A system view and analysis of essential hypertension

Alon Botzer, Ehud Grossman, John Moult, Ron Unger

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Objectives: The goal of this study was to investigate genes associated with essential hypertension from a system perspective, making use of bioinformatic tools to gain insights that are not evident when focusing at a detail-based resolution. Methods: Using various databases (pathways, Genome Wide Association Studies, knockouts etc.), we compiled a set of about 200 genes that play a major role in hypertension and identified the interactions between them. This enabled us to create a protein-protein interaction network graph, from which we identified key elements, based on graph centrality analysis. Enriched gene regulatory elements (transcription factors and microRNAs) were extracted by motif finding techniques and knowledge-based tools. Results: We found that the network is composed of modules associated with functions such as water retention, endothelial vasoconstriction, sympathetic activity and others. We identified the transcription factor SP1 and the two microRNAs miR27 (a and b) and miR548c-3p that seem to play a major role in regulating the network as they exert their control over several modules and are not restricted to specific functions. We also noticed that genes involved in metabolic diseases (e.g. insulin) are central to the network. Conclusion: We view the blood-pressure regulation mechanism as a system-of-systems, composed of several contributing subsystems and pathways rather than a single module. The system is regulated by distributed elements. Understanding this mode of action can lead to a more precise treatment and drug target discovery. Our analysis suggests that insulin plays a primary role in hypertension, highlighting the tight link between essential hypertension and diseases associated with the metabolic syndrome.

Original languageEnglish
Pages (from-to)1094-1103
Number of pages10
JournalJournal of Hypertension
Volume36
Issue number5
DOIs
StatePublished - 1 May 2018

Bibliographical note

Publisher Copyright:
© Copyright 2018 Wolters Kluwer Health, Inc. All rights reserved.

Keywords

  • bioinformatics
  • blood pressure
  • essential hypertension
  • hypertension
  • networks
  • systems biology

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