Project 452792

Gestational diabetes mellitus (GDM), defined as glucose intolerance first recognized during pregnancy, affects up to 14% of pregnancies worldwide. A GDM pregnancy significantly increases the risk of clinical complications to mothers and babies before and after delivery. In fact women with GDM have a 7 times greater chance of developing type 2 diabetes (T2D) within 10 years postpartum; leading to increased morbidity and mortality. The underlying cause of GDM and the transition from GDM to T2D remains unclear. The objective of the present proposal is to use a series methods to measure hundreds of substances (metabolites and proteins) found in blood of women before they develop GDM vs. women who do not develop GDM. We will then use a series of biostatistical methods and artificial intelligence to find new and better methods to predict future GDM in this group. Using similar methodologies we also propose to gain a deeper understanding of future T2D risk in this group, and find the underlying cause of why women with GDM progress to T2D at such a high rate. We anticipate that there are specific defects in insulin secretion that occur in those that develop GDM and then transition to T2D and we propose to identify those factors contributing to this process. We will then use preclinical genetic models and drugs to identify specific molecular targets that we hypothesize are causally related to the progression towards developing T2D. The significance of the proposed work is threefold. 1. We will devise new strategies to more easily, quickly and accurately assess future diabetes risk in women who have experienced GDM. 2. We will gain a deeper understanding of the pathology associated with the development of T2D in this group. 3. We will identify cells and proteins in the body where defects may lie that facilitate the transition to T2D from GDM and possibly identify new therapeutic targets to slow or prevent the onset of T2D.