SARS-CoV-2 antibodies, serum inflammatory biomarkers and clinical severity of hospitalized COVID-19 patients

  1. Roberto Gozalbo-Rovira
  2. Estela Gimenez
  3. Víctor Latorre
  4. Clara Francés-Gómez
  5. Eliseo Albert
  6. Javier Buesa
  7. Alberto Marina
  8. María Luisa Blasco
  9. Jaime Signes-Costa
  10. Jesús Rodríguez-Díaz
  11. Ron Geller
  12. David Navarro

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Abstract

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  1. Version published to 10.1016/j.jcv.2020.104611
  2. ScreenIT

    SciScore for 10.1101/2020.07.22.20159673: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The current study was approved by the Research Ethics Committee of Hospital Clínico Universitario INCLIVA (March, 2020).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    RBD IgG immunoassay: An enzyme-linked immunosorbent assay (ELISA) was used to quantitate IgG antibodies binding to SARS-CoV-2 RBD [25].
    quantitate IgG
    suggested: None
    SARS-CoV-2 neutralizing antibody assay: A green fluorescent protein (GFP) reporter-based neutralization assay which used a non-replicative vesicular stomatitis virus pseudotyped with the SARS-CoV-2 spike protein (VSV-S) was optimized as previously described (see supplementary methods) [27-29]
    GFP
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Neutralization assays were performed on Vero cells.
    Vero
    suggested: CLS Cat# 605372/p622_VERO, RRID:CVCL_0059)
    Software and Algorithms
    SentencesResources
    The analyses were performed using SPSS version 20.0 (SPSS, Chicago, IL, USA).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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:
    The current study has several limitations. First, its retrospective nature. Second, cohort size is relatively small in our study. Third, IL-6 data was only available from 18 patients (all but one at ICU); in addition, all these patients were treated with tocilizumab. Fourth, SARS-CoV-2 antibodies and inflammatory biomarkers levels were measured in the blood compartment, which may not necessarily mirror those in lung tissue. Fifth, serum levels of other cytokines (i.e. TNF-α, or IL1-β) or chemokines (IFNγ-induced protein 10) that may reflect more accurately the overall state of inflammation were not measured [4,5]. Sixth, the data reported in the current study may be interpreted as arguing against a role for neutralizing antibodies in mediating SARS-CoV-2 clearance, as found in other studies that show an association between SARS-CoV-2 antibody levels and COVID-19. This would certainly be oversimplistic and against data published in experimental models [11]. Seventh, epitope specificities of SARS-CoV-2 antibodies other than for the S protein in the case of the neutralization assays or RBD in the case of the IgG tests were not assessed. In this sense, antibodies mediating immunopathogenetic events, especially through ADE, are more likely to behave as sub- or non-neutralizing and target epitopes outside RBD [4]. In summary, the data presented herein do not support an association between SARS-CoV-2 RBD IgG or NtAb50 levels and COVID-19 severity. Further, well-powered studies overc...

    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.
    • Thank you for including a protocol registration statement.

    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 10.1101/2020.07.22.20159673 on medRxiv