Impaired Cytotoxic CD8 + T Cell Response in Elderly COVID-19 Patients

  1. Jaana Westmeier
  2. Krystallenia Paniskaki
  3. Zehra Karaköse
  4. Tanja Werner
  5. Kathrin Sutter
  6. Sebastian Dolff
  7. Marvin Overbeck
  8. Andreas Limmer
  9. Jia Liu
  10. Xin Zheng
  11. Thorsten Brenner
  12. Marc M. Berger
  13. Oliver Witzke
  14. Mirko Trilling
  15. Mengji Lu
  16. Dongliang Yang
  17. Nina Babel
  18. Timm Westhoff
  19. Ulf Dittmer
  20. Gennadiy Zelinskyy

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Abstract

Cytotoxic T cells are responsible for the elimination of infected cells and are key players in the control of viruses. CD8 + T cells with an effector phenotype express cytotoxic molecules and are able to perform target cell killing. COVID-19 patients with a mild disease course were analyzed for the differentiation status and cytotoxic profile of CD8 + T cells. SARS-CoV-2 infection induced a vigorous cytotoxic CD8 + T cell response. However, this cytotoxic profile of T cells was not detected in COVID-19 patients over the age of 80 years. Thus, the absence of a cytotoxic response in elderly patients might be a possible reason for the more frequent severity of COVID-19 in this age group than in younger patients.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.21.262329: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Written consent was obtained from each of the study participants.
    IACUC: The study was approved by the University Hospital Essen’s ethical committee (ethics vote 20-9216-BO).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    For the surface staining of human cells, specific antibodies against human CD3 (OKT3, BioLegend), CD4 (OKT4, BioLegend), CD8 (BW135/80, Miltenyi Biotec), CD45RO (UCHL1, BioLegend), CCR7 (G043H7, BioLegend), CD28 (CD28.2, BioLegend), and PD-1 (EH12.2 H7, BioLegend) were used.
    human CD3
    suggested: None
    OKT3
    suggested: None
    CD4
    suggested: None
    OKT4
    suggested: None
    CD8
    suggested: None
    CD45RO
    suggested: None
    UCHL1
    suggested: None
    CCR7
    suggested: None
    G043H7
    suggested: None
    CD28
    suggested: None
    CD28.2
    suggested: None
    PD-1
    suggested: None
    For intracellular staining antibodies against human GzmA (CB9, BioLegend), GzmB (QA16A02, BioLegend) and perforin (B-D48, BioLegend) were used.
    CB9
    suggested: None
    QA16A02
    suggested: None
    Software and Algorithms
    SentencesResources
    Analyses were done using FACSDiva software (Becton Dickinson) and FlowJo software (Becton Dickinson).
    FACSDiva
    suggested: (BD FACSDiva Software, RRID:SCR_001456)
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    A Pearson correlation coefficient was used for the definition of correlation. (GraphPad Prism software; GraphPad Software Inc.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • No funding statement was detected.
    • 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 10.1128/mbio.02243-20
  3. Version published to 10.1101/2020.08.21.262329v1 on bioRxiv