Dynamically Linking Influenza Virus Infection Kinetics, Lung Injury, Inflammation, and Disease Severity

Abstract

Influenza A viruses cause a significant amount of morbidity and mortality. Understanding how the infection is controlled by host immune responses and how different factors influence severity are critical to combat the infection. During infection, viral loads increase exponentially, peak, then decline until resolution. The viral decline is often biphasic, which we previously determined is a consequence of density-dependent infected cell clearance. The second, rapid clearance phase corresponds with the infiltration of CD8 + T cells, but how the rate changes with infected cell density and T cell density is unclear. Further, the kinetics of virus, infected cells, and CD8 + T cells all contribute to disease severity but do not seem to be directly correlated. Thus, we investigated the relations between viral loads, infected cells, CD8 + T cells, lung pathology, and disease severity/symptoms by infecting mice with influenza A/PR8, simultaneously measuring virus and CD8 + T cells, and developing and calibrating a kinetic model. The model predicted that infection resolution is sensitive to CD8 + T cell expansion, that there is a critical T cell magnitude below which the infection is significantly prolonged, and that the efficiency of T cell-mediated clearance is dependent on infected cell density. To further examine the latter finding and validate the model's predicted dynamics, we quantified infected cell kinetics using lung histomorphometry. These data showed that the area of lung infected matches the predicted cumulative infected cell dynamics, and that the area of resolved infection parallels the relative CD8 + T cell magnitude. Our analysis further revealed a nonlinear relationship between disease severity (i.e., weight loss) and the percent of the lung damaged. Establishing the predictive capabilities of the model and the critical connections that map the kinetics of virus, infected cells, CD8 + T cells, lung pathology, and disease severity during influenza virus infection aids our ability to forecast the course of infection, disease progression, and potential complications, thereby providing insight for clinical decisions.

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