Genome-wide+meta-analysis+increases+to+71+the+number+of+confirmed+Crohn\%27s+disease+susceptibility+loci},
	author = {Franke, Andre and McGovern, Dermot P B and Barrett, Jeffrey C and Kai Wang and Radford-Smith, Graham L and Ahmad, Tariq and Lees, Charlie W and Balschun, Tobias and Lee, James and Roberts, Rebecca and Anderson, Carl A and Bis, Joshua C and Bumpstead, Suzanne and Ellinghaus, David and Festen, Eleonora M and Georges, Michel and Green, Todd and Haritunians, Talin and Jostins, Luke and Latiano, Anna and Mathew, Christopher G and Montgomery, Grant W and Prescott, Natalie J and Raychaudhuri, Soumya and Rotter, Jerome I and Schumm, Philip and Sharma, Yashoda and Simms, Lisa A and Taylor, Kent D and Whiteman, David and Wijmenga, Cisca and Baldassano, Robert N and Barclay, Murray and Bayless, Theodore M and Brand, Stephan and B{\"u}ning, Carsten and Cohen, Albert and Colombel, Jean-Frederick and Cottone, Mario and Stronati, Laura and Denson, Ted and De Vos, Martine and D{\textquoteright}Inca, Renata and Dubinsky, Marla and Edwards, Cathryn and Florin, Tim and Franchimont, Denis and Gearry, Richard and Glas, J{\"u}rgen and Van Gossum, Andre and Guthery, Stephen L and Halfvarson, Jonas and Verspaget, Hein W and Hugot, Jean-Pierre and Karban, Amir and Laukens, Debby and Lawrance, Ian and Lemann, Marc and Levine, Arie and Libioulle, Cecile and Louis, Edouard and Mowat, Craig and Newman, William and Pan{\'e}s, Juli{\'a}n and Phillips, Anne and Proctor, Deborah D and Regueiro, Miguel and Russell, Richard and Rutgeerts, Paul and Sanderson, Jeremy and Sans, Miquel and Seibold, Frank and Steinhart, A Hillary and Stokkers, Pieter C F and Torkvist, Leif and Kullak-Ublick, Gerd and Wilson, David and Walters, Thomas and Targan, Stephan R and Brant, Steven R and Rioux, John D and D{\textquoteright}Amato, Mauro and Weersma, Rinse K and Kugathasan, Subra and Griffiths, Anne M and Mansfield, John C and Vermeire, Severine and Duerr, Richard H and Silverberg, Mark S and Satsangi, Jack and Schreiber, Stefan and Cho, Judy H and Annese, Vito and Hakonarson, Hakon and Daly, Mark J and Parkes, Miles}
}
@article {1109496,
	title = {Hundreds of variants clustered in genomic loci and biological pathways affect human height},
	journal = {Nature},
	volume = {467},
	number = {7317},
	year = {2010},
	month = {2010 Oct 14},
	pages = {832-8},
	abstract = {Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P \&lt; 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10\% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16\% of phenotypic variation (approximately 20\% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.},
	keywords = {Body Height, Chromosomes, Human, Pair 3, Genetic Loci, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Metabolic Networks and Pathways, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide},
	issn = {1476-4687},
	doi = {10.1038/nature09410},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Hundreds+of+variants+clustered+in+genomic+loci+and+biological+pathways+affect+human+height},
	author = {Lango Allen, Hana and Estrada, Karol and Lettre, Guillaume and Berndt, Sonja I and Weedon, Michael N and Rivadeneira, Fernando and Willer, Cristen J and Jackson, Anne U and Vedantam, Sailaja and Raychaudhuri, Soumya and Ferreira, Teresa and Wood, Andrew R and Weyant, Robert J and Segr{\`e}, Ayellet V and Speliotes, Elizabeth K and Wheeler, Eleanor and Soranzo, Nicole and Park, Ju-Hyun and Yang, Jian and Gudbjartsson, Daniel and Heard-Costa, Nancy L and Randall, Joshua C and Qi, Lu and Smith, Albert Vernon and M{\"a}gi, Reedik and Pastinen, Tomi and Liang, Liming and Heid, Iris M and Luan, Jian{\textquoteright}an and Thorleifsson, Gudmar and Winkler, Thomas W and Goddard, Michael E and Sin Lo, Ken and Palmer, Cameron and Workalemahu, Tsegaselassie and Aulchenko, Yurii S and Johansson, Asa and Zillikens, M Carola and Feitosa, Mary F and Esko, T{\~o}nu and Johnson, Toby and Ketkar, Shamika and Kraft, Peter and Mangino, Massimo and Prokopenko, Inga and Absher, Devin and Albrecht, Eva and Ernst, Florian and Glazer, Nicole L and Hayward, Caroline and Hottenga, Jouke-Jan and Jacobs, Kevin B and Knowles, Joshua W and Kutalik, Zolt{\'a}n and Monda, Keri L and Polasek, Ozren and Preuss, Michael and Rayner, Nigel W and Robertson, Neil R and Steinthorsdottir, Valgerdur and Tyrer, Jonathan P and Voight, Benjamin F and Wiklund, Fredrik and Xu, Jianfeng and Zhao, Jing Hua and Nyholt, Dale R and Pellikka, Niina and Perola, Markus and Perry, John R B and Surakka, Ida and Tammesoo, Mari-Liis and Altmaier, Elizabeth L and Amin, Najaf and Aspelund, Thor and Bhangale, Tushar and Boucher, Gabrielle and Chasman, Daniel I and Chen, Constance and Coin, Lachlan and Cooper, Matthew N and Dixon, Anna L and Gibson, Quince and Grundberg, Elin and Hao, Ke and Juhani Junttila, M and Kaplan, Lee M and Kettunen, Johannes and K{\"o}nig, Inke R and Kwan, Tony and Lawrence, Robert W and Levinson, Douglas F and Lorentzon, Mattias and McKnight, Barbara and Morris, Andrew P and M{\"u}ller, Martina and Suh Ngwa, Julius and Purcell, Shaun and Rafelt, Suzanne and Salem, Rany M and Salvi, Erika and Sanna, Serena and Shi, Jianxin and Sovio, Ulla and Thompson, John R and Turchin, Michael C and Vandenput, Liesbeth and Verlaan, Dominique J and Vitart, Veronique and White, Charles C and Ziegler, Andreas and Almgren, Peter and Balmforth, Anthony J and Campbell, Harry and Citterio, Lorena and De Grandi, Alessandro and Dominiczak, Anna and Duan, Jubao and Elliott, Paul and Elosua, Roberto and Eriksson, Johan G and Freimer, Nelson B and Geus, Eco J C and Glorioso, Nicola and Haiqing, Shen and Hartikainen, Anna-Liisa and Havulinna, Aki S and Hicks, Andrew A and Hui, Jennie and Igl, Wilmar and Illig, Thomas and Jula, Antti and Kajantie, Eero and Kilpel{\"a}inen, Tuomas O and Koiranen, Markku and Kolcic, Ivana and Koskinen, Seppo and Kovacs, Peter and Laitinen, Jaana and Liu, Jianjun and Lokki, Marja-Liisa and Marusic, Ana and Maschio, Andrea and Meitinger, Thomas and Mulas, Antonella and Par{\'e}, Guillaume and Parker, Alex N and Peden, John F and Petersmann, Astrid and Pichler, Irene and Pietil{\"a}inen, Kirsi H and Pouta, Anneli and Ridderstr{\r a}le, Martin and Rotter, Jerome I and Sambrook, Jennifer G and Sanders, Alan R and Schmidt, Carsten Oliver and Sinisalo, Juha and Smit, Jan H and Stringham, Heather M and Bragi Walters, G and Widen, Elisabeth and Wild, Sarah H and Willemsen, Gonneke and Zagato, Laura and Zgaga, Lina and Zitting, Paavo and Alavere, Helene and Farrall, Martin and McArdle, Wendy L and Nelis, Mari and Peters, Marjolein J and Ripatti, Samuli and van Meurs, Joyce B J and Aben, Katja K and Ardlie, Kristin G and Beckmann, Jacques S and Beilby, John P and Bergman, Richard N and Bergmann, Sven and Collins, Francis S and Cusi, Daniele and den Heijer, Martin and Eiriksdottir, Gudny and Gejman, Pablo V and Hall, Alistair S and Hamsten, Anders and Huikuri, Heikki V and Iribarren, Carlos and K{\"a}h{\"o}nen, Mika and Kaprio, Jaakko and Kathiresan, Sekar and Kiemeney, Lambertus and Kocher, Thomas and Launer, Lenore J and Lehtim{\"a}ki, Terho and Melander, Olle and Mosley, Tom H and Musk, Arthur W and Nieminen, Markku S and O{\textquoteright}Donnell, Christopher J and Ohlsson, Claes and Oostra, Ben and Palmer, Lyle J and Raitakari, Olli and Ridker, Paul M and Rioux, John D and Rissanen, Aila and Rivolta, Carlo and Schunkert, Heribert and Shuldiner, Alan R and Siscovick, David S and Stumvoll, Michael and T{\"o}njes, Anke and Tuomilehto, Jaakko and van Ommen, Gert-Jan and Viikari, Jorma and Heath, Andrew C and Martin, Nicholas G and Montgomery, Grant W and Province, Michael A and Kayser, Manfred and Arnold, Alice M and Atwood, Larry D and Boerwinkle, Eric and Chanock, Stephen J and Deloukas, Panos and Gieger, Christian and Gr{\"o}nberg, Henrik and Hall, Per and Hattersley, Andrew T and Hengstenberg, Christian and Hoffman, Wolfgang and Lathrop, G Mark and Salomaa, Veikko and Schreiber, Stefan and Uda, Manuela and Waterworth, Dawn and Wright, Alan F and Assimes, Themistocles L and Barroso, In{\^e}s and Hofman, Albert and Mohlke, Karen L and Boomsma, Dorret I and Caulfield, Mark J and Cupples, L Adrienne and Erdmann, Jeanette and Fox, Caroline S and Gudnason, Vilmundur and Gyllensten, Ulf and Harris, Tamara B and Hayes, Richard B and Jarvelin, Marjo-Riitta and Mooser, Vincent and Munroe, Patricia B and Ouwehand, Willem H and Penninx, Brenda W and Pramstaller, Peter P and Quertermous, Thomas and Rudan, Igor and Samani, Nilesh J and Spector, Timothy D and V{\"o}lzke, Henry and Watkins, Hugh and Wilson, James F and Groop, Leif C and Haritunians, Talin and Hu, Frank B and Kaplan, Robert C and Metspalu, Andres and North, Kari E and Schlessinger, David and Wareham, Nicholas J and Hunter, David J and O{\textquoteright}Connell, Jeffrey R and Strachan, David P and Wichmann, H-Erich and Borecki, Ingrid B and van Duijn, Cornelia M and Schadt, Eric E and Thorsteinsdottir, Unnur and Peltonen, Leena and Uitterlinden, Andr{\'e} G and Visscher, Peter M and Chatterjee, Nilanjan and Loos, Ruth J F and Boehnke, Michael and McCarthy, Mark I and Ingelsson, Erik and Lindgren, Cecilia M and Abecasis, Gon{\c c}alo R and Stefansson, Kari and Frayling, Timothy M and Hirschhorn, Joel N}
}
@article {1109461,
	title = {The landscape of somatic copy-number alteration across human cancers},
	journal = {Nature},
	volume = {463},
	number = {7283},
	year = {2010},
	month = {2010 Feb 18},
	pages = {899-905},
