Lempiainen, H;
Braenne, I;
Michoel, T;
Tragante, V;
Vilne, B;
Webb, TR;
Kyriakou, T;
... Bjorkegren, JLM; + view all
(2018)
Network analysis of coronary artery disease risk genes elucidates disease mechanisms and druggable targets.
Scientific Reports
, 8
, Article 3434. 10.1038/s41598-018-20721-6.
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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.
| Type: | Article |
|---|---|
| Title: | Network analysis of coronary artery disease risk genes elucidates disease mechanisms and druggable targets |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/s41598-018-20721-6 |
| Publisher version: | http://doi.org/10.1038/s41598-018-20721-6 |
| Language: | English |
| Additional information: | Copyright © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Te images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Cardiovascular genetics, Gene regulatory networks, Genome-wide association studies |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10045356 |
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