Epidemiological and Genetic Studies of Body Mass Index

描述(由申请人提供)：体重指数(BMI)水平升高 与心血管疾病死亡率和发病率的增加有关 疾病、高血压、糖尿病等疾病。肥胖的频率 在美国，与其相关的健康问题正在增加 人口。我们建议确定与基因增加相关的DNA多态 BMI，目的是识别与肥胖有关的基因。应用程序 在NHLBI家族心脏进行的BMI两阶段基因组扫描的基础上 研究(FHS)。首先，我们检查了101个家系，1027人 对7号染色体进行了基因分型，发现LOD为2.2。在第二阶段，我们检查了135 兄弟姐妹，380人，发现同一基因座的LOD为3.2。引人入胜 在联合研究中发现了连锁(LOD=4.9，CHR 7q31.3,137 cM)。 识别BMI等复杂性状的基因已被证明 难度非常大。我们提出了一种新的策略，将三个切割结合在一起 边方法：(1)回归树分析，以确定齐次子集 有证据表明BMI与7q31.3连锁的家系；(2)样本的DNA池 来自连锁家庭和非连锁家庭；以及(3)DNA池的定量PCR 非常高密度的SNP图谱。我们认为，这些方法的结合 将允许一种具有成本效益的方法来鉴定基因 与体重指数连锁不平衡的多态，并有可能 成为一种被广泛采用的复杂性状基因定位方法。成员 在设计回归的过程中发挥了主导作用 用于识别相关联家族的同质子集的树法， 基于人体测量、生活方式和生理因素的差异。 这一策略的设计是为了根据病因将这些家庭最佳地划分为 通过递归划分的齐次子群，根据 链接信号的强度。递归划分技术 极大地提高了检测样本大小中的连锁的能力 英国国民健康保险制度。DNA汇聚和等位基因频率的质量法 光谱学对我们的应用同样重要。使用200个DNA池 每个样本，池将由肥胖人群和以下人群创建 来自家庭的非肥胖者显示与7q31.3连锁的证据 基因座，并将这些与肥胖和非肥胖个体在 没有显示出关联证据的家庭。因为一个单一的聚合酶链式反应 表示对200名研究参与者的分析，以密度 在20到40 Mb的区域中，每50Kb就可以轻松实现一个SNP。我们 相信这一应用具有开发基因方法学的潜力 体重指数和其他复杂性状的定位和鉴定。

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.