Large-scale GWAS reveals genetic architecture in the VA Million Veteran Program

A large-scale genome-wide association study (GWAS) using data from the United States Department of Veterans Affairs (VA) Million Veterans Program (MVP) – one of the largest US-based biobanks – fills crucial gaps in our knowledge of the relationships between genes, traits, and disease across diverse populations, according to a new study. The findings underscore the importance of diversity in genetic studies and the need for expanding representation in future GWAS investigations. GWAS studies have provided foundational knowledge about the genetic basis of disease and have helped inform precision approaches in medicine for prevention and treatment. However, current GWAS have focused primarily on people of European descent, limiting the applicability of findings to more diverse population groups. To address this, Anurag Verma and colleagues leveraged data from the MVP, which includes more than 635,000 participants – a third of which are from non-European genetic backgrounds, roughly double the proportional representation seen in the most recent GWAS datasets. Using this data, Verma et al. conducted GWAS to analyze 2068 traits in participants from four population groups – African, Admixed American, East Asian, and European – allowing the authors to characterize the genetic architecture of complex traits within diverse populations and compare genetic predisposition between population groups. According to the findings, among 635,969 participants, the study identified 26,049 variant-trait associations across 1,270 traits. Overall, Verma et al. discovered more similarities than differences in gene-trait associations between ancestry groups, demonstrating substantial similarities in the genetic architecture of the sample group. Notably, the analysis revealed that 3,477 variant-trait associations were significant only when individuals from non-European populations were included, highlighting the importance of genetic diversity in population-wide GWAS analyses. “Verma et al. report that participants of the Million Veteran Program are older in age as compared with the general population, and only 8% are female. Therefore, the data limits studies to conditions that are specific or more prevalent in females or in younger individuals,” write Alice Williamson and Segun Fatumo in a related Perspective. “Nevertheless, these data provide a valuable complement to other large-scale biobank efforts and highlight the benefit of including more diverse populations in genomic discovery.”