Our research in Genetic Epidemiology of Complex Diseases focuses on understanding how genetic variation interacts with environmental, lifestyle, and social factors to influence the risk, development, and progression of multifactorial diseases. Unlike rare Mendelian disorders caused by mutations in a single gene, complex diseases—such as diabetes, cardiovascular disease, cancer, and autoimmune conditions—arise from the combined effects of many genetic variants, each contributing modestly to overall susceptibility. By uncovering these intricate relationships, we aim to identify the genetic architecture and biological pathways that underlie human disease and health disparities.

At the core of our work lies the integration of population-based studies and genomic technologies. We leverage large-scale datasets from genome-wide association studies (GWAS), whole-genome and exome sequencing, and multi-omics profiling to identify common and rare variants associated with disease risk. Using advanced statistical models and computational tools, we quantify heritability, map causal loci, and explore gene–environment interactions that shape disease outcomes across diverse populations.

Our research also emphasizes translational and interdisciplinary approaches. We collaborate with clinicians, epidemiologists, data scientists, and biostatisticians to link genetic findings with clinical phenotypes, biomarkers, and longitudinal health data. By bridging molecular genetics with population-level insights, we aim to translate genetic discoveries into meaningful applications for disease prediction, prevention, and personalized intervention.

A key component of our work involves studying genetic diversity and health equity. We recognize that most genomic studies have historically focused on populations of European ancestry, limiting the generalizability of findings. To address this gap, we prioritize the inclusion of underrepresented populations in genetic research, ensuring that advances in genomic medicine benefit all communities.

Our ongoing projects explore how polygenic risk scores, gene–environment correlations, and molecular networks contribute to disease susceptibility and treatment response. By combining large-scale genomics with epidemiologic principles, we are building comprehensive models that capture the complexity of human disease across biological, behavioral, and environmental dimensions.

Ultimately, our goal is to illuminate the genetic and environmental foundations of complex diseases, advancing the science of prediction and prevention. Through rigorous analysis, interdisciplinary collaboration, and a commitment to population health, our research in genetic epidemiology strives to bridge discovery and impact—transforming data into actionable knowledge that can inform precision medicine and improve health outcomes worldwide.