Moritz von Scheidt1,2, Yuqi Zhao, Thomas Q de Aguiar Vallim3,4, Nam Che3,5,6, Michael Wierer7, Marcus M Seldin8, Oscar Franzén9, Zeyneb Kurt10, Shichao Pang1, Dario Bongiovanni2,11, Masayuki Yamamoto12, Peter A Edwards3,4, Arno Ruusalepp13,14, Jason C Kovacic15, Matthias Mann7, Johan L M Björkegren9,14,15, Aldons J Lusis3,5,6, Xia Yang16, Heribert Schunkert1,2. 1. Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Munich, Germany (M.v.S., S.P., H.S.). 2. Deutsches Zentrum für Herz- und Kreislauferkrankungen, Partner Site Munich Heart Alliance, Germany (M.v.S., D.B., H.S.). 3. Departments of Medicine (T.Q.d.A.V., N.C., P.A.E., A.J.L.), David Geffen School of Medicine, University of California, Los Angeles. 4. Biological Chemistry (T.Q.d.A.V., P.A.E.), David Geffen School of Medicine, University of California, Los Angeles. 5. Microbiology, Immunology and Molecular Genetics (N.C., A.J.L.), David Geffen School of Medicine, University of California, Los Angeles. 6. Human Genetics (N.C., A.J.L.), David Geffen School of Medicine, University of California, Los Angeles. 7. Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Martinsried, Germany (M.W., M.M.). 8. Department of Biological Chemistry and Center for Epigenetics and Metabolism, University of California, Irvine (M.M.S.). 9. Integrated Cardio Metabolic Centre, Karolinska Institutet, Novum, Huddinge, Sweden (O.F., J.L.M.B.). 10. Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, United Kingdom (Z.K.). 11. Department of Internal Medicine, School of Medicine, University Hospital Rechts der Isar, Technical University of Munich, Germany (D.B.). 12. Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan (M.Y.). 13. Department of Cardiac Surgery, Tartu University Hospital, Estonia (A.R.). 14. Clinical Gene Networks AB, Stockholm, Sweden (A.R., J.L.M.B.). 15. Cardiovascular Research Center, Icahn School of Medicine at Mount Sinai, New York (J.C.K., J.L.M.B.). 16. Department of Integrative Biology and Physiology, Institute for Quantitative and Computational Biosciences (Y.Z., X.Y.), David Geffen School of Medicine, University of California, Los Angeles.
Abstract
BACKGROUND: Coronary artery disease (CAD) is a multifactorial condition with both genetic and exogenous causes. The contribution of tissue-specific functional networks to the development of atherosclerosis remains largely unclear. The aim of this study was to identify and characterize central regulators and networks leading to atherosclerosis. METHODS: Based on several hundred genes known to affect atherosclerosis risk in mouse (as demonstrated in knockout models) and human (as shown by genome-wide association studies), liver gene regulatory networks were modeled. The hierarchical order and regulatory directions of genes within the network were based on Bayesian prediction models, as well as experimental studies including chromatin immunoprecipitation DNA-sequencing, chromatin immunoprecipitation mass spectrometry, overexpression, small interfering RNA knockdown in mouse and human liver cells, and knockout mouse experiments. Bioinformatics and correlation analyses were used to clarify associations between central genes and CAD phenotypes in both human and mouse. RESULTS: The transcription factor MAFF (MAF basic leucine zipper transcription factor F) interacted as a key driver of a liver network with 3 human genes at CAD genome-wide association studies loci and 11 atherosclerotic murine genes. Most importantly, expression levels of the low-density lipoprotein receptor (LDLR) gene correlated with MAFF in 600 CAD patients undergoing bypass surgery (STARNET [Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task]) and a hybrid mouse diversity panel involving 105 different inbred mouse strains. Molecular mechanisms of MAFF were tested in noninflammatory conditions and showed positive correlation between MAFF and LDLR in vitro and in vivo. Interestingly, after lipopolysaccharide stimulation (inflammatory conditions), an inverse correlation between MAFF and LDLR in vitro and in vivo was observed. Chromatin immunoprecipitation mass spectrometry revealed that the human CAD genome-wide association studies candidate BACH1 (BTB domain and CNC homolog 1) assists MAFF in the presence of lipopolysaccharide stimulation with respective heterodimers binding at the MAF recognition element of the LDLR promoter to transcriptionally downregulate LDLR expression. CONCLUSIONS: The transcription factor MAFF was identified as a novel central regulator of an atherosclerosis/CAD-relevant liver network. MAFF triggered context-specific expression of LDLR and other genes known to affect CAD risk. Our results suggest that MAFF is a missing link between inflammation, lipid and lipoprotein metabolism, and a possible treatment target.
BACKGROUND: Coronary artery disease (CAD) is a multifactorial condition with both genetic and exogenous causes. The contribution of tissue-specific functional networks to the development of atherosclerosis remains largely unclear. The aim of this study was to identify and characterize central regulators and networks leading to atherosclerosis. METHODS: Based on several hundred genes known to affect atherosclerosis risk in mouse (as demonstrated in knockout models) and human (as shown by genome-wide association studies), liver gene regulatory networks were modeled. The hierarchical order and regulatory directions of genes within the network were based on Bayesian prediction models, as well as experimental studies including chromatin immunoprecipitation DNA-sequencing, chromatin immunoprecipitation mass spectrometry, overexpression, small interfering RNA knockdown in mouse and human liver cells, and knockout mouse experiments. Bioinformatics and correlation analyses were used to clarify associations between central genes and CAD phenotypes in both human and mouse. RESULTS: The transcription factor MAFF (MAF basic leucine zipper transcription factor F) interacted as a key driver of a liver network with 3 human genes at CAD genome-wide association studies loci and 11 atherosclerotic murine genes. Most importantly, expression levels of the low-density lipoprotein receptor (LDLR) gene correlated with MAFF in 600 CAD patients undergoing bypass surgery (STARNET [Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task]) and a hybrid mouse diversity panel involving 105 different inbred mouse strains. Molecular mechanisms of MAFF were tested in noninflammatory conditions and showed positive correlation between MAFF and LDLR in vitro and in vivo. Interestingly, after lipopolysaccharide stimulation (inflammatory conditions), an inverse correlation between MAFF and LDLR in vitro and in vivo was observed. Chromatin immunoprecipitation mass spectrometry revealed that the human CAD genome-wide association studies candidate BACH1 (BTB domain and CNC homolog 1) assists MAFF in the presence of lipopolysaccharide stimulation with respective heterodimers binding at the MAF recognition element of the LDLR promoter to transcriptionally downregulate LDLR expression. CONCLUSIONS: The transcription factor MAFF was identified as a novel central regulator of an atherosclerosis/CAD-relevant liver network. MAFF triggered context-specific expression of LDLR and other genes known to affect CAD risk. Our results suggest that MAFF is a missing link between inflammation, lipid and lipoprotein metabolism, and a possible treatment target.
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