Integrative Approaches to Identifying Function and Clinical Significance of Adiposity Susceptibility Genes

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SUMMARY In 2019, ~100 million Americans were obese, fueling increases in obesity-related morbidity, mortality, and health care costs, largely from cardiometabolic diseases (CMD). Large scale genetic studies have laid the foundation for many downstream investigations into the pathogenesis of disease and the translation of this information into public health applications. Over the last decade genome-wide association studies (GWAS) have substantially improved our understanding of the genetic architecture of obesity related traits. The potential of these study findings cannot be overstated for elucidating the biological or pathophysiological underpinnings of obesity and its costly morbidities. Although GWAS on common variants have made strides in identifying > 1,000 signals for obesity related traits, these studies are inherently limited without further translation into more actionable findings. In this proposal, we will narrow association signals and map causal genes and pathways underlying known obesity risk loci by applying innovative methods to integrate multiple OMICs (genOMICs, epigenOMICs, transcriptOMICs and metabolOMICs). Additionally, we will explore the clinical relevance of obesity susceptibility variants, genes, and pathways in a large BioBank linked to electronic health records (EHR) to validate expected phenotypic associations and reveal novel phenotypic associations. Finally, we will conduct in vitro functional studies of key variants and genes in physiologically relevant cells to reveal putative regulatory mechanisms of variants and effects on metabolites and thus the underlying mechanisms critical to obesity pathogenesis. Thus, in this proposal we leverage collaborations in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE), TransOMICs for Precision Medicine (TOPMed) Program, the Genome Sequencing Project (GSP), and the EHR database from the Geisinger MyCODE Community Health Initiative study (MyCode) to narrow in on genes underlying GWAS signals, perform clinical characterization, and conduct in vitro functional studies to characterize the molecular underpinnings and biological mechanisms of obesity-risk loci. Our approach will substantially move the field away from tag variants and loci to causal variants, genes, and mechanisms. We anticipate that this work will generate fundamental and important insights into the underlying etiology of obesity and ultimately point the way forward towards prevention and treatment.