(344b) Understanding Dysregulated Neutrophil Trafficking in Severe Sepsis

Song, S. O. - Presenter, University of Pittsburgh
Clermont, G. - Presenter, University of Pittsburgh School of Medicine
Parker, R. S. - Presenter, University of Pittsburgh
Hogg, J. S. - Presenter, University of Pittsburgh School of Medicine

Adequate recruitment of neutrophils to sites of infection is one of the early and important events of the innate immune response. Mounting evidence shows that severe sepsis is characterized by impaired neutrophil migration to the primary infectious inflammatory site and deleterious accumulation of neutrophils in distant organs, resulting in organ dysfunction and death. There are competing theories as to the mechanisms underlying this maladaptive immune response.

We propose that dysregulated neutrophil trafficking in severe sepsis might be effectively explained by a mathematical model that incorporates the dynamic interactions of compartmentalized inflammatory responses. We developed a three-compartmental (peritoneum, blood, and lung) system of ODE model including major effectors of the acute inflammatory response. In order to capture impaired recruitment of neutrophil in severe sepsis, several lines of evidence about the mechanisms influencing neutrophil migration in sepsis were reviewed and incorporated in the model. In the blood compartment, neutrophils can be characterized as belonging to one of three groups: resting, primed, and systemically activated. While primed blood neutrophils migrate to the infectious site and become activated locally in tissue, systemically activated blood neutrophils, which have fewer essential chemokine receptors, have impaired ability to migrate. A key hypothesis of the model is that the lung is a preferred site for homing and activation of primed neutrophils due to the long and narrow microvascular bed. As a result primed and systemically activated blood neutrophils can be sequestered in the lung when lung vascular endothelium becomes activated by systemic inflammatory mediators.

Distinct neutrophil kinetic responses to the inflammatory status were calibrated to reproduce relevant quantitative and qualitative literature information. Model parameters were optimized to reproduce key serum cytokine (TNF-a, IL1, IL10, IL6) time courses and neutrophil/bacteria counts for each compartment during sublethal and lethal sepsis in bacteria-induced or lipopolysaccharide-induced rodent experimental models. Simulations suggest that a systemic inflammation leads to functionally heterogeneous neutrophil subsets. Systemically activated neutrophils cause impairment of neutrophil migration to the tissue, and systemic neutrophil activation favors blood neutrophils sequestration in the lung.

There is strong evidence that non-specific adsorption of circulatory cytokines (hemadsorption[HA]) decreases lung accumulation of neutrophils and improves outcome, but the underlying mechanisms remain elusive. Therefore, the model was extended to incorporate flow-dependent blood purification (removal of circulating cytokines), along with hypothetical mechanisms that could explain the effects and advantages provided by systemic HA treatment. The model was calibrated with prospectively collected experimental data. Simulations support that the positive effect of HA could be ascribed partly to reducing circulating levels of inflammatory effectors, thus reducing lung endothelial activation and promoting neutrophil recruitment to the primary site of infection, resulting in improved clearance of infection. Simulations also generated another hypothesis that the HA device can capture activated neutrophils, thus competing with lung for activated neutrophils, reducing sequestered neutrophils in the lung, and improving survival. Further experimental studies about compartmental neutrophil populations are needed to clarify the relative contribution of these mechanisms. Taken together, mathematical modeling of distinct phenotypes of neutrophils as a way of quantifying the systemic inflammatory status might enhance our understanding of the complex network of interactions present in sepsis and guide future experiments as a quantitative framework for generating hypotheses.