Innate immune signaling in the olfactory epithelium reduces odorant receptor levels: modeling transient smell loss in COVID-19 patients

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Abstract

Post-infectious anosmias typically follow death of olfactory sensory neurons (OSNs) with a months-long recovery phase associated with parosmias. While profound anosmia is the leading symptom associated with COVID-19 infection, many patients regain olfactory function within days to weeks without distortions. Here, we demonstrate that sterile induction of anti-viral type I interferon signaling in the mouse olfactory epithelium is associated with diminished odor discrimination and reduced odor-evoked local field potentials. RNA levels of all class I, class II, and TAAR odorant receptors are markedly reduced in OSNs in a non-cell autonomous manner. We find that people infected with COVID-19 rate odors with lower intensities and have odor discrimination deficits relative to people that tested negative for COVID-19. Taken together, we propose that inflammatory-mediated loss of odorant receptor expression with preserved circuit integrity accounts for the profound anosmia and rapid recovery of olfactory function without parosmias caused by COVID-19.

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  1. SciScore for 10.1101/2020.06.14.20131128: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIACUC: Animals: All mouse work was in accordance with protocols approved by the Institutional Animal Care and Use Committee (IACUC) of Massachusetts General Hospital.
    IRB: Humans: All human research was in accordance with the Institution Review Board (IRB) at Mass General Brigham.
    Randomizationnot detected.
    BlindingThe video was analyzed for freezing, and the observer was blinded to the genotype.
    Power Analysisnot detected.
    Sex as a biological variableBriefly, approximately 2 month old male ND1 (n = 4) and littermate control (n= 4) mice were habituated individually to a clean mouse cage separated by a parafilm curtain partition that divides the arena into two compartments – one twice as large as the other – for 10 min.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Q-PCR primers were designed using PrimerBank (8), TAARS as in used in (48), and were only used for analysis if they had an efficiency of at least 90%.
    PrimerBank
    suggested: (PrimerBank, RRID:SCR_006898)
    Identifiable information was only accessed by research staff through the REDCap project and was utilized to access participant medical record number and their electronic health record to collect relevant medical variables and the timing and results from the COVID testing and the type of test used.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    Each statistical test was performed as described in the methods and figures legends using SAS, Microsoft Excel, or Apple Numbers.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    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 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.