Genetics of rheumatoid arthritis contributes to biology and drug discovery

Okada, Yukinori, Wu, Di, Trynka, Gosia, Raj, Towfique, Terao, Chikashi, Ikari, Katsunori, Kochi, Yuta, Ohmura, Koichiro, Suzuki, Akari, Yoshida, Shinji, Graham, Robert R., Manoharan, Arun, Ortmann, Ward, Bhangale, Tushar, Denny, Joshua C., Carroll, Robert J., Eyler, Anne E., Greenberg, Jeffrey D., Kremer, Joel M., Pappas, Dimitrios A., Jiang, Lei, Yin, Jian, Ye, Lingying, Su, Ding-Feng, Yang, Jian, Xie, Gang, Keystone, Ed, Westra, Harm-Jan, Esko, Tonu, Metspalu, Andreas, Zhou, Xuezhong, Gupta, Namrata, Mirel, Daniel, Stahl, Eli A., Diogo, Dorothee, Cui, Jing, Liao, Katherine, Guo, Michael H., Myouzen, Keiko, Kawaguchi, Takahisa, Coenen, Marieke J.H., van Riel, Piet L.C.M., van De Laar, Mart A.F.J., Guchelaar, Henk-Jan, Huizinga, Tom W.J., Dieude, Philippe, Mariette, Xavier, Bridges, S. Louise, Zhernakova, Alexandra, Toes, Rene E.M., Tak, Paul P., Miceli-Richard, Corinne, Bang, So-Young, Lee, Hye-Soon, Martin, Javier, Gonzalez-Gay, Miguel A., Rodriguez-Rodriguez, Luis, Rantapaa-Dahlqvist, Solbritt, Arlestig, Lisbeth, Choi, Hyon K., Kamatani, Yoichiro, Galan, Pilar, Lathrop, Mark, RACI consortium, GARNET consortium, Visscher, Peter M. and Brown, Matthew A. (2014) Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature, 506 7488: 376-381. doi:10.1038/nature12873

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads
UQ325199_OA.pdf Full text (open access) application/pdf 3.08MB 0

Author Okada, Yukinori
Wu, Di
Trynka, Gosia
Raj, Towfique
Terao, Chikashi
Ikari, Katsunori
Kochi, Yuta
Ohmura, Koichiro
Suzuki, Akari
Yoshida, Shinji
Graham, Robert R.
Manoharan, Arun
Ortmann, Ward
Bhangale, Tushar
Denny, Joshua C.
Carroll, Robert J.
Eyler, Anne E.
Greenberg, Jeffrey D.
Kremer, Joel M.
Pappas, Dimitrios A.
Jiang, Lei
Yin, Jian
Ye, Lingying
Su, Ding-Feng
Yang, Jian
Xie, Gang
Keystone, Ed
Westra, Harm-Jan
Esko, Tonu
Metspalu, Andreas
Zhou, Xuezhong
Gupta, Namrata
Mirel, Daniel
Stahl, Eli A.
Diogo, Dorothee
Cui, Jing
Liao, Katherine
Guo, Michael H.
Myouzen, Keiko
Kawaguchi, Takahisa
Coenen, Marieke J.H.
van Riel, Piet L.C.M.
van De Laar, Mart A.F.J.
Guchelaar, Henk-Jan
Huizinga, Tom W.J.
Dieude, Philippe
Mariette, Xavier
Bridges, S. Louise
Zhernakova, Alexandra
Toes, Rene E.M.
Tak, Paul P.
Miceli-Richard, Corinne
Bang, So-Young
Lee, Hye-Soon
Martin, Javier
Gonzalez-Gay, Miguel A.
Rodriguez-Rodriguez, Luis
Rantapaa-Dahlqvist, Solbritt
Arlestig, Lisbeth
Choi, Hyon K.
Kamatani, Yoichiro
Galan, Pilar
Lathrop, Mark
RACI consortium
GARNET consortium
Visscher, Peter M.
Brown, Matthew A.
Title Genetics of rheumatoid arthritis contributes to biology and drug discovery
Journal name Nature   Check publisher's open access policy
ISSN 0028-0836
Publication date 2014-01-01
Year available 2013
Sub-type Article (original research)
DOI 10.1038/nature12873
Open Access Status File (Author Post-print)
Volume 506
Issue 7488
Start page 376
End page 381
Total pages 6
Place of publication London, United Kingdom
Publisher Nature Publishing Group
Language eng
Subject 1000 General
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 >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 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.
Keyword Multidisciplinary Sciences
Science & Technology - Other Topics
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID R01-AR057108
K08 AR060257
P60 AR047785
R01 AR059648
T15 LM007450
U19 HL065962
U01 GM092691
K24 AR052403
R01 AR057108
R01 AR063759
R21 AR056042
R01 AR056768
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Brain Institute Publications
Official 2014 Collection
UQ Diamantina Institute Publications
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 459 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 524 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Tue, 11 Mar 2014, 11:11:46 EST by System User on behalf of UQ Diamantina Institute