Genetic Epidemiology of CVD Risk Factors

描述(申请人提供)：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实现的目标，但近年来在分子遗传技术、统计遗传方法和心血管疾病风险因素的表型评估方面的巨大进步促进了对心脏病风险的更复杂的基因研究。本研究的总体目标是阐明影响心血管疾病危险因素的遗传因素的作用，最终确定影响年龄相关的心血管疾病风险进展的特定基因。这一目标将通过一个新的创新合作研究项目来实现，该项目包括向莱特州立大学医学院和西南生物医学研究基金会提供协调的R01赠款。这项人口研究以五个大家庭(四个白人和一个非裔美国人)的764个个体为中心，这些大家庭是多代人，最初是在25年前进行的。从原始参与者那里收集的数据包括数百个生化、医学、生理、行为、身体、心理、遗传和人口统计学特征。然而，在某种程度上，最初的研究走在了时代的前面，因为成本效益高的全基因组图谱和统计遗传学方法用于有效分析大型亲属的家族数据还需要十年或二十年的时间。 拟议的研究包括四个具体目标：1)收集约500名原始参与者的25年随访数据，以及约500名未在原始研究中检查的亲属的新数据。收集的心血管危险因素表型包括血流动力学指标、颈动脉内膜-中层厚度和心肺功能指标。2)从这1000个个体中获取DNA样本，并使用现代高通量分子分型方法创建10 cM的遗传标记图谱。3)使用适合于来自大家庭亲属的横断面和系列(随访)数据的定量遗传学方法，量化和表征遗传对心血管疾病危险因素的影响的性质。4)进行连锁分析，以确定含有影响心血管疾病危险因素个体差异的基因的染色体区域(QTL)。在这些连锁分析之后，我们将通过精细定位连锁分析来更密切地检查我们最强的连锁信号，以便缩小感兴趣的染色体区域。

DESCRIPTION (provided by applicant): 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, multigenerational, 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 kindred's 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.