Cholinergic and lipid mediators crosstalk in Covid-19 and the impact of glucocorticoid therapy

  1. Malena M. Pérez
  2. Vinícius E. Pimentel
  3. Carlos A. Fuzo
  4. Pedro V. da Silva-Neto
  5. Diana M. Toro
  6. Camila O. S. Souza
  7. Thais F. C. Fraga-Silva
  8. Luiz Gustavo Gardinassi
  9. Jonatan C. S. de Carvalho
  10. Nicola T. Neto
  11. Ingryd Carmona-Garcia
  12. Camilla N. S. Oliveira
  13. Cristiane M. Milanezi
  14. Viviani Nardini Takahashi
  15. Thais Canassa De Leo
  16. Lilian C. Rodrigues
  17. Cassia F. S. L. Dias
  18. Ana C. Xavier
  19. Giovanna S. Porcel
  20. Isabelle C. Guarneri
  21. Kamila Zaparoli
  22. Caroline T. Garbato
  23. Jamille G. M. Argolo
  24. Ângelo A. F. Júnior
  25. Marley R. Feitosa
  26. Rogerio S. Parra
  27. José J. R. da Rocha
  28. Omar Feres
  29. Fernando C. Vilar
  30. Gilberto G. Gaspar
  31. Rafael C. da Silva
  32. Leticia F. Constant
  33. Fátima M. Ostini
  34. Alessandro P. de Amorim
  35. Augusto M. Degiovani
  36. Dayane P. da Silva
  37. Debora C. Nepomuceno
  38. Rita C. C. Barbieri
  39. Isabel K. F. M. Santos
  40. Sandra R. C. Maruyama
  41. Elisa M. S. Russo
  42. Angelina L. Viana
  43. Ana P. M. Fernandes
  44. Vânia L. D. Bonato
  45. Cristina R. B. Cardoso
  46. Carlos A. Sorgi
  47. Marcelo Dias-Baruffi
  48. Lúcia H. Faccioli

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Abstract

Cytokine storms and hyperinflammation, potentially controlled by glucocorticoids, occur in COVID-19; the roles of lipid mediators and acetylcholine (ACh) and how glucocorticoid therapy affects their release in Covid-19 remain unclear. Blood and bronchoalveolar lavage (BAL) samples from SARS-CoV-2- and non-SARS-CoV-2-infected subjects were collected for metabolomic/lipidomic, cytokines, soluble CD14 (sCD14), and ACh, and CD14 and CD36-expressing monocyte/macrophage subpopulation analyses. Transcriptome reanalysis of pulmonary biopsies was performed by assessing coexpression, differential expression, and biological networks. Correlations of lipid mediators, sCD14, and ACh with glucocorticoid treatment were evaluated. This study enrolled 190 participants with Covid-19 at different disease stages, 13 hospitalized non-Covid-19 patients, and 39 healthy-participants. SARS-CoV-2 infection increased blood levels of arachidonic acid (AA), 5-HETE, 11-HETE, sCD14, and ACh but decreased monocyte CD14 and CD36 expression. 5-HETE, 11-HETE, cytokines, ACh, and neutrophils were higher in BAL than in circulation (fold-change for 5-HETE 389.0; 11-HETE 13.6; ACh 18.7, neutrophil 177.5, respectively). Only AA was higher in circulation than in BAL samples (fold-change 7.7). Results were considered significant at P<0.05, 95%CI. Transcriptome data revealed a unique gene expression profile associated with AA, 5-HETE, 11-HETE, ACh, and their receptors in Covid-19. Glucocorticoid treatment in severe/critical cases lowered ACh without impacting disease outcome. We first report that pulmonary inflammation and the worst outcomes in Covid-19 are associated with high levels of ACh and lipid mediators. Glucocorticoid therapy only reduced ACh, and we suggest that treatment may be started early, in combination with AA metabolism inhibitors, to better benefit severe/critical patients.

