Persistent post-COVID-19 smell loss is associated with inflammatory infiltration and altered olfactory epithelial gene expression

  1. John B. Finlay
  2. David H. Brann
  3. Ralph Abi-Hachem
  4. David W. Jang
  5. Allison D. Oliva
  6. Tiffany Ko
  7. Rupali Gupta
  8. Sebastian A. Wellford
  9. E. Ashley Moseman
  10. Sophie S. Jang
  11. Carol H. Yan
  12. Hiroaki Matusnami
  13. Tatsuya Tsukahara
  14. Sandeep Robert Datta
  15. Bradley J. Goldstein

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Abstract

Most human subjects infected by SARS-CoV-2 report an acute alteration in their sense of smell, and more than 25% of COVID patients report lasting olfactory dysfunction. While animal studies and human autopsy tissues have suggested mechanisms underlying acute loss of smell, the pathophysiology that underlies persistent smell loss remains unclear. Here we combine objective measurements of smell loss in patients suffering from post-acute sequelae of SARS-CoV-2 infection (PASC) with single cell sequencing and histology of the olfactory epithelium (OE). This approach reveals that the OE of patients with persistent smell loss harbors a diffuse infiltrate of T cells expressing interferon-gamma; gene expression in sustentacular cells appears to reflect a response to inflammatory signaling, which is accompanied by a reduction in the number of olfactory sensory neurons relative to support cells. These data identify a persistent epithelial inflammatory process associated with PASC, and suggests mechanisms through which this T cell-mediated inflammation alters the sense of smell.

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  1. ScreenIT

    SciScore for 10.1101/2022.04.17.488474: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Study Approval: All human subjects studies were performed under protocols approved by Institutional Review Boards.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Anti-Tubulin β3 (BioLegend, clone TUJ1, 1:500), Anti-CD45 (BioLegend, clone HI30, 1:100), Anti-CD3 (BioLegend, clone HIT3a, 1:100), Anti-CD68 (BioLegend, clone BL13756, 1:100) or anti-ERMN (Thermo, #PA5-58327, 1:500) primary antibodies diluted in blocking buffer were incubated on tissue sections for 1 hour at room temperature or overnight at 4 degrees.
    Anti-Tubulin β3
    suggested: None
    Anti-CD45
    suggested: None
    Anti-CD3
    suggested: None
    Anti-CD68
    suggested: (BioLegend Cat# 375602, RRID:AB_2876705)
    anti-ERMN
    suggested: (Thermo Fisher Scientific Cat# PA5-58327, RRID:AB_2641113)
    #PA5-58327
    suggested: (Thermo Fisher Scientific Cat# PA5-58327, RRID:AB_2641113)
    Software and Algorithms
    SentencesResources
    Differentially expressed genes were found using the FindMarkers function with default settings (Wilcoxon Rank-Sum) and plotted using ggplot2 (identifying significant DE genes with >log2 fold-change, adjusted p<0.05).
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Images were analyzed using ImageJ software (V 2.3.0), and scale bars were applied using metadata from the original Leica acquisition software files.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    Statistics: All sequencing data set analyses were performed in Python or R using the toolkits and packages described above.
    Python
    suggested: (IPython, RRID:SCR_001658)
    Plots were produced using Scanpy, or ggplot2 in associated R toolkits30, or Graphpad Prism 9.
    Graphpad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    DE gene sets were analyzed for gene ontology, cellular pathway or tissue output terms using ToppGene Suite31.
    ToppGene
    suggested: ( ToppGene Suite , RRID:SCR_005726)

    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:
    There are several caveats related to our conclusions. Given challenges related to the pandemic, it has been difficult to obtain samples from large numbers of patients, and thus our conclusions are driven by findings we observe in common across our limited set of patients; furthermore, in these studies we have merged patient samples obtained by two different methods (surgical excision and brush biopsy). Finally, although we were careful to obtain biopsies from within the olfactory cleft region in these experiments, the possibility of sample-to-sample variation in the specific contents of each OE biopsy in unavoidable. The pandemic has highlighted the unmet need for new effective treatments for olfactory loss. The mechanistic insights provided here suggest potential new therapeutic strategies. For instance, selectively blocking local pro-inflammatory immune cells or directly inhibiting specific signaling nodes may interfere with a loop disrupting OE homeostasis or repair. The location of the OE, lining the olfactory cleft in the nose, is amenable to localized topical drug delivery, which may provide a means to avoid systemic or off-target effects of novel therapeutic agents. Further studies testing therapeutics in animal models and humans, and longer follow up with PASC olfactory dysfunction patients, will provide ongoing insights regarding the etiology and management of olfactory sensory dysfunction.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2022.04.17.488474v1 on bioRxiv