A sex-biased imbalance between Tfr, Tph, and atypical B cells determines antibody responses in COVID-19 patients

  1. Jonas Nørskov Søndergaard
  2. Janyerkye Tulyeu
  3. Ryuya Edahiro
  4. Yuya Shirai
  5. Yuta Yamaguchi
  6. Teruaki Murakami
  7. Takayoshi Morita
  8. Yasuhiro Kato
  9. Haruhiko Hirata
  10. Yoshito Takeda
  11. Daisuke Okuzaki
  12. Shimon Sakaguchi
  13. Atsushi Kumanogoh
  14. Yukinori Okada
  15. James Badger Wing

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Abstract

Sex-biased humoral immune responses to COVID-19 patients have been observed, but the cellular basis for this is not understood. Using single-cell proteomics by mass cytometry, we find disrupted regulation of humoral immunity in COVID-19 patients, with a sex-biased loss of circulating follicular regulatory T cells (cTfr) at a significantly greater rate in male patients. In addition, a male sex-associated cellular network of T-peripheral helper, plasma blasts, proliferating and extrafollicular/atypical CD11c + memory B cells was strongly positively correlated with neutralizing antibody concentrations and negatively correlated with cTfr frequency. These results suggest that sex-specific differences to the balance of cTfr and a network of extrafollicular antibody production-associated cell types may be a key factor in the altered humoral immune responses between male and female COVID-19 patients.

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  1. Version published to 10.1073/pnas.2217902120
  2. ScreenIT

    SciScore for 10.1101/2022.01.06.22268711: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: All participants provided written informed consent as approved by the ethical committees of Osaka University Graduate School of Medicine, and affiliated institutes
    IRB: All participants provided written informed consent as approved by the ethical committees of Osaka University Graduate School of Medicine, and affiliated institutes
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Mass cytometry data analysis: For analysis of the mass cytometry results, gating and de-barcoding was performed manually using Cytobank software (Beckman Coulter).
    Cytobank
    suggested: (Cytobank, RRID:SCR_014043)
    All dual count data channels were arcsinh-transformed (co-factor: 5) then compensated by the CATALYST R package preprocessing workflow (1.14.0) 72 in R (4.0.3).
    CATALYST
    suggested: (CATALYST, RRID:SCR_017127)
    Analysis of data was primarily performed as in “CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets” version 4 73 as implemented in the CATALYST R package (1.14.0) with packages cowplot (v1.1.1), flowCore (2.2.0), diffcyt (1.10.0), scater (1.18.3), SingleCellExperiment (1.12.0), ggplot2 (3.3.3).
    cowplot
    suggested: (cowplot, RRID:SCR_018081)
    flowCore
    suggested: (flowCore, RRID:SCR_002205)
    All cells were clustered by FlowSOM in the CATALYST R package with both x-dim and y-dim set to 10 to provide 100 initial SOM clusters and the consensus meta-clustering level varying from 50 to 20 in line with the expected complexity of the population.
    FlowSOM
    suggested: (FlowSOM, RRID:SCR_016899)
    Contours were added by ggplot2 (3.3.3) and RColorBrewer (1.1-2).
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Differential cluster abundance analysis by edgeR was performed with diffcyt (v1.10.0) 74 as implemented in the CATALYST R package (v1.14.0)
    edgeR
    suggested: (edgeR, RRID:SCR_012802)
    Line graphs and Spearman correlation analysis in Fig. 5B, 5C and 6C were performed in GraphPad prism (9.2).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Network diagrams: Network diagrams of correlations were produced in Gephi software (0.9.2).
    Gephi
    suggested: (Gephi, RRID:SCR_004293)
    Figure arrangement: Final figures were arranged in Adobe Illustrator (26.0.1)
    Adobe Illustrator
    suggested: (Adobe Illustrator, RRID:SCR_010279)

    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.
    • Thank you for including a protocol registration statement.

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

    About SciScore

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  3. Version published to 10.1101/2022.01.06.22268711v1 on medRxiv