Researchers have conducted a multi-ancestry GWAS of lipid levels in around 1.65 million individuals, including 350,000 individuals of non-European descent.
High blood lipid levels are a heritable risk factor of cardiovascular disease. Genome-wide association studies (GWAS) of blood lipid levels have led to important biological and clinical insights into cardiovascular disease, as well as uncovered new drug targets. But despite advances in prevention and treatment, for example, through reducing low-density lipoprotein cholesterol levels, cardiovascular disease remains the leading cause of death worldwide.
Most previous GWAS have been conducted in European ancestry populations. This is highly significant because cardiovascular disease has a varied prevalence worldwide, which is most likely due to the different diet patterns and medication use. Therefore, historic GWAS studies of cardiovascular disease are likely to have missed genetic variants that contribute to lipid-level variation in other ancestral groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns.
Multi-ancestry GWAS of lipid levels
Recently, a group of researchers conducted a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in around 1.65 million individuals, including 350,000 individuals of non-European descent. Their findings, published in Nature, are hoped to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes.
The team discovered that the number of significant loci relative to sample size were similar within each ancestry group and approximately linearly related to sample size. Although, there was a small increase in ancestry-specific variants observed in African ancestry cohorts relative to the others. They also demonstrated that the inclusion of additional ancestries through multi-ancestry fine-mapping reduced the set of candidate causal variants in credible sets and did so more rapidly than in single-ancestry analysis.
Additionally, and perhaps most importantly, the researchers found that the multi-ancestry score was generally the most informative score across all the major population groups examined. Therefore, this provides evidence for the fact that increasing the diversity, rather than studying additional individuals of European ancestry, results in substantial improvements in fine-mapping functional variants of polygenic prediction.
Genetics studies will benefit from diverse populations
Overall, this GWAS for blood-lipid traits, based on more than 1.65 million individuals from 5 ancestral groups, has confirmed that the contributions of common genetic variations to blood lipids are similar across diverse populations. The results also infer that genetic studies in the future will substantially benefit from meta-analyses across participants of diverse ancestries and will improve the discovery of new loci in diverse cohorts, particularly variants that are absent at present from arrays and imputation reference panels.
Ultimately, diversifying the populations under study, rather than simply increasing the sample size, is now the single most efficient approach to achieving these goals. This is certainly true for blood lipids, and probably the case for related downstream adverse health outcomes such as cardiovascular disease. Therefore, future large-scale recruitment efforts should be targeted at the enrolment and DNA collection of non-European ancestry participants. Geneticists and those responsible for cohort development should continue to diversify genetic discovery datasets, while increasing sample size in a cost-effective manner. This will ensure that genetic studies reduce, rather than exacerbate, existing health inequities across race, ancestry, geographical region and nationality.
Image credit: PatriotDirect Family Medicine