Network Medicine and Systems Pharmacology to Advance Precision Medicine in Combined Pulmonary Hypertension

摘要 左心衰竭所致的肺动脉高压(PH)是一种常见且高度病态的疾病，其特点是 分子、组织表型和临床的异质性阻碍了诊断和治疗目标的进展 发现号。左心衰竭-PH患者缺乏生化标记物和治疗方法。一些患者患有 左心疾病合并毛细血管前后PH(CPH)，特征是严重升高 肺血管阻力、血管重构和早期死亡。这种血管轮廓不能归因于 至单纯肺静脉高压(PVH)。例如，我们表明，与PVH相比，患有PVH的患者 CPH较年轻，但左心疾病的持续时间和严重程度相似。我们还报道了基因 CPH的特征与PVH患者不同，但在CPH患者中也是高度不同的。这 观察结果与在CPH尸检中观察到的复杂的血管重塑模式一致， 总而言之，提示可能存在利用个别CPH独特的病理生物学特征的机会 患者为优化诊断和治疗。 我们提出了创新网络医学的初步数据，以开发独特的病理生物学特征 与PH相关的复杂左心疾病患者。我们开发了专门针对患者的网络 关于功能/物理蛋白质-蛋白质相互作用(PPI)，为每个蛋白质生成唯一的分子“配线图” 有耐心的。网络拓扑预测肺血流动力学和组织学特征(例如纤维化) 个体患者，尽管队列中存在表型异质性。因此，我们建议利用这一点 在CPH中推进精确医学的方法，这为我们的中心假设建立了框架：在CPH中， 跨患者特定PPI网络的共享功能将识别下一代生物标志物(S) 关于功能分子通路、疾病特异性和预后。我们还假设，目标PPI是独一无二的 对于个体患者来说，使用系统药理学将为个体化药物治疗提供一条新的途径。 在目标1中，我们将描述CPH、PVH和肺动脉高压(PAH)转录组(N= 50个/组)，以确定所有CPH患者共享但不同于PVH/PAH的PPI。我们将使用 内表型丰富、网络拓扑、遗传背景和蛋白质表达数据作为过滤器来识别 硅胶领域的下一代CPH生物标志物候选者。最后，我们将验证CPH生物标志物的关联性 在两个外部队列和人肺样本中进行功能能力和预后的研究。在目标2中，我们将整合 药物-蛋白质相互作用和PPI网络数据，以确定患者特定的重新调整用途的治疗并使用功能性 遗传学、药物效应--蛋白质表达数据，以及筛选治疗药物的可获得性和安全性 候选人。最后，我们将使用机械性终点进行5个N-of-1安慰剂对照交叉试验 以检验我们的系统药理管道用于个体化药物选择的有效性。这些创新之处 实验推进了CPH的精准医学，CPH是一种高度病态的疾病，缺乏治疗。

ABSTRACT Pulmonary hypertension (PH) due to left heart failure is a common and highly morbid disease characterized by molecular, histophenotypic, and clinical heterogeneity that hampers progress in diagnosis and therapeutic target discovery. Biochemical markers and treatments for left heart failure-PH patients are lacking. Some patients with left heart disease develop combined pre- and post-capillary PH (CPH), characterized by severely elevated pulmonary vascular resistance, vascular remodeling, and early death. This vascular profile cannot be ascribed to pulmonary venous hypertension (PVH) alone. For example, we show that compared to PVH, patients with CPH are younger but have a similar duration and severity of left heart disease. We also reported that the genetic profile of CPH is divergent from patients with PVH but is also highly diverse among CPH patients. This observation is consistent with the complex patterns of vascular remodeling observed at autopsy in CPH, and, collectively, suggest that opportunity may exist to leverage the unique pathobiological profile of individual CPH patients for optimizing diagnosis and treatment. We present preliminary data innovating network medicine to exploit unique pathobiological features in patients with a complex left heart disease associated with PH. We developed patient-specific networks focusing on functional/physical protein-protein interactions (PPIs), generating a unique molecular ‘wiring map’ for each patient. Network topology predicted pulmonary hemodynamics and tissue histologic features (e.g. fibrosis) in individual patients despite phenotypic heterogeneity across the cohort. Therefore, we propose to use this approach to advance precision medicine in CPH, which sets the framework for our central hypothesis: In CPH, shared features across patient-specific PPI networks will identify next-generation biomarker(s) that are based on functional molecular pathways, disease-specific, and prognostic. We postulate also that targeting PPIs unique to individual patients using systems pharmacology will provide a novel avenue to individualize drug therapy. In Aim 1 we will profile the CPH, PVH, and pulmonary arterial hypertension (PAH) transcriptome (N= 50/group) to identify PPIs that are shared by all CPH patients, but distinct from PVH/PAH. We will use endophenotype enrichment, network topology, genetic context, and protein expression data as filters to identify next-generation CPH biomarker candidates in silico. Finally, we will validate the CPH biomarkers for associations with functional capacity and prognosis in two external cohorts and human lung samples. In Aim 2 we will integrate drug-protein interaction and PPI network data to identify patient-specific repurposed therapies and use functional genetics, drug effect-protein expression data, and drug availability and safety profiles to filter therapeutic candidates. Finally, we will perform five N-of-1 placebo-controlled cross-over trials using mechanistic endpoints to test the validity of our systems pharmacology pipeline for individualized drug selection. These innovative experiments advance precision medicine in CPH, a highly morbid disease that lacks treatment.