High levels of SARS-CoV-2–specific T cells with restricted functionality in severe courses of COVID-19

  1. David Schub
  2. Verena Klemis
  3. Sophie Schneitler
  4. Janine Mihm
  5. Philipp M. Lepper
  6. Heinrike Wilkens
  7. Robert Bals
  8. Hermann Eichler
  9. Barbara C. Gärtner
  10. Sören L. Becker
  11. Urban Sester
  12. Martina Sester
  13. Tina Schmidt

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

Patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) differ in the severity of disease. We hypothesized that characteristics of SARS-CoV-2–specific immunity correlate with disease severity.

METHODS

In this study, SARS-CoV-2–specific T cells and antibodies were characterized in uninfected controls and patients with different coronavirus disease 2019 (COVID-19) disease severity. SARS-CoV-2–specific T cells were flow cytometrically quantified after stimulation with SARS-CoV-2 peptide pools and analyzed for expression of cytokines (IFN-γ, IL-2, and TNF-α) and markers for activation, proliferation, and functional anergy. SARS-CoV-2–specific IgG and IgA antibodies were quantified using ELISA. Moreover, global characteristics of lymphocyte subpopulations were compared between patient groups and uninfected controls.

RESULTS

Despite severe lymphopenia affecting all major lymphocyte subpopulations, patients with severe disease mounted significantly higher levels of SARS-CoV-2–specific T cells as compared with convalescent individuals. SARS-CoV-2–specific CD4 + T cells dominated over CD8 + T cells and closely correlated with the number of plasmablasts and SARS-CoV-2–specific IgA and IgG levels. Unlike in convalescent patients, SARS-CoV-2–specific T cells in patients with severe disease showed marked alterations in phenotypical and functional properties, which also extended to CD4 + and CD8 + T cells in general.

CONCLUSION

Given the strong induction of specific immunity to control viral replication in patients with severe disease, the functionally altered characteristics may result from the need for contraction of specific and general immunity to counteract excessive immunopathology in the lung.

FUNDING

The study was supported by institutional funds to MS and in part by grants of Saarland University, the State of Saarland, and the Rolf M. Schwiete Stiftung.

Article activity feed

  1. Version published to 10.1172/jci.insight.142167
  2. ScreenIT

    SciScore for 10.1101/2020.07.08.20148718: (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 ethics committee of the Ärztekammer des Saarlandes (references 76/20; l62/20) and all individuals or their legal representatives gave written informed consent.
    Consent: The study was approved by the ethics committee of the Ärztekammer des Saarlandes (references 76/20; l62/20) and all individuals or their legal representatives gave written informed consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Quantitation of lymphocyte populations: Quantitation and characterization of lymphocyte subpopulations was performed on 100 µL of heparinized whole blood as described before 36 using monoclonal antibodies towards CD3 (clone SK7), CD4 (clone SK3), CD8 (clone RPA-T8 and SK1), CD16 (clone 3G8), CD19 (clone HIB19), CD27 (clone L128), CD38 (clone HB7), CD56 (clone B159), cytotoxic T lymphocyte antigen 4 (CTLA-4, clone BNI3), IgD (clone IA6-2) and programmed cell death 1 (PD-1, clone MIH4, all from BD Biosciences).
    CD4
    suggested: (BD Biosciences Cat# 557939, RRID:AB_2802162)
    CD8
    suggested: (BD Biosciences Cat# 557939, RRID:AB_2802162)
    CD16
    suggested: (BD Biosciences Cat# 557939, RRID:AB_2802162)
    CD19
    suggested: (BD Biosciences Cat# 557939, RRID:AB_2802162)
    CD38
    suggested: (RayBiotech Cat# CS-11-0123, RRID:AB_1228026)
    CTLA-4
    suggested: None
    IgD
    suggested: None
    PD-1
    suggested: None
    Differentiation status of CD19-positive B-cells was assessed using antibodies against IgD and CD27.
    antibodies against IgD
    suggested: None
    CD27
    suggested: None
    NK cells were identified using antibodies towards CD3, CD16 and CD56 and quantified as CD3 negative/CD16/CD56 positive lymphocytes.
    CD3
    suggested: None
    CD56
    suggested: None
    Analysis of SARS-CoV-2 specific antibodies: SARS-CoV-2 specific antibodies were quantified from heparinized plasma samples using an IgG and IgA assay coated with recombinant S1-domain of SARS-CoV-2 spike protein antigen according to the manufacturer’s instructions (Euroimmun, Lübeck, Germany).
    SARS-CoV-2 spike protein
    suggested: None
    An unpaired non-parametric Kruskall-Wallis test with Dunn’s post test was used to analyze differences for lymphocyte subpopulations, T-cell and antibody levels as wells as PD-1, CTLA-4 and Ki67 of total T-cells among the three groups.
    PD-1, CTLA-4
    suggested: (Thermo Fisher Scientific Cat# EPX140-15803-901, RRID:AB_2576106)
    Software and Algorithms
    SentencesResources
    Statistical analysis: Statistical analysis was carried out using GraphPad Prism 8.0 software using two-tailed tests.
    GraphPad Prism
    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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 10.1101/2020.07.08.20148718 on medRxiv