ABSTRACT
BACKGROUND: Within-host models describe the dynamics of immune cells when encountering a pathogen, and how these dynamics can lead to an individual-specific immune response. This systematic review aims to summarize which within-host methodology has been used to study and quantify antibody kinetics after infection or vaccination. In particular, we focus on data-driven and theory-driven mechanistic models. MATERIALS: PubMed and Web of Science databases were used to identify eligible papers published until May 2022. Eligible publications included those studying mathematical models that measure antibody kinetics as the primary outcome (ranging from phenomenological to mechanistic models). RESULTS: We identified 78 eligible publications, of which 8 relied on an Ordinary Differential Equations (ODEs)-based modelling approach to describe antibody kinetics after vaccination, and 12 studies used such models in the context of humoral immunity induced by natural infection. Mechanistic modeling studies were summarized in terms of type of study, sample size, measurements collected, antibody half-life, compartments and parameters included, inferential or analytical method, and model selection. CONCLUSIONS: Despite the importance of investigating antibody kinetics and underlying mechanisms of (waning of) the humoral immunity, few publications explicitly account for this in a mathematical model. In particular, most research focuses on phenomenological rather than mechanistic models. The limited information on the age groups or other risk factors that might impact antibody kinetics, as well as a lack of experimental or observational data remain important concerns regarding the interpretation of mathematical modeling results. We reviewed the similarities between the kinetics following vaccination and infection, emphasising that it may be worth translating some features from one setting to another. However, we also stress that some biological mechanisms need to be distinguished. We found that data-driven mechanistic models tend to be more simplistic, and theory-driven approaches lack representative data to validate model results.
Subject(s)
Antibody Formation , Vaccination , Immunity, Humoral , Models, TheoreticalABSTRACT
Introduction: Studying antibody dynamics following re-exposure to infection and/or vaccination is crucial for a better understanding of fundamental immunological processes, vaccine development, and health policy research. Methods: We adopted a nonlinear mixed modeling approach based on ordinary differential equations (ODE) to characterize varicella-zoster virus specific antibody dynamics during and after clinical herpes zoster. Our ODEs models convert underlying immunological processes into mathematical formulations, allowing for testable data analysis. In order to cope with inter- and intra-individual variability, mixed models include population-averaged parameters (fixed effects) and individual-specific parameters (random effects). We explored the use of various ODE-based nonlinear mixed models to describe longitudinally collected markers of immunological response in 61 herpes zoster patients. Results: Starting from a general formulation of such models, we study different plausible processes underlying observed antibody titer concentrations over time, including various individual-specific parameters. Among the converged models, the best fitting and most parsimonious model implies that once Varicella-zoster virus (VZV) reactivation is clinically apparent (i.e., Herpes-zoster (HZ) can be diagnosed), short-living and long-living antibody secreting cells (SASC and LASC, respectively) will not expand anymore. Additionally, we investigated the relationship between age and viral load on SASC using a covariate model to gain a deeper understanding of the population's characteristics. Conclusion: The results of this study provide crucial and unique insights that can aid in improving our understanding of VZV antibody dynamics and in making more accurate projections regarding the potential impact of vaccines.
