Quantitative plasma proteomics of survivor and non-survivor COVID-19 patients admitted to hospital unravels potential prognostic biomarkers and therapeutic targets

  1. Daniele C. Flora
  2. Aline D. Valle
  3. Heloisa A. B. S. Pereira
  4. Thais F. Garbieri
  5. Nathalia R. Buzalaf
  6. Fernanda N. Reis
  7. Larissa T. Grizzo
  8. Thiago J. Dionisio
  9. Aline L. Leite
  10. Virginia B. R. Pereira
  11. Deborah M. C. Rosa
  12. Carlos F. Santos
  13. Marília A. Rabelo Buzalaf

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Abstract

The development of new approaches that allow early assessment of which cases of COVID-19 will likely become critical and the discovery of new therapeutic targets are urgent demands. In this cohort study, we performed proteomic and laboratorial profiling of plasma from 163 patients admitted to Bauru State Hospital (Bauru, SP, Brazil) between May 4 th and July 4 th , 2020, who were diagnosed with COVID-19 by RT-PCR nasopharyngeal swab samples. Plasma samples were collected upon admission for routine laboratory analyses and shotgun quantitative label-free proteomics. Based on the course of the disease, the patients were further divided into 3 groups: a) mild symptoms, discharged without admission to an intensive care unit (ICU) (n=76); b) severe symptoms, discharged after admission to an ICU (n=56); c) critical, died after admission to an ICU (n=31). White cells and neutrophils were significantly higher in severe and critical patients compared to mild ones. Lymphocytes were significantly lower in critical patients compared to mild ones and platelets were significantly lower in critical patients compared to mild and severe ones. Ferritin, TGO, urea and creatinine were significantly higher in critical patients compared to mild and severe ones. Albumin, CPK, LDH and D-dimer were significantly higher in severe and critical patients compared to mild ones. PCR was significantly higher in severe patients compared to mild ones. Proteomic analysis revealed marked changes between the groups in plasma proteins related to complement activation, blood coagulation, antimicrobial humoral response, acute inflammatory response, and endopeptidase inhibitor activity. Higher levels of IREB2, GELS, POLR3D, PON1 and ULBP6 upon admission to hospital were found in patients with mild symptoms, while higher levels of Gal-10 were found in critical and severe patients. This needs to be validated in further studies. If confirmed, pathways involving these proteins might be potential new therapeutic targets for COVID-19.

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  1. ScreenIT

    SciScore for 10.1101/2020.12.26.20248855: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: 2.1 Ethical aspects: This project was approved by the Ethical Committee of Bauru School of Dentistry, University of São Paulo (CAAE 31019820.8.0000.5417) upon acquiescence of the Nucleus of Teaching and Research of the HEB.
    Consent: Patients participated after they (or their relatives) signed an informed consent document.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    PLGS also assigns peptide identifications to proteins through an iterative matching process (16).
    PLGS
    suggested: None
    Data were further processed with Microsoft Excel for additional data analysis and for the generation of figures and tables.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    The software CYTOSCAPE 3.7.2 (JAVA) was used to build networks of molecular interaction between the identified proteins, with the aid of ClueGo and ClusterMarker applications.
    CYTOSCAPE
    suggested: (Cytoscape, RRID:SCR_003032)
    ClueGo
    suggested: (ClueGO, RRID:SCR_005748)
    2.6 Statistical analysis: The software GraphPad InStat (version 3.0 for Windows; GraphPad Software Inc. La Jolla, Ca, USA) was used.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04358406RecruitingRhu-pGSN for Severe Covid-19 Pneumonia

    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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  2. Version published to 10.1101/2020.12.26.20248855v1 on medRxiv