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Genetics of rheumatoid arthritis contributes to biology and drug discovery.

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.

SUBMITTER: Okada Y

PROVIDER: S-EPMC3944098 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature

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Genetics of rheumatoid arthritis contributes to biology and drug discovery.

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

Nature 20131225 7488

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 polymo ...[more]

PMID: 24390342

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Project description: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?=?1.4×10(-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-?B transcription factor. Finally, we develop a high-throughput NF-?B 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-?B 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.

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Genetics of rheumatoid arthritis contributes to biology and drug discovery.

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Genetics of rheumatoid arthritis contributes to biology and drug discovery.

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