The goal is to use this knowledge as a basis for improved prevention among the Pima Indians. We also aim to apply this knowledge to other populations. We hope to identify individuals at risk for obesity and type 2 diabetes and contribute to the development of more targeted and even personalized prevention and treatment programs.
Escalating rates of obesity and type 2 diabetes are primarily attributed to changes in the environment, coupled with changes in lifestyle. In most developed countries, however, food is now plentiful and lifestyle is generally sedentary. Yet not all people become obese, nor do most obese people develop type 2 diabetes. Multiple studies have shown that heritable factors underlie a significant portion of the variation in risk for obesity and type 2 diabetes. Environmental variables influence expression of this genetic susceptibility. The Pima Indians of Arizona have the highest reported prevalence of type 2 diabetes of any population worldwide, and they also are a very obese population. Our lab is identifying and characterizing susceptibility genes for type 2 diabetes and obesity among this Native American population.
Our recent genetic studies have adopted genome-wide approaches to identify potential susceptibility loci for type 2 diabetes and obesity. We have completed two genome-wide association studies (GWAS) that utilized a 100,000 single-nucleotide polymorphism (SNP) and a 1 million SNP platform to identify common variants associated with type 2 diabetes, obesity, prediabetes, or preobesity traits in Pima Indians. A few variants associated with these diseases in GWAS from other ethnic groups showed associations similar to those seen in Pima Indians. We also identified several strong and reproducible associations not reported in other GWAS, a finding that suggests ethnic-specific heterogeneity in risk factors for these common diseases. We are conducting fine mapping and functional studies for several of these new susceptibility variants. We are also pursuing the hypothesis that multiple rare variants may underlie some proportion of the variance we have identified. We recently completed whole-exome sequencing on 180 Pima Indians and whole-genome sequencing on 135 Pima Indians. We also have genome-wide expression data (1M exons) from human skeletal muscle and adipose biopsies from more than 200 nondiabetic Pima Indians previously characterized for metabolic traits related to diabetes and obesity. We are using these data to identify expression profiles that may predict the onset of diabetes. We are also merging expression data with GWAS genotypic data and whole-genome sequence data to identify cis and transacting factors that may contribute to these polygenic diseases.
We believe that understanding and quantifying specific genetically determined susceptibility factors could lead to prevention by identifying individuals at risk for these diseases. The research could also identify novel therapeutic and personalized targets, which may lead to treatment improvements.