Genome-wide association studies (GWAS) have successfully identified genetic variants associated with common, complex diseases and quantitative traits. In the Metabolic Syndrome in Men (METSIM) study of 10,197 well-characterized individuals, we identified novel loci and additional signals for metabolic traits related to obesity, type 2 diabetes (T2D), and the metabolic syndrome. However, most of the underlying genes, their directions of effect, and mechanisms of action remain unknown. Subcutaneous adipose tissue serves as a buffering system for lipid energy balance and may play a protective role in metabolic risk. Initial gene expression data in subcutaneous adipose tissue from METSIM participants identified expression quantitative trait loci (eQTLs) coincident with GWAS signals that suggest new candidate genes at dozens of loci. A more thorough understanding of genetic influences on subcutaneous adipose expression variation would identify additional target genes, especially for insulin resistance traits including waist-hip ratio (WHR), lipids, and T2D. Further identifying genetic influences on chromatin variation in adipose tissue would help define molecular events that influence regulatory mechanisms. Our overall goal is to identify the functional variants, target genes, and mechanisms responsible for metabolic trait association signals. We hypothesize that examining regulatory variants in a disease-relevant tissue and a large population cohort will reveal genes and mechanisms for obesity, T2D, and metabolic syndrome. In the next phase of this study, we will identify allelic differences in subcutaneous adipose tissue gene expression and chromatin accessibility in an expanded analysis of METSIM samples. We will detect variants associated with expression, splicing, and chromatin accessibility and use the data to annotate new and existing metabolic trait-associated signals. We will perform mediation analyses to identify variants that act on traits via changes in chromatin accessibility and/or expression, and we will further investigate changes in chromatin accessibility or gene expression that interact with insulin resistance status. Finally, we will test variants for effects on transcriptional activity and transcription factor binding, and determine the effects on gene expression by deleting or activating regulatory elements in a human adipocyte cell strain. Excellent human tissue and clinical resources, technological advances in high-throughput sequencing, and advanced analysis methods make this project timely and feasible. Through this work we expect to identify novel genes for metabolic traits, discover pathogenic regulatory variants, and learn how environmental context can influence the dynamic range of gene regulation and the development of disease. Better understanding of these factors and mechanisms may lead to improved diagnoses and treatments for obesity, T2D, and metabolic syndrome.
Obesity, diabetes, and metabolic syndrome are leading causes of morbidity and mortality worldwide. Metabolic traits related to these diseases have a strong inherited basis. The proposed work will identify DNA variants that influence these traits and mechanisms by which the variants regulate gene expression and alter trait levels. The results may lead to improved disease diagnosis and treatment.
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