Risk and Resilience in Pulmonary Arterial Hypertension and Genetically Susceptible Individuals

摘要 摘要肺动脉高压(PAH)是一种诊断延迟且显著升高的孤儿疾病。 右心衰竭的死亡率。尽管FDA批准了近12种治疗PAH的药物，但中位存活率仅为 七年了。所有批准的治疗方法都针对三种血管扩张途径中的一种，没有一种是疾病 正在修改。此应用程序有两个目标：1)了解动态和静态关系 分子标志物与PAH进展和复原性；2)确定PAH风险的分子特征和 携带导致PAH突变的个体的弹性。目前尚不清楚为什么一些高危个体会患上 PAH和其他机构则不这么认为。BMPR2突变存在于约30%的PAH患者中，但临床上 外显率只有20%。未受影响的BMPR2突变携带者(UMCS)是一种独特的且未被研究的 这也可能为临床PAH患者的疾病轨迹提供线索。纵向自然 缺乏多环芳烃分子图谱的历史研究。多环芳烃的大多数分子图谱研究都是交叉的 这限制了对疾病进展和疾病标记物随时间的关系的了解。我们 提出了一种在多个时间点进行密集临床和分子表型分析的策略，以克服推断 横断面研究的局限性。该应用程序将利用构建的临床和研究基础设施 在我们对PAH患者的研究中，范德比尔特在过去的35年里。调查人员分享了广泛的 公布了招募这种罕见疾病和相关UMCS患者的记录。我们假设一个 全面了解患者和遗传易感性患者的风险和弹性随时间的变化 个人将提供对疾病严重性的洞察力，并确定PAH患者的新治疗靶点。 目标1将确定疾病进展和复原力的静态和动态分子特征。1A：表演 HPAH、IPAH和健康对照组的一系列临床、蛋白质组和基因表达谱分析 好几年了。生物信息学和网络医学分析将识别与变化相关的蛋白质和RNA 父母队列和两个外部验证队列的临床结果、功能容量和RV功能。 1B：测试添加分子风险/弹性标记物是否会改善广泛使用的PAH的性能 风险预测工具(显示2.0风险分数)。目标2将确定临床和分子因素促进 UMCS纵向队列中对多环芳烃的复原力和敏感性。UMCS将接受一系列临床和 分子表型，如目标1。反映多环芳烃的蛋白质/基因是“风险因素”，而那些反映a的蛋白/基因 健康的人口是“弹性因素”。将开发解释性模型并在验证中进行测试 一群人。我们将测试UMC的风险和恢复力特征与PAH患者临床结果的相关性 和风险预测性能。这些研究将确定PAH风险和恢复力的特征 进展和外显性，为个性化护理和监测迈出了第一步，由 生物数据。

ABSTRACT Pulmonary arterial hypertension (PAH) is an orphan disease with a delayed diagnosis and markedly elevated mortality from right heart failure. Despite nearly a dozen FDA-approved drugs for PAH, median survival is only seven years. All approved therapies target one of three vasodilatory pathways, and none are disease modifying. This application has two objectives: 1) Understand dynamic and static relationships between molecular markers and PAH progression and resilience; 2) Identify molecular features of PAH risk and resilience in individuals harboring a PAH-causing mutation. It is unknown why some at risk individuals develop PAH and others do not. BMPR2 mutations are present in about 30% of patients with PAH but clinical penetrance is only 20%. Unaffected BMPR2 mutation carriers (UMCs) are a unique and understudied population that may also provide clues to disease trajectory in patients with clinical PAH. Longitudinal natural history studies with molecular profiling in PAH are lacking. Most molecular profiling studies in PAH are cross- sectional which limits understanding of how disease progression and disease markers relate over time. We propose a strategy of dense clinical and molecular phenotyping at multiple timepoints to overcome inferential limitations of cross-sectional studies. This application will leverage the clinical and research infrastructure built at Vanderbilt over the past 35 years in our study of PAH patients. The investigators share an extensive published record of recruiting patients with this rare disease and related UMCs. We hypothesize that a comprehensive understanding of risk and resilience over time in patients and genetically susceptible individuals will provide insight into disease severity and identify novel therapeutic targets in patients with PAH. Aim 1 will identify static and dynamic molecular features of disease progression and resilience. 1a: Perform serial clinical, proteomic, and gene expression profiling in HPAH, IPAH, and healthy controls 3 times over 4 years. Bioinformatic and network medicine analyses will identify proteins and RNAs associated with changes in clinical outcomes, functional capacity, and RV function in the parent cohort and two external validation cohorts. 1b: Test whether adding molecular risk/resilience markers will improve the performance of a widely used PAH risk prediction tool (REVEAL 2.0 Risk Score). Aim 2 will identify the clinical and molecular factors that promote resilience and susceptibility to PAH in a longitudinal cohort of UMCs. UMCs will undergo serial clinical and molecular phenotyping as in Aim 1. Proteins/genes that mirror PAH are “risk factors” and those that mirror a healthy population are “resilience factors”. Explanatory models will be developed and tested in validation cohorts. We will test UMC risk and resilience features for associations with clinical outcomes in PAH patients and risk prediction performance. These studies will identify signatures of risk and resilience to PAH progression and penetrance, offering an initial step toward personalizing care and surveillance guided by biologic data.