Leveraging Diversity in Polygenic Risk Scores for Diabetes and Other Advances in Genetic and Molecular Epidemiology

Dr. Alisa Manning

In this lecture, Dr. Manning will introduce polygenic risk scores for common, complex diseases like type 1 diabetes and type 2 diabetes. Polygenic risk scores are a new precision medicine tool that uses 15 years of research in genetic epidemiology to obtain personalized relative risks. A current challenge is to develop polygenic risk scores using statistical methods and epidemiological models that promote and leverage diversity without exacerbating health disparities. In the US, the prevalence of diabetes is highest in African American and Hispanic or Latino communities and these patient populations are more likely to develop diabetic complications. To realize the precision medicine goal of early identification of diabetes and treatments targeted to the individual patient, Dr. Manning will show how her research takes advantage of multi-ancestry summary statistics from genome-wide association studies to create improved polygenic risk scores in diverse ancestries. 

Dr. Alisa K. Manning uses novel analytic methods in genetic and molecular epidemiology to study multifactorial diseases like type 2 diabetes to detangle their complex architecture, enable translational research, and accelerate precision medicine. She is an Assistant Investigator in the Clinical and Translational Epidemiology Unit (CTEU) within the Mongan Institute at Massachusetts General Hospital (MGH), an Assistant Professor in the Department of Medicine at Harvard Medical School, and an Associate Member of the Metabolism Program at the Broad Institute. She develops statistical methods and applies them on large and complex study data. She is a principal investigator in the NIDDK AMP-CMD Consortium, analyzing whole genome sequence association data, NHLBI’s TOPMed Consortium, leading the diabetes working group and studying ‘Omics data with T2D, NHGRI PRIMED Consortium, developing state-of-the-art polygenic models for diabetes outcomes and complications of diabetes, and the NHLBI BioData Catalyst Consortium, leading development of BioData Catalyst powered by Terra.