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

描述（由申请人提供）：混合物作图是一种筛选基因组中疾病基因的新方法。它与传统的基于单倍型的关联研究一样强大，但在今天是实用的，因为它只需要研究几千个多态性遗传标记。混合映射的想法是，最近种族混合的疾病患者应该有更大的可能性从具有更高疾病风险的祖先人群中继承DNA。例如，由于美洲印第安人血统与2型糖尿病的关联，平均有30%美洲印第安人和70%欧洲血统的拉丁美洲人可能倾向于在T2 D基因附近具有异常高的美洲印第安人血统。我们最近创建了非洲裔美国人混合映射的第一个实用资源，并开发了嵌套在马尔可夫链蒙特卡罗中的隐马尔可夫模型来分析混合扫描的数据，并将其应用于定位多发性硬化症的风险基因。我们现在建议为美洲印第安人混合人群创建一个实用的混合地图，并使用它来研究来自哥伦比亚安蒂奥基亚的600例2型糖尿病病例和250例对照。我们将开始这项研究，通过搜索一个公司数据库的156万单核苷酸多态性（SNP）与已知的频率在人口的美洲印第安人和欧洲裔美国人后裔。然后，我们将在我们的实验室中验证来自美洲印第安人，欧洲美洲人和非洲人群的377个样本中的4，608个SNP。基于此验证基因分型，我们将选择一个约1,536个标记的子集，这些标记对混合物作图具有最大的信息量。这组标记将构成我们的拉丁美洲混合物'地图'。作为该应用程序的第二个目标，我们将使用该地图来测量600例2型糖尿病病例和来自哥伦比亚的250名匹配对照的基因组血统。沿着基因组。这些病例都被广泛地分型为一系列2型糖尿病相关性状。使用我们的地图，我们将扫描基因组，以寻找2型糖尿病病例中异常高（或低）美洲印第安人血统的区域，这可能表明糖尿病风险基因的存在。这项试点研究将提供我们的混合图谱的第一个应用，有可能找到2型糖尿病的新风险基因。这项研究还将使更大的混合物映射研究与成千上万的2型糖尿病患者，我们想追求在美国拉丁美洲和拉丁美洲人口。

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.