	abstract = {A powerful way to discover key genes with causal roles in oncogenesis is to identify genomic regions that undergo frequent alteration in human cancers. Here we present high-resolution analyses of somatic copy-number alterations (SCNAs) from 3,131 cancer specimens, belonging largely to 26 histological types. We identify 158 regions of focal SCNA that are altered at significant frequency across several cancer types, of which 122 cannot be explained by the presence of a known cancer target gene located within these regions. Several gene families are enriched among these regions of focal SCNA, including the BCL2 family of apoptosis regulators and the NF-kappaBeta pathway. We show that cancer cells containing amplifications surrounding the MCL1 and BCL2L1 anti-apoptotic genes depend on the expression of these genes for survival. Finally, we demonstrate that a large majority of SCNAs identified in individual cancer types are present in several cancer types.},
	keywords = {Apoptosis, bcl-X Protein, Cell Line, Tumor, Cell Survival, DNA Copy Number Variations, Gene Amplification, Gene Dosage, Genomics, Humans, Multigene Family, Myeloid Cell Leukemia Sequence 1 Protein, Neoplasms, Proto-Oncogene Proteins c-bcl-2, Signal Transduction},
	issn = {1476-4687},
	doi = {10.1038/nature08822},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=The+landscape+of+somatic+copy-number+alteration+across+human+cancers},
	author = {Beroukhim, Rameen and Mermel, Craig H and Porter, Dale and Wei, Guo and Raychaudhuri, Soumya and Donovan, Jerry and Barretina, Jordi and Boehm, Jesse S and Dobson, Jennifer and Urashima, Mitsuyoshi and Mc Henry, Kevin T and Pinchback, Reid M and Ligon, Azra H and Cho, Yoon-Jae and Haery, Leila and Greulich, Heidi and Reich, Michael and Winckler, Wendy and Lawrence, Michael S and Weir, Barbara A and Tanaka, Kumiko E and Chiang, Derek Y and Bass, Adam J and Loo, Alice and Hoffman, Carter and Prensner, John and Liefeld, Ted and Gao, Qing and Yecies, Derek and Signoretti, Sabina and Maher, Elizabeth and Kaye, Frederic J and Sasaki, Hidefumi and Tepper, Joel E and Fletcher, Jonathan A and Tabernero, Josep and Baselga, Jos{\'e} and Tsao, Ming-Sound and Demichelis, Francesca and Rubin, Mark A and Janne, Pasi A and Daly, Mark J and Nucera, Carmelo and Levine, Ross L and Ebert, Benjamin L and Gabriel, Stacey and Rustgi, Anil K and Antonescu, Cristina R and Ladanyi, Marc and Letai, Anthony and Garraway, Levi A and Loda, Massimo and Beer, David G and True, Lawrence D and Okamoto, Aikou and Pomeroy, Scott L and Singer, Samuel and Golub, Todd R and Lander, Eric S and Getz, Gad and Sellers, William R and Meyerson, Matthew}
}
@article {1109481,
	title = {Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis},
	journal = {Nat Genet},
	volume = {42},
	number = {7},
	year = {2010},
	month = {2010 Jul},
	pages = {579-89},
	abstract = {By combining genome-wide association data from 8,130 individuals with type 2 diabetes (T2D) and 38,987 controls of European descent and following up previously unidentified meta-analysis signals in a further 34,412 cases and 59,925 controls, we identified 12 new T2D association signals with combined P\&lt;5x10(-8). These include a second independent signal at the KCNQ1 locus; the first report, to our knowledge, of an X-chromosomal association (near DUSP9); and a further instance of overlap between loci implicated in monogenic and multifactorial forms of diabetes (at HNF1A). The identified loci affect both beta-cell function and insulin action, and, overall, T2D association signals show evidence of enrichment for genes involved in cell cycle regulation. We also show that a high proportion of T2D susceptibility loci harbor independent association signals influencing apparently unrelated complex traits.},
	keywords = {Blood Glucose, Diabetes Mellitus, Type 2, Dual-Specificity Phosphatases, Fasting, Gene Dosage, Gene Expression Profiling, Genetic Heterogeneity, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Hepatocyte Nuclear Factor 1-alpha, Humans, KCNQ1 Potassium Channel, Meta-Analysis as Topic, Mitogen-Activated Protein Kinase Phosphatases, Polymorphism, Single Nucleotide},
	issn = {1546-1718},
	doi = {10.1038/ng.609},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Twelve+type+2+diabetes+susceptibility+loci+identified+through+large-scale+association+analysis},
	author = {Voight, Benjamin F and Scott, Laura J and Steinthorsdottir, Valgerdur and Morris, Andrew P and Dina, Christian and Welch, Ryan P and Zeggini, Eleftheria and Huth, Cornelia and Aulchenko, Yurii S and Thorleifsson, Gudmar and McCulloch, Laura J and Ferreira, Teresa and Grallert, Harald and Amin, Najaf and Wu, Guanming and Willer, Cristen J and Raychaudhuri, Soumya and McCarroll, Steve A and Langenberg, Claudia and Hofmann, Oliver M and Dupuis, Jos{\'e}e and Qi, Lu and Segr{\`e}, Ayellet V and van Hoek, Mandy and Navarro, Pau and Ardlie, Kristin and Balkau, Beverley and Benediktsson, Rafn and Bennett, Amanda J and Blagieva, Roza and Boerwinkle, Eric and Bonnycastle, Lori L and Bengtsson Bostr{\"o}m, Kristina and Bravenboer, Bert and Bumpstead, Suzannah and Burtt, Nois{\"e}l P and Charpentier, Guillaume and Chines, Peter S and Cornelis, Marilyn and Couper, David J and Crawford, Gabe and Doney, Alex S F and Elliott, Katherine S and Elliott, Amanda L and Erdos, Michael R and Fox, Caroline S and Franklin, Christopher S and Ganser, Martha and Gieger, Christian and Grarup, Niels and Green, Todd and Griffin, Simon and Groves, Christopher J and Guiducci, Candace and Hadjadj, Samy and Hassanali, Neelam and Herder, Christian and Isomaa, Bo and Jackson, Anne U and Johnson, Paul R V and J{\o}rgensen, Torben and Kao, Wen H L and Klopp, Norman and Kong, Augustine and Kraft, Peter and Kuusisto, Johanna and Lauritzen, Torsten and Li, Man and Lieverse, Aloysius and Lindgren, Cecilia M and Lyssenko, Valeriya and Marre, Michel and Meitinger, Thomas and Midthjell, Kristian and Morken, Mario A and Narisu, Narisu and Nilsson, Peter and Owen, Katharine R and Payne, Felicity and Perry, John R B and Petersen, Ann-Kristin and Platou, Carl and Proen{\c c}a, Christine and Prokopenko, Inga and Rathmann, Wolfgang and Rayner, N William and Robertson, Neil R and Rocheleau, Ghislain and Roden, Michael and Sampson, Michael J and Saxena, Richa and Shields, Beverley M and Shrader, Peter and Sigurdsson, Gunnar and Spars{\o}, Thomas and Strassburger, Klaus and Stringham, Heather M and Sun, Qi and Swift, Amy J and Thorand, Barbara and Tichet, Jean and Tuomi, Tiinamaija and van Dam, Rob M and van Haeften, Timon W and van Herpt, Thijs and van Vliet-Ostaptchouk, Jana V and Walters, G Bragi and Weedon, Michael N and Wijmenga, Cisca and Witteman, Jacqueline and Bergman, Richard N and Cauchi, Stephane and Collins, Francis S and Gloyn, Anna L and Gyllensten, Ulf and Hansen, Torben and Hide, Winston A and Hitman, Graham A and Hofman, Albert and Hunter, David J and Hveem, Kristian and Laakso, Markku and Mohlke, Karen L and Morris, Andrew D and Palmer, Colin N A and Pramstaller, Peter P and Rudan, Igor and Sijbrands, Eric and Stein, Lincoln D and Tuomilehto, Jaakko and Uitterlinden, Andre and Mark Walker and Wareham, Nicholas J and Watanabe, Richard M and Abecasis, Gon{\c c}alo R and Boehm, Bernhard O and Campbell, Harry and Daly, Mark J and Hattersley, Andrew T and Hu, Frank B and Meigs, James B and Pankow, James S and Pedersen, Oluf and Wichmann, H-Erich and Barroso, In{\^e}s and Florez, Jose C and Frayling, Timothy M and Groop, Leif and Sladek, Rob and Thorsteinsdottir, Unnur and Wilson, James F and Illig, Thomas and Froguel, Philippe and van Duijn, Cornelia M and Stefansson, Kari and Altshuler, David and Boehnke, Michael and McCarthy, Mark I and MAGIC investigators and GIANT Consortium}
}
@article {1001916,
	title = {Electronic medical records for discovery research in rheumatoid arthritis},
	journal = {Arthritis Care Res (Hoboken)},
	volume = {62},
	number = {8},
	year = {2010},
	month = {2010 Aug},
	pages = {1120-7},
	abstract = {OBJECTIVE: Electronic medical records (EMRs) are a rich data source for discovery research but are underutilized due to the difficulty of extracting highly accurate clinical data. We assessed whether a classification algorithm incorporating narrative EMR data (typed physician notes) more accurately classifies subjects with rheumatoid arthritis (RA) compared with an algorithm using codified EMR data alone. METHODS: Subjects with \&gt; or =1 International Classification of Diseases, Ninth Revision RA code (714.xx) or who had anti-cyclic citrullinated peptide (anti-CCP) checked in the EMR of 2 large academic centers were included in an "RA Mart" (n = 29,432). For all 29,432 subjects, we extracted narrative (using natural language processing) and codified RA clinical information. In a training set of 96 RA and 404 non-RA cases from the RA Mart classified by medical record review, we used narrative and codified data to develop classification algorithms using logistic regression. These algorithms were applied to the entire RA Mart. We calculated and compared the positive predictive value (PPV) of these algorithms by reviewing the records of an additional 400 subjects classified as having RA by the algorithms. RESULTS: A complete algorithm (narrative and codified data) classified RA subjects with a significantly higher PPV of 94\% than an algorithm with codified data alone (PPV of 88\%). Characteristics of the RA cohort identified by the complete algorithm were comparable to existing RA cohorts (80\% women, 63\% anti-CCP positive, and 59\% positive for erosions). CONCLUSION: We demonstrate the ability to utilize complete EMR data to define an RA cohort with a PPV of 94\%, which was superior to an algorithm using codified data alone.},
	keywords = {Adult, Aged, Algorithms, Arthritis, Rheumatoid, Autoantibodies, Cohort Studies, Electronic Health Records, Female, Humans, International Classification of Diseases, Male, Middle Aged, Research},
	issn = {2151-4658},
	doi = {10.1002/acr.20184},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/20235204},
	author = {Liao, Katherine P and Cai, Tianxi and Gainer, Vivian and Goryachev, Sergey and Zeng-Treitler, Qing and Raychaudhuri, Soumya and Szolovits, Peter and Churchill, Susanne and Murphy, Shawn and Kohane, Isaac and Karlson, Elizabeth W and Plenge, Robert M}
