Strong Heart Family Study

描述（由申请人提供）： 强心家族研究的长期目标是检测、绘制和鉴定影响心血管疾病（CVD）和其他相关疾病风险因素变化的多态性基因，这些疾病是美洲印第安人的主要健康问题。直接感兴趣的是风险因素和前体，例如脂质表型、糖尿病表型、肥胖的测量、与止血相关的测量以及心脏和动脉结构和功能的测量。在强心研究（SHS）的第三阶段和第四阶段，我们与其他SHS研究人员合作，在三个中心（亚利桑那州、俄克拉荷马州和达科他州）成功招募和检查了1,200多名大家庭成员。我们已经证明，许多心血管疾病相关的表型是可遗传的，我们将很快完成一个10厘摩的图谱，其中包括386个短串联重复序列（STRS）的基因型在每个3,600+个人。在多达2,100个个体的连锁筛选中，我们发现了许多含有有希望的连锁信号的染色体区域：（chr 12 p，LOD=5.3）;体重（LOD=5.17）和体重指数（LOD=5.08）（chr 4 q）;血浆胰岛素水平（LOD=3.5）和瘦体重（LOD=2.6）（chr 2 p）;射血分数（chr 1q，LOD=3.5）; LDL-C（chr 10p，LOD=3.7）;派-1（chr 11p，LOD=3.03）;以及通过因子分析确定的胰岛素抵抗综合征变量的聚类，包括葡萄糖/胰岛素/肥胖因子（chr 4，LOD=2.2）和血脂异常（chr 12，LOD=2.7）。我们将继续我们的连锁分析，并将做更精细的规模映射，以更精确地定位数量性状基因座（QTL）在目标染色体区域。这将涉及候选基因的优先级排序和每个QTL区域内多个候选基因的广泛测序，以确定单核苷酸多态性（SNP），然后对我们在候选基因中确定的所有SNP进行SNP分型。我们的分析将使我们能够测试特定的SNP多态性是否解释了我们的连锁信号。我们还将测试SNPs是否解释了SHS队列中人群水平的关联。新的贝叶斯方法的使用将使我们能够区分功能基因和与它们连锁不平衡的多态性，并将大大减少耗时的分子遗传分析，否则将有必要缩小功能多态性。(End摘要）

DESCRIPTION (provided by applicant): The long-term goal of the Strong Heart Family Study is to detect, map, and identify polymorphic genes that influence variation in risk factors for cardiovascular disease (CVD) and other related disorders that are major health problems in American Indians. Of immediate interest are risk factors and precursors such as lipid phenotypes, diabetes phenotypes, measures of obesity, measures associated with hemostasis, and measures of cardiac and arterial structure and function. In Phases III and IV of the Strong Heart Study (SHS), we have collaborated with the other SHS investigators in successfully recruiting and examining more than 1,200 members of extended families in each of three centers (in Arizona, Oklahoma, and the Dakotas). We have shown that many of the CVD-related phenotypes are heritable, and we will soon complete a 10centimorgan map that includes genotypes for 386 short tandem repeats (STRS) in each of the 3,600+individuals. In linkage screening of as many as 2,100 individuals, we have identified numerous chromosomal regions containing promising linkage signals: left ventricular mass normalized for height (chr 12p, LOD=5.3);weight (LOD=5.17) and body mass index (LOD=5.08) (chr 4q); plasma insulin level (LOD=3.5) and lean body mass (LOD=2.6) (chr 2p); ejection fraction (chr 1q, LOD=3.5); LDL-C (chr 10p, LOD=3.7); PAI-1 (chr 11p,LOD=3.03); and clusters of insulin resistance syndrome variables identified by factor analysis including factors for glucose/insulin/obesity (chr 4, LOD=2.2) and dyslipidemia (chr 12, LOD=2.7). We will continue our linkage analyses and will do finer scale mapping to more precisely localize quantitative trait loci (QTLs) within targeted chromosomal regions. This will involve prioritizing of candidate genes and extensive sequencing of multiple candidate genes within the region of each QTL to identify single nucleotide polymorphisms (SNPs), and then SNP typing of all SNPs that we identify in candidate genes. Our analyses will enable us to test whether specific SNP polymorphism(s) account for our linkage signals. We also will test whether the SNPs account for population-level association in the SHS cohort. The use of new Bayesian methods will enable us to distinguish functional genes from polymorphisms in linkage disequilibrium with them and will greatly reduce the amount of time-consuming molecular genetic analysis that would otherwise be necessary to narrow in on functional polymorphisms. (End of Abstract)