Candidate Gene Studies of Obesity Guided by Whole Genome Association Data
Obesity is strongly influenced by sequence variation in largely unknown susceptibility genes. Whole genome association scans offer a potentially powerful method for identifying common variants with modest effects on obesity, but the deluge of data from these studies will require careful analysis and rigorous follow-up. The combination of multiple large, well-characterized cohorts with measure of obesity, high throughput genotyping, and robust analytic methods will permit powerful meta-analysis of genome-wide association studies and permit us to follow up rapidly with sequencing and genotyping the preliminary results from the whole genome association scans. Specifically, we will be able to identify genetic variants that are truly associated with obesity, even if the effects are modest. This will lay the groundwork for additional studies of the phenotypic consequences of these variants on other obesity-related phenotypes, as well as studies to identify rare or structural variants at these loci. Many of the genes we have identified thus far relate to neurologic function. For example, we have identified variants at SH2B1 and BDNF that are associated with body mass index; large deletions that encompass these genes are also associated with mental retardation. Successful identification of genes that are convincingly associated with obesity would highlight key pathways that influence obesity in humans, guiding efforts at therapy and prevention.