Exploiting the GTEx resources to decipher the mechanisms at GWAS loci

Alvaro Barbeira(University of Chicago), Rodrigo Bonazzola(University of Chicago), Eric R. Gamazon(Vanderbilt University), Yanyu Liang(University of Chicago), YoSon Park(Translational Therapeutics (United States)), Sarah Kim-Hellmuth(Max Planck Institute of Psychiatry), Gao Wang(University of Chicago), Zhuoxun Jiang(University of Chicago), Dan Zhou(Vanderbilt University Medical Center), Farhad Hormozdiari(Broad Institute), Boxiang Liu(Stanford University), Abhiram Rao(Stanford University), Andrew R. Hamel(Broad Institute), Milton Pividori(University of Chicago), François Aguet(Broad Institute), GTEx GWAS Working Group(Vanderbilt University), Lisa Bastarache(Vanderbilt University), Daniel M. Jordan(Icahn School of Medicine at Mount Sinai), Marie Verbanck(Université Sorbonne Paris Nord), Ron Do(University of Chicago), Matthew Stephens(Broad Institute), Kristin Ardlie(Broad Institute), Mark McCarthy(University of Oxford), Stephen B. Montgomery(Broad Institute), Ayellet V. Segrè(Broad Institute), Christopher D. Brown(New York Genome Center), Tuuli Lappalainen(University of Michigan), Xiaoquan Wen(University of Michigan), Hae Kyung Im(University of Chicago)
Genome biology
January 26, 2021
Cited by 334Open Access
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Abstract

The resources generated by the GTEx consortium offer unprecedented opportunities to advance our understanding of the biology of human diseases. Here, we present an in-depth examination of the phenotypic consequences of transcriptome regulation and a blueprint for the functional interpretation of genome-wide association study-discovered loci. Across a broad set of complex traits and diseases, we demonstrate widespread dose-dependent effects of RNA expression and splicing. We develop a data-driven framework to benchmark methods that prioritize causal genes and find no single approach outperforms the combination of multiple approaches. Using colocalization and association approaches that take into account the observed allelic heterogeneity of gene expression, we propose potential target genes for 47% (2519 out of 5385) of the GWAS loci examined.


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