Whole Genome Sequencing to Identify Causal Genetic Variants Influencing CVD Risk

描述（由申请人提供）：心血管疾病（CVD）仍然是美国的主要死亡原因。虽然心血管疾病的风险是遗传的，但在风险途径中的致病基因的识别一直很慢。该项目的重点是通过集中于定量内表型的遗传解剖来鉴定影响CVD易感性变化的因果基因，所述内表型包括颈动脉壁厚度、脂质、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、以及脑白色物质高信号的测量，这些测量与CVD风险遗传相关。我们将利用现有的样本/数据，从一个宝贵的遗传资源，圣安东尼奥家庭研究（SAFS），涉及墨西哥裔美国人的大型扩展谱系。这个长期运行的非常成功的项目已经产生了大量的数量性状基因座（QTL）定位的相关性心血管疾病的风险。在这个项目中，我们从QTL定位到致病基因鉴定。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个大谱系的1，957个个体中所有可能的功能变体。使用的大谱系代表了检测罕见功能变异的最佳研究设计。将采用先进的统计遗传学方法来识别影响CVD风险的数量性状基因座（QTL）区域中可能的因果基因/变体。为了实现我们的目标，我们将（1）使用新的谱系特异性定位方法定位由于罕见功能变体而导致的其他CVD相关QTL，（2）获得1，957名墨西哥裔美国人个体的全基因组序列信息，（3）使用WGS信息鉴定影响CVD风险的现有QTL的致病基因，（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，以鉴定影响CVD风险的新的罕见功能性蛋白质改变变体，（5）使用测量变体特异性功能调节潜力的新型全基因组测定，以允许使用预测的功能变体进行全基因组直接关联扫描，从而鉴定影响CVD风险的新型罕见调节变体。鉴于CVD对死亡率的巨大影响和这种疾病造成的经济负担，很明显，新的基因组分析方法是必要的，以确定涉及疾病风险的新基因和途径。该项目的结果应确定CVD风险的致病基因。致病基因的识别将必然产生于这些基因的途径上，并将直接识别新的药物靶点。公共卫生相关性：心血管疾病（CVD）是美国最常见的死亡原因，也造成了巨大的经济负担。在这个项目中，我们专注于在扩展的家系中使用强大的全基因组测序方法来鉴定CVD风险的新基因。这种方法将引导我们识别影响CVD风险的新基因和潜在的新治疗靶点。

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. PUBLIC HEALTH RELEVANCE: Cardiovascular disease (CVD) is the most common cause of death in the United States and also poses a huge economic burden. In this project, we focus on the identification of novel genes underlying the CVD risk, using a powerful whole genome sequencing approach in extended pedigrees. Such an approach will lead us to the identification of novel genes and potential new therapeutic targets influencing CVD risk.