CD177, a specific marker of neutrophil activation, is associated with coronavirus disease 2019 severity and death

  1. Yves Lévy
  2. Aurélie Wiedemann
  3. Boris P. Hejblum
  4. Mélany Durand
  5. Cécile Lefebvre
  6. Mathieu Surénaud
  7. Christine Lacabaratz
  8. Matthieu Perreau
  9. Emile Foucat
  10. Marie Déchenaud
  11. Pascaline Tisserand
  12. Fabiola Blengio
  13. Benjamin Hivert
  14. Marine Gauthier
  15. Minerva Cervantes-Gonzalez
  16. Delphine Bachelet
  17. Cédric Laouénan
  18. Lila Bouadma
  19. Jean-François Timsit
  20. Yazdan Yazdanpanah
  21. Giuseppe Pantaleo
  22. Hakim Hocini
  23. Rodolphe Thiébaut

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Abstract

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  1. Version published to 10.1016/j.isci.2021.102711
  2. ScreenIT

    SciScore for 10.1101/2020.12.12.20246934: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics approval was given on February 5th by the French Ethics Committee CPP-Ile-de-France VI (ID RCB: 2020-A00256-33).
    Consent: The study was conducted with the understanding and the consent of each participant or its surrogate covering the sampling, storage, and use of biological samples.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    γδ T cells were identified using an anti-TCR γδ antibody.
    anti-TCR
    suggested: None
    Software and Algorithms
    SentencesResources
    FlowJo software version 9.9.6
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Transcript reads were aligned to the hg18 human reference genome using Salmon v0.8.2 69 and quantified relative to annotation model “hsapiens_gene_ensembl” recovered from the R package biomaRt v2.42.1 70.
    Salmon
    suggested: (Salmon, RRID:SCR_017036)
    biomaRt
    suggested: (biomaRt, RRID:SCR_019214)
    Quality control of the alignment was performed via MultiQC v1.4 69.
    MultiQC
    suggested: (MultiQC, RRID:SCR_014982)
    Pathway analyses of the genes involved in each comparison was performed using Ingenuity Pathway Analysis (IPA ®, Qiagen, Redwood City, California, Version 57662101, 2020).
    Ingenuity Pathway Analysis
    suggested: (Ingenuity Pathway Analysis, RRID:SCR_008653)
    URL: https://www.R-project.org/ Data availability: RNA sequencing data that support the findings of this study will be deposited in the Gene Expression Omnibus (GEO) repository.
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)

    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: We detected the following sentences addressing limitations in the study:
    One limitation of our study was that we did not repeat the RNA-seq analyses in these specific groups of patients. Nonetheless, it is noteworthy that these groups differed significantly by the time from disease onset. These findings provide clues in our understanding of the wide range of profiles previously described for COVID-19 by showing that these patterns may be mainly related to time-dependent changes in the blood during the course of the infection 15,64. For example, the observed lower abundance of IFN signaling genes in the last group of COVID-19 patients may be due to decreased abundance in more advanced disease and/or patients who constitutively present a lower abundance of ISG, as described in previous studies 65. Several months after the emergence of this new disease, treatment options for patients with severe disease requiring hospitalization are still limited to corticosteroids, which has emerged as the treatment of choice for critically ill patients 66,67. However, interventions that can be administered early during the course of infection to prevent disease progression and longer-term complications are urgently needed. A major obstacle for the design of “adapted” therapies to the various stages of disease evolution is a lack of markers associated with sudden worsening of the disease of patients with moderate to severe disease and markers to predict improvement. Our results show that the measurement of CD177 during the course of the disease may be helpful in fol...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04262921RecruitingFrench COVID Cohort

    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 10.1101/2020.12.12.20246934v1 on medRxiv