Dynamically linking influenza virus infection kinetics, lung injury, inflammation, and disease severity.

Margaret A Myers,Stacie Woolard,Rosemary Aogo,Lindey C Lane,Peter Vogel,Amber M Smith,David J Moquin,Paul Thomas,Amanda P Smith

doi:10.7554/elife.68864

Abstract

Influenza viruses cause a significant amount of morbidity and mortality. Understanding host immune control efficacy and how different factors influence lung injury and disease severity are critical. We established and validated dynamical connections between viral loads, infected cells, CD8+ T cells, lung injury, inflammation, and disease severity using an integrative mathematical model-experiment exchange. Our results showed that the dynamics of inflammation and virus-inflicted lung injury are distinct and nonlinearly related to disease severity, and that these two pathologic measurements can be independently predicted using the model-derived infected cell dynamics. Our findings further indicated that the relative CD8+ T cell dynamics paralleled the percent of the lung that had resolved with the rate of CD8+ T cell-mediated clearance rapidly accelerating by over 48,000 times in 2 days. This complimented our analyses showing a negative correlation between the efficacy of innate and adaptive immune-mediated infected cell clearance, and that infection duration was driven by CD8+ T cell magnitude rather than efficacy and could be significantly prolonged if the ratio of CD8+ T cells to infected cells was sufficiently low. These links between important pathogen kinetics and host pathology enhance our ability to forecast disease progression, potential complications, and therapeutic efficacy.

Highlights

Over 15 million respiratory infections and 200,000 hospitalizations result from influenza A viruses (IAVs) each year (Thompson et al, 2004; Simonsen et al, 2000; Taubenberger and Morens, 2008; Medina and Garcıa-Sastre, 2011)
Memory CD8+ T cell (EM ; denoted CD8M) generation occurs at rate z and proportional to CD8E t M days ago. (B) Fit of the CD8+ T cell model (Equation (1)-(6)) to virus and total CD8+ T cells from the lungs of mice infected with 75 TCID50 PR8 (10 mice per time point)
Because the rapid decay of virus is thought to be due to the clearance of infected cells by CD8+ T cells, it is unknown if early CD8+ T cell presence contributes to infected cell clearance, and no model has captured the entire CD8+ T cell time course, we developed a model that describes the dynamics of these cells and their efficiency in resolving the infection (Equation (1)(6); Figure 1A)

Summary

Introduction

Over 15 million respiratory infections and 200,000 hospitalizations result from influenza A viruses (IAVs) each year (Thompson et al, 2004; Simonsen et al, 2000; Taubenberger and Morens, 2008; Medina and Garcıa-Sastre, 2011). The incidence and severity of IAV infections increases when new strains emerge and/or when there is a lack of prior immunity. High viral loads can play a role in disease progression (Boon et al, 2011; de Jong et al, 2006), but these do not always correlate with the strength of the host response or with disease severity (Granados et al, 2017; Marathe et al, 2016; Toapanta and Ross, 2009; Smith et al, 2019; Gao et al, 2013). An understanding of how viral loads, host immune responses, and disease progression are related is critical to identify disease-specific markers that may help predict hospitalization or other complications

Methods

Results

Conclusion