Profound Treg perturbations correlate with COVID-19 severity

  1. Silvia Galván-Peña
  2. Juliette Leon
  3. Kaitavjeet Chowdhary
  4. Daniel A. Michelson
  5. Brinda Vijaykumar
  6. Liang Yang
  7. Angela M. Magnuson
  8. Felicia Chen
  9. Zachary Manickas-Hill
  10. Alicja Piechocka-Trocha
  11. Daniel P. Worrall
  12. Kathryn E. Hall
  13. Musie Ghebremichael
  14. Bruce D. Walker
  15. Jonathan Z. Li
  16. Xu G. Yu
  17. MGH COVID-19 Collection & Processing Team
  18. Diane Mathis
  19. Christophe Benoist
  20. Kendall Lavin-Parsons
  21. Blair Parry
  22. Brendan Lilley
  23. Carl Lodenstein
  24. Brenna McKaig
  25. Nicole Charland
  26. Hargun Khanna
  27. Justin Margolin
  28. Anna Gonye
  29. Irena Gushterova
  30. Tom Lasalle
  31. Nihaarika Sharma
  32. Brian C. Russo
  33. Maricarmen Rojas-Lopez
  34. Moshe Sade-Feldman
  35. Kasidet Manakongtreecheep
  36. Jessica Tantivit
  37. Molly Fisher Thomas

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Abstract

Regulatory T cells (Tregs) are responsible for restraining excessive inflammation, a hallmark of COVID-19. We identified a striking phenotype in Tregs from patients with severe disease, as well as an interesting role for interleukin (IL)-6 and IL-18. An increased suppressive profile, including increased Treg proportions, combined with the expression of proinflammatory mediators, distinguished severe patients and persisted in some of those recovered. This phenotype is in notable similarity to that found in tumor-infiltrating Tregs, which are generally associated with poor prognosis, and suggests both a detrimental role for these cells in COVID-19 as well as a potential explanation for some of the still largely unexplored complications associated with recovery.

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  1. Version published to 10.1073/pnas.2111315118
  2. ScreenIT

    SciScore for 10.1101/2020.12.11.416180: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: All participants provided written informed consent in accordance with protocols approved by the Partners Institutional Review Board and the MGH Human Subjects Institutional Review Board.
    IRB: All participants provided written informed consent in accordance with protocols approved by the Partners Institutional Review Board and the MGH Human Subjects Institutional Review Board.
    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: 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: Please consider improving the rainbow (“jet”) colormap(s) used on page 20. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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 10.1101/2020.12.11.416180v2 on bioRxiv
  4. ScreenIT

    SciScore for 10.1101/2020.12.11.416180: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your data.

    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: Please consider improving the rainbow (“jet”) colormap used on page 18. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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.

  5. Version published to 10.1101/2020.12.11.416180v1 on bioRxiv