4.8 Article

Systematic identification of trans eQTLs as putative drivers of known disease associations

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NATURE GENETICS
卷 45, 期 10, 页码 1238-U195

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NATURE PUBLISHING GROUP
DOI: 10.1038/ng.2756

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资金

  1. MRC [G0500070] Funding Source: UKRI
  2. Intramural NIH HHS [Z99 AG999999] Funding Source: Medline
  3. Medical Research Council [G0500070] Funding Source: Medline
  4. NHLBI NIH HHS [R01 HL085251, R01 HL073410] Funding Source: Medline
  5. Wellcome Trust [090532] Funding Source: Medline
  6. Medical Research Council [G0500070] Funding Source: researchfish
  7. National Institute for Health Research [ACF-2008-13-017, CL-2012-13-004] Funding Source: researchfish

向作者/读者索取更多资源

Identifying the downstream effects of disease-associated SNPs is challenging. To help overcome this problem, we performed expression quantitative trait locus (eQTL) meta-analysis in non-transformed peripheral blood samples from 5,311 individuals with replication in 2,775 individuals. We identified and replicated trans eQTLs for 233 SNPs (reflecting 103 independent loci) that were previously associated with complex traits at genome-wide significance. Some of these SNPs affect multiple genes in trans that are known to be altered in individuals with disease: rs4917014, previously associated with systemic lupus erythematosus (SLE)(1), altered gene expression of C1QB and five type I interferon response genes, both hallmarks of SLE2-4. DeepSAGE RNA sequencing showed that rs4917014 strongly alters the 3' UTR levels of IKZF1 in cis, and chromatin immunoprecipitation and sequencing analysis of the trans-regulated genes implicated IKZF1 as the causal gene. Variants associated with cholesterol metabolism and type 1 diabetes showed similar phenomena, indicating that large-scale eQTL mapping provides insight into the downstream effects of many trait-associated variants.

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