Vaccination Alters the Balance between Protective Immunity, Exhaustion, Escape, and Death in Chronic Infections

Abstract

While T cell-based vaccines have the potential to provide protection against chronic virus infections, they also have the potential to generate immunopathology following subsequent virus infection. We develop a mathematical model to investigate the conditions under which T cells lead to protection versus adverse pathology. The model illustrates how the balance between virus clearance and immune exhaustion may be disrupted when vaccination generates intermediate numbers of specific CD8 T cells. Surprisingly, our model suggests that this adverse effect of vaccination is largely unaffected by the generation of mutant viruses that evade T cell recognition and cannot be avoided by simply increasing the quality (affinity) or diversity of the T cell response. These findings should be taken into account when developing vaccines against persistent infections.Vaccination expands the numbers of lymphocytes specific for a given pathogen. However, in some circumstances, increasing the number of antigen-specific lymphocytes may fail to provide protection and instead lead to an adverse outcome following exposure to the pathogen. Vaccine-induced pathology can occur for many reasons. For instance, the recent adenovirus 5-based vaccination against human immunodeficiency virus (HIV) led to an increased probability of infection following exposure (18). Alternatively, the severity of infection might increase, as seen with respiratory syncytial virus (RSV) following early attempts at immunization (10, 13, 14) and as potentially occurs with dengue virus, with which previous infection with one serotype may result in more severe pathology following challenge with heterologous serotypes (11,19). The problem of adverse effects is of current relevance in the context of the development of vaccines against persistent infections. Conventional techniques have not yielded effective vaccines, but a promising approach involves the generation of vaccines that induce T cell responses against such infections. In this paper, we use mathematical models to explore pathology following T cell-based immunization against persistent infections.Laboratory experiments with mice have demonstrated that increasing the number of specific lymphocytes can lead to increased pathology in chronic diseases, such as those caused by lymphocytic choriomeningitis virus (LCMV) and hepatitis B virus (HBV). HBV-transgenic mice, which are used as a model for chronic human HBV infection, develop acute liver failure due to loss of liver cells after adoptive transfer of HBV-specific CD8 T cells (8). In mice infected with chronic LCMV, the extent of immunopathology depends on the initial dose of virus and initial numbers of naive-phenotype-specific CD8 T cells (6,9,22). Since these experiments tested only narrow immune responses, a natural hypothesis was that the increased pathology might be avoided by broadening the immune response (22). However, predicting pathology requires understanding the complex interplay between virus replication, immune exhaustion, and immune escape.In th...

Modeling how reversal of immune exhaustion elicits cure of chronic hepatitis C after the end of treatment with direct‐acting antiviral agents

“…The description has been employed successfully to explain the post‐treatment control of HIV‐1 infection 36. More sophisticated models that incorporate the dependence of exhaustion on sustained antigenic stimulation have been proposed,35, 37 but have been argued to have similar qualitative features as the simpler model employed here 36. Third, studies have argued that in addition to CTL function, NK cell function is restored during IFN‐free DAA therapy,53 which we did not consider.…”

“…We let the death rate of infected cells other than by CTL killing be the same as the natural death rate of target cells, neglecting any HCV‐induced cytopathicity; thus, ω =  d T . We let the CTL production, death and activation rates be λ = 1 cell mL −1 day −1 , μ = 2 day −1 , b E  = 1 day −1 and k B  = 10 3  cells mL −1 35, 36. The viral production and clearance rates, p and c , the drug efficacy, ε, the strength of CTL killing, m , and the parameters governing CTL exhaustion, d E , k D and n , are expected to vary across individuals.…”

Post-treatment control of HIV infection

“…39), that is greater than b E so that the effector population can be effectively reduced by exhaustion. We use the effector cell killing rate m as a second control parameter indicating the strength of the immune response.…”

How do antigenically varying pathogens avoid cross-reactive responses to invariant antigens?

“…However, recent experimental work on immune exhaustion suggests that this standard term for the expansion of immune cells may not be appropriate. We extend our model to incorporate immune exhaustion as previously described in the context of modelling lymphocytic choriomeningitis Antigenic variation versus cross-immunity P. L. F. Johnson et al 2779 virus [14]. Briefly, we add new variables to track the level of exhaustion for each population of antigen-specific, Q i , and cross-reactive immune cells, R. Exhaustion leads to a decay in the magnitude of the immune response in a flexible manner captured by a Hill function with exponent h and coefficient q c such that the maximum decay rate is d. Exhaustion itself increases according to antigen stimulus (i.e.…”