DESCRIPTION:

List of positional candidate genes after correcting for multiple testing and controlling the false discovery rate from genome wide association studies (GWAS) retrieved from the NHGRI-EBI Catalog of published genome-wide association studies (http://www.ebi.ac.uk/gwas/). The disease/trait examined in this study, as reported by the authors, was Rheumatoid arthritis. The EFO term rheumatoid arthritis was annotated to this set after curation by NHGRI-EBI. Intergenic SNPS were mapped to both the upstream and downstream gene. P-value uploaded. This gene set was generated using gwas2gs v. 0.1.8 and the GWAS Catalog v. 1.0.1.

LABEL:

GWAS: rheumatoid arthritis

SCORE TYPE:

P-Value

THRESHOLD:

<= 0.05

GENES IN THRESHOLD:

139

DATE ADDED:

2017-05-02

DATE UPDATED:

2024-10-22

SPECIES:

AUTHORS:

Y Okada, D Wu, G Trynka, T Raj, C Terao, K Ikari, Y Kochi, K Ohmura, A Suzuki, S Yoshida, RR Graham, A Manoharan, W Ortmann, T Bhangale, JC Denny, RJ Carroll, AE Eyler, JD Greenberg, JM Kremer, DA Pappas, L Jiang, J Yin, L Ye, DF Su, J Yang, G Xie, E Keystone, HJ Westra, T Esko, A Metspalu, X Zhou, N Gupta, D Mirel, EA Stahl, D Diogo, J Cui, K Liao, MH Guo, K Myouzen, T Kawaguchi, MJ Coenen, PL van Riel, MA van de Laar, HJ Guchelaar, TW Huizinga, P Dieudé, X Mariette, SL Bridges, A Zhernakova, RE Toes, PP Tak, C Miceli-Richard, SY Bang, HS Lee, J Martin, MA Gonzalez-Gay, L Rodriguez-Rodriguez, S Rantapää-Dahlqvist, L Arlestig, HK Choi, Y Kamatani, P Galan, M Lathrop, S Eyre, J Bowes, A Barton, N de Vries, LW Moreland, LA Criswell, EW Karlson, A Taniguchi, R Yamada, M Kubo, JS Liu, SC Bae, J Worthington, L Padyukov, L Klareskog, PK Gregersen, S Raychaudhuri, BE Stranger, PL De Jager, L Franke, PM Visscher, MA Brown, H Yamanaka, T Mimori, A Takahashi, H Xu, TW Behrens, KA Siminovitch, S Momohara, F Matsuda, K Yamamoto, RM Plenge

TITLE:

Genetics of rheumatoid arthritis contributes to biology and drug discovery.

JOURNAL:

Nature Feb 2014, Vol 506, pp. 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 >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. PUBMED: 24390342
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