Evaluating Genetic Tools for Diabetes Precision Medicine in Clinical Biobanks

Diabetes mellitus is heterogeneous, making it an ideal disease for precision medicine that individualizes treatment to maximize benefit and minimize harm. One axis of heterogeneity is the distinction between type 1 (T1D) and type 2 diabetes (T2D). Failure to recognize the disease subtype can lead to delays in treatment intensification and eventually to diabetes complications. A second important context for heterogeneity in diabetes care is in response to medications where favorable glycemic response must be balanced against the risk of hypoglycemia, a treatment-related adverse event. Recent advances in the genetics of T1D, T2D, response to metformin and sulfonylureas, and hypoglycemia have set the stage for studies evaluating how genetic information can be applied to clinical care using clinical biobanks with data representative of the real world diabetes patient population. In this study, we will complete two aims: 1) Test whether T1D and T2D genetic risk scores predict diabetes type and time to insulin dependence in two clinical biobanks; and 2) Evaluate metformin-, sulfonylurea-, and hypoglycemia-associated genetic variants as tools to guide oral diabetes medication choice. By exploring the relationships of diabetes-related genetic loci with aspects of patient care, we aim to make a translational research impact on precision diabetes care