COVID-19 mRNA vaccines drive differential Fc-functional profiles in pregnant, lactating, and non-pregnant women

  1. Caroline Atyeo
  2. Elizabeth A. DeRiso
  3. Christine Davis
  4. Evan A. Bordt
  5. Rose M. DeGuzman
  6. Lydia L. Shook
  7. Lael M. Yonker
  8. Alessio Fasano
  9. Babatunde Akinwunmi
  10. Douglas A. Lauffenburger
  11. Michal A. Elovitz
  12. Kathryn J. Gray
  13. Andrea G. Edlow
  14. Galit Alter

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Abstract

Significant immunological changes occur throughout pregnancy to tolerize the mother and allow growth of the fetal graft. However, additional local and systemic immunological adaptations also occur, allowing the maternal immune system to continue to protect the dyad against foreign invaders both during pregnancy and after birth through lactation. This fine balance of tolerance and immunity, along with physiological and hormonal changes, contribute to increased susceptibility to particular infections in pregnancy, including more severe COVID-19 disease. Whether these changes also make pregnant women less responsive to vaccination or induce altered immune responses to vaccination remains incompletely understood. To holistically define potential changes in vaccine response during pregnancy and lactation, we deeply profiled the humoral vaccine response in a group of pregnant and lactating women and non-pregnant age-matched controls. Vaccine-specific titers were comparable, albeit slightly lower, between pregnant and lactating women, compared to non-pregnant controls. Among pregnant women, we found higher antibody titers and functions in those vaccinated with the Moderna vaccine. FcR-binding and antibody effector functions were induced with delayed kinetics in both pregnant and lactating women compared to non-pregnant women. Antibody boosting resulted in high FcR-binding titers in breastmilk. These data point to an immune resistance to generate highly inflammatory antibodies during pregnancy and lactation, and a critical need to follow prime/boost timelines in this vulnerable population to ensure full immunity is attained.

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  1. ScreenIT

    SciScore for 10.1101/2021.04.04.438404: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Eligible women were: (n=84 pregnant; n=31 lactating; or n=16 non-pregnant and of reproductive age (18-45); greater than or equal to 18 years old, able to provide informed consent, and receiving the COVID-19 vaccine.
    IRB: The study was approved by the MGH Institutional Review Board.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableEligible women were: (n=84 pregnant; n=31 lactating; or n=16 non-pregnant and of reproductive age (18-45); greater than or equal to 18 years old, able to provide informed consent, and receiving the COVID-19 vaccine.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Antibody-dependent neutrophil phagocytosis: Antibody-dependent neutrophil phagocytosis was measured by a flow cytometry-based assay (48).
    Antibody-dependent neutrophil phagocytosis
    suggested: None
    Antibody-dependent
    suggested: None
    PE-coupled mouse anti-human detection antibodies (Southern Biotech) were used to detect antigen-specific antibody binding.
    anti-human detection antibodies (Southern Biotech)
    suggested: None
    antigen-specific
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Cell lines: THP-1 cells used in phagocytic assays were grown in RPMI media supplemented with 10% FBS, 5% penn/strep, 5% L-glutamine, 5% HEPES buffer (pH 7.2) and 0.5% 2-Mercaptoethanol, and maintained at 2.5×105 cells/ml.
    THP-1
    suggested: None
    Software and Algorithms
    SentencesResources
    Univariate statistical analysis: For univariate data analysis, statistics were run using GraphPad Prism version 8.0.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Multivariate analysis: Multivariate analyses were performed in R (version 4.0.0) and Python (version 3.9.1).
    Python
    suggested: (IPython, RRID:SCR_001658)

    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.

    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.

  2. Version published to 10.1101/2021.04.04.438404 on bioRxiv