Post-doc Fellow Daiichi Sankyo, Inc.; Rutgers University, United States
Disclosure(s):
Elise Vo: No financial relationships to disclose
Objectives: Aging is associated with immunosenescence, a decline in innate and adaptive immune functions, leading to diminished vaccine efficacy [1]. We anticipated the need to address these effects when constructing a QSP model of lipid nanoparticle-delivered mRNA vaccine response, which was adapted from the framework by Chen et al. [2]. We hypothesized that age-related immune alterations could be implemented in the model to predict the lower IgG level and neutralizing titer (NT) outcomes observed in elderly populations. This study aimed to refine the model by identifying key age-related changes and determine their influence on vaccine response.
Methods: We conducted a literature review to identify differences in immune system parameters between adult and elderly populations. Studies reporting quantitative changes in immune cell populations, functions, and vaccine responses were prioritized. Parameter selection was based on biological relevance, availability of numerical data, and feasibility of integration into the existing QSP model. Parameters were modified based on literature-derived values. Using the SimBiology toolbox in MATLAB R2024a, simulations were run over 150 days post-initial vaccine dose to assess early and late immune response dynamics. Global sensitivity analysis was performed using Sobol indices to assess the influence of parameters on vaccine response.
Results: The literature review identified age-related immune differences, from which eight were incorporated into the model. These included reductions to macrophage phagocytic capacity, MHC class II expression on dendritic cells (DCs), DC migration efficiency, naïve CD4+ T cell number, naïve CD4+ T cell proliferation, follicular helper T cell (Tfh) function, and naïve B cell number. Incorporating these changes led to approximately 40% reductions in both peak IgG levels and NTs, recapitulating the 33-60% reduced IgG levels and 50-75% reduced NTs in elderly patients reported in the literature [3-5]. Sensitivity analysis revealed five parameters with the greatest impact on IgG level and NT outcomes: naïve CD4+ T cell number, naïve CD4+ T cell proliferation, Tfh function, macrophage phagocytic capacity, and DC migration efficiency. The two latter parameters had the greatest impact on mRNA level, affecting the immune response ignition downstream of mRNA delivery. Naïve CD4+ T cell proliferation was the most influential at all immune response stages. The model with these five parameter changes recapitulated reduced outcomes comparable to simulations with all parameter changes.
Conclusions: Incorporating age-related changes helped capture the reduced immune response in elderly populations. Reductions in naïve CD4+ T cell number, naïve CD4+ T cell proliferation, Tfh function, macrophage phagocytic capacity, and DC migration efficiency had the greatest impact on the model’s outputs, suggesting that these factors are critical determinants of the diminished vaccine response in the elderly. This refined model provided a framework for understanding vaccine response and can support strategies for optimizing vaccination in aging populations.
Citations: [1] Allen JC, Toapanta FR, Chen W, Tennant SM. Understanding immunosenescence and its impact on vaccination of older adults. Vaccine. 2020;38(52):8264-8272. doi:10.1016/j.vaccine.2020.11.002 [2] Chen X, Hickling TP, Vicini P. A mechanistic, multiscale mathematical model of immunogenicity for therapeutic proteins: part 1-theoretical model. CPT Pharmacometrics Syst Pharmacol. 2014;3(9):e133. Published 2014 Sep 3. doi:10.1038/psp.2014.30 [3] Brockman MA, Mwimanzi F, Lapointe HR, et al. Reduced Magnitude and Durability of Humoral Immune Responses to COVID-19 mRNA Vaccines Among Older Adults. J Infect Dis. 2022;225(7):1129-1140. doi:10.1093/infdis/jiab592 [4] Hansen L, Brokstad KA, Bansal A, et al. Durable immune responses after BNT162b2 vaccination in home-dwelling old adults. Vaccine X. 2023;13:100262. doi:10.1016/j.jvacx.2023.100262 [5] Roeder AJ, Koehler MA, Jasbi P, et al. Longitudinal Comparison of Neutralizing Antibody Responses to COVID-19 mRNA Vaccines after Second and Third Doses. Vaccines (Basel). 2022;10(9):1459. Published 2022 Sep 3. doi:10.3390/vaccines10091459
