Hemerich, D;
Van Setten, J;
Tragante, V;
Asselbergs, FW;
(2018)
Integrative Bioinformatics Approaches for Identification of Drug Targets in Hypertension.
Frontiers in Cardiovascular Medicine
, 5
, Article 25. 10.3389/fcvm.2018.00025.
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Abstract
High blood pressure or hypertension is an established risk factor for a myriad of cardiovascular diseases. Genome-wide association studies have successfully found over nine hundred loci that contribute to blood pressure. However, the mechanisms through which these loci contribute to disease are still relatively undetermined as less than 10% of hypertension-associated variants are located in coding regions. Phenotypic cell-type specificity analyses and expression quantitative trait loci show predominant vascular and cardiac tissue involvement for blood pressure-associated variants. Maps of chromosomal conformation and expression quantitative trait loci (eQTL) in critical tissues identified 2,424 genes interacting with blood pressure-associated loci, of which 517 are druggable. Integrating genome, regulome and transcriptome information in relevant cell-types could help to functionally annotate blood pressure associated loci and identify drug targets.
| Type: | Article |
|---|---|
| Title: | Integrative Bioinformatics Approaches for Identification of Drug Targets in Hypertension |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fcvm.2018.00025 |
| Publisher version: | https://doi.org/10.3389/fcvm.2018.00025 |
| Language: | English |
| Additional information: | Copyright © 2018 Hemerich, van Setten, Tragante and Asselbergs. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | hypertension, blood pressure, epigenetic regulation, GWAS, data integration, functional annotation, drug target identification |
| 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/10092197 |
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