A genome-wide association study meta-analysis of more than 100,000 subjects of European and Asian ancestries reveals 42 new risk loci for rheumatoid arthritis, with follow-up studies identifying 98 biological candidate genes that are either already being targeted by drugs or could be in the future. Virtual screening in a genome-wide association study (GWAS) meta-analysis of more than 100,000 subjects of European and Asian ancestries has revealed 42 previously unknown risk loci for rheumatoid arthritis (RA). As a follow-up, the authors developed a new in silico pipeline to identify 98 biological candidate genes at all known RA risk loci. They show 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. 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)1. Here we performed a genome-wide association study meta-analysis in a total of >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, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7,8,9—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.

Copy number variants (CNVs) account for a major proportion of human genetic polymorphism and have been predicted to have an important role in genetic susceptibility to common disease. To address this we undertook a large, direct genome-wide study of association between CNVs and eight common human diseases. Using a purpose-designed array we typed ∼19,000 individuals into distinct copy-number classes at 3,432 polymorphic CNVs, including an estimated ∼50% of all common CNVs larger than 500 base pairs. We identified several biological artefacts that lead to false-positive associations, including systematic CNV differences between DNAs derived from blood and cell lines. Association testing and follow-up replication analyses confirmed three loci where CNVs were associated with disease—IRGM for Crohn’s disease, HLA for Crohn’s disease, rheumatoid arthritis and type 1 diabetes, and TSPAN8 for type 2 diabetes—although in each case the locus had previously been identified in single nucleotide polymorphism (SNP)-based studies, reflecting our observation that most common CNVs that are well-typed on our array are well tagged by SNPs and so have been indirectly explored through SNP studies. We conclude that common CNVs that can be typed on existing platforms are unlikely to contribute greatly to the genetic basis of common human diseases.

Jane Worthington and colleagues use a high-density genotyping chip to identify new susceptibility loci for rheumatoid arthritis and examine genetic overlap with other autoimmune diseases. Their results increase the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry and refine the location of many previously identified association signals to single genes. Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

The Study Group for Risk Factors for Rheumatoid Arthritis was established by the EULAR Standing Committee on Investigative Rheumatology to facilitate research into the preclinical and earliest clinically apparent phases of rheumatoid arthritis (RA). This report describes the recommendation for terminology to be used to define specific subgroups during different phases of disease, and defines the priorities for research in this area. Terminology was discussed by way of a three-stage structured process: A provisional list of descriptors for each of the possible phases preceding the diagnosis of RA were circulated to members of the study group for review and feedback. Anonymised comments from the members on this list were fed back to participants before a 2-day meeting. 18 participants met to discuss these data, agree terminologies and prioritise important research questions. The study group recommended that, in prospective studies, individuals without RA are described as having: genetic risk factors for RA; environmental risk factors for RA; systemic autoimmunity associated with RA; symptoms without clinical arthritis; unclassified arthritis; which may be used in a combinatorial manner. It was recommended that the prefix ‘pre-RA with:’ could be used before any/any combination of the five points above but only to describe retrospectively a phase that an individual had progressed through once it was known that they have developed RA. An approach to dating disease onset was recommended. In addition, important areas for research were proposed, including research of other tissues in which an adaptive immune response may be initiated, and the identification of additional risk factors and biomarkers for the development of RA, its progression and the development of extra-articular features. These recommendations provide guidance on approaches to describe phases before the development of RA that will facilitate communication between researchers and comparisons between studies. A number of research questions have been defined, requiring new cohorts to be established and new techniques to be developed to image and collect material from different sites.