Clinical and Molecular Epidemiology of High Risk Coronary Plaque

虽然目前的做法主要集中在检测和管理阻塞性 冠状动脉疾病（CAD），有显着的异质性之间的关系，CAD 和心血管（CV）事件的风险。一些患者，尽管患有阻塞性CAD， 发生心血管事件，而其他非梗阻性CAD患者则会发生。的机制 这种高风险冠状动脉斑块（HRCP）的发展还不完全清楚;应用 新兴成像和分子技术的发展为同时实现 识别潜在的生物学途径，早期非侵入性检测的标志物， HRCP的治疗靶点。因此，我们建议（1）确定炎症的作用， HRCP病理生理学中的其他候选生物学途径;（2）确定新的 通过机器学习分析介导HRCP发展的生物学途径 综合代谢组学、蛋白质组学和转录组学分析;以及（3）确定 这些影像学和分子生物标志物对临床预后的增量价值 因素，并创建CV事件风险预测的综合临床-分子模型。我们将 通过首次整合先进的基于CTA的表型分析， HRCP与分子特征分析和裁定的CV事件，利用现有的强大的 NIH资助的一项大型、独特的胸痛患者影像学临床试验的资源 （承诺）。这一建议具有重大的公共卫生意义， 基于群体和局部缺血的方法， 这些患者的风险最高。我们的研究结果将为开发 诊断和治疗针对特定的，罪魁祸首动脉粥样硬化表型， 分子途径

Although current practice focuses largely on the detection and management of obstructive coronary artery disease (CAD), there is marked heterogeneity in the relationship between CAD and risk for cardiovascular (CV) events. Some patients, despite having obstructive CAD, do not experience cardiovascular events, while others with non-obstructive CAD do. The mechanisms of this high risk coronary plaque (HRCP) development are incompletely understood; application of emerging imaging and molecular technologies holds great promise for simultaneously identifying underlying biological pathways, markers for early noninvasive detection, and novel therapeutic targets for HRCP. Thus, we propose to (1) determine the role of inflammation and other candidate biological pathways in the pathophysiology of HRCP; (2) identify novel biological pathways mediating development of HRCP through machine learning analyses of integrated metabolomic, proteomic and transcriptomic profiling; and (3) determine the incremental prognostic value of these imaging and molecular biomarkers over clinical factors and create an integrated clinico-molecular model of CV event risk prediction. We will accomplish these goals by, for the first time, integrating advanced CTA-based phenotyping of HRCP with molecular profiling and adjudicated CV events, leveraging the robust, existing resources of a large, unique NIH-funded clinical trial of imaging in chest pain patients (PROMISE). This proposal holds great public health significance by augmenting current population- and ischemia- based approaches and more precisely and preemptively identifying those patients at highest risk. Our findings will provide a critical foundation for the development of diagnostics and therapeutics targeted at specific, culprit atherosclerotic phenotypes and molecular pathways.