Whole blood immunophenotyping uncovers immature neutrophil-to-VD2 T-cell ratio as an early marker for severe COVID-19

  1. Guillaume Carissimo
  2. Weili Xu
  3. Immanuel Kwok
  4. Mohammad Yazid Abdad
  5. Yi-Hao Chan
  6. Siew-Wai Fong
  7. Kia Joo Puan
  8. Cheryl Yi-Pin Lee
  9. Nicholas Kim-Wah Yeo
  10. Siti Naqiah Amrun
  11. Rhonda Sin-Ling Chee
  12. Wilson How
  13. Stephrene Chan
  14. Bingwen Eugene Fan
  15. Anand Kumar Andiappan
  16. Bernett Lee
  17. Olaf Rötzschke
  18. Barnaby Edward Young
  19. Yee-Sin Leo
  20. David Chien Lye
  21. Laurent Renia
  22. Lai Guan Ng
  23. Anis Larbi
  24. Lisa FP Ng

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Abstract

SARS-CoV-2 is the novel coronavirus responsible for the current COVID-19 pandemic. Severe complications are observed only in a small proportion of infected patients but the cellular mechanisms underlying this progression are still unknown. Comprehensive flow cytometry of whole blood samples from 54 COVID-19 patients reveals a dramatic increase in the number of immature neutrophils. This increase strongly correlates with disease severity and is associated with elevated IL-6 and IP-10 levels, two key players in the cytokine storm. The most pronounced decrease in cell counts is observed for CD8 T-cells and VD2 γδ T-cells, which both exhibit increased differentiation and activation. ROC analysis reveals that the count ratio of immature neutrophils to VD2 (or CD8) T-cells predicts pneumonia onset (0.9071) as well as hypoxia onset (0.8908) with high sensitivity and specificity. It would thus be a useful prognostic marker for preventive patient management and improved healthcare resource management.

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  1. Version published to 10.1038/s41467-020-19080-6
  2. ScreenIT

    SciScore for 10.1101/2020.06.11.147389: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Ethics statement: Written informed consent was obtained from participants in accordance with the tenets of the Declaration of Helsinki.
    RandomizationRandomization: No randomization was done.
    Blindingnot detected.
    Power AnalysisSample Size: No power analysis was done.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    For COVID-19 blood/plasma collection, “A Multi-centred Prospective Study to Detect Novel Pathogens and Characterize Emerging Infections (The PROTECT study group)”, a domain specific review board (DSRB) evaluated the study design and protocol, which was approved under study number 2012/00917.
    PROTECT
    suggested: (ProTECT, RRID:SCR_004531)
    Data analysis was done on Bio-Plex ManagerTM 6.1.1 (Bio-Rad).
    Bio-Plex
    suggested: None
    Samples were then acquired using BD LSRII 5 laser configuration using automatic compensations and running BD FACS Diva Software version 8.0.1 (build 2014 07 03 11 47),
    BD FACS Diva
    suggested: (Resource Identification Portal, RRID:SCR_004098)
    Analysis of flow cytometric data was performed with FlowJo version 10.6.1.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Samples were then used for UMAP analysis using cytofkit2 R Packages with RStudio v3.5.2 56.
    RStudio
    suggested: (RStudio, RRID:SCR_000432)

    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 10.1101/2020.06.11.147389v1 on bioRxiv