A systems pharmacology model for inflammatory bowel disease

PLoS One. 2018 Mar 7;13(3):e0192949. doi: 10.1371/journal.pone.0192949. eCollection 2018.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Computer Simulation
  • Humans
  • Inflammatory Bowel Diseases / drug therapy
  • Inflammatory Bowel Diseases / metabolism*
  • Interferon-gamma / antagonists & inhibitors
  • Interferon-gamma / metabolism
  • Interleukin-17 / antagonists & inhibitors
  • Interleukin-17 / metabolism
  • Matrix Metalloproteinases / metabolism*
  • Models, Biological*
  • Molecular Targeted Therapy / methods
  • Tumor Necrosis Factor-alpha / antagonists & inhibitors
  • Tumor Necrosis Factor-alpha / metabolism

Substances

  • Interleukin-17
  • Tumor Necrosis Factor-alpha
  • Interferon-gamma
  • Matrix Metalloproteinases

Grant support

Development of the computational model was supported by a fellowship grant from the Navarra Government to Violeta Balbás-Martínez of 61.965 Euros (http://www.navarra.es/home_es/Actualidad/BON/Boletines/2017/18/Anuncio-5/) and Janssen Research and Development. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Janssen Research and Development provided support in the form of salaries for author AV, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific role of this author is articulated in the ‘author contributions’ section.