Discrete Dynamical Modeling of Influenza Virus Infection Suggests Age-Dependent Differences in Immunity

Abstract

Immunosenescence, an age-related decline in immune function, is a major contributor to morbidity and mortality in the elderly. Older hosts exhibit a delayed onset of immunity and prolonged inflammation after an infection, leading to excess damage and a greater likelihood of death. Our study applies a rule-based model to infer which components of the immune response are most changed in an aged host. Two groups of BALB/c mice (aged 12 to 16 weeks and 72 to 76 weeks) were infected with 2 inocula: a survivable dose of 50 PFU and a lethal dose of 500 PFU. Data were measured at 10 points over 19 days in the sublethal case and at 6 points over 7 days in the lethal case, after which all mice had died. Data varied primarily in the onset of immunity, particularly the inflammatory response, which led to a 2-day delay in the clearance of the virus from older hosts in the sublethal cohort. We developed a Boolean model to describe the interactions between the virus and 21 immune components, including cells, chemokines, and cytokines, of innate and adaptive immunity. The model identifies distinct sets of rules for each age group by using Boolean operators to describe the complex series of interactions that activate and deactivate immune components. Our model accurately simulates the immune responses of mice of both ages and with both inocula included in the data (95% accurate for younger mice and 94% accurate for older mice) and shows distinct rule choices for the innate immunity arm of the model between younger and aging mice in response to influenza A virus infection. Influenza virus infection causes high morbidity and mortality rates every year, especially in the elderly. The elderly tend to have a delayed onset of many immune responses as well as prolonged inflammatory responses, leading to an overall weakened response to infection. Many of the details of immune mechanisms that change with age are currently not well understood. We present a rule-based model of the intrahost immune response to influenza virus infection. The model is fit to experimental data for young and old mice infected with influenza virus. We generated distinct sets of rules for each age group to capture the temporal differences seen in the immune responses of these mice. These rules describe a network of interactions leading to either clearance of the virus or death of the host, depending on the initial dosage of the virus. Our models clearly demonstrate differences in these two age groups, particularly in the innate immune responses.

Risk Factors Associated with 30-Day Mortality in Older Patients with Influenza

“…This result is consistent with previous clinical and epidemiologic studies [1,2,6,12,13] and was confirmed by Mertz et al in a recent meta-analysis [22]. However, we assume that it could be difficult to distinguish physiological age from chronological age [23], and this result could be biased by confounding factors such as the immunological markers of immunosenescence [24].…”

Host‐pathogen kinetics during influenza infection and coinfection: insights from predictive modeling

“…A thorough investigation into the uncertainty of the estimates and the corresponding model solution is also required. This has been particularly true when attempting to determine significant differences in parameter estimates generated by fitting a model to data obtained under varied experimental conditions, such as during infection with different virus strains, with different doses, in different host genetic backgrounds, or in different aged individuals . For this, ensemble‐style methods have been particularly useful.…”

“…Viral kinetics generally split into ~5 phases: initial infection of cells, exponential growth, peak, a slow decay, and a fast decay/clearance. Major host responses influencing these phases include, type I interferons (IFN), natural killer (NK) cells, T cells, and antibody (Ab) infection with different virus strains, 16,41 with different doses, 15,59 in different host genetic backgrounds, 60 or in different aged individuals. 59,61 For this, ensemble-style methods have been particularly useful.…”

Short Communication: Oral Administration of Heat-killed Lactobacillus brevis KB290 in Combination with Retinoic Acid Provides Protection against Influenza Virus Infection in Mice

“…Here, we found that the ingestion of a combination of heat-killed KB290 and VA suppressed bodyweight loss and reduced the lung viral titre in mice challenged with a sublethal dose of IAV. Challenging mice with lethal doses of IAV results in markedly different immunopathology compared with challenging them with sublethal doses [ 56 , 57 , 58 , 59 , 60 ]. Sublethal infection with IAV is physiologically relevant because it can closely mimic seasonal influenza infection in humans.…”

“…Infection with a lethal dose of influenza virus results in an overwhelming release of proinflammatory cytokines and severe bodyweight loss of up to 35%, causing high mortality. Sublethal influenza virus doses have resulted in bodyweight losses of up to 20% and lower mortality compared with lethal doses [ 56 , 59 ]. To simulate naturally occurring influenza virus infections in humans, this study investigated mice challenged with a sublethal dose of IAV.…”