Enrichment analyses identify shared associations for 25 quantitative traits in over 600,000 individuals from seven diverse ancestries.

Genome-Wide Association Study / methods Humans Multifactorial Inheritance Phenotype Polymorphism, Single Nucleotide / genetics Racial Groups
GWAS, multi-ancestry, enrichment analyses

Journal

American journal of human genetics
ISSN: 1537-6605
Titre abrégé: Am J Hum Genet
Pays: United States
ID NLM: 0370475

Informations de publication

Date de publication:
05 05 2022
Historique:
received: 01 11 2021
accepted: 02 03 2022
pubmed: 30 3 2022
medline: 11 5 2022
entrez: 29 3 2022
Statut: ppublish

Résumé

Since 2005, genome-wide association (GWA) datasets have been largely biased toward sampling European ancestry individuals, and recent studies have shown that GWA results estimated from self-identified European individuals are not transferable to non-European individuals because of various confounding challenges. Here, we demonstrate that enrichment analyses that aggregate SNP-level association statistics at multiple genomic scales-from genes to genomic regions and pathways-have been underutilized in the GWA era and can generate biologically interpretable hypotheses regarding the genetic basis of complex trait architecture. We illustrate examples of the robust associations generated by enrichment analyses while studying 25 continuous traits assayed in 566,786 individuals from seven diverse self-identified human ancestries in the UK Biobank and the Biobank Japan as well as 44,348 admixed individuals from the PAGE consortium including cohorts of African American, Hispanic and Latin American, Native Hawaiian, and American Indian/Alaska Native individuals. We identify 1,000 gene-level associations that are genome-wide significant in at least two ancestry cohorts across these 25 traits as well as highly conserved pathway associations with triglyceride levels in European, East Asian, and Native Hawaiian cohorts.

Identifiants

DOI: 10.1016/j.ajhg.2022.03.005 PMID: 35349783 PMC: PMC9118115
pubmed: 35349783
pii: S0002-9297(22)00101-X
doi: 10.1016/j.ajhg.2022.03.005
pmc: PMC9118115
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

871-884

Subventions

Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
Organisme : NHLBI NIH HHS
ID : 75N92021D00001
Pays : United States
Organisme : NHLBI NIH HHS
ID : N01HC65234
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM128596
Pays : United States
Organisme : NHLBI NIH HHS
ID : N01HC65235
Pays : United States
Organisme : NHLBI NIH HHS
ID : N01HC65233
Pays : United States
Organisme : WHI NIH HHS
ID : 75N92021D00003
Pays : United States
Organisme : NHLBI NIH HHS
ID : N01 HC065236
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM118652
Pays : United States
Organisme : NHGRI NIH HHS
ID : R01 HG010297
Pays : United States
Organisme : NHLBI NIH HHS
ID : 75N92021D00002
Pays : United States
Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom
Organisme : NIGMS NIH HHS
ID : R35 GM139628
Pays : United States
Organisme : WHI NIH HHS
ID : 75N92021D00004
Pays : United States
Organisme : WHI NIH HHS
ID : 75N92021D00005
Pays : United States
Organisme : NHLBI NIH HHS
ID : N01 HC065237
Pays : United States

Informations de copyright

Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests C.G. owns stock in 23andMe. E.K. and C.G. are members of the scientific advisory board for Encompass Bioscience. E.K. consults for Illumina.

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Auteurs

Samuel Pattillo Smith (SP)

Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA; Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI 02912, USA.

Sahar Shahamatdar (S)

Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA; Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI 02912, USA.

Wei Cheng (W)

Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA; Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI 02912, USA.

Selena Zhang (S)

Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA.

Joseph Paik (J)

Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA.

Misa Graff (M)

Department of Epidemiology, University of North Carolina, Chapel Hill, Chapel Hill, NC 27599, USA.

Christopher Haiman (C)

Department of Preventative Medicine, University of Southern California, Los Angeles, CA 90089, USA.

T C Matise (TC)

Department of Genetics, Rutgers University, Piscataway, NJ 08854, USA.

Kari E North (KE)

Department of Epidemiology, University of North Carolina, Chapel Hill, Chapel Hill, NC 27599, USA.

Ulrike Peters (U)

Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.

Eimear Kenny (E)

The Center for Genomic Health, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA.

Chris Gignoux (C)

Division of Biomedical Informatics and Personalized Medicine, University of Colorado, Denver, CO 80204, USA.

Genevieve Wojcik (G)

Department of Epidemiology, Johns Hopkins University, Baltimore, MD 21287, USA.

Lorin Crawford (L)

Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA; Department of Biostatistics, Brown University, Providence, RI 02906, USA; Microsoft Research New England, Cambridge, MA 02142, USA.

Sohini Ramachandran (S)

Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA; Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI 02912, USA; Data Science Initiative, Brown University, Providence, RI 02912, USA. Electronic address: sramachandran@brown.edu.

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Classifications MeSH

questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Épidémiologie moléculaire › Étude d'association pangénomique › Enrichment analyses identify shared...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Enrichment analyses identify shared...
questionsmedicales.fr › Phénomènes génétiques › Modes de transmission héréditaire › Hérédité multifactorielle › Enrichment analyses identify shared...
questionsmedicales.fr › Phénomènes génétiques › Phénotype › Enrichment analyses identify shared...
questionsmedicales.fr › Phénomènes génétiques › Variation génétique › Polymorphisme génétique › Polymorphisme de nucléotide simple › Enrichment analyses identify shared...
questionsmedicales.fr › Personnes › Nord-Américains › Groupes de population aux États-Unis › Populations d'origine continentale › Enrichment analyses identify shared...