}
@article {1001926,
	title = {Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci},
	journal = {Nat Genet},
	volume = {42},
	number = {6},
	year = {2010},
	month = {2010 Jun},
	pages = {508-14},
	abstract = {To identify new genetic risk factors for rheumatoid arthritis, we conducted a genome-wide association study meta-analysis of 5,539 autoantibody-positive individuals with rheumatoid arthritis (cases) and 20,169 controls of European descent, followed by replication in an independent set of 6,768 rheumatoid arthritis cases and 8,806 controls. Of 34 SNPs selected for replication, 7 new rheumatoid arthritis risk alleles were identified at genome-wide significance (P \&lt; 5 x 10(-8)) in an analysis of all 41,282 samples. The associated SNPs are near genes of known immune function, including IL6ST, SPRED2, RBPJ, CCR6, IRF5 and PXK. We also refined associations at two established rheumatoid arthritis risk loci (IL2RA and CCL21) and confirmed the association at AFF3. These new associations bring the total number of confirmed rheumatoid arthritis risk loci to 31 among individuals of European ancestry. An additional 11 SNPs replicated at P \&lt; 0.05, many of which are validated autoimmune risk alleles, suggesting that most represent genuine rheumatoid arthritis risk alleles.},
	keywords = {Arthritis, Rheumatoid, Autoantibodies, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Risk Factors},
	issn = {1546-1718},
	doi = {10.1038/ng.582},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/20453842},
	author = {Stahl, Eli A and Raychaudhuri, Soumya and Remmers, Elaine F and Xie, Gang and Eyre, Stephen and Thomson, Brian P and Li, Yonghong and Kurreeman, Fina A S and Zhernakova, Alexandra and Hinks, Anne and Guiducci, Candace and Chen, Robert and Alfredsson, Lars and Amos, Christopher I and Ardlie, Kristin G and BIRAC Consortium and Barton, Anne and Bowes, John and Brouwer, Elisabeth and Burtt, Noel P and Catanese, Joseph J and Coblyn, Jonathan and Coenen, Marieke Jh and Costenbader, Karen H and Criswell, Lindsey A and Crusius, J Bart A and Cui, Jing and de Bakker, Paul I W and De Jager, Philip L and Ding, Bo and Emery, Paul and Flynn, Edward and Harrison, Pille and Hocking, Lynne J and Huizinga, Tom W J and Kastner, Daniel L and Ke, Xiayi and Lee, Annette T and Liu, Xiangdong and Martin, Paul and Morgan, Ann W and Padyukov, Leonid and Posthumus, Marcel D and Radstake, Timothy R D J and Reid, David M and Seielstad, Mark and Seldin, Michael F and Shadick, Nancy A and Steer, Sophia and Tak, Paul P and Thomson, Wendy and van der Helm-van Mil, Annette H M and van der Horst-Bruinsma, Irene E and van der Schoot, C Ellen and van Riel, Piet L C M and Weinblatt, Michael E and Wilson, Anthony G and Wolbink, Gert Jan and Wordsworth, B Paul and YEAR Consortium and Wijmenga, Cisca and Karlson, Elizabeth W and Toes, Rene E M and de Vries, Niek and Begovich, Ann B and Worthington, Jane and Siminovitch, Katherine A and Gregersen, Peter K and Klareskog, Lars and Plenge, Robert M}
}
@article {1001921,
	title = {Rheumatoid arthritis risk allele PTPRC is also associated with response to anti-tumor necrosis factor alpha therapy},
	journal = {Arthritis Rheum},
	volume = {62},
	number = {7},
	year = {2010},
	month = {2010 Jul},
	pages = {1849-61},
	abstract = {OBJECTIVE: Anti-tumor necrosis factor alpha (anti-TNF) therapy is a mainstay of treatment in rheumatoid arthritis (RA). The aim of the present study was to test established RA genetic risk factors to determine whether the same alleles also influence the response to anti-TNF therapy. METHODS: A total of 1,283 RA patients receiving etanercept, infliximab, or adalimumab therapy were studied from among an international collaborative consortium of 9 different RA cohorts. The primary end point compared RA patients with a good treatment response according to the European League Against Rheumatism (EULAR) response criteria (n = 505) with RA patients considered to be nonresponders (n = 316). The secondary end point was the change from baseline in the level of disease activity according to the Disease Activity Score in 28 joints (triangle upDAS28). Clinical factors such as age, sex, and concomitant medications were tested as possible correlates of treatment response. Thirty-one single-nucleotide polymorphisms (SNPs) associated with the risk of RA were genotyped and tested for any association with treatment response, using univariate and multivariate logistic regression models. RESULTS: Of the 31 RA-associated risk alleles, a SNP at the PTPRC (also known as CD45) gene locus (rs10919563) was associated with the primary end point, a EULAR good response versus no response (odds ratio [OR] 0.55, P = 0.0001 in the multivariate model). Similar results were obtained using the secondary end point, the triangle upDAS28 (P = 0.0002). There was suggestive evidence of a stronger association in autoantibody-positive patients with RA (OR 0.55, 95\% confidence interval [95\% CI] 0.39-0.76) as compared with autoantibody-negative patients (OR 0.90, 95\% CI 0.41-1.99). CONCLUSION: Statistically significant associations were observed between the response to anti-TNF therapy and an RA risk allele at the PTPRC gene locus. Additional studies will be required to replicate this finding in additional patient collections.},
	keywords = {Antibodies, Monoclonal, Antigens, CD45, Antirheumatic Agents, Arthritis, Rheumatoid, Disability Evaluation, Female, Genetic Predisposition to Disease, Health Status, Humans, International Cooperation, Male, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors, Severity of Illness Index, Treatment Outcome, Tumor Necrosis Factor-alpha},
	issn = {1529-0131},
	doi = {10.1002/art.27457},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Rheumatoid+arthritis+risk+allele+PTPRC+is+also+associated+with+response+to+anti-tumor+necrosis+factor+alpha+therapy},
	author = {Cui, Jing and Saevarsdottir, Saedis and Thomson, Brian and Padyukov, Leonid and van der Helm-van Mil, Annette H M and Nititham, Joanne and Hughes, Laura B and de Vries, Niek and Raychaudhuri, Soumya and Alfredsson, Lars and Askling, Johan and Wedr{\'e}n, Sara and Ding, Bo and Guiducci, Candace and Wolbink, Gert Jan and Crusius, J Bart A and van der Horst-Bruinsma, Irene E and Herenius, Marieke and Weinblatt, Michael E and Shadick, Nancy A and Worthington, Jane and Batliwalla, Franak and Kern, Marlena and Morgan, Ann W and Wilson, Anthony G and Isaacs, John D and Hyrich, Kimme and Seldin, Michael F and Moreland, Larry W and Behrens, Timothy W and Allaart, Cornelia F and Criswell, Lindsey A and Huizinga, Tom W J and Tak, Paul P and Bridges, S Louis and Toes, Rene E M and Barton, Anne and Klareskog, Lars and Gregersen, Peter K and Karlson, Elizabeth W and Plenge, Robert M}
}
@article {1001616,
	title = {Recent advances in the genetics of rheumatoid arthritis},
	journal = {Curr Opin Rheumatol},
	volume = {22},
	number = {2},
	year = {2010},
	month = {2010 Mar},
	pages = {109-18},
	abstract = {PURPOSE OF REVIEW: To review the recently discovered genetic risk loci in rheumatoid arthritis (RA), the pathways they implicate, and the genetic architecture of RA. RECENT FINDINGS: Since 2008 investigators have identified many common genetic variants that confer disease risk through single nucleotide polymorphism genotyping studies; the list of variants will no doubt continue to expand at a rapid rate as genotyping technologies evolve and case-control sample collections continue to grow. In aggregate, these variants implicate pathways leading to NF-kappaB (nuclear factor kappa-light-chain-enhancer of activated B cells) activation, the interluekin-2 signaling pathway, and T-cell activation. SUMMARY: Although the effect of any individual variant is modest and even in aggregate considerably less than that of the major histocompatability complex, discovery of recent risk variants suggests immunological processes that are involved in disease pathogenesis.},
	keywords = {Alleles, Arthritis, Rheumatoid, Genetic Association Studies, Genetic Predisposition to Disease, Humans, Major Histocompatibility Complex, Polymorphism, Single Nucleotide, Signal Transduction, Twin Studies as Topic},
	issn = {1531-6963},
	doi = {10.1097/BOR.0b013e328336474d},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/20075733},
	author = {Raychaudhuri, Soumya}
}
@article {1001611,
	title = {Leveraging human genetics to develop future therapeutic strategies in rheumatoid arthritis},
	journal = {Rheum Dis Clin North Am},
	volume = {36},
	number = {2},
	year = {2010},
	month = {2010 May},
	pages = {259-70},
	abstract = {The purpose of this article is to place these genetic discoveries in the context of current and future therapeutic strategies for patients with RA. More specifically, this article focuses on (1) a brief overview of genetic studies, (2) human genetics as an approach to identify the Achilles heel of disease pathways, (3) humans as the model organism for functional studies of human mutations, (4) pharmacogenetic studies to gain insight into the mechanism of action of drugs, and (5) next-generation patient registries to enable large-scale genotype-phenotype studies.},
	keywords = {Antirheumatic Agents, Arthritis, Rheumatoid, Drug Discovery, Genotype, Humans, Pharmacogenetics, Phenotype, Registries, Risk Factors},
	issn = {1558-3163},
	doi = {10.1016/j.rdc.2010.03.002},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Leveraging+human+genetics+to+develop+future+therapeutic+strategies+in+rheumatoid+arthritis},
	author = {Plenge, Robert M and Raychaudhuri, Soumya}
}
@article {1109451,
	title = {Association of a single-nucleotide polymorphism in CD40 with the rate of joint destruction in rheumatoid arthritis},
	journal = {Arthritis Rheum},
	volume = {60},
	number = {8},
