Genetic Epidemiology of CVD Risk Factors

超出所提供的空间。了解心血管疾病（CVD）等常见多因素疾病的遗传基础仍然是一个难以捉摸的目标，但近年来分子遗传技术、统计遗传方法和CVD危险因素表型评估的巨大进步促进了更复杂的心脏病风险遗传研究。本研究的总体目标是阐明遗传因素影响CVD危险因素的作用，最终确定影响CVD风险年龄相关进展的特定基因。这一目标将通过一项新的创新合作研究项目来实现，该项目由赖特州立大学医学院和西南生物医学研究基金会协调的R01赠款组成。这项研究以25年前开始调查的5个多代大家庭（4个白人和1个非裔美国人）中的764个人为中心。从原始参与者收集的数据包括数百种生化、医学、生理、行为、生理、心理、遗传和人口统计学特征。不过，从某种程度上说，最初的研究是超前的，因为成本效益高的全基因组图谱和统计遗传学方法，要想有效分析来自大量扩展亲属的家族数据，还需要10年或20年的时间。拟议的研究包括四个具体目标：1)从大约500名原始参与者中收集25年的随访数据，并从大约500名原始研究中未检查的亲属中收集新数据。收集的CVD危险因素表型包括血流动力学测量、颈动脉内膜-中膜厚度和心肺功能测量。2)从这1000个个体中获取DNA样本，利用现代高通量分子基因分型方法建立10 cM遗传标记图谱。3)量化和表征遗传对心血管疾病危险因素影响的性质，采用定量遗传学方法，适用于来自大家族亲属的横断面和连续（随访）数据。4)进行连锁分析，找出影响心血管疾病危险因素个体差异的染色体区域（qtl）。在这些连锁分析之后，我们将更仔细地检查我们最强的连锁信号与精细定位连锁分析，以缩小感兴趣的染色体区域。寿命健康研究中心社区健康莱特州立大学医学院凯特林，OH 45420国家人类基因组研究所巴尔的摩，马里兰州性能站点========================================部分结束===========================================

EXCEED THE SPACE PROVIDED. Understanding the genetic basis of common multifactorial diseases such as cardiovascular disease (CVD) remains an elusive goal, but the great advances in molecular genetic technology, statistical genetic methods, and phenotypic assessment of CVD risk factors in recent years have facilitated more sophisticated genetic studies of risks for heart disease. The overall goal of this study is to elucidate the role of genetic factors influencing risk factors for CVD, ultimately identifying specific genes influencing the age-related progression of CVD risks. This goal will be pursued through a new and innovative collaborative research project consisting of coordinated R01 grants to Wright State University School of Medicine and the Southwest Foundation for Biomedical Research. The study population centers on 764 individuals in five large, multigeneration, extended families (four white and one African-American) originally examined 25 years ago. Data collected from the original participants includes hundreds of biochemical, medical, physiological, behavioral, physical, psychological, genetic and demographic traits. To some extent, though, the original study was ahead of its time in that cost-effective whole genome mapping and statistical genetic methods for effective analysis of familial data from large extended kindreds were a decade or two away. The proposed study consists of four specific aims: 1) Collect 25-year follow-up data from approximately 500 of the original participants, and new data from approximately 500 of their relatives not examined in the original study. The CVD risk factor phenotypes to be collected include hemodynamic measures, carotid intima-media thickness, and measures of cardiopulmonary function. 2) Obtain DNA samples from these 1,000 individuals and use modern high-throughput molecular genotyping methods to create a 10 cM genetic marker map. 3) Quantify and characterize the nature of genetic influences on CVD risk factors using quantitative genetic methods suited for cross-sectional and serial (follow-up) data from relatives in large extended families. 4) Conduct linkage analyses to identify chromosomal regions (QTLs) harboring genes that influence individual variation in CVD risk factors. Following these linkage analyses, we will examine more closely our strongest linkage signals with fine mapping linkage analysis in order to narrow chromosomal regions of interest. Lifespan Health Research Center Department of Community Health Wright State University School of Medicine Kettering, OH 45420 National Human Genome Research Institute Baltimore, MD PERFORMANCE SITE ========================================Section End===========================================