Combined network and mathematical modeling suggests novel inflammation positive feedback circuit and role for IL-1α in experimental trauma/hemorrhage and hepatocyte hypoxia

13 Combined network and mathematical modeling suggests novel inflammation positive feedback circuit and role for IL-1 in experimental trauma/hemorrhage and hepatocyte hypoxia Nabil Azhar, Rami Namas, Bahiyyah Jefferson, Derek Barclay, Ruben Zamora, Yoram Vodovotz University of Pittsburgh, Pittsburgh, PA, USA Objectives: Trauma/hemorrhagic shock (T/HS) is the most common cause of death for young people in the United States, costing more than $400 billion annually. Most deaths from T/HS occur due to the multiple organ dysfunction syndrome. Multiple organ dysfunction syndrome is thought to be due, in part, to dysregulated inflammation. We have used computational modeling to define key networks and mechanisms of post-T/HS acute inflammation. We used a Dynamic Bayesian Network (DBN) algorithm (adapted from Grzegorczyk and Husmeier, Bioinformatics 2010;27:693). Given time-series data, DBNs provide a way of inferring causal relationships based on probabilistic measures. This approximation helps to suggest the overall network structure, including central nodes that exhibit feedback. Methods: C57Bl/6 mice were subjected to T/HS for 0 to 4 hours. Separately, C57Bl/6 hepatocytes were subjected to an in vitro surrogate of T/HS, namely, hypoxia (culture at 1% O2 for 1 to 72 hours). Cytokines/chemokines were assayed in the plasma (in vivo T/HS) as well as supernatants and lysates (in vitro hypoxia) by Luminex (MiraiBio, Alameda, CA), and the data were subjected to DBN analysis. Results: Dynamic Bayesian Network analysis suggested a core network that involves the cytokines IL-10 and IL-1α, as well as the chemokines IP-10 and MIG. Assigning biologically plausible functions to directed edges of the network resulted in a so-called incoherent type I feed forward loop that predicted pulsatile, “gatekeeper” behavior for the cytokine IL-1α—a behavior that was indeed observed in preliminary studies in mice subjected to T/ HS. An initial ordinary differential equation (ODE) model was constructed to analyze this behavior in further detail. Simulated trajectories of cytokines and chemokines in the ODE model corresponded closely with the data. Conclusions: Data-driven (DBN) and mechanistic (ODE) analyses suggest a novel inflammatory circuit with a central role for IL-1α in T/HS and hepatocyte hypoxia. http://dx.doi.org/10.1016/j.jcrc.2012.10.029