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A systems pharmacology model for inflammatory bowel disease
MOTIVATION: The literature on complex diseases is abundant but not always quantitative. This is particularly so for Inflammatory Bowel Disease (IBD), where many molecular pathways are qualitatively well described but this information cannot be used in traditional quantitative mathematical models emp...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5841748/ https://www.ncbi.nlm.nih.gov/pubmed/29513758 http://dx.doi.org/10.1371/journal.pone.0192949 |
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author | Balbas-Martinez, Violeta Ruiz-Cerdá, Leire Irurzun-Arana, Itziar González-García, Ignacio Vermeulen, An Gómez-Mantilla, José David Trocóniz, Iñaki F. |
author_facet | Balbas-Martinez, Violeta Ruiz-Cerdá, Leire Irurzun-Arana, Itziar González-García, Ignacio Vermeulen, An Gómez-Mantilla, José David Trocóniz, Iñaki F. |
author_sort | Balbas-Martinez, Violeta |
collection | PubMed |
description | MOTIVATION: The literature on complex diseases is abundant but not always quantitative. This is particularly so for Inflammatory Bowel Disease (IBD), where many molecular pathways are qualitatively well described but this information cannot be used in traditional quantitative mathematical models employed in drug development. We propose the elaboration and validation of a logic network for IBD able to capture the information available in the literature that will facilitate the identification/validation of therapeutic targets. RESULTS: In this article, we propose a logic model for Inflammatory Bowel Disease (IBD) which consists of 43 nodes and 298 qualitative interactions. The model presented is able to describe the pathogenic mechanisms of the disorder and qualitatively describes the characteristic chronic inflammation. A perturbation analysis performed on the IBD network indicates that the model is robust. Also, as described in clinical trials, a simulation of anti-TNFα, anti-IL2 and Granulocyte and Monocyte Apheresis showed a decrease in the Metalloproteinases node (MMPs), which means a decrease in tissue damage. In contrast, as clinical trials have demonstrated, a simulation of anti-IL17 and anti-IFNγ or IL10 overexpression therapy did not show any major change in MMPs expression, as corresponds to a failed therapy. The model proved to be a promising in silico tool for the evaluation of potential therapeutic targets, the identification of new IBD biomarkers, the integration of IBD polymorphisms to anticipate responders and non-responders and can be reduced and transformed in quantitative model/s. |
format | Online Article Text |
id | pubmed-5841748 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-58417482018-03-23 A systems pharmacology model for inflammatory bowel disease Balbas-Martinez, Violeta Ruiz-Cerdá, Leire Irurzun-Arana, Itziar González-García, Ignacio Vermeulen, An Gómez-Mantilla, José David Trocóniz, Iñaki F. PLoS One Research Article MOTIVATION: The literature on complex diseases is abundant but not always quantitative. This is particularly so for Inflammatory Bowel Disease (IBD), where many molecular pathways are qualitatively well described but this information cannot be used in traditional quantitative mathematical models employed in drug development. We propose the elaboration and validation of a logic network for IBD able to capture the information available in the literature that will facilitate the identification/validation of therapeutic targets. RESULTS: In this article, we propose a logic model for Inflammatory Bowel Disease (IBD) which consists of 43 nodes and 298 qualitative interactions. The model presented is able to describe the pathogenic mechanisms of the disorder and qualitatively describes the characteristic chronic inflammation. A perturbation analysis performed on the IBD network indicates that the model is robust. Also, as described in clinical trials, a simulation of anti-TNFα, anti-IL2 and Granulocyte and Monocyte Apheresis showed a decrease in the Metalloproteinases node (MMPs), which means a decrease in tissue damage. In contrast, as clinical trials have demonstrated, a simulation of anti-IL17 and anti-IFNγ or IL10 overexpression therapy did not show any major change in MMPs expression, as corresponds to a failed therapy. The model proved to be a promising in silico tool for the evaluation of potential therapeutic targets, the identification of new IBD biomarkers, the integration of IBD polymorphisms to anticipate responders and non-responders and can be reduced and transformed in quantitative model/s. Public Library of Science 2018-03-07 /pmc/articles/PMC5841748/ /pubmed/29513758 http://dx.doi.org/10.1371/journal.pone.0192949 Text en © 2018 Balbas-Martinez et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Balbas-Martinez, Violeta Ruiz-Cerdá, Leire Irurzun-Arana, Itziar González-García, Ignacio Vermeulen, An Gómez-Mantilla, José David Trocóniz, Iñaki F. A systems pharmacology model for inflammatory bowel disease |
title | A systems pharmacology model for inflammatory bowel disease |
title_full | A systems pharmacology model for inflammatory bowel disease |
title_fullStr | A systems pharmacology model for inflammatory bowel disease |
title_full_unstemmed | A systems pharmacology model for inflammatory bowel disease |
title_short | A systems pharmacology model for inflammatory bowel disease |
title_sort | systems pharmacology model for inflammatory bowel disease |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5841748/ https://www.ncbi.nlm.nih.gov/pubmed/29513758 http://dx.doi.org/10.1371/journal.pone.0192949 |
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