Impact of common regulatory single-nucleotide variants on gene expression profiles in whole blood.
- Authors
- Mehta, Divya; Heim, Katharina; Herder, Christian; Carstensen, Maren; Eckstein, Gertrud; Schurmann, Claudia; Homuth, Georg; Nauck, Matthias; Völker, Uwe; Roden, Michael; Illig, Thomas; Gieger, Christian; Meitinger, Thomas; Prokisch, Holger
- Year
- 2013
- Journal
- European journal of human genetics : EJHG
- PMID
- 22692066
- DOI
- 10.1038/ejhg.2012.106
- PMCID
- PMC3522194
Genome-wide association studies (GWASs) have uncovered susceptibility loci for a large number of complex traits. Functional interpretation of candidate genes identified by GWAS and confident assignment of the causal variant still remains a major challenge. Expression quantitative trait (eQTL) mapping has facilitated identification of risk loci for quantitative traits and might allow prioritization of GWAS candidate genes. One major challenge of eQTL studies is the need for larger sample numbers and replication. The aim of this study was to evaluate the robustness and reproducibility of whole-blood eQTLs in humans and test their value in the identification of putative functional variants involved in the etiology of complex traits. In the current study, we performed comphrehensive eQTL mapping from whole blood. The discovery sample included 322 Caucasians from a general population sample (KORA F3). We identified 363 cis and 8 trans eQTLs after stringent Bonferroni correction for multiple testing. Of these, 98.6% and 50% of cis and trans eQTLs, respectively, could be replicated in two independent populations (KORA F4 (n=740) and SHIP-TREND (n=653)). Furthermore, we identified evidence of regulatory variation for SNPs previously reported to be associated with disease loci (n=59) or quantitative trait loci (n=20), indicating a possible functional mechanism for these eSNPs. Our data demonstrate that eQTLs in whole blood are highly robust and reproducible across studies and highlight the relevance of whole-blood eQTL mapping in prioritization of GWAS candidate genes in humans.
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