Diabetes, obesity, metabolic syndrome, and cardiovascular disease are major causes of morbidity and mortality in the USA and worldwide. In the United States, ~34% of adults age e 20 years harbor a set of metabolic risk factors that include abdominal obesity, insulin resistance, atherogenic dyslipidemia, a proinflammatory state, and elevated blood pressure. Substantial evidence exists supporting a genetic component in the etiology of these traits. Our overall goal is to identify genetic variants that are responsible for variability in metabolic traits and risk to the related diseases. In this proposal, we aim to detect both rare variants and regulatory variants to further understand the genes, mechanisms, and pathways that influence obesity, metabolic syndrome, and diabetes. Large population cohorts are needed to identify less common (.005 d MAF <.05) and rare (MAF <.005) genetic determinants, to dissect the genetic contributions to correlated traits, and to evaluate the relative effects of and interactions between genes, environment, and behavior. One of the largest single-site population-based cohorts in which to evaluate genetic determinants of metabolic traits, the METSIM cohort of 10,197 individuals was ascertained in Kuopio, Finland during 2005- 2010. Participants were subjected to extensive clinical exams including oral glucose tolerance tests, body composition analysis, and measurement of plasma biomarkers and metabolites, and behavioral and clinical diagnostic data were collected for diabetes, diabetes complications, and cardiovascular events. In the context of the METSIM study, we will sequence total genomic DNA from 1,000 individuals at >4X coverage and impute genetic variants into 9,197 additional METSIM individuals. We will test variants for association with up to 200 metabolic quantitative traits and follow up association results via imputing variants into >15,000 additional samples. Using subcutaneous adipose samples from a subset of 400 METSIM participants, we will identify allele-specific differences in adipocyte expression and test potentially causal metabolic disease variants for functional regulatory effects. In addition, we will assess evidence for interactions and causal relationships between metabolic traits. Through this work we expect to identify novel genetic determinants of metabolic traits, discover pathogenic regulatory variants, and determine multivariate genetic, regulatory, and environmental relationships that lead to diabetes, obesity, and the metabolic syndrome. Better understanding of these factors and mechanisms may lead to clearer characteristics of disease subgroups and more targeted diagnoses and treatments.
Diabetes, obesity, and the metabolic syndrome are leading causes of morbidity and mortality worldwide. Traits related to these diseases have a strong inherited basis. The proposed work will identify novel variants that influence these traits and mechanisms by which DNA variants influence gene expression and disease. The results may lead to improved disease diagnosis and treatment.
|Cannon, Maren E; Duan, Qing; Wu, Ying et al. (2017) Trans-ancestry Fine Mapping and Molecular Assays Identify Regulatory Variants at the ANGPTL8 HDL-C GWAS Locus. G3 (Bethesda) 7:3217-3227|
|Varshney, Arushi; Scott, Laura J; Welch, Ryan P et al. (2017) Genetic regulatory signatures underlying islet gene expression and type 2 diabetes. Proc Natl Acad Sci U S A 114:2301-2306|
|Civelek, Mete; Wu, Ying; Pan, Calvin et al. (2017) Genetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits. Am J Hum Genet 100:428-443|
|Roman, Tamara S; Cannon, Maren E; Vadlamudi, Swarooparani et al. (2017) A Type 2 Diabetes-Associated Functional Regulatory Variant in a Pancreatic Islet Enhancer at the ADCY5 Locus. Diabetes 66:2521-2530|
|Kraja, Aldi T; Cook, James P; Warren, Helen R et al. (2017) New Blood Pressure-Associated Loci Identified in Meta-Analyses of 475?000 Individuals. Circ Cardiovasc Genet 10:|
|McCarthy, Shane; Das, Sayantan; Kretzschmar, Warren et al. (2016) A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet 48:1279-83|
|Walford, Geoffrey A; Gustafsson, Stefan; Rybin, Denis et al. (2016) Genome-Wide Association Study of the Modified Stumvoll Insulin Sensitivity Index Identifies BCL2 and FAM19A2 as Novel Insulin Sensitivity Loci. Diabetes 65:3200-11|
|Johnson, Amy R; Qin, Yuanyuan; Cozzo, Alyssa J et al. (2016) Metabolic reprogramming through fatty acid transport protein 1 (FATP1) regulates macrophage inflammatory potential and adipose inflammation. Mol Metab 5:506-26|
|Kaminska, Dorota; Käkelä, Pirjo; Nikkola, Elina et al. (2016) Regulation of alternative splicing in human obesity loci. Obesity (Silver Spring) 24:2033-7|
|Simon, Jeremy M; Davis, James P; Lee, Saangyoung E et al. (2016) Alterations to chromatin in intestinal macrophages link IL-10 deficiency to inappropriate inflammatory responses. Eur J Immunol 46:1912-25|
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