title: Global sensitivity analysis of a mathematical model of acute inflammation identifies nonlinear dependence of cumulative tissue damage on host interleukin-6 responses.
abstract: The precise inflammatory role of the cytokine interleukin (IL)-6 and its utility as a biomarker or therapeutic target have been the source of much debate, presumably due to the complex pro- and anti-inflammatory effects of this cytokine. We previously developed a nonlinear ordinary differential equation (ODE) model to explain the dynamics of endotoxin (lipopolysaccharide; LPS)-induced acute inflammation and associated whole-animal damage/dysfunction (a proxy for the health of the organism), along with the inflammatory mediators tumor necrosis factor (TNF)-α, IL-6, IL-10, and nitric oxide (NO). The model was partially calibrated using data from endotoxemic C57Bl/6 mice. Herein, we investigated the sensitivity of the area under the damage curve (AUCD) to the 51 rate parameters of the ODE model for different levels of simulated LPS challenges using a global sensitivity approach called Random Sampling High Dimensional Model Representation (RS-HDMR). We explored sufficient parametric Monte Carlo samples to generate the variance-based Sobol' global sensitivity indices, and found that inflammatory damage was highly sensitive to the parameters affecting the activity of IL-6 during the different stages of acute inflammation. The AUCIL6 showed a bimodal distribution, with the lower peak representing healthy response and the higher peak representing sustained inflammation. Damage was minimal at low AUCIL6, giving rise to a healthy response. In contrast, intermediate levels of AUCIL6 resulted in high damage, and this was due to the insufficiency of damage recovery driven by anti-inflammatory responses from IL-10 and the activation of positive feedback sustained by IL-6. At high AUCIL6, damage recovery was interestingly restored in some population of simulated animals due to the NO-mediated anti-inflammatory responses. These observations suggest that the host's health status during acute inflammation depends in a nonlinear fashion on the magnitude of the inflammatory stimulus, on the host's propensity to produce IL-6, and on NO-mediated downstream responses.
authors.affiliation: Department of Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA. Electronic address: shm82@pitt.edu.
authors.forename: Shibin
authors.initials: S
authors.lastname: Mathew
authors.affiliation: Immunetrics, Inc., Pittsburgh, PA 15203, USA.
authors.forename: John
authors.initials: J
authors.lastname: Bartels
authors.affiliation: Department of Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15219, USA; McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.
authors.forename: Ipsita
authors.initials: I
authors.lastname: Banerjee
authors.affiliation: Immunetrics, Inc., Pittsburgh, PA 15203, USA; Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA; Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA. Electronic address: vodovotzy@upmc.edu.
authors.forename: Yoram
authors.initials: Y
authors.lastname: Vodovotz
mesh_terms: D000208:Acute Disease; D006801:Humans; D015850:Interleukin-6 / Q000096:biosynthesis*; D015233:Models, Statistical; D008962:Models, Theoretical; D009010:Monte Carlo Method; D017711:Nonlinear Dynamics
chemical_list: D015850:Interleukin-6
keywords: Cytokines; Endotoxin; Inflammation dynamics; Meta-modeling; Nitric oxide