The power of genetic diversity in genome-wide association studies of lipids

Sarah E. Graham, Alaitz Poveda, Azra Kurbasic, Valeriya Lyssenko, Paul Franks, Cristen J. Willer, VA Million Veteran Program, Global Lipids Genetics Consortium

Research output: Contribution to journalArticlepeer-review

Abstract

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4–23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice. © 2021, The Author(s), under exclusive licence to Springer Nature Limited.
Original languageEnglish
Pages (from-to)675-679
Number of pages5
JournalNature
Volume600
Issue number7890
DOIs
Publication statusPublished - 2021

Subject classification (UKÄ)

  • Medical Genetics

Free keywords

  • allele
  • cardiovascular disease
  • cause of death
  • drug
  • genome
  • lipid
  • meta-analysis
  • risk factor

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