Obesity is rapidly becoming an epidemic in the US with an increasing prevalence and severity of consequence among minority populations. Obesity induces an inflammatory state that is implicated in adverse health conditions, e.g. insulin resistance, diabetes and non-alcoholic fatty liver disease. The over-arching goal of this proposal is to identify common and rare genetic variants underlying variation in quantitative intermediate phenotypes of obesity and inflammation in the largest US minority group, Hispanics. In the Insulin Resistance Atherosclerosis Family Study (IRASFS;funded for two five-year cycles by NHLBI and now funded under the GUARDIAN Consortium by NIDDK to study glucose homeostasis genetics) we have recruited a large Hispanic cohort and obtained detailed and novel measures of obesity, glucose homeostasis and relevant biomarkers. Through heritability, linkage, candidate gene and pilot genome-wide association studies (GWAS), we have explored the genetic determinants and identified potential loci associated with a subset of these traits. In this application, we propose to extend these findings through secondary analysis of existing GWAS, exome sequencing and candidate gene data in an effort to identify common and rare genetic variation associated with obesity and inflammation. The strengths of the proposed study include the large pedigrees in our Hispanic cohort, highly detailed, quantitative obesity and inflammation phenotypes not previously examined via GWAS, measured biomarkers that are more proximal to the gene products than aggregate traits, e.g. diabetes and heart disease, development of a novel analytic tool designed to increase the power to detect uncommon SNP associations with quantitative traits and our long-standing, highly productive collaborative team. The proposed research has the potential to impact our understanding of the genetic architecture of obesity and inflammation, traits intertwined with diabetes and heart disease, in the fastest growing US minority population.
We will investigate the genetic architecture of obesity and inflammation through analysis of quantitative intermediate phenotypes and integration of existing linkage, genome-wide association and exome sequencing data. The insight gained will provide insight into causal factors and disease pathogenesis leading to preemptive treatment, novel therapeutics and an overall decrease in incidence.