Lymphopenia-induced T cell proliferation is a hallmark of severe COVID-19

  1. Sarah Adamo
  2. Stéphane Chevrier
  3. Carlo Cervia
  4. Yves Zurbuchen
  5. Miro E. Raeber
  6. Liliane Yang
  7. Sujana Sivapatham
  8. Andrea Jacobs
  9. Esther Bächli
  10. Alain Rudiger
  11. Melina Stüssi-Helbling
  12. Lars C. Huber
  13. Dominik J. Schaer
  14. Bernd Bodenmiller
  15. Onur Boyman
  16. Jakob Nilsson

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Abstract

Coronavirus disease 2019 (COVID-19), caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has a broad clinical presentation ranging from asymptomatic infection to fatal disease. Different features associated with the immune response to SARS-CoV-2, such as hyperinflammation and reduction of peripheral CD8 + T cell counts are strongly associated with severe disease. Here, we confirm the reduction in peripheral CD8 + T cells both in relative and absolute terms and identify T cell apoptosis and migration into inflamed tissues as possible mechanisms driving peripheral T cell lymphopenia. Furthermore, we find evidence of elevated serum interleukin-7, thus indicating systemic T cell paucity and signs of increased T cell proliferation in patients with severe lymphopenia. Following T cell lymphopenia in our pseudo-longitudinal time course, we observed expansion and recovery of poly-specific antiviral T cells, thus arguing for lymphopenia-induced T cell proliferation. In summary, this study suggests that extensive T cell loss and subsequent T cell proliferation are characteristic of severe COVID-19.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.04.236521: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Both hospitalized patients and outpatients were recruited into the study and all participants gave written informed consent.
    IRB: The study was approved by the Cantonal Ethics Committee of Zurich (BASEC
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data were acquired on a Navios flow cytometer and analyzed using the Kaluza software.
    Kaluza
    suggested: (Kaluza, RRID:SCR_016182)
    Data were analyzed with the Flow-jo software.
    Flow-jo
    suggested: None
    Analyses were performed with R (version 4.0.0) and with Graph Pad Prism.
    Graph Pad 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 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 10.1101/2020.08.04.236521v1 on bioRxiv