Leveraging Large-Scale Multi-Ethnic, Multi-Omic Data for Functional Analysis of Central Obesity Loci

Obesity, defined as an abnormal or excessive accumulation of fat, is a major risk factor for many chronic diseases (heart disease, stroke, diabetes, osteoarthritis, some cancers) and is associated with increased morbidity, mortality, and health care costs. Rates of obesity have been increasing worldwide, nearly tripling since 1975. Central obesity (e.g., waist-to-hip ratio [WHR], WHR adjusted for BMI [WHRadjBMI], and/or waist circumference [WC]) is more strongly associated with detrimental body fat accumulation and is a better predictor of cardiovascular disease (CVD), type 2 diabetes (T2D), and mortality than BMI. Genetic factors play a major role in central obesity, based upon genome-wide association scans (GWAS) and fine mapping having established hundreds of loci, with associated variants located in non-coding regions of the genome and, therefore, are predicted to regulate gene expression. The target gene(s) that impact biologic pathways may not be the gene(s) closest to the associated SNPs. In order to identify putative causal central obesity genes, we will identify expression quantitative trait loci (eQTLs) and protein quantitative trait loci (pQTLs) using multiple methods of colocalization, Mendelian randomization, and Bayesian networks applied to data from nine longitudinal studies in the NHLBI TOPMed (Trans-Omics for Precision Medicine) program. These studies will provide diverse genetic ancestry and multiomic data (whole genome sequence, transcriptomic, and proteomic) that will establish a priority list of genes. Combining evidence from multiple independent analysis approaches with multiomics data will be critical to link central obesity GWAS variants to putative target genes. The prioritized central obesity genes will be validated using in vitro (human cells) and in vivo (diet-induced mouse) models of human obesity. We will use cultured adipocytes from male and female donors of European- and African-ancestry as an in vitro model and perform gene silencing and overexpression for metabolic impact on adipocyte functions relevant to central obesity. Measures of in vitro effects will guide gene selection for in vivo testing of male and female mice using high fat diet-induced model of human obesity. The in vivo model uses an adeno-associated viral (AAV) construct overexpressing the gene under control of the Adipoq promoter/enhancer (with control having an AAV encoding eGFP) that will provide longitudinal metabolic measures and adipose tissue-derived assessment of cellular and molecular effects. The analyses of multiomics data coupled with in vitro and in vivo experimental results will nominate and validate central obesity genes. This research will increase our understanding of genes and biologic pathways contributing to the development of central obesity, thereby linking human GWAS findings to targeted interventions and therapeutics in obesity. Project Number: 1R01HL181987-01 | Fiscal Year: 2025 | NIH Institute/Center: National Heart Lung and Blood Institute (NHLBI) | Principal Investigator: Stephen Rich (+2 co-PIs) | Institution: UNIVERSITY OF VIRGINIA, CHARLOTTESVILLE, VA | Award Amount: $732,261 | Activity Code: R01 | Study Section: Special Emphasis Panel[ZRG1 MGG-D (90)] View on NIH RePORTER: https://reporter.nih.gov/project-details/1R01HL18198701