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Updated: Oct 10, 2025
Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
The power of genetic diversity in genome-wide association studies of lipids
Sarah E Graham1, Shoa L Clarke2,3, Kuan-Han H Wu4
1Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA.
Insights
Genome-wide association studies (GWAS) on blood lipid levels benefit from diverse ancestry. Including non-European ancestries improves genetic discovery and polygenic prediction for cardiovascular disease prevention.
Area of Science:
- Genetics and Genomics
- Cardiovascular Disease Research
- Population Health
Background:
- Elevated blood lipid levels are heritable risk factors for cardiovascular disease (CVD), a leading global cause of death.
- Genome-wide association studies (GWAS) have identified genetic variants influencing lipid levels, aiding CVD insights and drug discovery.
- Previous GWAS predominantly focused on European ancestry populations, potentially missing crucial genetic variations in other groups.
Purpose of the Study:
- To conduct a large-scale, multi-ancestry genome-wide genetic discovery meta-analysis of blood lipid levels.
- To quantify the benefits of including non-European ancestries in genetic discovery for lipid levels.
- To assess the impact of increased ancestry diversity on fine-mapping functional variants and polygenic prediction portability.
Main Methods:
- Performed a genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals.
- Included a significant proportion (350,000) of individuals from non-European ancestries.
- Evaluated improvements in fine-mapping and polygenic prediction portability across 7 ancestry groupings (approx. 295,000 individuals).
Main Results:
- Increasing study diversity, rather than solely expanding European ancestry cohorts, significantly enhances functional variant fine-mapping and polygenic prediction.
- Achieved modest gains in the discovery of novel genetic loci and ancestry-specific variants related to lipid levels.
- Demonstrated the value of including even smaller sample sizes from underrepresented ancestries.
Conclusions:
- Multi-ancestry GWAS meta-analysis is crucial for a comprehensive understanding of genetic influences on blood lipid levels.
- Enhanced diversity in GWAS participant recruitment leads to more accurate and equitable application of polygenic scores in precision medicine.
- Supports the expansion of recruitment efforts to include diverse ancestry groups to advance CVD research and clinical applications.
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.
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