Multiple sclerosis therapies differentially affect SARS-CoV-2 vaccine–induced antibody and T cell immunity and function

  1. Joseph J. Sabatino
  2. Kristen Mittl
  3. William M. Rowles
  4. Kira McPolin
  5. Jayant V. Rajan
  6. Matthew T. Laurie
  7. Colin R. Zamecnik
  8. Ravi Dandekar
  9. Bonny D. Alvarenga
  10. Rita P. Loudermilk
  11. Chloe Gerungan
  12. Collin M. Spencer
  13. Sharon A. Sagan
  14. Danillo G. Augusto
  15. Jessa R. Alexander
  16. Joseph L. DeRisi
  17. Jill A. Hollenbach
  18. Michael R. Wilson
  19. Scott S. Zamvil
  20. Riley Bove

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Abstract

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  1. Version published to 10.1172/jci.insight.156978
  2. ScreenIT

    SciScore for 10.1101/2021.09.10.21262933: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: All enrolled participants provided written, informed consent for this study, which was approved by the UCSF Committee on Human Research (IRB# 21-33240).
    IRB: All enrolled participants provided written, informed consent for this study, which was approved by the UCSF Committee on Human Research (IRB# 21-33240).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Samples were incubated for 1 hour at room temperature, washed, and stained with 1:2000 anti-human IgG Fc antibody PE (BioLegend #637310) in PBST for 30 minutes at room temperature.
    anti-human IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Flow cytometry analysis was completed using FlowJo (BD).
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Enriched libraries were analyzed in BioAnalyzer (Agilent) and quantified by digital-droplet PCR.
    BioAnalyzer
    suggested: (BioAnalyzer 2100, RRID:SCR_019715)

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.09.10.21262933v1 on medRxiv