| Title: | Enrichment analyses identify shared associations for 25 quantitative traits in over 600,000 individuals from seven diverse ancestries |
| Journal: | American Journal of Human Genetics |
| Published: | 28 Mar 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35349783/ |
| DOI: | https://doi.org/10.1016/j.ajhg.2022.03.005 |
| URL: | http://www.cell.com/article/S000292972200101X/pdf |
| Citations: | 9 (7 in last 2 years) as of 8 Aug 2024 |
Publication 7163
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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.15 Authors
- 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
1 Application
| Application ID | Title |
|---|---|
| 22419 | Identifying gene networks underlying complex traits in the UK Biobank |
Enabling scientific discoveries that improve human health