PREreview of Specific long-term changes in anti-SARS-CoV-2 IgG modifications and antibody functions in mRNA, adenovector, and protein subunit vaccines

Review of “Sebastian Reinig, Kou-Chin, Chia-Chun Wu, Sheng-Yu Huang, Jau Song Yu, & Shin-ru Shih. (2023). Anti-SARS-CoV-2 IgG profile of protein subunit, adenovector and mRNA vaccines. medRxiv, 2023.06.16.23291455. https://doi.org/10.1101/2023.06.16.23291455”

This review was written collaboratively by undergraduates at Mount Holyoke College (MA, USA) who selected this preprint for an assignment in a course on vaccine development taught by Dr. Rebeccah S. Lijek, Assistant Professor of Biological Sciences. Student-reviewers who give their permission to list their names are: Mariam Baig, Shannon Breen, Olivia Chiu, Madison Dresler, Celeste Keep, Rachael Larson, Dina Markovich-Koyfman, Emily Mock, Kim Sawyer-Wheeler, Madigan Stichter, Zoe Wolfel

Disclosures: The reviewers acknowledge a limitation of their review is that some of the glycosylation methodology was beyond the scope of their expertise, being undergraduate students and not practicing vaccinologists. We thank the authors for sharing their manuscript as a preprint.

COI: The review authors declare no conflict of interest and have no personal or financial relationship with the study's authors.

Summary

The objective of this research was to compare the anti-spike IgG profiles of 41 Taiwanese individuals who received various SARS-CoV-2 vaccines: the Taiwanese protein subunit vaccine from Medigen, the adenovirus vectored vaccine from AstraZeneca, and the mRNA vaccines from BNT and Moderna. IgG subclass and glycosylation was examined by ELISA and LC-MS/MS. The researchers found that the anti-spike IgG subclass distribution is IgG1 and IgG3 dominated, which is similar amongst the different vaccines. mRNA vaccines were found to induce higher galactosylation and sialylation on IgG when compared to non-mRNA vaccines. A clearer articulation of the relevance of these findings would benefit the manuscript. Overall, this study provides novel and useful information to better understand the immune responses to different SARS-CoV-2 vaccine platforms, in particular the Taiwanese Medigen protein subunit vaccine and how it compares to the more widely available AZ, Moderna, and BNT vaccines. Limitations in the study design suggest that further edits and proofreading would benefit this manuscript prior to publication. 

Strengths

• This study provides novel information about the IgG profile of the Medigen subunit vaccine. We appreciate the comparison to the globally relevant mRNA vaccines and adenovectored vaccine, which provides a more complete picture of the vaccine landscape.

• The methods that were selected (ELISA, LC-MS/MS) were appropriate for the research questions. The authors described the methods sufficiently so that they could be repeated. 

• Pre-vaccine serum as baseline serum was collected before the experiment.

• The authors' interpretation of the data aligns with our interpretation of the data from the figures. In addition, the authors choice of which results to highlight in the text aligned with our interpretation of the major take home messages from the figures. 

• The discussion section illustrates some of the limitations and areas of improvement of the study very clearly and mentions how future research could address these shortcomings. For example, we appreciated how the authors mention that the observation period for their current data is too short for the slight increase in anti-S IgG4 to be considered statistically significant. It was also important to mention the major confounding factor that people in their study could have previously been infected with COVID-19, which shows up in the analysis of the IgG antibodies. 

• These findings were consistent with previous research on COVID-19 and subunit protein vaccines against other viruses like Hepatitis B. Specifically, the results aligned with previous findings comparing Astrazeneca and mRNA vaccines - where Astrazeneca recipients exhibited reduced galactosylation and sialylation. The discussion section was well-cited and showed that these findings are consistent with how we expect these vaccines to behave. 

Major Critiques

• A hypothesis is never explicitly stated in the manuscript and so it is difficult to understand the justification for why this research is important. The manuscript would benefit from a clear hypothesis about which vaccine would be more effective at inducing an antibody response, or what the IgG subclass and glycosylation differences might be, and why these are valuable to know. The discussion could then include a comparison of the results to the hypothesis & justification stated in the introduction section. 

• The methods section states that the sera were collected between 14 and 157 days after immunization. This is a major limitation of the study design and analysis, since antibody levels can significantly change over this broad period of time, and fucosylation levels can decrease soon after vaccination. To address this weakness, the authors should justify why the sample collection dates have such a wide range and provide evidence that highly variable sampling time does not impact the study conclusions. 

• Another limitation is that it is not clear whether participants were tested for prior SARS-CoV-2 infection, which would introduce a new variable with significant impact on the metrics being studied (anti-Spike IgG profiles). Though the results section states that sera came from “41 Taiwanese people who had not been exposed to the disease before receiving the immunization,” the statement in the results section that the samples were collected prior to April 2022 is not enough to rule out prior infection. The authors mention obtaining “pre-vaccine sera of seronegative individuals” though this critical set of controls is not shown in the dataset. If sera are available prior to vaccination, it would be important to test those for pre-existing antibodies and include that data clearly in the manuscript. The authors could consider doing ELISAs for anti-NC antibodies to determine whether individuals experienced viral infection (vs. anti-spike antibodies alone from the vaccination.) If these data cannot be added, then the manuscript should be edited to specify that the prior infection status is unknown and explain the limitations that would cause. If medical records are available, the authors could state that these patients had not reported experiencing COVID-19 disease, if true.

• The statistical comparisons are confusing and require further explanation. Please add text in the figure legends that explains which tests are being used to generate the comparisons on the graphs and how the data are being binned. It is not clear whether there is a control group, e.g. pre-sera of the same individuals, see bullet point above requesting these data. The study would benefit from the inclusion of sera from unvaccinated but infected individuals if that was available. 

Minor Critiques

• The reader would benefit from further explanation of the formulation of the Medigen vaccine and justification for studying it (e.g. providing data and context for how widely it is being used in Taiwan and beyond). Similarly, more information about how IgG galactosylation, sialylation, and fucosylation impacts downstream antibody function would better justify the choice of doing these analyses. 

• The readability and flow of the figures could be improved, especially because the graphs in Figures 2 and 3 are very small. The labels for Fig. 2 and 3 are inconsistent between the Figures themselves and as referenced in the results section and figure legends. Readability may be improved by condensing some of the graphs within Fig. 2 and 3 as well, which would allow them to be larger: for example, in Fig. 2, graphs D1-D4 could be condensed into one graph. Another suggestion is to make the graphs of IgG fold changes by vaccine groups supplemental figures instead of part of Fig 2.

• A supplemental table that clarified the participant demographics (e.g. age, time of sera collection post vaccination, previous COVID-19 infection) would be useful, especially if the raw data were provided for each participant. 

• The manuscript would benefit from proofreading for spelling and grammatical errors.

Competing interests

The author declares that they have no competing interests.