PT - JOURNAL ARTICLE AU - Alvaro N Barbeira AU - Rodrigo Bonazzola AU - Eric R Gamazon AU - Yanyu Liang AU - YoSon Park AU - Sarah Kim-Hellmuth AU - Gao Wang AU - Zhuoxun Jiang AU - Dan Zhou AU - Farhad Hormozdiari AU - Boxiang Liu AU - Abhiram Rao AU - Andrew R Hamel AU - Milton D Pividori AU - François Aguet AU - GTEx GWAS Working Group AU - Lisa Bastarache AU - Daniel M Jordan AU - Marie Verbanck AU - Ron Do AU - GTEx Consortium AU - Matthew Stephens AU - Kristin Ardlie AU - Mark McCarthy AU - Stephen B Montgomery AU - Ayellet V Segrè AU - Christopher D. Brown AU - Tuuli Lappalainen AU - Xiaoquan Wen AU - Hae Kyung Im TI - Exploiting the GTEx resources to decipher the mechanisms at GWAS loci AID - 10.1101/814350 DP - 2020 Jan 01 TA - bioRxiv PG - 814350 4099 - http://biorxiv.org/content/early/2020/05/23/814350.short 4100 - http://biorxiv.org/content/early/2020/05/23/814350.full AB - 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% (2,519 out of 5,385) of the GWAS loci examined. Our results demonstrate the translational relevance of the GTEx resources and highlight the need to increase their resolution and breadth to further our understanding of the genotype-phenotype link.Competing Interest StatementDetails of competing interests are listed on the manuscript.