The phenotypic changes of γδ T cells in COVID‐19 patients

  1. Lei Lei
  2. Hongbo Qian
  3. Xiaofang Yang
  4. Xingzhe Zhang
  5. Dan Zhang
  6. Tongxin Dai
  7. Rui Guo
  8. Lin Shi
  9. Yanbin Cheng
  10. Baojun Zhang
  11. Xiaobo Zhou
  12. Jinsong Hu
  13. Yaling Guo

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Abstract

A novel pneumonia‐associated respiratory syndrome named coronavirus disease‐2019 (COVID‐19), which was caused by SARS‐CoV‐2，broke out in Wuhan, China, in the end of 2019. Unfortunately, there is no specific antiviral agent or vaccine available to treat SARS‐CoV‐2 infections. The information regarding the immunological characteristics in COVID‐19 patients remains limited. Here, we collected the blood samples from 18 healthy donors (HD) and 38 COVID‐19 patients to analyze changes on γδ T cell population. In comparison with HD, the γδ T cell percentage decreased, while the activation marker CD25 expression increased in response to SARS‐CoV‐2 infection. Interestingly, the CD4 expression was upregulated in γδ T cells reflecting the occurrence of a specific effector cell population, which may serve as a biomarker for the assessment of SARS‐CoV‐2 infection.

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  1. Version published to 10.1111/jcmm.15620
  2. ScreenIT

    SciScore for 10.1101/2020.04.05.20046433: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics statement: This study was approved by the Research Ethics Commission of the Eighth Hospital of Xi’an (20190730-1346).
    Consent: All subjects signed informed consent forms upon admission to hospital.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    FlowJo 8 was used for data analysis.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Statistical analysis: The student’s t test was performed for two group analysis using GraphPad Prism 7.0 software. * and ** stands for P<0.05 and P<0.01, respectively.
    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 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 10.1101/2020.04.05.20046433v1 on medRxiv