Network module‐based drug repositioning for pulmonary arterial hypertension

Abstract

Pulmonary arterial hypertension (PAH) is a progressive disorder characterized by pulmonary vascular remodeling leading to increased pulmonary vascular resistance and pulmonary arterial pressure. PAH is a highly morbid cardiopulmonary disease adversely affecting lifespan and quality of life. Despite increased awareness and advances of medical therapies in recent decades, long-term prognosis and survival remain poor for patients with PAH. Novel therapies that can target the underlying pathobiology of PAH and reverse pulmonary vascular remodeling are clearly needed. In this study, we develop a network module-based framework to examine potential drug repositioning for PAH.The rationale for this approach is that in order to have therapeutic effects, the targets of potential drugs must be significantly proximate to the disease module of interest in the human protein-protein interactome. Based on 15 existing drugs for treating PAH, our framework integrates drug-drug interactions, drug-drug chemical similarity, drug targets, and PAH disease proteins into the human interactome, and prioritizes candidate drugs for PAH. We identified 53 drugs that could potentially be repurposed for PAH. Many of these candidates have strong literature support. Compared to blackbox-like machine learning models, network module-based drug repositioning can provide mechanistic insights into how repositioned drugs can target the underlying pathobiological mechanisms of PAH.

Association Between Circulating CD4+ T Cell Methylation Signatures of Network-Oriented SOCS3 Gene and Hemodynamics in Patients Suffering Pulmonary Arterial Hypertension

“…Furthermore, due to availability of biological biospecimens from our study population, we were not able to perform experimental validation (qRT-PCR and Western Blot) on CD4 + T cells but only in PBMC fraction. Larger prospective studies are needed to evaluate whether network-oriented DMGs may be used as potential biomarkers to optimize prognosis in PAH [1,3,[50][51][52]. Nonetheless, circulating DNA methylome analyzed via network analysis may yield insight into early disease pathogenesis and suggest noninvasive biomarkers that can be used to optimize patient phenotyping and, possibly, predicted outcome in PAH.…”

Proline and glucose metabolic reprogramming supports vascular endothelial and medial biomass in pulmonary arterial hypertension

“…Constructing the networks. The consolidated human protein-protein interactome were assembled from different resources as described before which contains 16,470 proteins and 233,957 interactions (19,23,24). We mapped the differentially expressed rat genes to human orthologs using the HGNC Comparison of Ortholog Predictions search tool, HCOP (https://www.genenames.org/tools/hcop/) and obtained 2,626 human genes.…”

“…Genes associated with amino acids were from the Gene Ontology (GO) database (http://geneontology.org/). Genes associated with PAH were compiled from different resources (19,23,24) and mapped to the human interactome to form a PAH disease module. Genes associated with pathophenotypes were compiled from Phenopedia and DisGeNET (52,53).…”

Uncovering common pathobiological processes between COVID‐19 and pulmonary arterial hypertension by integrating Omics data

“…We used the comprehensive human protein–protein interactome consolidated in our previous study. 15 This human interactome contains physical, macromolecular interaction data from different human sources, including protein–protein interactions, protein complexes, kinase‐substrate interactions, and signaling pathways. High‐quality protein–protein interactions are identified from several high‐throughput yeast‐two‐hybrid studies, mass spectrometry, as well as the literature.…”