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Using an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variation

Authors :
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Gamazon, Eric R.
Segrè, Ayellet V.
van de Bunt, Martijn
Wen, Xiaoquan
Xi, Hualin S.
Hormozdiari, Farhad
Ongen, Halit
Konkashbaev, Anuar
Derks, Eske M.
Aguet, François
Quan, Jie
GTEx Consortium
Nicolae, Dan L.
Eskin, Eleazar
Kamvysselis, Manolis
Getz, Gad
McCarthy, Mark I.
Dermitzakis, Emmanouil T.
Cox, Nancy J.
Ardlie, Kristin G.
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Gamazon, Eric R.
Segrè, Ayellet V.
van de Bunt, Martijn
Wen, Xiaoquan
Xi, Hualin S.
Hormozdiari, Farhad
Ongen, Halit
Konkashbaev, Anuar
Derks, Eske M.
Aguet, François
Quan, Jie
GTEx Consortium
Nicolae, Dan L.
Eskin, Eleazar
Kamvysselis, Manolis
Getz, Gad
McCarthy, Mark I.
Dermitzakis, Emmanouil T.
Cox, Nancy J.
Ardlie, Kristin G.
Source :
PMC
Publication Year :
2019

Abstract

We apply integrative approaches to expression quantitative loci (eQTLs) from 44 tissues from the Genotype-Tissue Expression project and genome-wide association study data. About 60% of known trait-associated loci are in linkage disequilibrium with a cis-eQTL, over half of which were not found in previous large-scale whole blood studies. Applying polygenic analyses to metabolic, cardiovascular, anthropometric, autoimmune, and neurodegenerative traits, we find that eQTLs are significantly enriched for trait associations in relevant pathogenic tissues and explain a substantial proportion of the heritability (40-80%). For most traits, tissue-shared eQTLs underlie a greater proportion of trait associations, although tissue-specific eQTLs have a greater contribution to some traits, such as blood pressure. By integrating information from biological pathways with eQTL target genes and applying a gene-based approach, we validate previously implicated causal genes and pathways, and propose new variant and gene associations for several complex traits, which we replicate in the UK BioBank and BioVU.<br />National Institutes of Health (U.S.) (Contract HHSN268201000029C)

Details

Database :
OAIster
Journal :
PMC
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1113935050
Document Type :
Electronic Resource