
Ancestry-Aware Genomics to Advance Precision Medicine for All Populations
The Gouveia Lab develops and applies advanced ancestry-aware genomic methods to understand the genetic architecture of complex diseases in multi-ancestry populations. Our lab integrates population genetics and genetic epidemiology to improve the design, analysis, and interpretation of genetic association studies. This includes genome-wide association studies (GWAS) and admixture mapping, which tests whether DNA segments with an excess of a specific ancestry are associated with differential odds of disease or other complex traits (e.g., height). We leverage the fact that continental ancestries (e.g., African and European) are not homogeneous but are composed of diverse subcontinental ancestries (e.g., North and South European). Because all human populations are admixed to varying degrees, individual genomes are mosaics of DNA segments derived from different ancestral origins, a concept known as local ancestry. A central focus of our research is the integration of subcontinental and local ancestry into genetic association studies to facilitate discovery of disease- and trait-associated variants while reducing false-positive findings. We further leverage local ancestry to identify ancestry-enriched associations using admixture mapping. Leveraging large-scale biobanks, including the All of Us Research Program, we investigate how fine-scale genetic variation shapes disease susceptibility, resilience, and the performance of polygenic risk scores. Our goal is to ensure that genomic discoveries and precision medicine tools are accurate and informative for all populations, not only those of predominantly European ancestry.
About the Lab
The Gouveia Lab is a bioinformatics research group based at Morehouse School of Medicine (MSM) within the Department of Public Health Education, with affiliations to the Institute for Translational Genomics and the Cardiovascular Research Institute. The lab focuses on an integrative approach that brings together population genetics, genetic epidemiology, and ancestry-aware genomics.
Genetic Diversity
Our lab develops methods and analytical frameworks that:
Capture fine-scale population structure
Improve association mapping in admixed cohorts
Contribute to reducing health disparities in genomic research
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