A mechanistic framework for cardiometabolic and coronary artery diseases

心脏代谢和冠状动脉疾病的机制框架

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作者:Simon Koplev, Marcus Seldin, Katyayani Sukhavasi, Raili Ermel, Shichao Pang, Lingyao Zeng, Sean Bankier, Antonio Di Narzo, Haoxiang Cheng, Vamsidhar Meda, Angela Ma, Husain Talukdar, Ariella Cohain, Letizia Amadori, Carmen Argmann, Sander M Houten, Oscar Franzén, Giuseppe Mocci, Omar A Meelu, Kiyota

Abstract

Coronary atherosclerosis results from the delicate interplay of genetic and exogenous risk factors, principally taking place in metabolic organs and the arterial wall. Here we show that 224 gene-regulatory coexpression networks (GRNs) identified by integrating genetic and clinical data from patients with (n = 600) and without (n = 250) coronary artery disease (CAD) with RNA-seq data from seven disease-relevant tissues in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study largely capture this delicate interplay, explaining >54% of CAD heritability. Within 89 cross-tissue GRNs associated with clinical severity of CAD, 374 endocrine factors facilitated inter-organ interactions, primarily along an axis from adipose tissue to the liver (n = 152). This axis was independently replicated in genetically diverse mouse strains and by injection of recombinant forms of adipose endocrine factors (EPDR1, FCN2, FSTL3 and LBP) that markedly altered blood lipid and glucose levels in mice. Altogether, the STARNET database and the associated GRN browser (http://starnet.mssm.edu) provide a multiorgan framework for exploration of the molecular interplay between cardiometabolic disorders and CAD.

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