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，代谢综合征是一组 表型包括2型糖尿病(T2D)、肥胖、高血压和血脂异常。这些表型 占美国公共卫生负担的不成比例的比例。进化遗传学提供了一种 研究代谢综合征的强大框架，因为风险基因类型是假设的 这是新陈代谢适应祖先人类不同环境的结果。在这 多研究者提议，我们将在以下具体目标中解决群体遗传学假说： 1.我们将开发统计方法来检验SNP等位基因频率与 环境变量与人口相关性的零模型 历史。我们还将选择约为。参与代谢的生物过程的200个基因 综合症和300个不受限制的基因组区域作为“对照”。总计3072个单核苷酸多态(SNPs) 变成大约。候选基因中2700个标签SNP和控制区300个SNP(1个SNP/控制区) -将对来自全球52个人口的1056个人进行基因分型。新发展的统计学 将使用方法学来分析SNP基因分型数据。 2.一套近似值。20个候选基因将在来自3个种群的16个个体中进行重新测序 分别起源于非洲、欧洲和亚洲。将分析重新排序数据以确定是否存在 正向自然选择的特征出现在这些基因中，并估计所选等位基因的年龄。 3.我们将为代谢综合征的演变开发一个正式模型，在该模型中，疾病风险是由于 在古代人类种群中通过净化选择而保持的祖先等位基因，并成为 在转向西方生活方式后，要么是中性的，要么是有害的。这一现象的群体遗传学模拟 将执行模型来描述疾病变异的预期模式并将其与中性联系起来 变种。 我们的研究结果可能识别出可能影响新陈代谢风险的新基因变异 症状，更广泛地说，将有助于有效地设计疾病关联研究和 解释旨在复制原始联系的研究结果。

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.