Repurposing of Approved Cardiovascular Drugs against Ischemic Cerebrovascular Disease by Disease-Disease Associated Network-Assisted Prediction.

Abstract

Stroke is one of the leading causes of death and disability globally, while intravenous thrombolysis with recombinant tissue plasminogen activator remains the only Food and Drug Administration (FDA)-approved therapy for ischemic stroke. The attempts to develop new treatments for acute ischemic stroke meet costly and spectacularly disappointing results, which requires both long time and high costs, whereas repurposing of safe existing drugs to new indications provides a cost-effective and not time-consuming alternative. Vascular protection is a promising strategy for improving stroke outcome, as vascular function is critical to both cardiovascular diseases (CVD) and ischemic cerebrovascular disease (ICD). Vascular function related biological processes and pathways maybe the critical associations between CVD and ICD. In this study, a multi-database, in silico target identification, gene function enrichment, and network pharmacology analysis integration approach was proposed and applied to investigate the FDA-approved CVD drugs repurposing for ICD. A list of 119 candidate drugs can be obtained for further investigation of their potential in ICD treatment. As a pleiotropic drug with multi-target, carvedilol was set an example to investigate its promising potential for ICD therapy. Our results indicated that the mode of action of carvedilol for ICD treatment may tightly associated with vascular function regulation and the mechanism is multi-target and multi-signaling pathway related. The disease-disease association network-assisted prediction needs further investigations. In summary, the proposed methods herein may provide a promising alternative to inferring novel disease indications for known drugs.