Leveraging ancestry to jointly characterize genetic and environmental contributions to health disparities
Genetic ancestry inference at scale
Developing algorithms for genetic ancestry inference at biobank scale, with an emphasis on local ancestry inference, i.e. characterization of the ancestral origins of specific genes genome-wide
Local ancestry mapping
Using local ancestry mapping to jointly characterize the genetic and environmental contributions to health disparities in diverse cosmopolitan populations
The relative importance of genetic versus environmental effects for health and disease, i.e. the enduring question of nature versus nurture, particularly for complex common diseases that have multifactorial etiologies and show disparate impacts among populations, has long been debated. However, the reality is that health outcomes are influenced by a combination of genetic and environmental factors and the interaction among them. Despite this complex reality, health disparity research programs tend to be siloed with an exclusive focus on either genetic or environmental contributions to differences in health outcomes among groups. The overall goal of my research program is to leverage the massive datasets that are being generated as part of population biobank efforts underway around the world to study both the genetic and environmental contributions to health disparities.