Background: The systemic inflammatory response syndrome often accompanies critical illness and can be an important cause of morbidity and mortality (Nystrom 1998). In any physiological system, signaling pathways are characterized by the presence of adequate controlling steps (Chung and Adcock 2005). In this study, we develop an indirect response model of a human endotoxin-induced inflammation that integrates the opposing effect of two signaling pathways, one associated with the activation of NF-kB that drives downstream transcriptional activation of inflammatory mediators and one related to the signaling of exogenous corticosteroids as the putative controllers of inflammation (Hoffmann, Levchenko et al. 2002; Barken, Wang et al. 2005; Covert, Leung et al. 2005; Rhen and Cidlowski 2005).

Materials: The experimental data analyzed in this study were generated as part of the Inflammation and Host Response to Injury Large Scale Collaborative Project funded by the USPHS, U54 GM62119 (Calvano, Xiao et al. 2005; Storey, Xiao et al. 2005). Human subjects were injected intravenously with endotoxin (CC-RE, lot 2) at a dose of 2-ng/kg body weight or 0.9% sodium chloride. The transcript abundance of leukocytes was measured by microarray before endotoxin administration (0hr) and 2, 4, 6, 9 and 24 hrs after endotoxin administration.

Methods: Based on our prior work, we developed an indirect response model of endotoxin-induced inflammation that integrates the extracellular signal (endotoxin, LPS) with the activation of the essential transcriptional responses. One of the key aspects of this model is the systematic identification of an elementary set of temporal responses that describe the trajectory of systemic inflammation in human blood leukocytes when exposed to endotoxin stimulus (Foteinou, Calvano et al. 2007). Therefore such responses define the state space of the probed system and we effectively integrated these responses into a mathematical model using the basic principles of an Indirect Response Model (IDR) (Krzyzanski and Jusko 1997). However, in this study we propose to improve the structure of the inflammatory model taking regulation into consideration. We suggest the association of the activity of NF-kappaB with the up-regulation of inflammatory mediators. We aim to simulate the dynamic interactions of a minimal model of NF-kappaB that consists of a basis set of signaling molecules that affect maximally the dynamic behavior of NF-kappaB. In addition to this, we prompt to model the pharmacodynamic effect of exogenous corticosteroids against inflammation based on the “Fifth Generation Model for Corticosteroid Pharmacodynamics” (Ramakrishnan, DuBois et al. 2002). The resulting model is described by a set of ordinary differential equations that contain the NF-kappaB dependent propagation of LPS signaling coupled with the opposing signaling effect of corticosteroids. We demonstrate the potential of the proposed in silico model evaluating a series of biological relevant scenarios. Such a model is coupled with the corticosteroid intervention envelope and results show the beneficial effect of an early intervention strategy. Regardless of the implications of high LPS, pre-exposuring the system into hypercortisolemia “reprograms” the dynamics of the system towards a balanced immune response. The development of such a mechanistic modeling approach allows us to gain insight about how the system responds to a multitude of external signals through the dynamic interaction of signaling modules. The proposed model opens the research avenues to evaluate the effectiveness of corticosteroids under various treatment schedules establishing an in silico zone of therapeutic opportunity thereby facilitating the clinical making decision

Results: The potential of the proposed in silico model evaluating a series of biologically relevant scenarios is demonstrated. Such a model is coupled with the corticosteroid intervention envelope and the results show the beneficial effect of an early intervention strategy. Regardless of the implications of high LPS, pre-exposing the system to hypercortisolemia “reprograms” the dynamics of the system towards a more balanced immune response.

Conclusions: We have developed a mechanistic modeling approach that allows us to gain insight about how the system responds to multiple external signals through the dynamic interaction of signaling modules. The proposed model opens research avenues to evaluate the effectiveness of corticosteroids under various treatment schedules establishing an in silico zone of therapeutic opportunity which may facilitate clinical decision making.

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