Evolutionary Genetics of the Metabolic Syndrome

这项建议的最终目标是了解代谢综合征的遗传基础，这是一组遗传学上的疾病。 表型包括2型糖尿病（T2 D）、肥胖、高血压和血脂异常。这些表型 在美国的公共卫生负担中占了不成比例的比例。进化遗传学提供了一个 一个强大的框架，调查代谢综合征，因为风险基因型是假设的 是人类祖先对不同环境的代谢适应的结果。在这 根据多研究者的建议，我们将在以下具体目标中讨论群体遗传学假设： 1.我们将开发统计学方法来检验SNP等位基因频率与 环境变量对人口之间的相关性的零模型，由于人口 历史我们也会选择接近。200个基因参与了新陈代谢的生物过程 综合征和300个不受约束的基因组区域用作“对照”。共3072个SNP-分为 进入近似。候选基因中2700个标签SNP和对照区中300个SNP（1个SNP/对照区） - 将对来自全球52个人群的1056名个体进行基因分型。新开发的统计 方法学将用于分析SNP基因分型数据。 2.一组近似。20个候选基因将在16个个体中重新测序，每个个体来自3个群体， 分别来自非洲、欧洲和亚洲。将分析重新测序数据，以确定 这些基因中存在积极自然选择的标志，并估计所选等位基因的年龄。 3.我们将建立一个代谢综合征演变的正式模型，其中疾病风险是由于 在古代人类群体中通过净化选择保持的祖先等位基因， 在转向西方生活方式后，要么是中性的，要么是有害的。群体遗传学模拟 将执行模型来表征疾病变异的预期模式， 变化量 我们的研究结果可能会发现新的遗传变异，这些变异可能会影响代谢性疾病的风险。 综合征，并将，更普遍地说，有助于有效地设计疾病相关性研究，并在 对旨在复制原始关联的研究结果的解释。

The ultimate goal of this proposal is to understand the genetic basis of the metabolic syndrome, a cluster of phenotypes that includes type 2 diabetes (T2D), obesity, hypertension, and dyslipidemia. These phenotypes account for a disproportionate amount of the public health burden in the US. Evolutionary genetics offers a powerful framework for investigating the metabolic syndrome because the risk genotypes are hypothesized to be result of metabolic adaptations to the diverse environments of ancestral human populations. In this multi-investigator proposal, we will address population genetics hypotheses in the following specific aims: 1. We will develop statistical methodology to test correlations between SNP allele frequencies and environmental variables against a null model of the correlations between populations due to population history. We will also select approx. 200 genes involved in the biological processes underlying the metabolic syndrome and 300 unconstrained genomic regions to be used as 'controls'. A total of 3072 SNPs - divided into approx. 2700 tag SNPs in the candidate genes and 300 SNPs in control regions (1 SNP/control region) -will be genotyped in 1056 individuals from 52 worldwide populations. The newly developed statistical methodology will be used to analyze the SNP genotyping data. 2. A set of approx. 20 candidate genes will be re-sequenced in 16 individuals each from 3 populations of African, European and Asian origin, respectively. The re-sequencing data will be analyzed to determine if a signature of positive natural selection is present in these genes and estimate the age of the selected alleles. 3. We will develop a formal model for the evolution of the metabolic syndrome in which disease risk is due to ancestral alleles that were maintained by purifying selection in ancient human populations and became either neutral or deleterious after the switch to the Western lifestyle. Population genetics simulations of this model will be performed to characterize the expected patterns of disease variation and linked neutral variation. The results of our study are likely to identify novel genetic variants that may affect the risk to the metabolic syndrome and will, more generally, help in the efficient design of disease association studies and in the interpretation of the results of studies aimed at replicating the original associations.