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Sökning: WFRF:(John Denny) > (2010-2014)

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1.
  • Postmus, Iris, et al. (författare)
  • Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins.
  • 2014
  • Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 5
  • Tidskriftsartikel (refereegranskat)abstract
    • Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.
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2.
  • Okada, Yukinori, et al. (författare)
  • Genetics of rheumatoid arthritis contributes to biology and drug discovery
  • 2014
  • Ingår i: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 506:7488, s. 376-381
  • Tidskriftsartikel (refereegranskat)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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