	year = {2009},
	month = {2009 Aug},
	pages = {2242-7},
	abstract = {OBJECTIVE: The severity of joint destruction in rheumatoid arthritis (RA) is highly variable from patient to patient and is influenced by genetic factors. Genome-wide association studies have enormously boosted the field of the genetics of RA susceptibility, but risk loci for RA severity remain poorly defined. A recent meta-analysis of genome-wide association studies identified 6 genetic regions for susceptibility to autoantibody-positive RA: CD40, KIF5A/PIP4K2C, CDK6, CCL21, PRKCQ, and MMEL1/TNFRSF14. The purpose of this study was to investigate whether these newly described genetic regions are associated with the rate of joint destruction. METHODS: RA patients enrolled in the Leiden Early Arthritis Clinic were studied (n=563). Yearly radiographs were scored using the Sharp/van der Heijde method (median followup 5 years; maximum followup 9 years). The rate of joint destruction between genotype groups was compared using a linear mixed model, correcting for age, sex, and treatment strategies. A total of 393 anti-citrullinated protein antibody (ACPA)-positive RA patients from the North American Rheumatoid Arthritis Consortium (NARAC) who had radiographic data available were used for the replication study. RESULTS: The TT and CC/CG genotypes of 2 single-nucleotide polymorphisms, rs4810485 (CD40) and rs42041 (CDK6), respectively, were associated with a higher rate of joint destruction in ACPA-positive RA patients (P=0.003 and P=0.012, respectively), with rs4810485 being significant after Bonferroni correction for multiple testing. The association of the CD40 minor allele with the rate of radiographic progression was replicated in the NARAC cohort (P=0.021). CONCLUSION: A polymorphism in the CD40 locus is associated with the rate of joint destruction in patients with ACPA-positive RA. Our findings provide one of the first non-HLA-related genetic severity factors that has been replicated.},
	keywords = {Antigens, CD40, Arthritis, Rheumatoid, Arthrography, Female, Genetic Predisposition to Disease, Health Status, Humans, Joints, Male, Middle Aged, Peptides, Cyclic, Polymorphism, Single Nucleotide, Range of Motion, Articular, Severity of Illness Index},
	issn = {0004-3591},
	doi = {10.1002/art.24721},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Association+of+a+single-nucleotide+polymorphism+in+CD40+with+the+rate+of+joint+destruction+in+rheumatoid+arthritis},
	author = {van der Linden, Michael P M and Feitsma, Anouk L and le Cessie, Saskia and Kern, Marlena and Olsson, Lina M and Raychaudhuri, Soumya and Begovich, Ann B and Chang, Monica and Catanese, Joseph J and Kurreeman, Fina A S and van Nies, Jessica and van der Heijde, D{\'e}sir{\'e}e M and Gregersen, Peter K and Huizinga, Tom W J and Toes, Ren{\'e} E M and van der Helm-van Mil, Annette H M}
}
@article {1109446,
	title = {Complex diseases, complex genes: keeping pathways on the right track},
	journal = {Epidemiology},
	volume = {20},
	number = {4},
	year = {2009},
	month = {2009 Jul},
	pages = {508-11},
	keywords = {Genetic Predisposition to Disease, Genetics, Medical, Genomics, Humans, Polymorphism, Single Nucleotide},
	issn = {1531-5487},
	doi = {10.1097/EDE.0b013e3181a93b98},
	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2704602/},
	author = {Kraft, Peter and Raychaudhuri, Soumya}
}
@article {1109441,
	title = {Identifying relationships among genomic disease regions: predicting genes at pathogenic SNP associations and rare deletions},
	journal = {PLoS Genet},
	volume = {5},
	number = {6},
	year = {2009},
	month = {2009 Jun},
	pages = {e1000534},
	abstract = {Translating a set of disease regions into insight about pathogenic mechanisms requires not only the ability to identify the key disease genes within them, but also the biological relationships among those key genes. Here we describe a statistical method, Gene Relationships Among Implicated Loci (GRAIL), that takes a list of disease regions and automatically assesses the degree of relatedness of implicated genes using 250,000 PubMed abstracts. We first evaluated GRAIL by assessing its ability to identify subsets of highly related genes in common pathways from validated lipid and height SNP associations from recent genome-wide studies. We then tested GRAIL, by assessing its ability to separate true disease regions from many false positive disease regions in two separate practical applications in human genetics. First, we took 74 nominally associated Crohn{\textquoteright}s disease SNPs and applied GRAIL to identify a subset of 13 SNPs with highly related genes. Of these, ten convincingly validated in follow-up genotyping; genotyping results for the remaining three were inconclusive. Next, we applied GRAIL to 165 rare deletion events seen in schizophrenia cases (less than one-third of which are contributing to disease risk). We demonstrate that GRAIL is able to identify a subset of 16 deletions containing highly related genes; many of these genes are expressed in the central nervous system and play a role in neuronal synapses. GRAIL offers a statistically robust approach to identifying functionally related genes from across multiple disease regions--that likely represent key disease pathways. An online version of this method is available for public use (http://www.broad.mit.edu/mpg/grail/).},
	keywords = {Crohn Disease, Databases, Genetic, Gene Deletion, Genome, Human, Genome-Wide Association Study, Genomics, Humans, Meta-Analysis as Topic, Polymorphism, Single Nucleotide, Schizophrenia},
	issn = {1553-7404},
	doi = {10.1371/journal.pgen.1000534},
	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2694358/},
	author = {Raychaudhuri, Soumya and Plenge, Robert M and Rossin, Elizabeth J and Ng, Aylwin C Y and International Schizophrenia Consortium and Purcell, Shaun M and Sklar, Pamela and Scolnick, Edward M and Xavier, Ramnik J and Altshuler, David and Daly, Mark J}
}
@article {1109456,
	title = {Parental origin of sequence variants associated with complex diseases},
	journal = {Nature},
	volume = {462},
	number = {7275},
	year = {2009},
	month = {2009 Dec 17},
	pages = {868-74},
	abstract = {Effects of susceptibility variants may depend on from which parent they are inherited. Although many associations between sequence variants and human traits have been discovered through genome-wide associations, the impact of parental origin has largely been ignored. Here we show that for 38,167 Icelanders genotyped using single nucleotide polymorphism (SNP) chips, the parental origin of most alleles can be determined. For this we used a combination of genealogy and long-range phasing. We then focused on SNPs that associate with diseases and are within 500 kilobases of known imprinted genes. Seven independent SNP associations were examined. Five-one with breast cancer, one with basal-cell carcinoma and three with type 2 diabetes-have parental-origin-specific associations. These variants are located in two genomic regions, 11p15 and 7q32, each harbouring a cluster of imprinted genes. Furthermore, we observed a novel association between the SNP rs2334499 at 11p15 and type 2 diabetes. Here the allele that confers risk when paternally inherited is protective when maternally transmitted. We identified a differentially methylated CTCF-binding site at 11p15 and demonstrated correlation of rs2334499 with decreased methylation of that site.},
	keywords = {Alleles, Binding Sites, Breast Neoplasms, Carcinoma, Basal Cell, Chromosomes, Human, Pair 11, Chromosomes, Human, Pair 7, Diabetes Mellitus, Type 2, DNA Methylation, Fathers, Female, Genetic Predisposition to Disease, Genome, Human, Genomic Imprinting, Haplotypes, Humans, Iceland, Male, Mothers, Pedigree, Polymorphism, Single Nucleotide, Repressor Proteins},
	issn = {1476-4687},
	doi = {10.1038/nature08625},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/20016592},
	author = {Kong, Augustine and Steinthorsdottir, Valgerdur and Masson, Gisli and Thorleifsson, Gudmar and Sulem, Patrick and Besenbacher, Soren and Jonasdottir, Aslaug and Sigurdsson, Asgeir and Kristinsson, Kari Th and Jonasdottir, Adalbjorg and Frigge, Michael L and Gylfason, Arnaldur and Olason, Pall I and Gudjonsson, Sigurjon A and Sverrisson, Sverrir and Stacey, Simon N and Sigurgeirsson, Bardur and Benediktsdottir, Kristrun R and Sigurdsson, Helgi and Jonsson, Thorvaldur and Benediktsson, Rafn and Olafsson, Jon H and Johannsson, Oskar Th and Hreidarsson, Astradur B and Sigurdsson, Gunnar and DIAGRAM Consortium and Ferguson-Smith, Anne C and Gudbjartsson, Daniel F and Thorsteinsdottir, Unnur and Stefansson, Kari}
}
@article {1001941,
	title = {The PRL -1149 G/T polymorphism and rheumatoid arthritis susceptibility},
	journal = {Arthritis Rheum},
	volume = {60},
	number = {5},
	year = {2009},
	month = {2009 May},
	pages = {1250-4},
	abstract = {OBJECTIVE: Previous studies have demonstrated that the PRL -1149 T (minor) allele decreases prolactin expression and may be associated with autoimmune disease. The aim of this study was to determine the role of the PRL -1149 G/T polymorphism (rs1341239) in rheumatoid arthritis (RA) susceptibility.

METHODS: We examined the association between PRL -1149 G/T and RA risk in 4 separate study populations, consisting of a total of 3,405 RA cases and 4,111 controls of self-reported white European ancestry. Samples were genotyped using 1 of 3 genotyping platforms, and strict quality control metrics were applied. We tested for association using a 2-tailed Cochran-Mantel-Haenszel additive, fixed-effects model.

RESULTS: In the individual populations, odds ratios (ORs) for an association between PRL -1149 T and RA risk ranged from 0.80 to 0.97. In a joint meta-analysis across all 4 populations, the OR for an association between PRL -1149 T and RA risk was 0.90 (95\% confidence interval 0.84-0.96, P=0.001).

