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

网络医学和系统药理学推进联合肺动脉高压的精准医学

• 批准号: 10467751
• 负责人: Evan L Brittain
• 金额: $ 79.88万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-20 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10467751
• 关键词: Academic Medical Centers; Activities of Daily Living; Address; Attention; Autopsy; Biochemical Markers; Biological Markers; Biology; Blood Vessels; Blood capillaries; Cardiovascular Diseases; Cessation of life; Clinical; Clinical Trials; Collaborations; Complex; Cross-Over Trials; Data; Development; Diagnosis; Disease; Experimental Models; Fibrosis; Genetic; Heart Diseases; Heart failure; Heterogeneity; Histologic; Human; Hypertrophic Cardiomyopathy; In Situ; Individual; Individual Differences; Left; Lung; Maps; Medicine; Methods; Mission; Molecular; National Heart, Lung, and Blood Institute; Outcome; Pathology; Pathway interactions; Patients; Pattern; Pharmaceutical Preparations; Pharmacology; Pharmacotherapy; Phenotype; Placebo Control; Plasma; Prognosis; Proteins; Pulmonary Heart Disease; Pulmonary Hypertension; Pulmonary Vascular Resistance; Pulmonary arterial remodeling; Reporting; Research; Safety; Sampling; Severities; System; Testing; Tissues; United Kingdom; United States National Institutes of Health; Validation; Variant; Vascular remodeling; Vulnerable Populations; Work; analytical method; arterial remodeling; base; biobank; biomarker discovery; candidate marker; clinical heterogeneity; cohort; endophenotype; experimental study; functional status; hemodynamics; high risk; human disease; improved; in silico; individual patient; innovation; mortality; next generation; novel; precision medicine; predictive test; prognostic; prognostication; protein expression; protein protein interaction; pulmonary arterial hypertension; pulmonary vascular disorder; pulmonary venous hypertension; sex; therapeutic candidate; therapeutic target; transcriptome; treatment response; venule

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.

抽象的 左心衰竭引起的肺动脉高压（PH）是一种常见且发病率高的疾病，其特征是 阻碍诊断和治疗目标进展的分子、组织表型和临床异质性 发现。左心衰竭PH患者缺乏生化标志物和治疗方法。一些患者患有 左心疾病合并毛细血管前和后 PH (CPH)，其特征是严重升高 肺血管阻力、血管重塑和早期死亡。这种血管分布不能归因于 单独治疗肺静脉高压（​​PVH）。例如，我们发现与 PVH 患者相比， CPH 较年轻，但左心疾病的持续时间和严重程度相似。我们还报道了遗传 CPH 的概况与 PVH 患者不同，但 CPH 患者之间也高度不同。这 观察结果与 CPH 尸检中观察到的血管重塑的复杂模式一致，并且， 总的来说，表明可能存在利用个体 CPH 独特病理生物学特征的机会 患者以优化诊断和治疗。 我们提供创新网络医学的初步数据，以利用独特的病理生物学特征 患有与 PH 相关的复杂左心疾病的患者。我们开发了针对患者的网络，重点关注 功能/物理蛋白质-蛋白质相互作用（PPI），为每个蛋白质生成独特的分子“线路图” 病人。网络拓扑预测肺血流动力学和组织组织学特征（例如纤维化） 尽管队列中的表型异质性，但个体患者。因此，我们建议使用这个 推进 CPH 精准医学的方法，为我们的中心假设奠定了框架：在 CPH 中， 跨患者特定 PPI 网络的共享特征将识别基于 关于功能分子途径、疾病特异性和预后。我们还假设针对 PPI 的独特性 使用系统药理学为个体患者提供个体化药物治疗的新途径。 在目标 1 中，我们将分析 CPH、PVH 和肺动脉高压 (PAH) 转录组 (N= 50/组）来识别所有 CPH 患者共有的 PPI，但与 PVH/PAH 不同。我们将使用 内表型富集、网络拓扑、遗传背景和蛋白质表达数据作为过滤器来识别 下一代 CPH 生物标志物候选物。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具有功能能力和预后。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用途疗法并使用功能 遗传学、药物效应-蛋白质表达数据以及药物可用性和安全性概况，以筛选治疗方法 候选人。最后，我们将使用机械终点进行五次 N-of-1 安慰剂对照交叉试验 测试我们的系统药理学管道用于个体化药物选择的有效性。这些创新的 实验推进了 CPH 的精准医学治疗，CPH 是一种高度发病且缺乏治疗的疾病。