An ODE framework to understand the role of polyfunctionality and heterozygous Fc receptor polymorphisms in Fc-mediated immune responses

Introduction:: Antibodies generally provide protection against infection by neutralizing, or tightly binding to pathogens via the Fab portion of the antibody, but can also activate the innate immune system (via the Fc portion) to induce protective cellular functions including antibody-dependent cellular phagocytosis (ADCP) and antibody- dependent cellular cytotoxicity (ADCC). These functions are enacted when IgG dimers bind to antigen and Fc gamma receptors (FγRs) on innate immune cells to form complexes. FcγRIIa is primarily found on monocytes and triggers phagocytosis while FcγRIII on natural killer (NK) cells induces secretion of cytotoxic factors to kill infected cells. FcγR receptor genetic polymorphisms have been identified, which can affect the binding affinity of IgG to FcγRs (e.g. FcγRIIa-H has a higher affinity for IgG than FcγRIIa-R) and can be inherited in homozygous or heterozygous patterns. Additionally, there are four subclasses of IgG which can vary in concentration between individuals and bind FcγRs at different rates. In order to better understand this complex system, we created a new computational model that is able to account for interaction between multiple FcRs which can give insight into genetic variability between individuals or multiple simultaneous Fc effector functions (polyfunctionality) induced by different classes of FcγRs.


Materials and Methods:: We expanded the system of ordinary differential equations (ODEs) established in Lemke et. al (2021) to account for the potential binding of antigen-bound IgG dimers to multiple different classes of FcγRs, using the corresponding binding affinities unique to each class (Figure 1). Systems of equations were written using the laws of mass action kinetics, in combination with conservation equations for total antigen, total FcR, and each IgG subtype. We performed analyses using Matlab’s (Mathworks) ODE solver to calculate the concentration of each species over time and measured the model outputs were set to the summed totals of complexes (including FcγRII and FcγRIII). We assumed a well-mixed system without spatial constraints and no degradation or production of species. Initial concentration for the IgG subclasses were determined using the average sample assay values from the HIV RV144 vaccine trial as implemented in Lemke et. al. The SPR-measured binding affinity of IgG to HIV envelope antigen (env) from Lemke et. al was used for the antigen binding rate and FcγR binding rates were obtained from the literature. The initial concentrations of antigen and FcR detector were set based on the experimental conditions for an experimental multiplex assay and validation was performed by comparing model predictions to experimental results. A sensitivity analysis was used to identify which parameters significantly influenced total complex formation (sum of FcγRII and FcγRIII).




Results, Conclusions, and Discussions:: The sensitivity analysis revealed that the most sensitive parameters for FcγRIIa complex formation were those related to the binding of IgG1 to antigen, the binding of FcγRIIa to IgG1, IgG1 concentration, and FcγRII concentration (Figure 2). A similar pattern was observed for FcγRIII, except that the binding for FcγRIII to IgG1 was the key binding parameter. The analysis also indicated that FcγRIII complexes were sensitive to IgG3 concentration and FcγRII-IgG3 binding at very high concentrations or affinities. When the ratio of FcγRII to FcγRIII complexes (ADCP:ADCC) was set as the output for the sensitivity analysis, it revealed that increases in IgG1 saturated the skew towards phagocytosis, whereas increases in IgG3 skewed the response towards cytotoxicity. The balance of ADCP and ADCC in relationship to antigen-specific IgG1 and IgG3 concentrations has been explored in Chung et. al (2014) and showed an IgG3-driven polyfunctional Fc-effector relationship in the HIV RV144 trial.

In this study, we were able to provide a novel framework to explore polyfunctionality and heterozygosity. This is the first known model of its kind to build on the complexity of a single FcγR model to account for multiple classes, which can correspond to multiple cell types and functionality. Some limitations include the fact that FcγRII and FcγRIII are not solely expressed on phagocytes and cytotoxic cells respectively; these receptors are expressed across multiple cell types in differing ratios across tissue location, but this model still provides a useful framework that could be further expanded to explore this complexity. Future work includes performing multiplex assays with multiple classes of FcγRs as detectors to validate the model using experimental data.


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References (Optional): :

1. Lemke, M. M. et al. A systems approach to elucidate personalized mechanistic complexities of antibody-Fc receptor activation post-vaccination. Cell Reports Medicine 2, 100386 (2021).


2. Raedler MD, Heyne S, Wagner E, et al. Serologic assay to quantify human immunoglobulin G antibodies to the Staphylococcus aureus iron surface determinant B antigen. Clin Vaccine Immunol. 2009;16(5):739-748. doi:10.1128/CVI.00478-08


3. Chung AW et al., Polyfunctional Fc-Effector Profiles Mediated by IgG Subclass Selection Distinguish RV144 and VAX003 Vaccines.Sci. Transl. Med.6,228ra38-228ra38(2014).DOI:10.1126/scitranslmed.3007736