ABSTRACT: Gestational diabetes mellitus (GDM) is a heterogenous disease that is defined by the occurrence of glucose intolerance or hyperglycemia during the late second trimester and occurs when pancreatic β cells cannot secrete sufficient insulin when there is increasing insulin resistance. GDM affects approximately 10% of all pregnancies and negatively impacts the short-and long-term health of both pregnant mothers and their offspring. microRNAs (miRNAs, 18-25 nt) are a class of small non-coding RNAs that post transcriptionally modulate gene expression and have been shown to regulate several key processes within the β cell. miRNAs have also been implicated as potential biomarkers for type 1 diabetes, and type 2 diabetes. Past studies have also demonstrated a potential for miRNAs to serve as biomarkers for GDM as well, but most only employed targeted approaches and did not consider the contribution of maternal overweight/obesity. Against this background, we obtained plasma samples collected from pregnant mothers enrolled in the Nulliparous Pregnancy Outcomes Study-Monitoring Mothers-to-be (nuMoM2b; NCT01322529) study to perform unbiased miRNA sequencing. Our preliminary data showed that maternal overweight/obesity status (defined as BMI≥25) influenced plasma miRNA signatures. Compared to controls in the same BMI category, we identified a set of miRNAs that were different in pregnant mothers who subsequently developed GDM. This result indicates the potential of miRNA signatures to predict GDM onset prior to onset of hyperglycemia. Interestingly, we also found that miR-517a-3p, a placental-enriched miRNA that is known to increase cellular proliferation, was downregulated in mothers who subsequently developed GDM. In Aim 1, we hypothesize that the upregulation of miR-517a-3p positively regulates β cell function and survival. To test this hypothesis, we will define the unreported role of miR-517a-3p in regulating β cell function using INS-1 cells, murine islets, and human islet models, as well as using state-of-the-art RNA-seq approach to uncover the modulated genes and molecular pathways. In Aim 2, we hypothesize that a combination of miRNA signatures and clinical variables will improve the prediction of GDM. This hypothesis will be tested by quantifying the expression levels of these miRNA signatures using expanded sample sets from the multi-center nuMoM2b study and analyzed using appropriate model-selection methods in collaboration with Dr. Joanne Daggy (IU Dept of Biostatistics and Health Data Science). This R01 supplement will also support time for the candidate (Dr. Kua) to perform experiments and attend training courses to acquire new research skills to pursue a career as an independent physician scientist. The candidate training will include three main objectives: (1) Obtain state-of-the-art training in miRNA biology and their role in modulating β cell function and gestational diabetes risk, (2) develop experimental toolkits to support trans...