Whole Genome Sequencing to Identify Causal Genetic Variants Influencing CVD Risk

简介(申请人提供)：心血管疾病(CVD)仍然是美国主要的死亡原因。尽管心血管疾病的风险是可遗传的，但风险途径中的因果基因识别一直很缓慢。本项目致力于通过对定量内表型的遗传解剖，包括颈动脉壁厚度、血脂、肥胖相关表型、血压相关表型、胰岛素/葡萄糖轴、炎症标志物、氧化应激标志物、止血/凝血因子以及脑白质高信号的测量，来识别影响心血管疾病易感性差异的原因基因。我们将利用有价值的遗传资源圣安东尼奥家族研究(SAFS)的现有样本/数据，该研究涉及墨西哥裔美国人的大型扩展家系。这个长期成功的项目已经产生了大量与心血管疾病风险相关的数量性状基因座(QTL)定位。在这个项目中，我们从QTL定位转移到因果基因识别。我们发现心血管疾病风险基因的方法是全面的；我们将利用全基因组测序来捕获来自45个大型家系的1,957个个体的所有可能的功能变异。将使用的大型家系代表了检测稀有功能变异的最佳研究设计。先进的统计遗传学方法将被用来识别影响心血管疾病风险的数量性状基因(QTL)区域中可能的原因基因/变量。为了实现我们的目标，我们将(1)使用新的谱系特定定位方法来定位由于罕见功能变异而导致的额外的与心血管疾病相关的QTL，(2)获得1,957名墨西哥裔美国人的全基因组序列信息，(3)使用WGS信息识别潜在影响心血管疾病风险的现有QTL的原因基因，(4)使用非同义编码变体进行不可知的全基因组直接关联扫描，以识别影响心血管疾病风险的新的罕见功能蛋白改变变体，以及，(5)使用一种新的全基因组分析方法，测量变异体特定的功能调节潜力，以允许使用预测的功能变异体进行全基因组直接关联扫描，以识别影响心血管疾病风险的新的罕见调节变异体。鉴于心血管疾病对死亡率的巨大影响和这种疾病造成的经济负担，显然有必要采用新的基因组分析方法来识别与疾病风险有关的新基因和途径。该项目的结果应该确定心血管疾病风险的原因基因。对致病基因的识别将在这些基因的途径上产生，并将直接识别新的药物靶点。

DESCRIPTION (provided by applicant): Cardiovascular disease (CVD) remains the leading cause of death in the United States. Although CVD risk is heritable, identification of causal genes in risk pathways has been slow. This project focuses on the identification of causal genes that influence variation in susceptibility to CVD by concentrating on genetic dissection of quantitative endophenotypes including carotid wall thickness, lipids, obesity-related phenotypes, blood pressure-related phenotypes, the insulin/glucose axis, inflammatory markers, oxidative stress markers, hemostasis/coagulation factors, and measures of brain white matter hyperintensities that are genetically correlated with CVD risk. We will utilize existing samples/data from a valuable genetic resource, the San Antonio Family Study (SAFS), involving large extended pedigrees of Mexican American individuals. This long- running highly successful project has produced a large number of quantitative trait locus (QTL) localizations of relevance for CVD risk. In this project, we move from QTL localization to causal gene identification. Our approach to CVD-risk gene discovery is comprehensive; we will utilize whole genome sequencing to capture all possible functional variants in 1,957 individuals from 45 large pedigrees. The large pedigrees to be used represent an optimal study design for the detection of rare functional variants. Advanced statistical genetic methods will be employed to identify the likely causal genes/variants in quantitative trait locus (QTL) regions influencing CVD risk. To achieve our objectives, we will (1) localize additional CVD-related QTLs due to rare functional variants using novel pedigree-specific localization methods, (2) obtain whole genome sequence information for 1,957 Mexican American individuals, (3) identify causal genes underlying existing QTLs influencing CVD risk using WGS information, (4) perform agnostic genome-wide direct association scans using non-synonymous coding variants to identify novel rare functional protein-altering variants influencing CVD risk and, (5) use a novel whole genome assay measuring variant-specific functional regulatory potential to permit genome-wide direct association scans using the predicted functional variants to identify novel rare regulatory variants influencing CVD risk. Given the enormous impact of CVD to mortality rates and the economic burden this disease imposes, it is clear that new methods of genomic analysis are necessary to enable the identification of novel genes and pathways involved in disease risk. The results of this project should identify causal genes underlying CVD risk. Identification of the causal genes will obligately generate on the pathways of these genes and will directly identify novel drug targets.