PROJECT SUMMARY Rare genetic defects of the primary cilium can cause a number of phenotypically-overlapping Mendelian syndromes, known as ciliopathies. Intriguingly, many ciliopathy patients show signs of impaired glucose homeostasis, with accumulating evidence suggesting that insulin receptor must be specifically trafficked into the cilium to initiate insulin-dependent signaling cascades. However, we do not yet know if variants in ciliary genes increase an individual’s risk for diabetes more generally, nor do we understand the mechanisms by which ciliary genes might affect insulin receptor signaling to cause pathology. The goal of this proposal is to fill this gap in our knowledge using complementary bioinformatic and cell biologic approaches. My clinical and scientific expertise in ciliary biology and human genetics, coupled with my exciting preliminary results, rigorous research plan, and outstanding mentorship team, provide a solid foundation for this project. In completing the proposed work, specifically with its focus on providing me additional training in the field of bioinformatics and in lab management, I will be perfectly poised to begin my independent academic career as a physician scientist seeking to better understand the genetics and biology of ciliary dysfunction in human disease. I have secured the complete support of my institution, and will benefit greatly from the unparalleled resources and mentorship available at both the University of Pennsylvania and the Children’s Hospital of Philadelphia over the course of this award. I hypothesize that variants in ciliary genes increase risk for diabetes by perturbing cell signaling pathways essential to normal insulin signaling. My preliminary analyses in the UK and Penn Medicine Biobanks have already identified numerous ciliary genes and variants significantly associated with glucose and hemoglobin A1c levels, and demonstrate significant changes in ciliary gene expression in response to insulin. I will further investigate these associations with two complementary sets of analyses. Specifically, I will (1) use bioinformatic approaches in large patient datasets to identify and characterize ciliary genes and pathways that confer increased risk for type 2 diabetes phenotypes and (2) validate these findings in cell models of disease, with a specific focus on understanding how genetic variation in ciliary genes perturbs the ciliary transport and downstream signaling of insulin receptor. Through the careful use of cell and molecular biologic approaches including signaling assays, RNAseq, and live cell imaging, I will quantify differences in insulin receptor signaling and ciliary transport of insulin receptor when individual ciliary candidate genes, identified in Aim 1, are knocked down in cell models. The completion of the proposed work will advance our knowledge of cilium biology and common disease genetics, open new avenues for patient risk assessment, and has the potential to identify novel...