BBB seminar: Johan Björkegren
An integrated systems network approach reveals major adipose-to-liver endocrine signalling in cardiometabolic and coronary artery disease
Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA, and Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
Coronary atherosclerosis, a late-onset common disease, derives from the interplay of genetic and exogenous factors jointly disturbing the functions of various cell types in metabolic organs and the arterial wall. To capture this delicate molecular interplay that ultimately results in cardiometabolic disorders (CMDs), we have integrated genetic and clinical data from patients with (n=600) and without (n=250) coronary artery disease (CAD) with high-quality RNA sequence data obtained from seven disease-relevant tissues in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study. By applying gene co-expression analysis and machine-learning based modeling, we identified 135 tissue-specific and 89 cross-tissue gene regulatory networks (GRNs) that were independently replicated. In integrative analysis with data from genome-wide association studies of CAD, the genetic regulation of these GRNs was shown to jointly explain >54% of CAD heritability. Responsible for organ-to-organ communication, the 89 cross-tissue GRNs to a greater extent captured CAD heritability and variation associated with clinical severity of coronary atherosclerosis. Within these cross-tissue GRNs, we identified 374 endocrine factors as candidates for facilitating their inter-organ gene-gene interactions, acting primarily along an axis from subcutaneous and abdominal fat to the liver (n=152). Forty-two factors in this axis were independently reidentified in RNAseq data from genetically diverse mouse strains. Moreover, injection of recombinant forms of adipose endocrine factors – EPDR1, FCN2, FSTL3, and LBP – central to the cross-tissue GRN hierarchy, markedly altered hepatic control of blood lipids and glucose in mice. Taken together, GRNs identified from the STARNET represent a multi-organ framework for mechanistic exploration of disease etiologies across tissues, providing a rich account of the molecular interplay between CMDs and CAD.
Chairperson: Tom Michoel, CBU, Department of Informatics