Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, United States; The Information School at the University of Sheffield, Sheffield, United Kingdom
Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, United States; Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los Angeles, Los Angeles, United States
Rio Barrere-Cain
Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, United States
Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, United States
Simon Koplev
Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, United States
Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, United States
Johan Björkegren
Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, United States; Department of Medicine, (Huddinge), Karolinska Institutet, Huddinge, Sweden
Department of Medicine, Division of Cardiology, University of California, Los Angeles, Los Angeles, United States; Departments of Human Genetics & Microbiology, Immunology, and Molecular Genetics, UCLA, Los Angeles, United States; Cardiovascular Research Laboratory, David Geffen School of Medicine, UCLA, Los Angeles, United States
Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, United States; Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los Angeles, Los Angeles, United States
Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, United States; Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los Angeles, Los Angeles, United States; Interdepartmental Program of Bioinformatics, University of California, Los Angeles, Los Angeles, United States; Department of Molecular and Medical Pharmacology, University of California, Los Angeles, Los Angeles, United States
Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.
