Comparative Pathogenesis Of COVID-19, MERS And SARS In A Non-Human Primate Model

  1. Barry Rockx
  2. Thijs Kuiken
  3. Sander Herfst
  4. Theo Bestebroer
  5. Mart M. Lamers
  6. Dennis de Meulder
  7. Geert van Amerongen
  8. Judith van den Brand
  9. Nisreen M.A. Okba
  10. Debby Schipper
  11. Peter van Run
  12. Lonneke Leijten
  13. Ernst Verschoor
  14. Babs Verstrepen
  15. Jan Langermans
  16. Christian Drosten
  17. Martje Fentener van Vlissingen
  18. Ron Fouchier
  19. Rik de Swart
  20. Marion Koopmans
  21. Bart L. Haagmans

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Abstract

A novel coronavirus, SARS-CoV-2, was recently identified in patients with an acute respiratory syndrome, COVID-19. To compare its pathogenesis with that of previously emerging coronaviruses, we inoculated cynomolgus macaques with SARS-CoV-2 or MERS-CoV and compared with historical SARS-CoV infections. In SARS-CoV-2-infected macaques, virus was excreted from nose and throat in absence of clinical signs, and detected in type I and II pneumocytes in foci of diffuse alveolar damage and mucous glands of the nasal cavity. In SARS-CoV-infection, lung lesions were typically more severe, while they were milder in MERS-CoV infection, where virus was detected mainly in type II pneumocytes. These data show that SARS-CoV-2 can cause a COVID-19-like disease, and suggest that the severity of SARS-CoV-2 infection is intermediate between that of SARS-CoV and MERS-CoV.

One Sentence Summary

SARS-CoV-2 infection in macaques results in COVID-19-like disease with prolonged virus excretion from nose and throat in absence of clinical signs.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.17.995639: (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: 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 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 10.1101/2020.03.17.995639 on bioRxiv