F. Liu (1), L.B.S. Aulin (1,2), J.G.C. van Hasselt (1)
(1) Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands, (2) Department of Biology, Chemistry, and Pharmacy, Freie Universität Berlin, Berlin, Germany
Objectives:
Sepsis is a life-threatening condition driven by the dysregulated host immune response to an infection, in which the activation of Toll-like receptor 4 (TLR4) signaling pathways by lipopolysaccharide (LPS) is a critical upstream event in the pathogenesis. Currently, the complex and interacting mechanisms underlying sepsis are not well-characterized and most clinical trials investigating drug treatment against sepsis have failed. Molecular level qualitative data on biological components along with their interactions involved in sepsis have been described in literature. Boolean network model can use to integrate such literature data and infer systems behavior. Here, we describe the use of a Boolean network modeling strategy to obtain deeper mechanistic insight into sepsis pathogenesis in order to evaluate promising novel therapeutic targets, with a focus on TLR4-mediated pathways.
Methods:
We constructed a Boolean network based on collection of previously published regulatory relationships among key immune components associated with sepsis pathogenesis after TLR4 activation. Different activation levels of each immune cell in the network were explored to investigate the impact of immune components on disease severity. Perturbation analyses were conducted to identify therapeutic targets either decreasing organ dysfunction or enhancing host mediated antibacterial activity.
Results:
The constructed network consisted of 42 nodes, e.g. immune components and procedures, and 183 interactions representing host response to bacterial infection stimulated via the LPS/TLR4 pathway.
While varying immune cell activation levels, we identified four cell nodes whose activation magnitude had considerable effect on the selected endpoints: 1) The activation level of endothelial cells was positively correlated with Angiopoietin 2 activity which is related to vessel leakage; 2) Both the increasing monocyte and platelet activation correlates with the risk of thrombosis; and 3) Higher levels B-cell activation lead to lower levels of phagocytosis, which is a crucial mechanism for bacterial clearance. The activation of these immune cells might have impact on the disease severity in sepsis.
Our perturbation analysis revealed: 1) For mono-target drug treatments, blockade of TNF-a or over-expression of sTNF-R, tissue factor (TF), or pro-inflammatory cytokines (IL-1B, IFN-gamma, or IL-12) lead to a reduction of organ dysfunction endpoints, while over-expression of complement factor C3b and C5b could increase the bacterial clearance related endpoint; 2) For multi-target treatment strategies, more than 10 combinations were shown to decrease organ dysfunction, e.g. blocking IFN-gamma and IL-10 together reduced the risk of vessel leakage, while blocking TLR4 and IL-1B reduced the risk of Thrombosis; 3) When combining with antibiotic therapy, 10 targets were identified to be beneficial to decreasing organ dysfunction in which the most significant one was blocking the pro-inflammatory cytokine IL-1B.
Conclusions:
We developed a qualitative Boolean network model describing TLR4-mediated host immune response in early phase of sepsis. The developed model constitutes a tool which can be utilized to deepen the understanding of systemic inflammatory diseases, analyze the influences of immune cells diversity among patient groups, and identify potential therapeutic targets for sepsis.
Reference: PAGE 30 (2022) Abstr 10083 [www.page-meeting.org/?abstract=10083]
Poster: Drug/Disease Modelling - Other Topics