Poster M9 - Using A Computational Model to Investigate Fcγ Receptor Competition and the Effect of Fcγ Receptor Polymorphisms and Different Tissues

Introduction: Non-neutralizing IgG antibodies can provide protection against infection by binding Fcγ receptors (FcγRs) on innate immune cells to induce protective functions including Antibody-Dependent Cellular Cytotoxicity (ADCC, activated by FcγRIIIa) and Antibody-Dependent Cellular Phagocytosis (ADCP, activated by FcγRIIa). Recent studies indicate that these functions are important for protection against various viral infections. However, optimal IgG titers for maximizing these functions are unknown, complicated by FcγR competition, IgG subclass concentration variability, and host genetic factors that alter FcγR binding. This challenge is magnified in peripheral tissues, where experimental measurements are limited and IgG concentration and FcγR availability varies. In this study, we developed a computational framework with two FcγRs to predict ADCP and ADCC simultaneously, allowing us to generate new insight into mechanisms that may underpin these processes in different tissue types.

Materials and

Methods: We created an ordinary differential equation (ODE) model that predicts the formation of antigen-IgG-FcγRIIa (ADCP) and antigen-IgG-FcγRIIIa (ADCC) complexes as a function of concentration and binding properties of participating IgG and FcγR species. Simulations were performed for blood, rectal, and penile tissues by altering concentrations of antigen, IgG1, IgG2, IgG3, IgG4, FcγRIIa and FcγRIIIa according to calculations from measurements in the published literature. FcγR polymorphisms were simulated by altering the binding rate constant of IgG to respective FcγRs. Sensitivity analysis were used to assess additional interactions between sensitive parameters. Vaccine boosting was simulated by increasing IgG1-4 titers in a population of individuals from an HIV vaccine trial.

Results, Conclusions, and Discussions: Results/

Discussion: The sensitivity analysis for blood revealed that parameters related to IgG1 and IgG3 were critical for both ADCP and ADCC (Figure 1A). Surprisingly, the model revealed how elevated titers of IgG1 and IgG3 have the capacity to reduce ADCP and ADCC, respectively (Figure 1C). High titers of both IgG1 and IgG3 were not predicted to maximize Fc effector functions, due to competition of IgGs for antigen and differential binding to Fcγ receptors (Figure 1A). Simulated boosting of IgG1 or IgG3 in individuals from an HIV vaccine trial illustrated how the results of boosting are affected by this competition. For example, a 10x boost of IgG1 significantly reduced FcγRIIIa complex formation compared to baseline (p < 0.05). The model also showed that different combinations of FcγR polymorphisms can change which function is dominantly activated. The combination of FcγIIaR and FcγRIIIaV resulted in FcγRIIIa formation being dominant throughout the entire range of concentrations tested, as compared to the other polymorphism combinations that had variable dominant complex formation. FcγR concentration also changes between tissues, which the model shows results in different functions being dominantly activated. For example, in penile tissue, FcγRIIIa complex formation was dominant throughout the entire range of concentrations tested.

Conclusions: This quantitative approach suggests a new mechanism by which increasing antibody titers has the capacity to decrease Fc effector functions. This has important implications for vaccine boosting to increase IgG titers, suggesting that specific changes in IgG subclass concentrations from boosting can skew protective responses towards different Fc effector functions. Furthermore, different polymorphism combinations and different tissues can induce variable function activation.

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