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