Epidemiological and Genetic Studies of Body Mass Index

体重指数的流行病学和遗传学研究

• 批准号: 6421942
• 负责人: RICHARD H MYERS
• 金额: $ 57.43万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-12-05 至 2004-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6421942
• 关键词: DNA; alleles; body weight; clinical research; disease /disorder etiology; family genetics; gene frequency; genetic polymorphism; genetic screening; genetic susceptibility; genotype; human data; human genetic material tag; leptin; linkage disequilibriums; linkage mapping; mass spectrometry; obesity; phenotype; quantitative trait loci; single nucleotide polymorphism

DESCRIPTION (provided by applicant): Increased levels of Body Mass Index (BMI) are associated with increased mortality and morbidity from cardiovascular disease, hypertension, diabetes and other disorders. The frequency of obesity and its associated health-related problems is increasing in the American population. We propose to identify DNA polymorphisms associated with increased BMI, with the goal of identifying genes involved in obesity. The application builds upon a two-stage genome scan for BMI performed in the NHLBI Family Heart Study (FHS). In the first, we examined 101 pedigrees with 1027 persons genotyped and found a LOD of 2.2 on chromosome 7. In stage 2 we examined 135 sibships, 380 persons, and found a LOD of 3.2 for the same locus. Compelling linkage was found in the combined study (LOD = 4.9, chr 7q31.3, 137cM). Identifying genes responsible for complex traits such as BMI has proven remarkably difficult. We propose a novel strategy which combines three cutting edge methods: (1) Regression Tree analyses to identify a homogenous subset of families with evidence for BMI linkage to 7q31.3; (2) DNA pooling of samples from linked versus unlinked families; and (3) quantitative PCR of DNA pools for very high-density SNP mapping. We believe that the combination of these methods will permit a cost effective approach for the identification of genetic polymorphisms in linkage disequilibrium with BMI, and has the potential to become a widely adopted method for gene localization of complex traits. Members of our investigative team have taken a lead role in designing the Regression Tree method for the identification of homogeneous subsets of linked families, based upon differences in anthropometry, lifestyle and physiologic factors. This strategy is designed to optimally divide the families into etiologically homogeneous subgroups by recursive partitioning, defined in terms of the strength of the linkage signal. The recursive partitioning technique dramatically increases power to detect linkage in a sample size such as that of the FHS. Methods for DNA pooling and allele frequency quantification by Mass Spectroscopy are equally fundamental to our application. Using DNA pools of 200 samples each, pools will be created from groups of obese and groups of non-obese individuals from families showing evidence for linkage to the 7q31.3 locus, and contrasting these with pools of obese and non-obese individuals in families that do not show evidence of linkage. Because a single PCR reaction represents the analysis of 200 study participants, fine mapping at a density of one SNP per 50Kb across a region of 20 to 40 Mb becomes readily achievable. We believe that this application has potential to develop methodologies for gene localization and identification for BMI and other complex traits.

描述（由申请人提供）：身体质量指数 (BMI) 水平增加 与心血管疾病死亡率和发病率增加有关 疾病、高血压、糖尿病和其他疾病。肥胖发生频率 及其相关的健康相关问题在美国正在增加 人口。我们建议鉴定与增加相关的 DNA 多态性 BMI，目的是识别与肥胖有关的基因。应用 基于 NHLBI Family Heart 进行的 BMI 两阶段基因组扫描 研究（FHS）。首先，我们检查了 101 个家谱，涉及 1027 人 基因分型并发现 7 号染色体上的 LOD 为 2.2。在第 2 阶段，我们检查了 135 同胞，380 人，发现同一基因座的 LOD 为 3.2。引人注目 联合研究中发现了连锁（LOD = 4.9，chr 7q31.3，137cM）。 事实证明，识别负责BMI等复杂性状的基因 非常困难。我们提出了一种结合了三种切割的新颖策略 边缘方法：（1）回归树分析来识别同质子集 有 BMI 与 7q31.3 关联证据的家庭； (2) 样本DNA汇集 来自有联系和无联系的家庭； (3) DNA池的定量PCR 非常高密度的 SNP 作图。我们相信这些方法的结合 将允许采用具有成本效益的方法来识别遗传 与 BMI 连锁不平衡的多态性，有可能 成为复杂性状基因定位的广泛采用的方法。会员 我们的调查团队在回归设计中发挥了主导作用 用于识别相关家族的同质子集的树方法， 基于人体测量、生活方式和生理因素的差异。 该策略旨在根据病因将家庭最佳地划分为 通过递归划分的齐次子群，定义为 联动信号的强度。递归划分技术 显着提高了检测样本量（例如 FHS。 DNA 混合和等位基因频率质量定量方法 光谱学对于我们的应用同样重要。使用 200 个 DNA 池 每个样本，将根据肥胖组和肥胖组创建池 来自家庭的非肥胖个体显示出与 7q31.3 相关的证据 基因座，并将其与肥胖和非肥胖个体的群体进行对比 没有显示出联系证据的家庭。因为单个 PCR 反应 代表对 200 名研究参与者的分析，以密度为 在 20 至 40 Mb 的区域中每 50 Kb 一个 SNP 变得很容易实现。我们 相信该应用程序有潜力开发基因方法 BMI 和其他复杂特征的定位和识别。