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dc.contributor.authorGamazon, Eric R.
dc.contributor.authorSegrè, Ayellet V.
dc.contributor.authorvan de Bunt, Martijn
dc.contributor.authorWen, Xiaoquan
dc.contributor.authorXi, Hualin S.
dc.contributor.authorHormozdiari, Farhad
dc.contributor.authorOngen, Halit
dc.contributor.authorKonkashbaev, Anuar
dc.contributor.authorDerks, Eske M.
dc.contributor.authorAguet, François
dc.contributor.authorQuan, Jie
dc.contributor.authorGTEx Consortium
dc.contributor.authorNicolae, Dan L.
dc.contributor.authorEskin, Eleazar
dc.contributor.authorKamvysselis, Manolis
dc.contributor.authorGetz, Gad
dc.contributor.authorMcCarthy, Mark I.
dc.contributor.authorDermitzakis, Emmanouil T.
dc.contributor.authorCox, Nancy J.
dc.contributor.authorArdlie, Kristin G.
dc.date.accessioned2019-06-07T21:12:22Z
dc.date.available2019-06-07T21:12:22Z
dc.date.issued2018-06
dc.identifier.issn1061-4036
dc.identifier.issn1546-1718
dc.identifier.urihttps://hdl.handle.net/1721.1/121227
dc.description.abstractWe 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.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Contract HHSN268201000029C)en_US
dc.language.isoen
dc.publisherSpringer Natureen_US
dc.relation.isversionofhttp://dx.doi.org/10.1038/S41588-018-0154-4en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcePMCen_US
dc.titleUsing an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variationen_US
dc.typeArticleen_US
dc.identifier.citationGamazon, Eric R. "Using an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variation." Nature Genetics 50, 7 (July 2018): 956–967 © 2018 The Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalNature Geneticsen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2019-06-07T15:07:35Z
dspace.date.submission2019-06-07T15:07:38Z
mit.journal.volume50en_US
mit.journal.issue7en_US


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