The incidence of type 2 diabetes (T2DM) continues to rise and increasingly affects individuals of all ages across all ethnic groups. Individuals from certain ethnic groups including Mexican Americans have an increased propensity towards developing T2DM. The growing magnitude of T2DM and its huge monetary and social costs mandate a need for new methods to provide early risk estimates as well as novel avenues of intervention. Genetic studies consistently indicate that T2DM is familial in nature, and there is mounting evidence for susceptibility loci from over 20 genome-wide scans for linkage of T2DM. However, the genes influencing susceptibility to the common forms of T2DM remain largely unknown. In 1999, we published the results of a genome-wide linkage scan conducted to localize those genes in the San Antonio Family Diabetes Study (SAFADS), an extended pedigree study comprised of Mexican Americans. The analysis was the first to show significant evidence for linkage of the traits diabetes and diabetes age-of-onset to a genetic region on chromosome 10q. Since then, results from a number of genome scans for T2DM and related quantitative measures in other populations have also implicated chromosome 10q as a region which might harbor a gene(s) influencing susceptibility to these traits. We have recently confirmed linkage in SAFADS with an expanded dataset and a new CIDR marker genome scan. We have made exciting progress toward identifying a variant in a positional candidate gene that increases risk for diabetes more than 2-fold in SAFADS and accounts for part but not all of the linkage in the 10q region. Additionally, we have recently observed supportive evidence of a novel diabetes susceptibility gene in the region that was recently identified through positional cloning of a synthetic mouse QTL. This application aims to further examine the linked region for gene(s) that influence diabetes susceptibility and/or diabetes age-of-onset. We are proposing a combined strategy that will exploit the strengths of linkage disequilibrium mapping and thorough evaluation of positional candidate genes. Using this strategy, we will examine all 202 genes that have been identified to be located within the gene-rich 26 Mb 1.5 LOD support interval. Furthermore, the utilization of a novel statistical functional genomic analysis (Bayesian quantitative trait nucleotide analysis) should enhance the final stage of identifying the specific variants involved. ? ? ?

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Research Project (R01)
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Special Emphasis Panel (ZRG1-KNOD-N (01))
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Mckeon, Catherine T
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University of Texas Health Science Center San Antonio
Internal Medicine/Medicine
Schools of Medicine
San Antonio
United States
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