Genetics of rheumatoid arthritis contributes to biology and drug discovery.
Genetics of rheumatoid arthritis contributes to biology and drug discovery.
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作者：
人类遗传学的一个主要挑战是设计一个系统的策略，将疾病相关的变异与不同的基因组和生物数据集整合，以深入了解疾病的发病机制，并指导药物发现复杂的性状，如类风湿性关节炎（RA）。在这里，我们通过评估约1000万个单核苷酸多态性（SNP），对总计> 100，000名欧洲和亚洲血统的受试者（29，880例RA病例和73，758例对照）进行了全基因组关联研究（GWAS）荟萃分析。我们在全基因组水平上发现了42个新的RA风险位点，使总数达到101个。我们设计了一个基于功能注释，顺式作用表达数量性状基因座（cis-eQTL）和途径分析的生物信息学方法，以及基于与人类原发性免疫缺陷（PID），血液癌体细胞突变和敲除小鼠表型的遗传重叠的新方法，以确定这101个风险基因座的98个生物候选基因。我们证明了这些基因是批准的RA治疗的靶点，并进一步表明批准用于其他适应症的药物可能被重新用于治疗RA。总之，这项全面的遗传学研究揭示了有助于RA发病机制的基本基因、途径和细胞类型，并提供了经验证据，表明RA的遗传学可以为药物发现提供重要信息。
A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological datasets 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 (GWAS) 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 (SNPs). We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101. We devised an in-silico pipeline using established bioinformatics methods based on functional annotation, cis-acting expression quantitative trait loci (cis-eQTL), and pathway analyses – as well as novel methods based on genetic overlap with human primary immunodeficiency (PID), hematological cancer somatic mutations and knock-out 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.
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影响因子：
30.8
作者：
Westra, Harm-Jan;Peters, Marjolein J.;Esko, Tonu;Yaghootkar, Hanieh;Schurmann, Claudia;Kettunen, Johannes;Christiansen, Mark W.;Fairfax, Benjamin P.;Schramm, Katharina;Powell, Joseph E.;Zhernakova, Alexandra;Zhernakova, Daria V.;Veldink, Jan H.;Van den Berg, Leonard H.;Karjalainen, Juha;Withoff, Sebo;Uitterlinden, Andre G.;Hofman, Albert;Rivadeneira, Fernando;'t Hoen, Peter A. C.;Reinmaa, Eva;Fischer, Krista;Nelis, Mari;Milani, Lili;Melzer, David;Ferrucci, Luigi;Singleton, Andrew B.;Hernandez, Dena G.;Nalls, Michael A.;Homuth, Georg;Nauck, Matthias;Radke, Doerte;Voelker, Uwe;Perola, Markus;Salomaa, Veikko;Brody, Jennifer;Suchy-Dicey, Astrid;Gharib, Sina A.;Enquobahrie, Daniel A.;Lumley, Thomas;Montgomery, Grant W.;Makino, Seiko;Prokisch, Holger;Herder, Christian;Roden, Michael;Grallert, Harald;Meitinger, Thomas;Strauch, Konstantin;Li, Yang;Jansen, Ritsert C.;Visscher, Peter M.;Knight, Julian C.;Psaty, Bruce M.;Ripatti, Samuli;Teumer, Alexander;Frayling, Timothy M.;Metspalu, Andres;van Meurs, Joyce B. J.;Franke, Lude
通讯作者：
Franke, Lude
影响因子：
4.5
作者：
Rossin EJ;Lage K;Raychaudhuri S;Xavier RJ;Tatar D;Benita Y;International Inflammatory Bowel Disease Genetics Constortium;Cotsapas C;Daly MJ
通讯作者：
Daly MJ
来自1,092个人基因组的遗传变异的综合图。
影响因子：
64.8
作者：
通讯作者：
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影响因子：
30.8
作者：
通讯作者：
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影响因子：
30.8
作者：
Trynka, Gosia;Sandor, Cynthia;Han, Buhm;Xu, Han;Stranger, Barbara E.;Liu, X. Shirley;Raychaudhuri, Soumya
通讯作者：
Raychaudhuri, Soumya