Genetic Mediators of Metabolic Cardiovascular Disease Risk

描述（由申请人提供）：这个大机会（RC 2）补助金是为了响应NHLBI呼吁对大规模DNA测序和分子分析的良好表型NHLBI队列的建议和描述分子分析的附录部分。心血管风险的分子预测因子的识别是非常有趣的，不仅因为它们有可能显着提高我们在临床环境中对疾病负担和风险进行更精细和准确评估的能力，而且还因为它们提供了了解冠状动脉疾病生物学和这种不可预测疾病中事件风险的能力。为了在风险评估和新的治疗方法方面取得进展，我们必须了解前瞻性研究队列中分子标记物的遗传结构，其中研究受试者已被精细表征和表型化，并且随访是完整和详细的。队列。该项目将使用杜克导管生物储存库，这是一个前瞻性队列，招募了2001年1月至今首次与杜克心导管实验室接触的个体。所有个人在第一次接触后六个月和每年接受后续健康状况调查。此外，每年的死亡率是使用医疗上可用的资源，如国家死亡指数进行评估的。该项目将重点关注后续事件（主要是心肌梗死和死亡）。研究队列所有成员的药物数据均可用。分子特征分析。我们已经从该队列中获得了2000例匹配病例和对照（各1000例）的集中代谢谱，并观察到无论疾病状态如何，后续事件的重要代谢预测因子。此外，我们最近发表了来自该队列的数据，显示了外周基因表达生物标志物的显著预测能力。最后，一个详细的预测模型正在构建这个队列，其中输入是现成的，众所周知的心血管风险的临床预测。目标。在这项研究中，我们建议：1）对已经进行代谢谱分析的同一2000名受试者队列进行外周基因表达谱分析; 2）在同一队列中进行GWA。一旦有了重要的遗传和外周基因表达预测因子，我们将：3）单独定义分子预测因子的预测能力，并与临床模型相结合; 4）定义由遗传变异定义的分子途径和遗传因素导致的风险比例。 公共卫生相关性：个性化医疗是国家当前健康目标的一个目标，需要识别和量化个人风险的方法。为了在风险评估方面取得进展并开发新的治疗方法，必须了解前瞻性研究队列中分子标记物的遗传结构，其中研究受试者已被精细表征和表型化，并且随访是完整和详细的。我们将联合收割机结合心血管风险的外周小分子代谢标志物、外周基因表达谱和全基因组SNP筛选的知识，开发心血管风险的综合分子谱。

DESCRIPTION (provided by applicant): This Grand Opportunity (RC2) grant is written in response to NHLBI call for proposals on Large-scale DNA Sequencing and Molecular Profiling of Well-phenotyped NHLBI Cohorts and the addendum portion describing Molecular Profiling. The identification of molecular predictors of cardiovascular risk is of great interest, not only because of their potential to significant improve our ability to make more refined and accurate assessment of disease burden and risk in the clinical environment, but also because of the power they provide to understand the biology of coronary artery disease and event risk in this unpredictable disease. In order to make advancements in risk assessment and new therapeutic approaches, it is imperative that we understand the genetic architecture of molecular markers in prospective study cohorts where the study subjects have been exquisitely characterized and phenotyped and on which follow-up is complete and detailed. Cohort. The project will use the Duke CATHGEN biorepository, which is a prospective cohort of individuals enrolled upon first encounter with the Duke Cardiac Catheterization Laboratory between January 2001 and present. All individuals obtain follow-up health status surveys at six months and then yearly following their first encounter. Also, yearly death is assessed using publically available resources, such as the National Death Index. The project will focus on subsequent events (primarily myocardial infarction and death). Medication data are available on all members of the study cohort. Molecular Profiling. We have already obtained focused metabolic profiling on 2000 matched cases and controls (1000 of each) from this cohort and observed significant metabolic predictors of subsequent events irrespective of disease status. Also, we recently have published data from this cohort showing significant predictive power of peripheral gene expression biomarkers. Finally, a detailed predictor model is being constructed on this cohort, where the input is readily available and well know clinical predictors of cardiovascular risk. Aims. In this study, we propose to: 1) Perform peripheral gene expression profiling on the same 2000 subject cohort in which the metabolic profiling has been performed; 2) Perform a GWAs in this same cohort. Once significant genetic, and peripheral gene expression predictors are available, we will: 3) Define the predictive power of the molecular predictors alone and in combination with the clinical model; 4) Define the molecular pathways defined by the genetic variants and the proportion of risk that is due to genetic contributors. PUBLIC HEALTH RELEVANCE: Personalized medicine, a goal of the current health goals of the country, requires methods to identify and quantify individual risk. In order to make advancements in risk assessment and develop new therapeutic approaches, it is imperative that one understand the genetic architecture of molecular markers in prospective study cohorts where the study subjects have been exquisitely characterized and phenotyped and on which follow-up is complete and detailed. We will combine knowledge of peripheral small molecular metabolic markers of cardiovascular risk, peripheral gene expression profiles and a genome wide SNP screen to develop comprehensive molecular profiles of cardiovascular risk.