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Nature Research, Nature Genetics, 10(45), p. 1238-1243, 2013

DOI: 10.1038/ng.2756

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

Journal article published in 2013 by Harm-Jan Westra ORCID, Marjolein J. Peters, Tonu Esko ORCID, Hanieh Yaghootkar, Claudia Schurmann ORCID, Johannes Kettunen, Mark W. Christiansen, Benjamin P. Fairfax, Katharina Schramm, Joseph E. Powell ORCID, Alexandra Zhernakova, Daria V. Zhernakova, Jan H. Veldink, Leonard H. Van den Berg, Juha Karjalainen and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Identifying the downstream effects of disease-associated single nucleotide polymorphisms (SNPs) is challenging: the causal gene is often unknown or it is unclear how the SNP affects the causal gene, making it difficult to design experiments that reveal functional consequences. To help overcome this problem, we performed the largest expression quantitative trait locus (eQTL) meta-analysis so far reported in non-transformed peripheral blood samples of 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. Although we did not study specific patient cohorts, we identified trait-associated SNPs that affect multiple trans-genes that are known to be markedly altered in patients: for example, systemic lupus erythematosus (SLE) SNP rs49170141 altered C1QB and five type 1 interferon response genes, both hallmarks of SLE2-4. Subsequent ChIP-seq data analysis on these trans-genes implicated transcription factor IKZF1 as the causal gene at this locus, with DeepSAGE RNA-sequencing revealing that rs4917014 strongly alters 3’ UTR levels of IKZF1. 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.