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 mechani...