CONCLUSION: Our findings indicate a possible association between the PRL -1149 T allele and decreased RA risk. The effect size is small but similar to ORs for other genetic polymorphisms associated with complex traits, including RA.},
	keywords = {Alleles, Arthritis, Rheumatoid, Female, Genetic Predisposition to Disease, Humans, Male, Polymorphism, Genetic, Prolactin},
	issn = {0004-3591},
	doi = {10.1002/art.24468},
	author = {Lee, Yvonne C and Raychaudhuri, Soumya and Cui, Jing and De Vivo, Immaculata and Ding, Bo and Alfredsson, Lars and Padyukov, Leonid and Costenbader, Karen H and Seielstad, Mark and Graham, Robert R and Klareskog, Lars and Gregersen, Peter K and Plenge, Robert M and Karlson, Elizabeth W}
}
@article {1001931,
	title = {Genetic variants at CD28, PRDM1 and CD2/CD58 are associated with rheumatoid arthritis risk},
	journal = {Nat Genet},
	volume = {41},
	number = {12},
	year = {2009},
	month = {2009 Dec},
	pages = {1313-8},
	abstract = {To discover new rheumatoid arthritis (RA) risk loci, we systematically examined 370 SNPs from 179 independent loci with P \&lt; 0.001 in a published meta-analysis of RA genome-wide association studies (GWAS) of 3,393 cases and 12,462 controls. We used Gene Relationships Across Implicated Loci (GRAIL), a computational method that applies statistical text mining to PubMed abstracts, to score these 179 loci for functional relationships to genes in 16 established RA disease loci. We identified 22 loci with a significant degree of functional connectivity. We genotyped 22 representative SNPs in an independent set of 7,957 cases and 11,958 matched controls. Three were convincingly validated: CD2-CD58 (rs11586238, P = 1 x 10(-6) replication, P = 1 x 10(-9) overall), CD28 (rs1980422, P = 5 x 10(-6) replication, P = 1 x 10(-9) overall) and PRDM1 (rs548234, P = 1 x 10(-5) replication, P = 2 x 10(-8) overall). An additional four were replicated (P \&lt; 0.0023): TAGAP (rs394581, P = 0.0002 replication, P = 4 x 10(-7) overall), PTPRC (rs10919563, P = 0.0003 replication, P = 7 x 10(-7) overall), TRAF6-RAG1 (rs540386, P = 0.0008 replication, P = 4 x 10(-6) overall) and FCGR2A (rs12746613, P = 0.0022 replication, P = 2 x 10(-5) overall). Many of these loci are also associated to other immunologic diseases.},
	keywords = {Antigens, CD2, Antigens, CD28, Antigens, CD58, Arthritis, Rheumatoid, Case-Control Studies, Genetic Predisposition to Disease, Genetic Variation, Genotype, Humans, Polymorphism, Single Nucleotide, Repressor Proteins, Risk Factors},
	issn = {1546-1718},
	doi = {10.1038/ng.479},
	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3142887/},
	author = {Raychaudhuri, Soumya and Thomson, Brian P and Remmers, Elaine F and Eyre, Stephen and Hinks, Anne and Guiducci, Candace and Catanese, Joseph J and Xie, Gang and Stahl, Eli A and Chen, Robert and Alfredsson, Lars and Amos, Christopher I and Ardlie, Kristin G and BIRAC Consortium and Barton, Anne and Bowes, John and Burtt, Noel P and Chang, Monica and Coblyn, Jonathan and Costenbader, Karen H and Criswell, Lindsey A and Crusius, J Bart A and Cui, Jing and De Jager, Phillip L and Ding, Bo and Emery, Paul and Flynn, Edward and Harrison, Pille and Hocking, Lynne J and Huizinga, Tom W J and Kastner, Daniel L and Ke, Xiayi and Kurreeman, Fina A S and Lee, Annette T and Liu, Xiangdong and Li, Yonghong and Martin, Paul and Morgan, Ann W and Padyukov, Leonid and Reid, David M and Seielstad, Mark and Seldin, Michael F and Shadick, Nancy A and Steer, Sophia and Tak, Paul P and Thomson, Wendy and van der Helm-van Mil, Annette H M and van der Horst-Bruinsma, Irene E and Weinblatt, Michael E and Wilson, Anthony G and Wolbink, Gert Jan and Wordsworth, Paul and YEAR Consortium and Altshuler, David and Karlson, Elizabeth W and Toes, Rene E M and de Vries, Niek and Begovich, Ann B and Siminovitch, Katherine A and Worthington, Jane and Klareskog, Lars and Gregersen, Peter K and Daly, Mark J and Plenge, Robert M}
}
@article {1001936,
	title = {Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci},
	journal = {Nat Genet},
	volume = {41},
	number = {7},
	year = {2009},
	month = {2009 Jul},
	pages = {776-82},
	abstract = {We report the results of a meta-analysis of genome-wide association scans for multiple sclerosis (MS) susceptibility that includes 2,624 subjects with MS and 7,220 control subjects. Replication in an independent set of 2,215 subjects with MS and 2,116 control subjects validates new MS susceptibility loci at TNFRSF1A (combined P = 1.59 x 10(-11)), IRF8 (P = 3.73 x 10(-9)) and CD6 (P = 3.79 x 10(-9)). TNFRSF1A harbors two independent susceptibility alleles: rs1800693 is a common variant with modest effect (odds ratio = 1.2), whereas rs4149584 is a nonsynonymous coding polymorphism of low frequency but with stronger effect (allele frequency = 0.02; odds ratio = 1.6). We also report that the susceptibility allele near IRF8, which encodes a transcription factor known to function in type I interferon signaling, is associated with higher mRNA expression of interferon-response pathway genes in subjects with MS.},
	keywords = {Antigens, CD, Antigens, Differentiation, T-Lymphocyte, Case-Control Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Interferon Regulatory Factors, Multiple Sclerosis, Oligonucleotide Array Sequence Analysis, Receptors, Tumor Necrosis Factor, Type I},
	issn = {1546-1718},
	doi = {10.1038/ng.401},
	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2757648/},
	author = {De Jager, Philip L and Jia, Xiaoming and Wang, Joanne and de Bakker, Paul I W and Ottoboni, Linda and Aggarwal, Neelum T and Piccio, Laura and Raychaudhuri, Soumya and Tran, Dong and Aubin, Cristin and Briskin, Rebeccah and Romano, Susan and International MS Genetics Consortium and Baranzini, Sergio E and McCauley, Jacob L and Pericak-Vance, Margaret A and Haines, Jonathan L and Gibson, Rachel A and Naeglin, Yvonne and Uitdehaag, Bernard and Matthews, Paul M and Kappos, Ludwig and Polman, Chris and McArdle, Wendy L and Strachan, David P and Evans, Denis and Cross, Anne H and Daly, Mark J and Compston, Alastair and Sawcer, Stephen J and Weiner, Howard L and Hauser, Stephen L and Hafler, David A and Oksenberg, Jorge R}
}
@article {1109436,
	title = {Common variants at CD40 and other loci confer risk of rheumatoid arthritis},
	journal = {Nat Genet},
	volume = {40},
	number = {10},
	year = {2008},
	month = {2008 Oct},
	pages = {1216-23},
	abstract = {To identify rheumatoid arthritis risk loci in European populations, we conducted a meta-analysis of two published genome-wide association (GWA) studies totaling 3,393 cases and 12,462 controls. We genotyped 31 top-ranked SNPs not previously associated with rheumatoid arthritis in an independent replication of 3,929 autoantibody-positive rheumatoid arthritis cases and 5,807 matched controls from eight separate collections. We identified a common variant at the CD40 gene locus (rs4810485, P = 0.0032 replication, P = 8.2 x 10(-9) overall, OR = 0.87). Along with other associations near TRAF1 (refs. 2,3) and TNFAIP3 (refs. 4,5), this implies a central role for the CD40 signaling pathway in rheumatoid arthritis pathogenesis. We also identified association at the CCL21 gene locus (rs2812378, P = 0.00097 replication, P = 2.8 x 10(-7) overall), a gene involved in lymphocyte trafficking. Finally, we identified evidence of association at four additional gene loci: MMEL1-TNFRSF14 (rs3890745, P = 0.0035 replication, P = 1.1 x 10(-7) overall), CDK6 (rs42041, P = 0.010 replication, P = 4.0 x 10(-6) overall), PRKCQ (rs4750316, P = 0.0078 replication, P = 4.4 x 10(-6) overall), and KIF5A-PIP4K2C (rs1678542, P = 0.0026 replication, P = 8.8 x 10(-8) overall).},
	keywords = {Antigens, CD40, Arthritis, Rheumatoid, Case-Control Studies, Chromosome Mapping, Chromosomes, Human, Genetic Linkage, Genetic Predisposition to Disease, Genome, Human, Haplotypes, Humans, Polymorphism, Single Nucleotide},
	issn = {1546-1718},
	doi = {10.1038/ng.233},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/18794853},
	author = {Raychaudhuri, Soumya and Remmers, Elaine F and Lee, Annette T and Hackett, Rachel and Guiducci, Candace and Burtt, No{\"e}l P and Gianniny, Lauren and Korman, Benjamin D and Padyukov, Leonid and Kurreeman, Fina A S and Chang, Monica and Catanese, Joseph J and Ding, Bo and Wong, Sandra and van der Helm-van Mil, Annette H M and Neale, Benjamin M and Coblyn, Jonathan and Cui, Jing and Tak, Paul P and Wolbink, Gert Jan and Crusius, J Bart A and van der Horst-Bruinsma, Irene E and Criswell, Lindsey A and Amos, Christopher I and Seldin, Michael F and Kastner, Daniel L and Ardlie, Kristin G and Alfredsson, Lars and Costenbader, Karen H and Altshuler, David and Huizinga, Tom W J and Shadick, Nancy A and Weinblatt, Michael E and de Vries, Niek and Worthington, Jane and Seielstad, Mark and Toes, Rene E M and Karlson, Elizabeth W and Begovich, Ann B and Klareskog, Lars and Gregersen, Peter K and Daly, Mark J and Plenge, Robert M}
}
@article {1001946,
	title = {Practical aspects of imputation-driven meta-analysis of genome-wide association studies},
	journal = {Hum Mol Genet},
	volume = {17},
	number = {R2},
	year = {2008},
	month = {2008 Oct 15},
	pages = {R122-8},
	abstract = {Motivated by the overwhelming success of genome-wide association studies, droves of researchers are working vigorously to exchange and to combine genetic data to expediently discover genetic risk factors for common human traits. The primary tools that fuel these new efforts are imputation, allowing researchers who have collected data on a diversity of genotype platforms to share data in a uniformly exchangeable format, and meta-analysis for pooling statistical support for a genotype-phenotype association. As many groups are forming collaborations to engage in these efforts, this review collects a series of guidelines, practical detail and learned experiences from a variety of individuals who have contributed to the subject.},
	keywords = {Data Interpretation, Statistical, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Meta-Analysis as Topic, Phenotype, Polymorphism, Single Nucleotide},
	issn = {1460-2083},
	doi = {10.1093/hmg/ddn288},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Practical+aspects+of+imputation-driven+meta-analysis+of+genome-wide+association+studies},
	author = {de Bakker, Paul I W and Ferreira, Manuel A R and Jia, Xiaoming and Neale, Benjamin M and Raychaudhuri, Soumya and Voight, Benjamin F}
}
@article {1109431,
	title = {The computational analysis of scientific literature to define and recognize gene expression clusters},
	journal = {Nucleic Acids Res},
	volume = {31},
	number = {15},
	year = {2003},
	month = {2003 Aug 01},
	pages = {4553-60},
	abstract = {A limitation of many gene expression analytic approaches is that they do not incorporate comprehensive background knowledge about the genes into the analysis. We present a computational method that leverages the peer-reviewed literature in the automatic analysis of gene expression data sets. Including the literature in the analysis of gene expression data offers an opportunity to incorporate functional information about the genes when defining expression clusters. We have created a method that associates gene expression profiles with known biological functions. Our method has two steps. First, we apply hierarchical clustering to the given gene expression data set. Secondly, we use text from abstracts about genes to (i) resolve hierarchical cluster boundaries to optimize the functional coherence of the clusters and (ii) recognize those clusters that are most functionally coherent. In the case where a gene has not been investigated and therefore lacks primary literature, articles about well-studied homologous genes are added as references. We apply our method to two large gene expression data sets with different properties. The first contains measurements for a subset of well-studied Saccharomyces cerevisiae genes with multiple literature references, and the second contains newly discovered genes in Drosophila melanogaster; many have no literature references at all. In both cases, we are able to rapidly define and identify the biologically relevant gene expression profiles without manual intervention. In both cases, we identified novel clusters that were not noted by the original investigators.},
