Genetic analysis of blood molecular phenotypes reveals regulatory networks affecting complex traits: a DIRECT study.
Andrew Anand BrowniD, Juan J. Fernandez-TajesiD, Mun‐Gwan HongiD, Caroline BrorssoniD, Robert Wilhelm KoivulaiD, David DavtianiD, Théo DupuisiD, Ambra Sartori, Theodora-Dafni MichalettouiD, Ian M. ForgieiD, Jonathan AdamiD, Kristine Højgaard AlliniD, Robert J. CaiazzoiD, Henna CederbergiD, Federico De MasiiD, Petra J. M. EldersiD, Giuseppe Nicola GiordanoiD, Mark HaidiD, Torben F. HanseniD, Tue H. HanseniD, Andrew Tym HattersleyiD, Alison J. HeggieiD, Cédric HowaldiD, Angus G. JonesiD, Tarja KokkolaiD, , Ulrik Plesner JacobseniD
Abstract
Genetic variants identified by genome-wide association studies can contribute to disease risk by altering the production and abundance of mRNA, proteins and other molecules. However, the interplay between molecular intermediaries that define the pathway from genetic variation to disease is not well understood. Here, we evaluated the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3,029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant was associated with multiple molecular phenotypes over multiple genomic regions. We find varying proportions of shared genetic regulation across phenotypes, highest between expression and proteins (66.6%). We were able to recapitulate a substantial proportion of gene expression genetic regulation in a diverse set of 44 tissues, with a median of 88% shared associations for blood expression and 22.3% for plasma proteins. Finally, the genetic and molecular associations were represented in networks including 2,828 known GWAS variants. One sub-network shows the trans relationship between rs149007767 and RTEN, and identifies GRB10 and IKZF1 as candidates mediating genes. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants across different molecular phenotypes.
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