Genetic Studies of Diabetic Complications

University Of Chicago, Chicago IL

Investigators

Linked publications & trials

Abstract

[unreadable] DESCRIPTION (provided by applicant): [unreadable] We, as a society, have made tremendous investments in developing the scientific infrastructure to enable breakthrough discoveries on the primary biological risk factors for common disorders, such as diabetes, and its common complications, including kidney failure. These disorders account for a disproportionate and growing share of public health care expenditures. While it is clear that the relationships between genetic variation and these common disease phenotypes are complex, there is good preliminary evidence that identifying genetic risk factors for common disorders will improve understanding of their etiology and pathogenesis, leading to more specific and effective therapies. Moreover, since virtually all common disease arises as a consequence of the actions and interactions of both genetic and non-genetic risk factors, the identification of genetic risk factors should allow design of epidemiological studies to identify more specific non-genetic risk factors that might be cost-effective targets for prevention of disease. The recent development of high-throughput platforms for very large-scale SNP genotyping makes genome-wide association (GWA) mapping a viable additional tool in the effort to identify genetic risk factors for diabetic complications including kidney failure and related phenotypes. Effective use of this tool, however, requires both investment in methods of genetic analysis and a keen understanding of the phenotypes. We have thus put together a multi-disciplinary team including statistical geneticists, molecular geneticists, and experts on kidney function and failure and propose to apply a variety of approaches for genome-wide association studies on kidney failure and related quantitative phenotypes using the GoKinD samples. Specifically, we propose to 1) genotype all probands and parents in the GoKinD collection (2,807 individuals) using the Illumina HapMap 300 beadchip platform; 2) conduct both standard and novel genetic analyses of the data to map genes associated with diabetic nephropathy and related phenotypes; 3) verify genotyping and carry out fine-mapping studies in genes or regions showing association with diabetic nephropathy, related quantitative phenotypes, and other measures of diabetic complications measured in the GoKinD samples. Identification of the genes and the specific genetic variants that contribute to the development of diabetic nephropathy will lead to new approaches for preventing and treating this common long-term complication of diabetes. [unreadable] [unreadable] [unreadable]