	keywords = {Animals, Cluster Analysis, Computational Biology, Databases, Genetic, Drosophila melanogaster, Gene Expression Profiling, Genes, Fungal, Genes, Insect, Proteins, Publications, Saccharomyces cerevisiae, Sequence Homology, Nucleic Acid},
	issn = {1362-4962},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=The+computational+analysis+of+scientific+literature+to+define+and+recognize+gene+expression+clusters},
	author = {Raychaudhuri, Soumya and Chang, Jeffrey T and Imam, Farhad and Altman, Russ B}
}
@article {1109426,
	title = {A literature-based method for assessing the functional coherence of a gene group},
	journal = {Bioinformatics},
	volume = {19},
	number = {3},
	year = {2003},
	month = {2003 Feb 12},
	pages = {396-401},
	abstract = {MOTIVATION: Many experimental and algorithmic approaches in biology generate groups of genes that need to be examined for related functional properties. For example, gene expression profiles are frequently organized into clusters of genes that may share functional properties. We evaluate a method, neighbor divergence per gene (NDPG), that uses scientific literature to assess whether a group of genes are functionally related. The method requires only a corpus of documents and an index connecting the documents to genes. RESULTS: We evaluate NDPG on 2796 functional groups generated by the Gene Ontology consortium in four organisms: mouse, fly, worm and yeast. NDPG finds functional coherence in 96, 92, 82 and 45\% of the groups (at 99.9\% specificity) in yeast, mouse, fly and worm respectively.},
	keywords = {Abstracting and Indexing as Topic, Animals, Caenorhabditis elegans, Cluster Analysis, Databases, Genetic, Drosophila, Gene Expression Profiling, Gene Expression Regulation, Information Storage and Retrieval, Mice, Natural Language Processing, PubMed, Saccharomyces cerevisiae, Sequence Alignment},
	issn = {1367-4803},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=A+literature-based+method+for+assessing+the+functional+coherence+of+a+gene+group},
	author = {Raychaudhuri, Soumya and Altman, Russ B}
}
@article {1109411,
	title = {Associating genes with gene ontology codes using a maximum entropy analysis of biomedical literature},
	journal = {Genome Res},
	volume = {12},
	number = {1},
	year = {2002},
	month = {2002 Jan},
	pages = {203-14},
	abstract = {Functional characterizations of thousands of gene products from many species are described in the published literature. These discussions are extremely valuable for characterizing the functions not only of these gene products, but also of their homologs in other organisms. The Gene Ontology (GO) is an effort to create a controlled terminology for labeling gene functions in a more precise, reliable, computer-readable manner. Currently, the best annotations of gene function with the GO are performed by highly trained biologists who read the literature and select appropriate codes. In this study, we explored the possibility that statistical natural language processing techniques can be used to assign GO codes. We compared three document classification methods (maximum entropy modeling, na{\"\i}ve Bayes classification, and nearest-neighbor classification) to the problem of associating a set of GO codes (for biological process) to literature abstracts and thus to the genes associated with the abstracts. We showed that maximum entropy modeling outperforms the other methods and achieves an accuracy of 72\% when ascertaining the function discussed within an abstract. The maximum entropy method provides confidence measures that correlate well with performance. We conclude that statistical methods may be used to assign GO codes and may be useful for the difficult task of reassignment as terminology standards evolve over time.},
	keywords = {Algorithms, Computational Biology, Databases, Genetic, Genes, Fungal, Research, Saccharomyces cerevisiae},
	issn = {1088-9051},
	doi = {10.1101/gr.199701},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Associating+genes+with+gene+ontology+codes+using+a+maximum+entropy+analysis+of+biomedical+literature},
	author = {Raychaudhuri, Soumya and Chang, Jeffrey T and Sutphin, Patrick D and Altman, Russ B}
}
@article {1109416,
	title = {Determining the genomic locations of repetitive DNA sequences with a whole-genome microarray: IS6110 in Mycobacterium tuberculosis},
	journal = {J Clin Microbiol},
	volume = {40},
	number = {6},
	year = {2002},
	month = {2002 Jun},
	pages = {2192-8},
	abstract = {The mycobacterial insertion sequence IS6110 has been exploited extensively as a clonal marker in molecular epidemiologic studies of tuberculosis. In addition, it has been hypothesized that this element is an important driving force behind genotypic variability that may have phenotypic consequences. We present here a novel, DNA microarray-based methodology, designated SiteMapping, that simultaneously maps the locations and orientations of multiple copies of IS6110 within the genome. To investigate the sensitivity, accuracy, and limitations of the technique, it was applied to eight Mycobacterium tuberculosis strains for which complete or partial IS6110 insertion site information had been determined previously. SiteMapping correctly located 64\% (38 of 59) of the IS6110 copies predicted by restriction fragment length polymorphism analysis. The technique is highly specific; 97\% of the predicted insertion sites were true insertions. Eight previously unknown insertions were identified and confirmed by PCR or sequencing. The performance could be improved by modifications in the experimental protocol and in the approach to data analysis. SiteMapping has general applicability and demonstrates an expansion in the applications of microarrays that complements conventional approaches in the study of genome architecture.},
	keywords = {DNA Transposable Elements, DNA, Bacterial, Genome, Bacterial, Humans, Molecular Sequence Data, Mycobacterium tuberculosis, Oligonucleotide Array Sequence Analysis, Repetitive Sequences, Nucleic Acid},
	issn = {0095-1137},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Determining+the+genomic+locations+of+repetitive+DNA+sequences+with+a+whole-genome+microarray\%3A+IS6110+in+Mycobacterium+tuberculosis},
	author = {Kivi, M{\r a}rten and Liu, Xuemin and Raychaudhuri, Soumya and Altman, Russ B and Small, Peter M}
}
@article {1109421,
	title = {Using text analysis to identify functionally coherent gene groups},
	journal = {Genome Res},
	volume = {12},
	number = {10},
	year = {2002},
	month = {2002 Oct},
	pages = {1582-90},
	abstract = {The analysis of large-scale genomic information (such as sequence data or expression patterns) frequently involves grouping genes on the basis of common experimental features. Often, as with gene expression clustering, there are too many groups to easily identify the functionally relevant ones. One valuable source of information about gene function is the published literature. We present a method, neighbor divergence, for assessing whether the genes within a group share a common biological function based on their associated scientific literature. The method uses statistical natural language processing techniques to interpret biological text. It requires only a corpus of documents relevant to the genes being studied (e.g., all genes in an organism) and an index connecting the documents to appropriate genes. Given a group of genes, neighbor divergence assigns a numerical score indicating how "functionally coherent" the gene group is from the perspective of the published literature. We evaluate our method by testing its ability to distinguish 19 known functional gene groups from 1900 randomly assembled groups. Neighbor divergence achieves 79\% sensitivity at 100\% specificity, comparing favorably to other tested methods. We also apply neighbor divergence to previously published gene expression clusters to assess its ability to recognize gene groups that had been manually identified as representative of a common function.},
	keywords = {Algorithms, Artificial Intelligence, Cluster Analysis, Computational Biology, Databases, Genetic, Discriminant Analysis, Gene Expression Profiling, Genes, Fungal, Genome, Fungal, Information Services, Natural Language Processing, Research Design, Saccharomyces cerevisiae},
	issn = {1088-9051},
	doi = {10.1101/gr.116402},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Using+text+analysis+to+identify+functionally+coherent+gene+groups},
	author = {Raychaudhuri, Soumya and Sch{\"u}tze, Hinrich and Altman, Russ B}
}
@article {1109401,
	title = {Basic microarray analysis: grouping and feature reduction},
	journal = {Trends Biotechnol},
	volume = {19},
	number = {5},
	year = {2001},
	month = {2001 May},
	pages = {189-93},
	abstract = {DNA microarray technologies are useful for addressing a broad range of biological problems - including the measurement of mRNA expression levels in target cells. These studies typically produce large data sets that contain measurements on thousands of genes under hundreds of conditions. There is a critical need to summarize this data and to pick out the important details. The most common activities, therefore, are to group together microarray data and to reduce the number of features. Both of these activities can be done using only the raw microarray data (unsupervised methods) or using external information that provides labels for the microarray data (supervised methods). We briefly review supervised and unsupervised methods for grouping and reducing data in the context of a publicly available suite of tools called CLEAVER, and illustrate their application on a representative data set collected to study lymphoma.},
	keywords = {Algorithms, Cluster Analysis, Humans, Internet, Lymphoma, Oligonucleotide Array Sequence Analysis, RNA, Messenger, Software},
	issn = {0167-7799},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Basic+microarray+analysis\%3A+grouping+and+feature+reduction},
	author = {Raychaudhuri, S and Sutphin, P D and Chang, J T and Altman, R B}
}
@article {1109396,
	title = {Including biological literature improves homology search},
	journal = {Pac Symp Biocomput},
	year = {2001},
	month = {2001},
	pages = {374-83},
	abstract = {Annotating the tremendous amount of sequence information being generated requires accurate automated methods for recognizing homology. Although sequence similarity is only one of many indicators of evolutionary homology, it is often the only one used. Here we find that supplementing sequence similarity with information from biomedical literature is successful in increasing the accuracy of homology search results. We modified the PSI-BLAST algorithm to use literature similarity in each iteration of its database search. The modified algorithm is evaluated and compared to standard PSI-BLAST in searching for homologous proteins. The performance of the modified algorithm achieved 32\% recall with 95\% precision, while the original one achieved 33\% recall with 84\% precision; the literature similarity requirement preserved the sensitive characteristic of the PSI-BLAST algorithm while improving the precision.},
	keywords = {Algorithms, Computational Biology, Databases, Factual, Natural Language Processing, Periodicals as Topic, Sensitivity and Specificity, Sequence Alignment, Software},
	issn = {2335-6936},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Including+biological+literature+improves+homology+search},
