Genetics of rheumatoid arthritis contributes to biology and drug discovery

Yukinori Okada, Di Wu, Gosia Trynka, Towfique Raj, Chikashi Terao, Katsunori Ikari, Yuta Kochi, Koichiro Ohmura, Akari Suzuki, Shinji Yoshida, Robert R. Graham, Arun Manoharan, Ward Ortmann, Tushar Bhangale, Joshua C. Denny, Robert J. Carroll, Anne E. Eyler, Jeffrey D. Greenberg, Joel M. Kremer, Dimitrios A. Pappas, Lei Jiang, Jian Yin, Lingying Ye, Ding-Feng Su, Jian Yang, Gang Xie, Ed Keystone, Harm-Jan Westra, Tõnu Esko, Andres Metspalu, Xuezhong Zhou, Namrata Gupta, Daniel Mirel, Eli A. Stahl, Dorothée Diogo, Jing Cui, Katherine Liao, Michael H. Guo, Keiko Myouzen, Takahisa Kawaguchi, Marieke J. H. Coenen, Piet L. C. M. van Riel, Mart A. F. J. van de Laar, Henk-Jan Guchelaar, Tom W. J. Huizinga, Philippe Dieudé, Xavier Mariette, S. Louis Bridges Jr, Alexandra Zhernakova, Rene E. M. Toes, Paul P. Tak, Corinne Miceli-Richard, So-Young Bang, Hye-Soon Lee, Javier Martin, Miguel A. Gonzalez-Gay, Luis Rodriguez-Rodriguez, Solbritt Rantapää-Dahlqvist, Lisbeth Ärlestig, Hyon K. Choi, Yoichiro Kamatani, Pilar Galan, Mark Lathrop, Steve Eyre, John Bowes, Anne Barton, Niek de Vries, Larry W. Moreland, Lindsey A. Criswell, Elizabeth W. Karlson, Atsuo Taniguchi, Ryo Yamada, Michiaki Kubo, Jun S. Liu, Sang-Cheol Bae, Jane Worthington, Leonid Padyukov, Lars Klareskog, Peter K. Gregersen, Soumya Raychaudhuri, Barbara E. Stranger, Philip L. De Jager, Lude Franke, Peter M. Visscher, Matthew A. Brown, Hisashi Yamanaka, Tsuneyo Mimori, Atsushi Takahashi, Huji Xu, Timothy W. Behrens, Katherine A. Siminovitch, Shigeki Momohara, Fumihiko Matsuda, Kazuhiko Yamamoto, Robert M. Plenge

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 >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.