Abstract 12437: Network-Based Identification of Tissue-Specific Regulators and Drug Repurposing Candidates for Coronary Artery Disease

Abstract

Coronary artery disease (CAD) is the leading cause of mortality worldwide. Recent genomic studies in human populations and mouse models have revealed numerous novel genetic loci that may affect pathways and gene networks in CAD relevant tissues. In this study, we aim to use network-based systems biology approaches to identify regulators and drug repurposing candidates based on CAD gene networks. Through integration of multiomics datasets encompassing genetic association studies, transcriptomic profiles, and tissue-specific gene regulation from human and mouse populations, we previously modeled gene networks in vascular and liver tissues that are affected by CAD genetic loci in both species. Based on the shared CAD gene networks between human and mouse, we predicted candidate key regulatory genes and further examined multiple single-cell RNA sequencing datasets of vascular and liver tissues to pinpoint the specific cell types and molecular pathways in each tissue through which the top predicted regulators function. We further used network-based drug repositioning approaches to predict drugs targeting the CAD networks in each tissue, revealing both currently used medications and potential novel therapeutic agents. The cross-species networks, predicted key regulatory genes, their cellular and tissue context, and the network-based drug repositioning analyses offer tissue and cell-type specific targets and potential existing drugs that can be repurposed for CAD treatment.