Genetics of rheumatoid arthritis contributes to biology and drug discovery
By Yukinori Okada, Di Wu, G. Trynka, T. Raj, C. Terao, K. Ikari, Y. Kochi, K. Ohmura, A. Suzuki, S. Yoshida and 85 more. Nature, 2013
742 citations recorded by the source corpus.
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.
Subfields: Genetics, Oncology, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/7fa569052bb636a298305e5ebf304d40857088f5
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Citations in the corpus
- Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics (2016, methodology): “Gene scores were computed on two GWAS (one HapMap imputed[23], one 1KG imputed[22,25]) for 18,132 genes on a single core.”
- Research review: Polygenic methods and their application to psychiatric traits. (2014, background): “For example, genes identified through GWAS associated with variation in LDL levels are the targets of statins (Teslovich et al., 2010) and those associated with rheumatoid arthritis are the targets of known drugs that are effective therapies for this disease (Okada et al., 2013).”
- Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks (2015, background): “Among the agreements with PICS was rs4409785, associated with vitiligo (Jin et al. 2012), rheumatoid arthritis (Okada et al. 2013), and immune mechanisms in multiple sclerosis (Sawcer et al. 2011).”
- Partitioning heritability by functional annotation using genome-wide association summary statistics (2015, neutral): “• Rheumatoid arthritis summary statistics [35]: http://plaza.”
- Immunopathogenesis of rheumatoid arthritis (2017, positive): “RA-associated SNPs tend to cluster around immune genes (Okada et al., 2014).”