Effect of Different Disease-Modifying Therapies on Humoral Response to BNT162b2 Vaccine in Sardinian Multiple Sclerosis Patients

  1. Maristella Pitzalis
  2. Maria Laura Idda
  3. Valeria Lodde
  4. Annalisa Loizedda
  5. Monia Lobina
  6. Magdalena Zoledziewska
  7. Francesca Virdis
  8. Giuseppe Delogu
  9. Federica Pirinu
  10. Maria Giuseppina Marini
  11. Maura Mingoia
  12. Jessica Frau
  13. Lorena Lorefice
  14. Marzia Fronza
  15. Daniele Carmagnini
  16. Elisa Carta
  17. Valeria Orrù
  18. Sergio Uzzau
  19. Paolo Solla
  20. Federica Loi
  21. Marcella Devoto
  22. Maristella Steri
  23. Edoardo Fiorillo
  24. Matteo Floris
  25. Ignazio Roberto Zarbo
  26. Eleonora Cocco
  27. Francesco Cucca

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Abstract

Vaccination against COVID-19 is highly recommended to patients affected by multiple sclerosis (MS); however, the impact of MS disease-modifying therapies (DMTs) on the immune response following vaccination has been only partially investigated. Here, we aimed to elucidate the effect of DMTs on the humoral immune response to mRNA-based anti-SARS-CoV-2 vaccines in MS patients.

Methods

We obtained sera from 912 Sardinian MS patients and 63 healthy controls 30 days after the second dose of BNT162b2 vaccine and tested them for SARS-CoV-2 response using anti-Spike (S) protein-based serology. Previous SARS-CoV-2 infection was assessed by anti-Nucleocapsid (N) serology. Patients were either untreated or undergoing treatment with a total of 13 different DMTs. Differences between treatment groups comprised of at least 10 patients were assessed by generalized linear mixed-effects model. Demographic and clinical data and smoking status were analyzed as additional factors potentially influencing humoral immunity from COVID-19 vaccine.

Results

MS patients treated with natalizumab, teriflunomide, azathioprine, fingolimod, ocrelizumab, and rituximab showed significantly lower humoral responses compared to untreated patients. We did not observe a statistically significant difference in response between patients treated with the other drugs (dimethyl fumarate, interferon, alemtuzumab and glatiramer acetate) and untreated patients. In addition, older age, male sex and active smoking were significantly associated with lower antibody titers against SARS-CoV-2. MS patients previously infected with SARS-CoV-2 had significantly higher humoral responses to vaccine than uninfected patients.

Conclusion

Humoral response to BNT162b2 is significantly influenced by the specific DMTs followed by patients, as well as by other factors such as previous SARS-CoV-2 infection, age, sex, and smoking status. These results are important to inform targeted strategies to prevent clinically relevant COVID-19 in MS patients.

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  1. Version published to 10.3389/fimmu.2021.781843
  2. ScreenIT

    SciScore for 10.1101/2021.09.26.21264067: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: Ethics and data collection: The study was approved by the local Ethical Review Boards prot.
    Consent: All enrolled individuals provided written informed consent.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Detection of anti-SARS-CoV-2-S and anti-SARS-CoV-2-N antibodies in serum samples was performed using the electrochemiluminescence immunoassays Elecsys® Anti-SARS-CoV-S and Elecsys® Anti-SARS-CoV-N (Roche) on the automated Cobas e-411 analyzer, according to the manufacturer’s instructions.
    anti-SARS-CoV-2-S
    suggested: None
    anti-SARS-CoV-2-N
    suggested: None
    Anti-SARS-CoV-N
    suggested: None
    Considering the nature of the outcome (Anti-S, non-negative count data), differences between groups of patients defined by therapy and negative to Anti-N antibody, were assessed by a negative binomial generalized linear mixed-effects model; the contribution of age, sex, Expanded Disability Status Scale (EDSS), disease duration, previous SARS-CoV-2 infection, and the clinical sampling center were also analyzed.
    Anti-S
    suggested: None
    Anti-N
    suggested: None

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  3. Version published to 10.1101/2021.09.26.21264067v1 on medRxiv