Key thematic research interests

Gene-lifestyle interactions

We seek to understand the interplay of genetic and lifestyle factors in exacerbating the prevalence of NCDs in African populations. We do this through approaches such as the variance heterogeneity tests

Polygenic Prediction in African Populations

Currently polygenic risks are less accurate and their predictivity is variable within Africa. Our work seeks to understand the factors contributing to the variability of polygenic risk scores with the quest of developing generalizable one that can help in their wide use and application in the resource limited settings of Africa

Diabetes Precision Medicine

Diabetes will increase the most by 145% in Africa.Diabetes in Africa is characterized by unique lean phenotypes.Our research seeks to generate the evidence for the need for more precise “accurate” medicine in Africa. We also work to evaluate leapfrog options to that can help increase access to this accurate form of medicine

Multi-omics, machine learning, BMI sex differences and CVD risk

70% of black South African women are obese compared to 30% men. However, the prevalences of diabetes are similar and men are more susceptible to insulin resistance compared to women. We are working to use multi-omics, machine learning to understand BMI sex differences and their heterogeneous effects on CVD risk in black South Africans