Method for predicting neutralization and protection based on variant-specific antibody measurements to SARS-CoV-2 antigens

In a recent study posted to the medRxiv* preprint server, researchers reported a method to predict neutralization and protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens.

Study: Humoral Immunity to SARS-CoV-2 and Inferred Protection from Infection in a French Longitudinal Community Cohort. Image Credit: Immersion Imagery/Shutterstock
Study: Humoral Immunity to SARS-CoV-2 and Inferred Protection from Infection in a French Longitudinal Community Cohort. Image Credit: Immersion Imagery/Shutterstock

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Background

With over 529 million global cases and 6.28 million deaths to date, the coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 has adversely impacted public health with significant morbidity and mortality. Besides the infection-induced immunity, much of the world’s population has been vaccinated, and vaccination coverage varies from 30% to 90% between countries.

Seroprevalence is estimated by measuring antibodies against SARS-CoV-2 spike (S) or nucleocapsid (N) protein. Although the presence of antibodies is associated with protection, it is not always predictive of protection. Unlike most serologic tests, a neutralization assay quantifies neutralizing antibodies (nAbs) blocking viral replication/infection. nAbs are more likely to be protective given their direct antiviral activity. It has been shown that neutralization titers correlate well with protection against symptomatic COVID-19 and subsequent hospitalization.

About the study

In the current study, researchers developed a multiplex serologic assay quantifying the binding of different immunoglobulin subtypes to a range of SARS-CoV-2 antigens. A prediction model was generated based on the correlation between serologic measurements and neutralizing activities against different SARS-CoV-2 variants. Using the predicted neutralization titers, the team projected protection estimates.

Serum samples were collected from vaccinated or convalescent subjects to assess the correlation of antibodies with neutralizing titers. These participants were enrolled in two clinical cohorts: Orleans and Strasbourg cohorts. Participants from the COVID-Oise study, a longitudinal cohort study, were invited to provide biological specimens and epidemiological data. Samples and data from the first three sessions (of collection) were used for the current analysis.

The authors extrapolated a previously described bead-based 9-plex assay to detect antibodies against 30 antigens simultaneously (30-plex or multiplex), including the stabilized spike (S) ectodomain trimer receptor-binding domain (RBD), envelope (E), nucleocapsid (N), and membrane (M) proteins. Recombinant RBD and S antigens of ancestral SARS-CoV-2, Alpha, Beta, and Delta variants were used. Additionally, antibodies against S and N antigens of seasonal coronaviruses (CoVs) like NL63, HKU1, 229E, and OC43 were tested. IgA and IgG levels of each sample were measured separately in two assays.

Further, an avidity assay was performed to assess the antibody binding strength. S-Fuse neutralization assays and luciferase-linked immunosorbent assay (LuLISA) were performed. To estimate/predict neutralization titers, random forest regression models were generated using multiplex and neutralization assay data to estimate/predict neutralization titers. The association between neutralization levels and observed protection from infection SARS-CoV-2 was evaluated using phases 1 and 2 immunogenicity data and phase 3 efficacy data of seven COVID-19 vaccines. This was further extended by including real-world data on vaccine effectiveness.

Findings

Overall, for 304 serum samples, the study team estimated nAb titers for different SARS-CoV-2 variants, IgA and IgG levels, and avidity to all SARS-CoV-2 and seasonal CoV antigens. Of these, 198 samples were from vaccinated subjects, and the remaining were from convalescent individuals. The highest correlation was found between anti-S IgG levels and neutralization activity. Random forest regression models revealed a strong association between relative antibody units and variant-specific neutralization titers.

Neutralizing titers against SARS-CoV-2 variants could be predicted by measuring nAb titers against ancestral strain and adjusting for the fold reduction in nAb titers between SARS-CoV-2 variants. The associations between neutralizing titers between ancestral SARS-CoV-2, Delta, and Omicron variants were determined using censored linear regression models. The researchers found a 62% and 97.7% decrease in neutralization activity against Delta and Omicron variants, respectively, relative to the ancestral strain.

The COVID-Oise cohort established during Winter 2020 had two follow-up sessions (during Spring and Winter) in 2021. Overall, 905 participants enrolled in these sessions, and 2582 samples were obtained. By the third session (in December 2021), 87% of the participants had been vaccinated with at least one dose. All these samples were analyzed using the multiplex assay. They observed that 36% of the samples tested positive in April 2020, which increased to 47% by November 2021.

The risk of COVID-19 and severe disease was lower upon multiple vaccinations and prior infection history than in immunologically naïve individuals. The team observed a 42% reduced risk for infection with SARS-CoV-2 Delta among convalescents and 96% among triple-vaccinated subjects. Immunologically naïve subjects had lower protection against COVID-19 and severe disease by SARS-CoV-2 Delta, whereas vaccinated and convalescents had further reduced risks to infection and severe clinical course.

Among the subjects with vaccine-induced immunity alone, 35% were under-protected against symptomatic disease due to Delta infection after a single vaccination. This further decreased to 14% following the second dose and 11% after the third vaccination. Among those with hybrid (infection- and vaccine-induced) immunity, 1% were under-protected after a single dose, 5% after two doses, and 3% after the third dose.

Moreover, the oldest age group had the most significant reduction in risk of COVID-19, partly attributable to the extensive and prioritized vaccination coverage before other age groups.

Conclusions

The present study demonstrated a novel approach wherein seroprevalence estimates could be translated to reflect protection estimates. Consistent with previous reports, the team found that people with hybrid immunity are better protected than double vaccinated individuals. The authors could not estimate protection against disease due to SARS-CoV-2 Omicron due to a lack of validated correlations of protection, though they could indirectly assess neutralization titers against it.

Moreover, these inferred estimates might not represent the current French population which has seen a substantial number of Omicron infections since its emergence. Nonetheless, the researchers indicated that the assay could be readily extrapolated by including antigens from SARS-CoV-2 Omicron or other relevant variants.

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
Tarun Sai Lomte

Written by

Tarun Sai Lomte

Tarun is a writer based in Hyderabad, India. He has a Master’s degree in Biotechnology from the University of Hyderabad and is enthusiastic about scientific research. He enjoys reading research papers and literature reviews and is passionate about writing.

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