Journal
CELL SYSTEMS
Volume 2, Issue 3, Pages 196-208Publisher
CELL PRESS
DOI: 10.1016/j.cels.2016.02.002
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Funding
- Swedish Heart-Lung Foundation
- Swedish Research Council
- King Gustaf V and Queen Victoria's Foundation of Freemasons
- Astra-Zeneca Translational Science Centre-Karolinska Institutet
- University of Tartu
- Estonian Research Council [8853]
- Biotechnology and Biological Sciences Research Council (BBSRC) [BB/J004235/1, BB/M020053/1]
- American Heart Association [14SFRN20490315, 14SFRN20840000]
- NIH (National Heart, Lung, and Blood Institute [NHLBI] [R01HL71207, K23HL111339, K99HL121172]
- EU [HEALTH-F2-2013-601456]
- BBSRC [BB/M020053/1, BBS/E/D/20211552] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [BBS/E/D/20211552, BB/M020053/1] Funding Source: researchfish
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Inferring molecular networks can reveal how genetic perturbations interact with environmental factors to cause common complex diseases. We analyzed genetic and gene expression data from seven tissues relevant to coronary artery disease (CAD) and identified regulatory gene networks (RGNs) and their key drivers. By integrating data from genome-wide association studies, we identified 30 CAD-causal RGNs interconnected in vascular and metabolic tissues, and we validated them with corresponding data from the Hybrid Mouse Diversity Panel. As proof of concept, by targeting the key drivers AIP, DRAP1, POLR2I, and PQBP1 in a cross-species-validated, arterial-wall RGN involving RNA-processing genes, we re-identified this RGN in THP-1 foam cells and independent data from CAD macrophages and carotid lesions. This characterization of the molecular landscape in CAD will help better define the regulation of CAD candidate genes identified by genomewide association studies and is a first step toward achieving the goals of precision medicine.
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