	author = {Chang, J T and Raychaudhuri, S and Altman, R B}
}
@article {1109406,
	title = {Whole-genome expression analysis: challenges beyond clustering},
	journal = {Curr Opin Struct Biol},
	volume = {11},
	number = {3},
	year = {2001},
	month = {2001 Jun},
	pages = {340-7},
	abstract = {Measuring the expression of most or all of the genes in a biological system raises major analytic challenges. A wealth of recent reports uses microarray expression data to examine diverse biological phenomena - from basic processes in model organisms to complex aspects of human disease. After an initial flurry of methods for clustering the data on the basis of similarity, the field has recognized some longer-term challenges. Firstly, there are efforts to understand the sources of noise and variation in microarray experiments in order to increase the biological signal. Secondly, there are efforts to combine expression data with other sources of information to improve the range and quality of conclusions that can be drawn. Finally, techniques are now emerging to reconstruct networks of genetic interactions in order to create integrated and systematic models of biological systems.},
	keywords = {Gene Expression Profiling, Gene Expression Regulation, Genome, Humans},
	issn = {0959-440X},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Whole-genome+expression+analysis\%3A+challenges+beyond+clustering},
	author = {Altman, R B and Raychaudhuri, S}
}
@article {1109386,
	title = {Pattern recognition of genomic features with microarrays: site typing of Mycobacterium tuberculosis strains},
	journal = {Proc Int Conf Intell Syst Mol Biol},
	volume = {8},
	year = {2000},
	month = {2000},
	pages = {286-95},
	abstract = {Mycobacterium tuberculosis (M. tb.) strains differ in the number and locations of a transposon-like insertion sequence known as IS6110. Accurate detection of this sequence can be used as a fingerprint for individual strains, but can be difficult because of noisy data. In this paper, we propose a non-parametric discriminant analysis method for predicting the locations of the IS6110 sequence from microarray data. Polymerase chain reaction extension products generated from primers specific for the insertion sequence are hybridized to a microarray containing targets corresponding to each open reading frame in M. tb. To test for insertion sites, we use microarray intensity values extracted from small windows of contiguous open reading frames. Rank-transformation of spot intensities and first-order differences in local windows provide enough information to reliably determine the presence of an insertion sequence. The nonparametric approach outperforms all other methods tested in this study.},
	keywords = {Genome, Bacterial, Mycobacterium tuberculosis, Oligonucleotide Array Sequence Analysis},
	issn = {1553-0833},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Pattern+recognition+of+genomic+features+with+microarrays\%3A+site+typing+of+Mycobacterium+tuberculosis+strains},
	author = {Raychaudhuri, S and Stuart, J M and Liu, X and Small, P M and Altman, R B}
}
@article {1109391,
	title = {Principal components analysis to summarize microarray experiments: application to sporulation time series},
	journal = {Pac Symp Biocomput},
	year = {2000},
	month = {2000},
	pages = {455-66},
	abstract = {A series of microarray experiments produces observations of differential expression for thousands of genes across multiple conditions. It is often not clear whether a set of experiments are measuring fundamentally different gene expression states or are measuring similar states created through different mechanisms. It is useful, therefore, to define a core set of independent features for the expression states that allow them to be compared directly. Principal components analysis (PCA) is a statistical technique for determining the key variables in a multidimensional data set that explain the differences in the observations, and can be used to simplify the analysis and visualization of multidimensional data sets. We show that application of PCA to expression data (where the experimental conditions are the variables, and the gene expression measurements are the observations) allows us to summarize the ways in which gene responses vary under different conditions. Examination of the components also provides insight into the underlying factors that are measured in the experiments. We applied PCA to the publicly released yeast sporulation data set (Chu et al. 1998). In that work, 7 different measurements of gene expression were made over time. PCA on the time-points suggests that much of the observed variability in the experiment can be summarized in just 2 components--i.e. 2 variables capture most of the information. These components appear to represent (1) overall induction level and (2) change in induction level over time. We also examined the clusters proposed in the original paper, and show how they are manifested in principal component space. Our results are available on the internet at http:{\textquestiondown}www.smi.stanford.edu/project/helix/PCArray .},
	keywords = {Computer Simulation, Databases, Factual, Gene Expression, Genes, Fungal, Models, Genetic, Oligonucleotide Array Sequence Analysis, Saccharomyces cerevisiae, Spores, Fungal},
	issn = {2335-6936},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Principal+components+analysis+to+summarize+microarray+experiments\%3A+application+to+sporulation+time+series},
	author = {Raychaudhuri, S and Stuart, J M and Altman, R B}
}
@article {1109381,
	title = {Backbone makes a significant contribution to the electrostatics of alpha/beta-barrel proteins},
	journal = {Protein Sci},
	volume = {6},
	number = {9},
	year = {1997},
	month = {1997 Sep},
	pages = {1849-57},
	abstract = {The electrostatic properties of seven alpha/beta-barrel enzymes selected from different evolutionary families were studied: triose phosphate isomerase, fructose-1,6-bisphosphate aldolase, pyruvate kinase, mandelate racemase, trimethylamine dehydrogenase, glycolate oxidase, and narbonin, a protein without any known enzymatic activity. The backbone of the alpha/beta-barrel has a distinct electrostatic field pattern, which is dipolar along the barrel axis. When the side chains are included in the calculations the general effect is to modulate the electrostatic pattern so that the electrostatic field is generally enhanced and is focused into a specific area near the active site. We use the electrostatic flux through a square surface near the active site to gauge the functionally relevant magnitude of the electrostatic field. The calculations reveal that in six out of the seven cases the backbone itself contributes greater than 45\% of the total flux. The substantial electrostatic contribution of the backbone correlates with the known preference of alpha/beta-barrel enzymes for negatively charged substrates.},
	keywords = {Alcohol Oxidoreductases, Enzymes, Fructose-Bisphosphate Aldolase, Globulins, Models, Molecular, Oxidoreductases, N-Demethylating, Protein Folding, Protein Structure, Secondary, Pyruvate Kinase, Racemases and Epimerases, Static Electricity, Triose-Phosphate Isomerase, Vegetable Proteins},
	issn = {0961-8368},
	doi = {10.1002/pro.5560060905},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Backbone+makes+a+significant+contribution+to+the+electrostatics+of+alpha\%2Fbeta-barrel+proteins},
	author = {Raychaudhuri, S and Younas, F and Karplus, P A and Faerman, C H and Ripoll, D R}
}
@article {1109376,
	title = {Stabilized bubbles in the body: pressure-radius relationships and the limits to stabilization},
	journal = {J Appl Physiol (1985)},
	volume = {82},
	number = {6},
	year = {1997},
	month = {1997 Jun},
	pages = {2045-53},
	abstract = {We previously outlined the fundamental principles that govern behavior of stabilized bubbles, such as the microbubbles being put forward as ultrasound contrast agents. Our present goals are to develop the idea that there are limits to the stabilization and to provide a conceptual framework for comparison of bubbles stabilized by different mechanisms. Gases diffuse in or out of stabilized bubbles in a limited and reversible manner in response to changes in the environment, but strong growth influences will cause the bubbles to cross a threshold into uncontrolled growth. Also, bubbles stabilized by mechanical structures will be destroyed if outside influences bring them below a critical small size. The in vivo behavior of different kinds of stabilized bubbles can be compared by using plots of bubble radius as a function of forces that affect diffusion of gases in or out of the bubble. The two ends of the plot are the limits for unstabilized growth and destruction; these and the curve{\textquoteright}s slope predict the bubble{\textquoteright}s practical usefulness for ultrasonic imaging or O2 carriage to tissues.},
	keywords = {Excipients, Gases, Humans, Mathematics, Models, Biological, Particle Size, Pressure},
	issn = {8750-7587},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Stabilized+bubbles+in+the+body\%3A+pressure-radius+relationships+and+the+limits+to+stabilization},
	author = {Van Liew, H D and Raychaudhuri, S}
}
@article {1109371,
	title = {Insights into the local residual entropy of proteins provided by NMR relaxation},
	journal = {Protein Sci},
	volume = {5},
	number = {12},
	year = {1996},
	month = {1996 Dec},
	pages = {2647-50},
	abstract = {A simple model is used to illustrate the relationship between the dynamics measured by NMR relaxation methods and the local residual entropy of proteins. The expected local dynamic behavior of well-packed extended amino acid side chains are described by employing a one-dimensional vibrator that encapsulates both the spatial and temporal character of the motion. This model is then related to entropy and to the generalized order parameter of the popular "model-free" treatment often used in the analysis of NMR relaxation data. Simulations indicate that order parameters observed for the methyl symmetry axes in, for example, human ubiquitin correspond to significant local entropies. These observations have obvious significance for the issue of the physical basis of protein structure, dynamics, and stability.},
	keywords = {Entropy, Humans, Magnetic Resonance Spectroscopy, Models, Theoretical, Proteins},
	issn = {0961-8368},
	doi = {10.1002/pro.5560051228},
	url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=Insights+into+the+local+residual+entropy+of+proteins+provided+by+NMR+relaxation},
	author = {Li,Z. and Raychaudhuri, S and Wand, A J}
}
@article {1540154,
	title = {Functional reconstitution of the malate carrier of barley mesophyll vacuoles in liposomes},
	journal = {Biochim Biophys Acta},
	volume = {1062},
	number = {2},
	year = {1991},
	month = {1991 Feb 25},
	pages = {271-8},
	abstract = {The malate carrier of barley (Hordeum vulgare L.) mesophyll vacuoles was highly purified by chromatography on hydroxyapatite followed by affinity-chromatography using 5-amino-1,2,3-benzenetricarboxylic acid as ligand. The carrier, reconstituted in asolectin liposomes, had properties similar to those described previously for the carrier in intact vacuoles (Martinoia, E., Fl{\"u}gge, U.I., Kaiser, G., Heber, U. and Heldt, H.W. (1985) Biochim. Biophys. Acta 806, 311-319). The apparent Km for malate uptake was 2-3 mM, and the uptake was inhibited by other carboxylic acids (preferentially tricarboxylic). The sulfhydryl reagent, p-chloromercuribenzenesulfonate, as well as the anion transport inhibitor 4,4{\textquoteright}-diisothiocyano-2,2{\textquoteright}-stilbenedisulfonic acid, also inhibited malate uptake. The transport was dependent on the membrane potential with an optimum at about 35 mV.},
	keywords = {Carrier Proteins, Cell Fractionation, Chromatography, Affinity, Chromatography, Gel, Electrophoresis, Polyacrylamide Gel, Hordeum, Intracellular Membranes, Liposomes, Malates, Membrane Potentials, Plant Proteins, Vacuoles},
