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- Okada, Yukinori, et al.
(author)
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Genetics of rheumatoid arthritis contributes to biology and drug discovery
- 2014
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In: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 506:7488, s. 376-381
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Journal article (peer-reviewed)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)(1). 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 similar to 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(5), cis-acting expression quantitative trait loci(6) and pathway analyses(7-9)-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.
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2. |
- Han, Buhm, et al.
(author)
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Fine Mapping Seronegative and Seropositive Rheumatoid Arthritis to Shared and Distinct HLA Alleles by Adjusting for the Effects of Heterogeneity
- 2014
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In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 94:4, s. 522-532
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Journal article (peer-reviewed)abstract
- Despite progress in defining human leukocyte antigen (HLA) alleles for anti-citrullinated-protein-autoantibody-positive (ACPA(+)) rheumatoid arthritis (RA), identifying HLA alleles for ACPA-negative (ACPA(-)) RA has been challenging because of clinical heterogeneity within clinical cohorts. We imputed 8,961 classical HLA alleles, amino acids, and SNPs from Immunochip data in a discovery set of 2,406 ACPA(-) RA case and 13,930 control individuals. We developed a statistical approach to identify and adjust for clinical heterogeneity within ACPA RA and observed independent associations for serine and leucine at position 11 in HLA-DR beta 1 (p = 1.4 x 10 (13), odds ratio [OR] = 1.30) and for aspartate at position 9 in HLA-B (p = 2.7 x 10(-12), OR = 1.39) within the peptide binding grooves. These amino acid positions induced associations at HLA-DRB1*03 (encoding serine at 11) and HLA-B*08 (encoding aspartate at 9). We validated these findings in an independent set of 427 ACPA(-) case subjects, carefully phenotyped with a highly sensitive ACPA assay, and 1,691 control subjects (HLA-DR beta 1 Ser11+Leu11: p = 5.8 x 10(-4), OR = 1.28; HLA-B Asp9: p = 2.6 x 10(-3), OR = 1.34). Although both amino acid sites drove risk of ACPA(+) and ACPA(-) disease, the effects of individual residues at HLA-DR beta 1 position 11 were distinct (p < 2.9 x 10(-107)). We also identified an association with ACPA(+) RA at HLA-A position 77 (p = 2.7 x 10(-8), OR = 0.85) in 7,279 ACPA(+) RA case and 15,870 control subjects. These results contribute to mounting evidence that ACPA(+) and ACPA(-) RA are genetically distinct and potentially have separate autoantigens contributing to pathogenesis. We expect that our approach might have broad applications in analyzing clinical conditions with heterogeneity at both major histocompatibility complex (MHC) and non-MHC regions.
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