RECTOR & VISITORS OF THE UNIVERSITY OF VIRGINIA
It is estimated that 3.2 million African Americans aged 20 years or older have type 2 diabetes. This represents approximately 13% of the AA population and a significant proportion of the more than 20 million Americans believed to be living with diabetes, a disease that costs the U.S. over $174 billion a year in direct and indirect costs. Given current trends, 40-49% of AA born in 2000 will develop T2DM in their lifetime. Established diabetes risk factors such as diet and lifestyle play major roles in defining diabetes risk at a population level, but prediction of individual risk remains unrealized. Recent genome-wide association studies (GWAS) have successfully identified genetic variants that influence diabetes risk in European populations; however most do not have a major impact on diabetes risk in populations of African descent. The African American population from the Sea Islands of coastal South Carolina and Georgia has high rates of type 2 diabetes, low levels of admixture and, in general, consumes a diet rich in saturated fats. We postulate that this unique combination of ancestral and environmental factors results in a more consistent penetrance of diabetes risk alleles, as well as enrichment of risk alleles of African origin. The existing DNA samples and rich phenotypic data from the Sea Island Families Project comprise a unique resource for genetic studies of type 2 diabetes and related metabolic traits such as dyslipidemia. Our central hypothesis is that the increased risk for type 2 diabetes in AA compared with EA is due, in part, to susceptibility alleles of African origin, and that these alleles can be identified using a GWAS.
RELEVANCE:
The African American population from the Sea Islands of coastal South Carolina and Georgia has high rates of type 2 diabetes, and the existing Sea Island Families Project is a unique resource for identifying inherited factors for diabetes. We propose applying this proven strategy to identify new therapeutic targets and allow translation to novel diagnostic, prevention, and treatment strategies for type 2 diabetes.