Building a Latino admixture map & pilot study to find Type 2 Diabetes risk

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DESCRIPTION (provided by applicant): Admixture mapping is a novel way to screen the genome for disease genes. It has as much power as a traditional haplotype-based association study, but is practical today, because it requires studying only a couple of thousand polymorphic genetic markers. The idea of admixture mapping is that people with disease who descend from the recent mixing of ethnic groups should have an increased probability of inheriting DNA from the ancestral population with higher disease risk. For example, because of the association of Amerindian ancestry with Type 2 diabetes, Latino Americans who have 30% Amerindian and 70% European ancestry on average might tend to have an unusually high level of Amerindian ancestry near a T2D gene. We recently created the first practical resource for admixture mapping in African Americans, and developed a Hidden Markov Model nested within a Markov Chain Monte Carlo to analyze data from admixture scans, and applied it to localize a risk gene for multiple sclerosis. We now propose to create a practical admixture map for Amerindian mixed populations, and to use it to study Type 2 Diabetes in 600 cases and 250 controls from Antioquia, Colombia. We will begin this study by searching a company database of 1.56 million single nucleotide polymorphisms (SNPs) with known frequencies in populations of both Amerindian and European American descent. We will then validate 4,608 of these SNPs in our laboratory in 377 samples drawn from Amerindian, European American, and African populations. Based on this validation genotyping, we will then select a subset of about 1,536 markers that are maximally informative for admixture mapping. This panel of markers will constitute our Latino admixture 'map'. As the second goal of this application, we will use the map to measure ancestry along the genome in 600 Type 2 diabetes cases, and 250 matched controls from Colombia. The cases have all been extensively phenotyped for a range of Type 2 Diabetes-related traits. Using our map, we will scan the genome to look for regions of unusually high (or low) Amerindian ancestry in the Type 2 Diabetes cases, which could indicate the presence of a diabetes risk gene. This pilot study will provide a first application of our admixture map, with potential to find new risk genes for Type 2 Diabetes. The study will also enable larger admixture mapping studies with many thousands of patients with Type 2 Diabetes, which we would like to pursue both in U.S. Latino and in Latin American populations.