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Unraveling the polygenic architecture of complex traits using blood eQTL meta-analysis
Marc Jan Bonder,
Benjamin P Fairfax,
Bastiaan T. Heijmans,
Julian C Knight,
Urko M Marigorta,
Eline P Slagboom,
Coen D.A. Stehouwer,
Peter A.C. ‘t Hoen,
Jenny van Dongen,
Maarten van Iterson,
Grant W. Montgomery,
Joyce van Meurs,
Bruce M. Psaty,
Sina A. Gharib,
Peter M Visscher,
Posted 19 Oct 2018
bioRxiv DOI: 10.1101/447367
Posted 19 Oct 2018
While many disease-associated variants have been identified through genome-wide association studies, their downstream molecular consequences remain unclear. To identify these effects, we performed cis- and trans-expression quantitative trait locus (eQTL) analysis in blood from 31,684 individuals through the eQTLGen Consortium. We observed that cis-eQTLs can be detected for 88% of the studied genes, but that they have a different genetic architecture compared to disease-associated variants, limiting our ability to use cis-eQTLs to pinpoint causal genes within susceptibility loci. In contrast, trans-eQTLs (detected for 37% of 10,317 studied trait-associated variants) were more informative. Multiple unlinked variants, associated to the same complex trait, often converged on trans-genes that are known to play central roles in disease etiology. We observed the same when ascertaining the effect of polygenic scores calculated for 1,263 genome-wide association study (GWAS) traits. Expression levels of 13% of the studied genes correlated with polygenic scores, and many resulting genes are known to drive these traits.
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