SARS-CoV-2 specific T cell responses are lower in children and increase with age and time after infection

  1. Carolyn A. Cohen
  2. Athena P. Y. Li
  3. Asmaa Hachim
  4. David S. C. Hui
  5. Mike Y. W. Kwan
  6. Owen T. Y. Tsang
  7. Susan S. Chiu
  8. Wai Hung Chan
  9. Yat Sun Yau
  10. Niloufar Kavian
  11. Fionn N. L. Ma
  12. Eric H. Y. Lau
  13. Samuel M. S. Cheng
  14. Leo L. M. Poon
  15. Malik Peiris
  16. Sophie A. Valkenburg

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Abstract

SARS-CoV-2 infection of children leads to a mild illness and the immunological differences with adults are unclear. Here, we report SARS-CoV-2 specific T cell responses in infected adults and children and find that the acute and memory CD4 + T cell responses to structural SARS-CoV-2 proteins increase with age, whereas CD8 + T cell responses increase with time post-infection. Infected children have lower CD4 + and CD8 + T cell responses to SARS-CoV-2 structural and ORF1ab proteins when compared with infected adults, comparable T cell polyfunctionality and reduced CD4 + T cell effector memory. Compared with adults, children have lower levels of antibodies to β-coronaviruses, indicating differing baseline immunity. Total T follicular helper responses are increased, whilst monocyte numbers are reduced, indicating rapid adaptive co-ordination of the T and B cell responses and differing levels of inflammation. Therefore, reduced prior β-coronavirus immunity and reduced T cell activation in children might drive milder COVID-19 pathogenesis.

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  1. Version published to 10.1038/s41467-021-24938-4
  2. ScreenIT

    SciScore for 10.1101/2021.02.02.21250988: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the institutional review board of the respective hospitals, viz.
    Consent: All of patients provided informed consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Cells were stained with Zombie-NIR (all antibodies from Biolegend and clone used) followed by anti-human CD3-PE/Dazzle 594 (UCHT1), CD4-BV605 (OKT4), CD8-AlexaFluor700 (SK1), CD107a-PacificBlue (H4A3), CCR5-PE (J418F1), CCR7-PerCP/Cy5.5 (G043H7) and CD45RA-APC (HI100) and a dump channel containing CD19-BV510 (HIB19), CD56- BV510 (HCD56) and CD14-BV510 (M5E2).
    anti-human CD3-PE/Dazzle 594
    suggested: None
    UCHT1
    suggested: (BD Biosciences Cat# 563109, RRID:AB_2732053)
    CD4-BV605
    suggested: None
    CD8-AlexaFluor700
    suggested: None
    CCR5-PE
    suggested: None
    CCR7-PerCP/Cy5.5
    suggested: None
    CD45RA-APC
    suggested: None
    HIB19
    suggested: (BD Biosciences Cat# 740164, RRID:AB_2739917)
    CD56-
    suggested: None
    BV510
    suggested: (BioLegend Cat# 318339, RRID:AB_2561385)
    CD14-BV510
    suggested: None
    Software and Algorithms
    SentencesResources
    Stained cells were acquired via flow cytometry (AttuneNxT) and analysed by FlowJo v10
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Statistical Analysis: Statistical analysis was performed on Prism 9 (Graphpad).
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)

    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.

  3. Version published to 10.1101/2021.02.02.21250988v1 on medRxiv