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  1. Version published to 10.1101/2021.01.07.20248970v2 on medRxiv
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    SciScore for 10.1101/2021.01.07.20248970: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: All participants were over 16 years old and chosen according to the inclusion and exclusion criteria described in Table S1 and in the protocol, after providing signed consent.
    IRB: Ethical considerations: All participants provided written consent in accordance with the regulations of the Conselho Nacional de Pesquisa em Humanos (CONEP) and the Human Ethical Committee from Faculdade de Ciências Farmacêuticas de Ribeirão Preto (CEP-FCFRP-USP).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Blood samples collected from patients positive for Covid-19 (n=190) were analyzed by RT-qPCR (Biomol OneStep/Covid-19 kit; Institute of Molecular Biology of Paraná - IBMP Curitiba/PR, Brazil) using nasopharyngeal swabs and/or serological assays to detect IgM/IgG/IgA (SARS-CoV-2® antibody test; Guangzhou Wondfo Biotech, China).
    SARS-CoV-2®
    suggested: None
    ) (BD Biosciences) and incubated with monoclonal antibodies specific for CD14 (1:100) (M5E2; Biolegend), HLA-DR (1:100) (G46-6; BD Biosciences), CD16 (1:100) (3G8; Biolegend), and CD36 (1:100) (CB38, BD Biosciences) for 30 min at 4°C.
    CD14
    suggested: (BioLegend Cat# 348805, RRID:AB_2889063)
    HLA-DR
    suggested: None
    CD16
    suggested: (BD Biosciences Cat# 557939, RRID:AB_2802162)
    CD36
    suggested: None
    Software and Algorithms
    SentencesResources
    Differential leukocyte counts were conducted using an average of 200 cells after staining with Fast Panoptic (LABORCLIN; Laboratory Products Ltd, Pinhais, Brazil) and examined under an optical microscope (Zeiss EM109; Carl Zeiss AG, Oberkochen, Germany) with a 100× objective (immersion oil) equipped with a Veleta CCD digital camera (Olympus Soft Imaging Solutions Gmbh, Germany) and ImageJ (1.45s) (National Institutes of Health, Rockville, MD, USA)12.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    High-performance liquid chromatography coupled with tandem Mass Spectrometry (LC-MS/MS) assay: Acetylcholine measurement: ACh was measured in heparinized plasma (SST® Gel Advance®; BD Diagnostics, Franklin Lakes, NJ, USA) and in BAL using a commercially available immunofluorescence kit (ab65345; Abcam, Cambridge, UK) according to the manufacturer’s instructions.
    BD Diagnostics
    suggested: None
    Data were evaluated using FlowJo® software (version 10.7.0)
    FlowJo®
    suggested: (FlowJo, RRID:SCR_008520)
    Re-analysis of transcriptome data from lung biopsies of patients with Covid-19: To gain a better understanding of the correlation between the altered concentrations of ACh, AA, and AA-metabolites detected in the plasma and BAL fluid of severe/critical Covid-19 patients, we performed a new analysis by re-using a previously published transcriptome open dataset 18, deposited in the Gene Expression Omnibus repository under accession no. GSE150316 19.
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    Then, the co-expression modules were analysed for the occurrence of ACh and AA genes list obtained from the Reactome pathways 21, as well as the Covid-19-related genes obtained from the literature (Supplementary Appendix I).
    Reactome
    suggested: (Reactome, RRID:SCR_003485)
    Next, differential gene expression between samples from the lung biopsy transcriptome (CV, NCV, CVL, and CVH) was measured using the DESeq2 package 22, with p-values adjusted using the Benjamini and Hochberg method 23.
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    Finally, a first-order biological network was constructed using co-expression module(s) containing genes associated with the ACh and AA pathways to characterise the interplay between these mediators in combination with Covid-19 severity markers, as well as to identify relevant DEGs and hub genes in this network, using the BioGRID repository 24.
    BioGRID
    suggested: (BioGrid Australia, RRID:SCR_006334)
    The results were tabulated using GraphPad Prism software (version 8.0) and the differences were considered statistically significant at p<0.05. See the Additional Statistical Report section for more information.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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: 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

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  3. Version published to 10.1101/2021.01.07.20248970v1 on medRxiv