SARS-CoV-2 causes brain inflammation and induces Lewy body formation in macaques

  1. Ingrid H.C.H.M. Philippens
  2. Kinga P. Böszörményi
  3. Jacqueline A. Wubben
  4. Zahra C. Fagrouch
  5. Nikki van Driel
  6. Amber Q. Mayenburg
  7. Diana Lozovagia
  8. Eva Roos
  9. Bernadette Schurink
  10. Marianna Bugiani
  11. Ronald E. Bontrop
  12. Jinte Middeldorp
  13. Willy M. Bogers
  14. Lioe-Fee de Geus-Oei
  15. Jan A.M. Langermans
  16. Marieke A. Stammes
  17. Babs E. Verstrepen
  18. Ernst J. Verschoor

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Abstract

SARS-CoV-2 may cause acute respiratory disease, but the infection can also initiate neurological symptoms. Here we show that SARS-CoV-2 infection causes brain inflammation in the macaque model. An increased metabolic activity in the pituitary gland of two macaques was observed by longitudinal positron emission tomography-computed tomography (PET-CT). Post-mortem analysis demonstrated infiltration of T-cells and activated microglia in the brain, and viral RNA was detected in brain tissues from one animal. We observed Lewy bodies in brains of all rhesus macaques. These data emphasize the virus’ capability to induce neuropathology in this nonhuman primate model for SARS-CoV-2 infection. As in humans, Lewy body formation is an indication for the development of Parkinson’s disease, this data represents a warning for potential long-term neurological effects after SARS-CoV-2 infection.

Teaser

SARS-CoV-2 causes brain inflammation and Lewy bodies, a hallmark for Parkinson, after an asymptomatic infection in macaques.

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  1. Version published to 10.1101/2021.02.23.432474v2 on bioRxiv
  2. ScreenIT

    SciScore for 10.1101/2021.02.23.432474: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIACUC: The research protocol was approved by an independent animal ethics committee (DEC), as well as BPRC’s institutional animal welfare body (IvD).
    Randomizationnot detected.
    BlindingThe counting of cells was performed in a blind matter.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line AuthenticationAuthentication: Hematoxyline-eosine (HE) staining was used for general morphology.

    Table 2: Resources

    Antibodies
    SentencesResources
    Sections were stained with virus antibody staining for virus detection and immunohistochemistry for immune reaction such as T-cell staining (CD3), B-cell staining (CD20), MHC-II cell staining (HLA-DR).
    CD20
    suggested: None
    HLA-DR
    suggested: None
    Immunohistochemistry: The optimal concentration was determined for each antibody: CD3 (polyclonal rabbit – anti-human CD3 IgG, cat. no. A045201-2
    CD3
    suggested: None
    anti-human CD3 IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    All macaques were mature, outbred animals, purpose-bred and socially housed at the BPRC.
    BPRC
    suggested: None
    2, Agilent Technologies), 1:150.
    Agilent Technologies
    suggested: (Agilent Technologies, RRID:SCR_013575)

    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 10.1101/2021.02.23.432474v1 on bioRxiv