Antibodies play a major role in neutralizing pathogens and preventing illness following infection of the host. In the current pandemic of the coronavirus disease 2019 (COVID-19), the levels of neutralizing antibodies have the primary method of evaluating the efficacy of vaccines and therapeutic monoclonal antibodies.
A new study published on the preprint server medRxiv* explores the polyclonal antibody response to SARS-CoV-2 in greater detail. The scientists apply machine learning to understand various effectors and neutralizing functions of antibodies. The data presented here will likely be useful in predicting how a given antibody profile correlates with actual activity.
Study: Antibody Attributes that Predict the Neutralization and Effector Function of Polyclonal Responses to SARS-CoV-2. Image Credit: Kateryna Kon / Shutterstock.com
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
Background
Following the large-scale vaccination of populations of various developed countries, serologic studies have shown that seroconversion and high levels of neutralizing antibodies are associated with low levels of reinfection. However, convalescent plasma proved to be an inconsistent tool, with conflicting results from different studies.
“Antibody responses between individuals are highly variable. This variability uggests that monoclonal antibody and convalescent plasma therapy, as well as vaccine design, can be improved by determining the factors that contribute to a functionally protective antibody response.”
Aside from neutralization additional antibody effector functions include both humoral and cell-mediated activity. Complement activation by antibodies leads to direct lysis of the virus and/or infected host cell, or neutralization. Antibodies can also promote or induce phagocytosis, or trigger the release of toxic chemicals, cytokines, or reactive oxygen species.
This often involves the binding of the constant fragment of the antibody (Fc) domain of the antibody to Fcγ Receptors (FcγR). This binding event has therefore been the focus of research on COVID-19 vaccines and therapeutics.
Following SARS-CoV-2 infection, antibodies have been found to cause antibody-dependent cell-mediated phagocytosis (ADCP) by monocytes, antibody-dependent complement cascade component C3b deposition (ADCD), and natural killer (NK) cell-mediated antibody-dependent cellular cytotoxicity (ADCC).
Both antibody-dependent cellular cytotoxicity (ADCC) and antibody-dependent cell-mediated phagocytosis (ADCP) are important in anti-coronavirus responses. In fact, some scientists believed that these two antibody functions play an important role in defending the host against SARS-CoV-2. Many studies, including those in which antibodies were transferred from immune sera to a non-immune subject, show that antibodies conferred protection in vivo by both humoral and effector functions.
The roles played by different antibodies and their effects on antiviral immunity were studied in the sera of convalescent and uninfected subjects. Both the variable fragment of the antibody (Fv) and Fc were examined in parallel.
What were the findings?
The researchers observed high variability in the levels and types of antibodies elicited with most convalescents, especially those collected from patients who had been hospitalized, showing high immunoglobulin G (IgG) antibody levels. Conversely, a small number of convalescents did not show seroconversion.
Further analysis showed that antibodies with FcgR-binding functionality to the spike S1 domain, the receptor-binding domain (RBD), and nucleoprotein (N) antigens were more likely to have effector functions and were correlated with total immunoglobulin G (IgG) responses. Conversely, neutralization potency was linked to IgA and IgM titers.
ADCC and ADCP were driven primarily by antibodies specific to RBD or, more broadly, to S1, while neutralization was associated with antibodies targeting the stabilized pre-fusion spike protein. Deposition of the complement cascade component C3b (ADCD) was predicted by spike trimer recognition.
In contrast, S2 binding was not found to be linked to effector functionality. Additionally, IgA reactivity to other coronaviruses was negatively associated with ADCC. This suggests that cross-reactive IgA antibodies, which may cross-react with other coronaviruses, may inhibit anti-spike IgG activity.
Since the FcR is not required for neutralization, the IgG titer was the most predictive factor for neutralization potency. In contrast, FcγRIII- and FcγRII-binding responses were most often found to predict ADCC and ADCP, respectively.
Though IgG3 forms only a small part of IgG in circulation, it drives effector functions. As a result, anti-RBD IgG3 antibodies contributed to both the latter functions.
IgM directed against S1 was linked to neutralization potency. This may a primary rather than cross-reactive memory B-cell response originally elicited by other coronaviruses. Total IgM was significantly linked to the neutralization titer, with its removal being associated with 1.6-73-fold reductions. In contrast, IgG and IgA titers were not significantly affected.
What are the implications?
Both Fv-specific and Fc-related characteristics showed that different features predicted antibody functions. The predictions of functional activity based on SARS-CoV-2-specific antibody responses were robust and could be generalized. This confirms the validity of this biophysical antibody profile-based modeling approach.
Not only was this a simpler method, but it allowed easier interpretation of the findings. Despite this advantage, it may be more difficult to recognize some biological mechanisms by not including features already associated with selected variables.
Spike-specific FcγR-binding antibodies were also found to be important, with FcγRIIa and FcγRIIIa being implicated in phagocytosis and NK activity, respectively. IgG3 was recognized to have disproportionate importance. IgM antibodies specific to the virus were predictive of neutralization potency, which corroborates associations of reduced mortality with higher IgM levels.
“SARS-CoV-2 specific IgM administered intranasally has been shown to be effective in treating novel SARS-CoV-2 variants of concern, including the alpha, beta, and gamma variants in a mouse model.”
Conversely, gamma-globulin concentrates, from which IgM has been removed, may be correspondingly weaker in their neutralizing activity. However, IgM is cleared faster from plasma, which may require more frequent administration of convalescent plasma.
With emerging SARS-CoV-2 variants posing a threat to the control of COVID-19, the functional efficacy of elicited antibodies may become more relevant in understanding susceptibility to SARS-CoV-2 and the choice of vaccine regimens. For such a task, the ability to profile antibody binding rapidly using remnant plasma, as in this study, could be important.
“This multivariate analysis provides a blueprint for carrying out such investigation. The discovery of antibody functions associated with passive antibody efficacy could allow optimization of serological characteristics of mAbs, plasma and gamma globulin products for prevention and therapy of COVID-19.”
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
Journal references:
- Preliminary scientific report.
Natarajan, H., Xu, S., Crowley, A. R., et al. (2021). Antibody Attributes that Predict the Neutralization and Effector Function of Polyclonal Responses to SARS-CoV-2. medRxiv. doi:10.1101/2021.08.06.21261710. https://www.medrxiv.org/content/10.1101/2021.08.06.21261710v1
- Peer reviewed and published scientific report.
Natarajan, Harini, Shiwei Xu, Andrew R. Crowley, Savannah E. Butler, Joshua A. Weiner, Evan M. Bloch, Kirsten Littlefield, et al. 2022. “Antibody Attributes That Predict the Neutralization and Effector Function of Polyclonal Responses to SARS-CoV-2.” BMC Immunology 23 (1). https://doi.org/10.1186/s12865-022-00480-w. https://bmcimmunol.biomedcentral.com/articles/10.1186/s12865-022-00480-w.
Article Revisions
- Apr 11 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.