Mass cytometry and artificial intelligence define CD169 as a specific marker of SARS-CoV2-induced acute respiratory distress syndrome

  1. M. Roussel
  2. J. Ferrant
  3. F. Reizine
  4. S. Le Gallou
  5. J. Dulong
  6. S. Carl
  7. M. Lesouhaitier
  8. M. Gregoire
  9. N. Bescher
  10. C. Verdy
  11. M. Latour
  12. I. Bézier
  13. M. Cornic
  14. S. Leonard
  15. J. Feuillard
  16. V.K. Tiwari
  17. J.M. Tadié
  18. M. Cogné
  19. K. Tarte

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Abstract

Acute respiratory distress syndrome (ARDS) is the main complication of COVID-19, requiring admission to Intensive Care Unit (ICU). Despite recent immune profiling of COVID-19 patients, to what extent COVID-19-associated ARDS specifically differs from other causes of ARDS remains unknown, To address this question, we built 3 cohorts of patients categorized in COVID-19 neg ARDS pos , COVID-19 pos ARDS pos , and COVID-19 pos ARDS neg , and compared their immune landscape analyzed by high-dimensional mass cytometry on peripheral blood followed by artificial intelligence analysis. A cell signature associating S100A9/calprotectin-producing CD169 pos monocytes, plasmablasts, and Th1 cells was specifically found in COVID-19 pos ARDS pos , unlike COVID-19 neg ARDS pos patients. Moreover, this signature was shared by COVID-19 pos ARDS neg patients, suggesting severe COVID-19 patients, whatever they experienced or not ARDS, displayed similar immune dysfunctions. We also showed an increase in CD14 pos HLA-DR low and CD14 low CD16 pos monocytes correlated to the occurrence of adverse events during ICU stay. Our study demonstrates that COVID-19-associated ARDS display a specific immune profile, and might benefit from personalized therapy in addition to standard ARDS management.

One Sentence Summary

COVID-19-associated ARDS is biologically distinct from other causes of ARDS.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.22.307975: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: n°35RC20_9795_HARMONICOV, ClinicalTrials.gov Identifier: NCT04373200) and informed consent was obtained from patients in accordance with the Declaration of Helsinki.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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:
    Besides the low number of included patients, our study has some limitations. By focusing on severe patients with and without ARDS, we cannot make conclusions about phenotypic changes in mild and moderate diseases. Moreover, since the mass cytometry was conducted on PBMCs, we lack information on the neutrophil lineage, which appears affected in the COVID-19 (18). It would also be interesting to link these data with in situ data from lung tissue samples and bronchoalveolar lavages. However, our detailed analysis of circulating immune cells shows that immune monitoring of severe COVID-19 patients brings interesting prognostic biomarkers independently of their clinical classification in ARDSpos versus ARDSneg. Moreover, we demonstrated that at the biological level, COVID-19 associated ARDS is different from other causes of ARDS, and might benefit from personalized therapy in addition to standard ARDS management (18, 43).

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

    IdentifierStatusTitle
    NCT04373200RecruitingHuman Ab Response & immunoMONItoring of COVID-19 Patients

    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.

  2. Version published to 10.1101/2020.09.22.307975 on bioRxiv