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

Samuel Pattillo Smith; Sahar Shahamatdar; Wei Cheng; Selena Zhang; Joseph Paik; Misa Graff; Christopher Haiman; T C Matise; Kari E North; Ulrike Peters; Eimear Kenny; Chris Gignoux; Genevieve Wojcik; Lorin Crawford; Sohini Ramachandran

doi:10.1016/j.ajhg.2022.03.005

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

Am J Hum Genet. 2022 May 5;109(5):871-884. doi: 10.1016/j.ajhg.2022.03.005. Epub 2022 Mar 28.

Authors

Affiliations

¹ Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA; Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI 02912, USA.
² Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA.
³ Department of Epidemiology, University of North Carolina, Chapel Hill, Chapel Hill, NC 27599, USA.
⁴ Department of Preventative Medicine, University of Southern California, Los Angeles, CA 90089, USA.
⁵ Department of Genetics, Rutgers University, Piscataway, NJ 08854, USA.
⁶ Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
⁷ 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.
⁸ Division of Biomedical Informatics and Personalized Medicine, University of Colorado, Denver, CO 80204, USA.
⁹ Department of Epidemiology, Johns Hopkins University, Baltimore, MD 21287, USA.
¹⁰ 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.
¹¹ 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.

Abstract

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.

Keywords: GWAS, multi-ancestry, enrichment analyses.

Publication types

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

MeSH terms

Genome-Wide Association Study* / methods
Humans
Multifactorial Inheritance
Phenotype
Polymorphism, Single Nucleotide* / genetics
Racial Groups

Abstract

Publication types

MeSH terms

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