1. Publications

A mechanistic framework for cardiometabolic and coronary artery diseases

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, Kiyotake Ishikawa, Carl Whatling, Anamika Jain, Rajeev Kumar Jain, Li-Ming Gan, Chiara Giannarelli, Panos Roussos, Ke Hao, Heribert Schunkert, Tom Michoel, Arno Ruusalepp, Eric E Schadt, Jason C Kovacic, Aldon J Lusis, Johan L M Björkegren.
Nat Cardiovasc Res. 2022-01-12;1(1):85-100.
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.
Consortium data used in this publication
Case and control STARNET data are available at the dbGAP site (dbGaP study accession phs001203.v1.p1). Validation data are provided by the HMDP, GTEx and morbid obesity studies. Liver RNA-seq data generated in response to injecting mice with recombinant endocrine factors are available under GEO entry GSE189001. Source data are provided with this paper.

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The website was developed with a Python Flask backend and a sqlite3 database, with an application programming interface for fetching data. Interactive visualizations were developed in JavaScript using D3 and Plotly.