Abstract 21339: Deciphering Endocrine Factors Underlying Regulatory-Gene Network Signaling Between Metabolic and Vascular Tissues in Coronary Artery Disease

Abstract

Introduction: Endocrine proteins play central roles at all stages of coronary artery disease (CAD) development from endothelium activation, leukocyte migration to foam cell formation, smooth muscle cell migration and the formation of advanced atherosclerotic plaques. Although some endocrine factors already have been identified, the systemic landscape of endocrine signaling acting between fat, liver, skeletal muscle and the arterial wall in CAD remains largely unknown. Hypothesis: Systemic endocrine signaling underlying cross-tissue metabolic and arterial wall networks is essential for CAD development. Methods: We studied the underlying endocrine signaling between tissues by inferring 89 cross-tissue and 135 tissue-specific regulatory-gene networks (RGNs) from genotype and RNA-seq data in seven tissues including blood, arterial and metabolic tissues isolated from 672 CAD patients in the Stockholm Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study. Within the cross-tissue RGNs, we detected 1,358 transcripts encoding secreted proteins and identified their cross-tissue target transcripts. Next, we validated these endocrine factors and their cross-tissue regulatory interactions using expression data from mice and experimentally in relevant cell models. Results: As judged from a super-network containing all RGNs, a majority of identified endocrine factors in cross-tissue RGNs were found between visceral abdominal fat and liver. However, one RGN active in visceral abdominal fat contained the endocrine factors: ALB, APOH, APOC3, APOA2, AHSG, AMBP, FGA, FGB, FGG, and GC, targeting an arterial wall RGN enriched for blood microparticle genes and for CAD risk genes identified by genome-wide association studies, and was associated with SYNTAX scores of the STARNET patients. Conclusions: Previously unknown endocrine factors acting in cross-tissue RGNs contribute to CAD and may be useful as targets for novel CAD therapies.