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Approaches towards a reversed engineered model of systemic inflammation in humans

P.T. Foteinou1, S.E. Calvano2, S.F. Lowry2, I.P. Androulakis1

1Rutgers University, 2UMDNJ-Robert Wood Johnson Medical School

The systemic inflammatory response syndrome (SIRS) often accompanies critical illnesses and can be an important cause of morbidity and mortality. Despite the growing knowledge about the molecular and cellular mechanisms of SIRS, its complexity has made therapeutic strategies elusive. Successful interventions depend on the stage and trajectory of the disease making systems-based approaches appealing. Significant opportunities emerge in the context of systems biology which aims at the deconvolution of complex phenomena to their constitutive elements and the quantification of the dynamic interactions between these components through the development of appropriate computational models. We opt therefore to explore the possibility of developing a reverse-engineered model of endotoxin-induced human inflammation though the integration of transcriptional profiling and indirect response models to assess the effects of propagating the initiating signaling across a network of interacting components. The work to be discussed here addresses two questions:

1. Is it possible to develop semi-mechanistic based host response models that integrate signaling and pharmacokinetic models for the modulation of the inflammatory response?  
   During the onset of an inflammatory response signaling pathways are activated for “translating” extracellular signals into intracellular responses. Such a signal transduction cascade converges to the activation of effector proteins (transcription factors) that regulate the expression of critical genes. Nuclear factor (NF)-kB is a central transcription factor that plays a major role in driving the inflammatory response. An inadequate control of its transcriptional activity is associated with the progression of an unresolved inflammatory response making it a desired therapeutic target. Anti-inflammatory drugs such as corticosteroids play a critical role in modulating the progression of inflammation interfering transcriptionally with the activity of NF-kB. The dynamic integration of regulatory signaling information with the opposing effect of corticosteroids, as the putative controllers of inflammation, would allow us to perform various “what-if” scenarios rationalizing the success/failure of particular interventions. To meet this challenge, an integrated inflammatory model is proposed that couples the anti-inflammatory effect of corticosteroids with the activation of pro-inflammatory signaling pathways is proposed.
    
2. Is it possible to model the multi-scale nature of the interplay CNS and inflammation?  
   Inflammation as a protective mechanism in response to various stimuli involves the complex interplay of inflammatory mediators that span multiple scales. Accordingly, the central nervous system (CNS) plays a critical role in system’s homeostasis composed of sensory organs that detect the state of the body and organs releasing stress hormones that play an integral role in immunomodulation. The evolving concept of autonomic dysfunction during the progression of inflammation demonstrates the existence of a bidirectional relationship between CNS and inflammation. Researchers attempt to measure physiologic response variables, e.g. heart rate variability indices, in order to assess autonomic imbalance. Driven by the premise to develop a multi-scale model of systemic inflammation we propose to integrate peripheral immune responses with neural-based mechanisms.