Severe COVID-19 is marked by dysregulated serum levels of carboxypeptidase A3 and serotonin

  1. Rodolfo Soria-Castro
  2. Yatsiri G Meneses-Preza
  3. Gloria M Rodríguez-López
  4. Sandra Romero-Ramírez
  5. Víctor A Sosa-Hernández
  6. Rodrigo Cervantes-Díaz
  7. Alfredo Pérez-Fragoso
  8. José J Torres-Ruíz
  9. Diana Gómez-Martín
  10. Marcia Campillo-Navarro
  11. Violeta D Álvarez-Jiménez
  12. Sonia M Pérez-Tapia
  13. Alma D Chávez-Blanco
  14. Sergio Estrada-Parra
  15. José L Maravillas-Montero
  16. Rommel Chacón-Salinas

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Abstract

The immune response plays a critical role in the pathophysiology of SARS-CoV-2 infection ranging from protection to tissue damage and all occur in the development of acute respiratory distress syndrome (ARDS). ARDS patients display elevated levels of inflammatory cytokines and innate immune cells, and T and B cell lymphocytes have been implicated in this dysregulated immune response. Mast cells are abundant resident cells of the respiratory tract and are able to release different inflammatory mediators rapidly following stimulation. Recently, mast cells have been associated with tissue damage during viral infections, but their role in SARS-CoV-2 infection remains unclear. In this study, we examined the profile of mast cell activation markers in the serum of COVID-19 patients. We noticed that SARS-CoV-2-infected patients showed increased carboxypeptidase A3 (CPA3) and decreased serotonin levels in their serum when compared with symptomatic SARS-CoV-2-negative patients. CPA3 levels correlated with C-reactive protein, the number of circulating neutrophils, and quick SOFA. CPA3 in serum was a good biomarker for identifying severe COVID-19 patients, whereas serotonin was a good predictor of SARS-CoV-2 infection. In summary, our results show that serum CPA3 and serotonin levels are relevant biomarkers during SARS-CoV-2 infection. This suggests that mast cells and basophils are relevant players in the inflammatory response in COVID-19 and may represent targets for therapeutic intervention.

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  1. Version published to 10.1002/jlb.4hi0221-087r
  2. ScreenIT

    SciScore for 10.1101/2021.02.02.21251020: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the Research and Ethics Committee of the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán
    Consent: All participants of this study signed an informed consent form to participate in this study.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analysis: All statistical analyses were performed with SigmaPlot software version 14.0
    SigmaPlot
    suggested: (SigmaPlot, RRID:SCR_003210)
    The r values for each of the correlations were plotted in a bubble chart generated with Microsoft Excel 2019 (https://office.microsoft.com/excel).
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    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 10.1101/2021.02.02.21251020v1 on medRxiv