	issn = {0006-3002},
	doi = {10.1016/0005-2736(91)90402-t},
	author = {Martinoia, E and Vogt, E and D Rentsch and Amrhein, N}
}
@article {1540161,
	title = {Activation and nuclear translocation of protein kinase during transsynaptic induction of tyrosine 3-monooxygenase},
	journal = {Proc Natl Acad Sci U S A},
	volume = {73},
	number = {4},
	year = {1976},
	month = {1976 Apr},
	pages = {1058-62},
	abstract = {The tyrosine-3-monooxygenase activity [L-tyrosine, tetrahydropteridine: oxygen oxidoreductase (3-hydroxylating); EC 1.14.16.2] of rat adrenal medulla is induced 20-24 hr after the injection of reserpine (16 mumol/kg intraperitoneally). This and other inducing stimuli increase the 3{\textquoteright}: 5{\textquoteright}-cyclic AMP (cAMP) content in the medulla for longer than 60 min and activate the cAMP-dependent protein kinase (ATP: protein phosphotransferase; EC 2.7.1.37) for several hours. Corticotropin (ACTH), dopamine, and propranolol do not induce the monooxygenase, but elicit an increase in the cAMP content of the medulla which fails to activate protein kinase and lasts less than 1 hr. A high- and low-molecular-weight protein kinase are separated by gel filtration from the 20,000 X g pellet extract of adrenal medulla homogenate. The activity of the low-molecular-weight enzyme is expressed as its ability to phosphorylate histone. The protein kinase activity of the pellet is increased between 3 and 17 hr after reserpine injection. Our evidence indicates that this increase is due to a translocation from cytosol to subcellular structures of a kinase that utilizes lysine-rich histone as phosphate acceptor. The protein kinase activity that is extracted from a purified nuclear fraction prepared from the adrenal medulla of rats injected 7 hr previously with reserpine is greater than that extracted from medulla of saline-treated rats.},
	keywords = {Adrenal Medulla, Animals, Cell Fractionation, Cell Nucleus, Cyclic AMP, Cytoplasm, Enzyme Activation, Enzyme Induction, Histones, Male, Molecular Weight, Protein Kinases, Rats, Reserpine, Time Factors, Tyrosine 3-Monooxygenase},
	issn = {0027-8424},
	doi = {10.1073/pnas.73.4.1058},
	author = {E Costa and Kurosawa, A and Guidotti, A}
}
@article {1540164,
	title = {Studies of oxygen binding energy to hemoglobin molecule},
	journal = {Biochem Biophys Res Commun},
	volume = {66},
	number = {4},
	year = {1975},
	month = {1975 Oct 27},
	pages = {1424-31},
	keywords = {Binding Sites, Cobalt, Hemoglobins, Humans, Hydrogen-Ion Concentration, Iron, Ligands, Mathematics, Oxygen, Oxyhemoglobins, Protein Binding, Spectrum Analysis},
	issn = {0006-291X},
	doi = {10.1016/0006-291x(75)90518-5},
	author = {Chow, Y W and Pietranico, R and Mukerji, A}
}
@article {1540158,
	title = {The active form of cytochrome P-450 from bovine adrenocortical mitochondria},
	journal = {J Biol Chem},
	volume = {250},
	number = {21},
	year = {1975},
	month = {1975 Nov 10},
	pages = {8445-8},
	abstract = {Cytochrome P-450 from bovine adrenocortical mitochondria exists in three forms of molecular weight: 850,000 (protein 16), of one-half (protein 8), and of one-quarter of this value (protein 4). The forms of the enzyme are named according to the number of subunits and all appear to be active in converting cholesterol to 3beta-hydroxy-5-pregnen-20-one (side chain cleavage) (Shikita, M., and Hall, P.F. (1973) J. Biol. Chem. 248, 5606). To determine whether all three forms are active at their characteristic molecular weights, the three cytochromes were each layered onto separate sucrose density gradients and centrifuged at 49,000 rpm for 60 min; the gradients contained all the factors necessary for side chain cleavage including one of the following substrates: cholesterol, 20S-hydroxycholesterol, and 20S,22R-dihydroxycholesterol. Regardless of the form of P-450 layered onto the gradient and regardless of the substrate, enzyme activity (side chain cleavage) was observed only in fractions corresponding to a sedimentation coefficient of 20 to 22 S which is that for protein 16. No activity was observed at S values corresponding to either protein 8 or protein 4. These findings indicate that the active form of cytochrome P-450 from adrenocortical mitochondria is that containing 16 subunits, i.e. the form in which the cytochrome is normally isolated from adrenal mitochondria. Forms consisting of eight and four subunits which can be prepared from protein 16 become active only by forming protein 16, at least in an aqueous medium in vitro.},
	keywords = {Adrenal Cortex, Adrenal Glands, Animals, Cattle, Centrifugation, Density Gradient, Cytochrome P-450 Enzyme System, Kinetics, Macromolecular Substances, Mitochondria, Molecular Weight, NADP, Temperature},
	issn = {0021-9258},
	author = {Takagi, Y and Shikita, M}
}
@article {1540155,
	title = {Delineation of the intimate details of the backbone conformation of pyridine nucleotide coenzymes in aqueous solution},
	journal = {Biochem Biophys Res Commun},
	volume = {66},
	number = {4},
	year = {1975},
	month = {1975 Oct 27},
	pages = {1173-9},
	keywords = {Fourier Analysis, Magnetic Resonance Spectroscopy, Models, Molecular, Molecular Conformation, NAD, NADP, Structure-Activity Relationship, Temperature},
	issn = {1090-2104},
	doi = {10.1016/0006-291x(75)90482-9},
	author = {Bose, K S and Sarma, R H}
}
@article {1540153,
	title = {Digitoxin metabolism by rat liver microsomes},
	journal = {Biochem Pharmacol},
	volume = {24},
	number = {17},
	year = {1975},
	month = {1975 Sep 01},
	pages = {1639-41},
	keywords = {Animals, Chromatography, Thin Layer, Digitoxigenin, Digitoxin, Hydroxylation, In Vitro Techniques, Male, Microsomes, Liver, NADP, Rats, Time Factors},
	issn = {1873-2968},
	author = {Schmoldt, A and Benthe, H F and Haberland, G}
}
@article {1540148,
	title = {Formate assay in body fluids: application in methanol poisoning},
	journal = {Biochem Med},
	volume = {13},
	number = {2},
	year = {1975},
	month = {1975 Jun},
	pages = {117-26},
	keywords = {Aldehyde Oxidoreductases, Animals, Body Fluids, Carbon Dioxide, Formates, Haplorhini, Humans, Hydrogen-Ion Concentration, Kinetics, Methanol, Methods, Pseudomonas},
	issn = {0006-2944},
	doi = {10.1016/0006-2944(75)90147-7},
	author = {Makar, A B and McMartin, K E and Palese, M and Tephly, T R}
}
@article {1540162,
	title = {Identification of adenylate cyclase-coupled beta-adrenergic receptors with radiolabeled beta-adrenergic antagonists},
	journal = {Biochem Pharmacol},
	volume = {24},
	number = {18},
	year = {1975},
	month = {1975 Sep 15},
	pages = {1651-8},
	keywords = {Adenylyl Cyclases, Adrenergic beta-Antagonists, Alprenolol, Animals, Anura, Binding Sites, Catecholamines, Cattle, Cell Membrane, Eels, Erythrocytes, Guinea Pigs, In Vitro Techniques, Isoproterenol, Kinetics, Propranolol, Receptors, Adrenergic, Stereoisomerism, Tritium},
	issn = {0006-2952},
	doi = {10.1016/0006-2952(75)90001-5},
	author = {Lefkowitz, R J}
}
@article {1540151,
	title = {Increase in acetyl CoA synthetase activity after phenobarbital treatment},
	journal = {Biochem Pharmacol},
	volume = {24},
	number = {18},
	year = {1975},
	month = {1975 Sep 15},
	pages = {1725-7},
	keywords = {Acetate-CoA Ligase, Acetylesterase, Acetylglucosamine, Animals, Coenzyme A Ligases, Cycloheximide, Glucosamine, Glutamine-Fructose-6-Phosphate Transaminase (Isomerizing), Liver, Male, Phenobarbital, Phosphotransferases, Proteins, Rats, Stimulation, Chemical},
	issn = {0006-2952},
	doi = {10.1016/0006-2952(75)90013-1},
	author = {Akamatsu, N and Nakajima, H and Ono, M and Miura, Y}
}
@article {1540152,
	title = {Inhibition of aldehyde reductase by acidic metabolites of the biogenic amines},
	journal = {Biochem Pharmacol},
	volume = {24},
	number = {18},
	year = {1975},
	month = {1975 Sep 15},
	pages = {1731-3},
	keywords = {Aldehyde Oxidoreductases, Animals, Biogenic Amines, Brain, Homovanillic Acid, In Vitro Techniques, Kinetics, NADP, Pyrimidines, Sheep},
	issn = {0006-2952},
	doi = {10.1016/0006-2952(75)90016-7},
	author = {Turner, A J and Hick, P E}
}
@article {1540157,
	title = {The interaction of SO2 with proteins},
	journal = {Environ Lett},
	volume = {9},
	number = {3},
	year = {1975},
	month = {1975},
	pages = {265-77},
	keywords = {Animals, Binding Sites, Blood Proteins, Hydrogen-Ion Concentration, Osmolar Concentration, Protein Binding, Protein Conformation, Rabbits, Spectrometry, Fluorescence, Spectrophotometry, Spectrophotometry, Ultraviolet, Sulfites, Sulfur Dioxide},
	issn = {0013-9300},
	doi = {10.1080/00139307509435855},
	author = {Eickenroht, E Y and Gause, E M and Rowlands, J R}
}
@article {1540149,
	title = {Letter: Acid secretion by gastric mucous membrane},
	journal = {Am J Physiol},
	volume = {229},
	number = {6},
	year = {1975},
	month = {1975 Dec},
	pages = {1726},
	keywords = {Animals, Gastric Juice, Gastric Mucosa, Hydrogen-Ion Concentration, Methods},
	issn = {0002-9513},
	doi = {10.1152/ajplegacy.1975.229.6.1726},
	author = {Durbin, R P}
}
@article {1540160,
	title = {Letter: Duration of action of AH8165},
	journal = {Br J Anaesth},
	volume = {47},
	number = {9},
	year = {1975},
	month = {1975 Sep},
	pages = {1033},
	keywords = {Dose-Response Relationship, Drug, Hemodynamics, Humans, Pyridinium Compounds, Time Factors},
	issn = {0007-0912},
	doi = {10.1093/bja/47.9.1033},
	author = {Thornton, J A and Harrison, M J}
}
@article {1540150,
	title = {Maturation of the adrenal medulla--IV. Effects of morphine},
	journal = {Biochem Pharmacol},
	volume = {24},
	number = {16},
	year = {1975},
	month = {1975 Aug 15},
	pages = {1469-74},
	keywords = {Adrenal Medulla, Aging, Animals, Animals, Newborn, Body Weight, Catecholamines, Dopamine beta-Hydroxylase, Epinephrine, Female, Humans, In Vitro Techniques, Maternal-Fetal Exchange, Metaraminol, Morphine, Morphine Dependence, Pregnancy, Rats, Tyrosine 3-Monooxygenase},
	issn = {1873-2968},
	doi = {10.1016/0006-2952(75)90020-9},
	author = {Randerson, James, T and Slotkin, T A}
}
@article {1540159,
	title = {Metal substitutions incarbonic anhydrase: a halide ion probe study},
	journal = {Biochem Biophys Res Commun},
	volume = {66},
	number = {4},
	year = {1975},
	month = {1975 Oct 27},
	pages = {1281-6},
	keywords = {Animals, Binding Sites, Cadmium, Carbonic Anhydrases, Cattle, Humans, Hydrogen-Ion Concentration, Magnetic Resonance Spectroscopy, Mercury, Protein Binding, Protein Conformation, Zinc},
	issn = {0006-291X},
	doi = {10.1016/0006-291x(75)90498-2},
	author = {Smith, R J and Bryant, R G}
}
@article {1540156,
	title = {Pleural effusion associated with aortitis syndrome},
	journal = {Chest},
	volume = {68},
	number = {6},
	year = {1975},
	month = {1975 Dec},
	pages = {826-8},
	abstract = {A patient with aortitis syndrome had a pleural effusion which subsided but reappeared with an exacerbation of aortitis symptoms while under antituberculosis treatment. The character of the fluid was that of an exudate, and the glucose concentration was normal. Clinical and laboratory features of the case suggest that the effusion was part of the aortitis syndrome per se.},
	keywords = {Adult, Aortic Arch Syndromes, Humans, Male, Pleural Effusion, Takayasu Arteritis, Tuberculosis, Pleural},
	issn = {0012-3692},
	doi = {10.1378/chest.68.6.826},
	author = {Kawai, T and Y. Yamada and Tsuneda, J and Aoyagi, T and Mikata, A}
}
@article {1540163,
	title = {Studies of oxygen binding energy to hemoglobin molecule},
	journal = {Biochem Biophys Res Commun},
	volume = {66},
	number = {4},
	year = {1975},
	month = {1975 Oct 27},
	pages = {1424-31},
	keywords = {Binding Sites, Cobalt, Hemoglobins, Humans, Hydrogen-Ion Concentration, Iron, Ligands, Mathematics, Oxygen, Oxyhemoglobins, Protein Binding, Spectrum Analysis},
	issn = {0006-291X},
	doi = {10.1016/0006-291x(75)90518-5},
	author = {Chow, Y W and Pietranico, R and Mukerji, A}
}
