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Sci Rep. 2018 Feb 21;8(1):3434. doi: 10.1038/s41598-018-20721-6.

Network analysis of coronary artery disease risk genes elucidates disease mechanisms and druggable targets.

Author information

1
Genedata AG, Basel, Switzerland. harri.lempiainen@genedata.com.
2
Institute for Cardiogenetics, Lübeck, Germany.
3
Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.
4
Clinical Gene Networks AB, Stockholm, Sweden.
5
Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands.
6
Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany.
7
DZHK (German Centre for Cardiovascular Research), Munich Heart Alliance, Munich, Germany.
8
Department of Cardiovascular Sciences, University of Leicester and NIHR Leicester Biomedical Research Centre, Leicester, United Kingdom.
9
Division of Cardiovascular Medicine, Radcliffe Department of Medicine, John Radcliffe Hospital, Oxford, United Kingdom.
10
Genedata AG, Basel, Switzerland.
11
Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA.
12
Laboratory of Experimental Cardiology, Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands.
13
Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden.
14
Laboratory of Clinical Chemistry and Hematology, Division Laboratories and Pharmacy, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands.
15
Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom.
16
Clinical Gene Networks AB, Stockholm, Sweden. johan.bjorkegren@mssm.edu.
17
Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA. johan.bjorkegren@mssm.edu.
18
Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden. johan.bjorkegren@mssm.edu.

Abstract

Genome-wide association studies (GWAS) have identified over two hundred chromosomal loci that modulate risk of coronary artery disease (CAD). The genes affected by variants at these loci are largely unknown and an untapped resource to improve our understanding of CAD pathophysiology and identify potential therapeutic targets. Here, we prioritized 68 genes as the most likely causal genes at genome-wide significant loci identified by GWAS of CAD and examined their regulatory roles in 286 metabolic and vascular tissue gene-protein sub-networks ("modules"). The modules and genes within were scored for CAD druggability potential. The scoring enriched for targets of cardiometabolic drugs currently in clinical use and in-depth analysis of the top-scoring modules validated established and revealed novel target tissues, biological processes, and druggable targets. This study provides an unprecedented resource of tissue-defined gene-protein interactions directly affected by genetic variance in CAD risk loci.

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