Identification and Functional Characaterization of SIM1 Obesity-Associated Variants
Location(s): United States
Obesity leads to an increased risk for type 2 diabetes, heart attack, many types of cancer, hypertension, stroke, and is estimated to soon be the leading cause of death in the US. Through twin and family studies, obesity has been found to have a 40-70% heritability rate, pointing to a strong genetic etiology. In a large-scale human resequencing project of obese and lean individuals we have discovered that rare coding variants in the Single Minded 1 (SIM1) gene could have a large effect on obesity predisposition. Haploinsuficiency of SIM1 in humans and in heterozygous null Sim1 mice was shown to lead to severe obesity, and a common non- synonymous haplotype predisposes to obesity, suggesting that both altered function and altered expression of SIM1 can lead to obesity susceptibility. We will take advantage of comparative genomics coupled with zebrafish and mouse enhancer assays to identify SIM1 regulatory elements. Using this approach we have already uncovered five hypothalamus enhancers in the SIM1 region. These functional regulatory elements in addition to the SIM1 coding region will be sequenced in several large cohorts of obese and lean individuals in order to uncover obesity-associated variants. Obesity-associated coding variants will be assessed for their effect on the protein function using an in vitro functional assay that we generated for this project. Enhancer variants will be assayed for differential enhancer activity in mice compared to the reference allele. Future assays, such as removal of an obesity-associated enhancer in mice and further sequencing of SIM1 obesity-associated variants in the NIDDK Longitudinal Assessment of Bariatric Surgery (LABS) cohort (a cohort of adults that have undergone bariatric surgery and that is being analyzed for their subsequent outcome) will be considered as a follow-up to this proposal. Identifying and functionally characterizing SIM1 obesity-associated nucleotide variants will increase our understanding of the different genetic contributions of SIM1 to this phenotype. In addition, this study will serve as a model to functionally characterize the effect of noncoding regulatory elements on human disease.