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Uncovering the interdependence between hypertension and the inflammatory response for the patient affected by Covid 19 through mathematical modeling and computer-based analysis

10 pagesPublished: May 1, 2023

Abstract

We explore here the systems-based regulatory mechanisms that determine human blood pressure patterns. This in the context of the reported negative association between hypertension and COVID-19 disease. We are particularly interested in the key role that plays angiotensin converting enzyme 2 (ACE2), one of the first identified receptors that enable the entry of the SARS-CoV-2 virus into a cell. Taking into account the two main systems involved in the regulation of blood pressure, that is, the Renin-Angiotensin system and the Kallikrein-Kinin system, we follow a Bottom-Up systems biology modeling approach in order to built the discrete Boolean model of the gene regulatory network that underlies both the typical hypertensive phenotype and the hypotensive/normotensive phenotype. These phenotypes correspond to the dynamic attractors of the regulatory network modeled on the basis of publicly available experimental information. Our model recovers the observed phenotypes and shows the key role played by the inflammatory response in the emergence of hypertension.

Keyphrases: covid 19, discrete boolean networks, gene regulatory networks, human blood pressure patterns, hypertension, inflammatory response, methematical modeling, systems biology

In: Hisham Al-Mubaid, Tamer Aldwairi and Oliver Eulenstein (editors). Proceedings of International Conference on Bioinformatics and Computational Biology (BICOB-2023), vol 92, pages 25-34.

BibTeX entry
@inproceedings{BICOB-2023:Uncovering_interdependence_between_hypertension,
  author    = {Rosario Pacheco-Marin and Carolina Caballero-Cordero and Jorge Arturo Arciniega-González and Elena R. Álvarez-Buylla and Juan Carlos Martínez-García},
  title     = {Uncovering the interdependence between hypertension and the inflammatory response for the patient affected by Covid 19 through mathematical modeling and computer-based analysis},
  booktitle = {Proceedings of International Conference on Bioinformatics and Computational Biology (BICOB-2023)},
  editor    = {Hisham Al-Mubaid and Tamer Aldwairi and Oliver Eulenstein},
  series    = {EPiC Series in Computing},
  volume    = {92},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/ttVG},
  doi       = {10.29007/b5v4},
  pages     = {25-34},
  year      = {2023}}
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