Type 2 diabetes (T2D) is a major cause of morbidity and mortality in the USA and worldwide. Identification of genes increasing susceptibility to T2D would substantially affect the public health by providing biological and clinical data about development and treatment of T2D and by advising lifestyle changes in at-risk individuals. Our overall goal is to identify the functional variants, target genes, and mechanisms responsible for T2D and diabetes-related quantitative trait (QT) association signals. Previously, we have identified novel loci for T2D and QTs using both low-frequency and common variants. We developed strategies to annotate regulatory variants and, at several loci, defined variants and the mechanisms by which variant alleles bind transcriptional regulators and increase or decrease expression of specific target genes. In this proposal, we extend these previous successes to further define molecular and biological mechanisms and assess the contribution of hundreds of specific plasma metabolites to QT variation and T2D risk. Specifically, guided by experimental evidence of regulatory elements and resources correlating genotype, regulatory element activity, and chromatin structure with expression level, we will test variants for allele-specific differences in transcriptional activity and protein-DNA interactions, identify transcriptional regulators, and validate results in primary cells, transient expression in model organisms, and genome editing in human cell lines. For insulin processing and secretion loci at which we have already implicated single variants, we will perform detailed characterization of the genes and their encoded proteins and determine the effects of the reference and alternate alleles on basal and glucose-stimulated proinsulin and insulin secretion. In addition, we will test association of genetic variants with >700 metabolites, determine their role in T2D risk and QT variation, and assess prediction of future T2D in unaffected at-risk individuals. We will use metabolite associations to annotate loci, identify causal contributions by Mendelian randomization, and assess the contribution to models that predict T2D risk using resources from the 20-year Finland United States Investigation of NIDDM Genetics (FUSION) study. Successful completion of these aims will translate T2D association signals into biological insights and potential therapeutic targets. Risk variants, the mechanisms by which they affect gene function, and their pathological effects on disease processes will be determined, guiding studies that evaluate novel therapies and intervene in at-risk individuals to prevent disease. The productive and longstanding collaboration of the investigators make achievement of these aims feasible and likely highly informative to the public health crisis posed by T2D.
Type 2 diabetes, obesity, and the metabolic syndrome are leading causes of morbidity and mortality worldwide. Metabolic traits related to these diseases have a strong inherited basis, and recent studies have revealed novel genes associated with these traits. The proposed work will validate novel genes that influence diabetes, determine how DNA variants influence gene function, and may provide targets for new therapies.
Showing the most recent 10 out of 112 publications
