Evaluation of the performance of SARS-CoV-2 serological tools and their positioning in COVID-19 diagnostic strategies

  1. Aurelie Velay
  2. Floriane Gallais
  3. Ilies Benotmane
  4. Marie Josée Wendling
  5. François Danion
  6. Olivier Collange
  7. Jérôme De Sèze
  8. Catherine Schmidt-Mutter
  9. Francis Schneider
  10. Pascal Bilbault
  11. Ferhat Meziani
  12. Samira Fafi-Kremer

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Abstract

Rapid and accurate diagnosis is crucial for successful outbreak containment. During the current coronavirus disease 2019 (COVID-19) public health emergency, the gold standard for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection diagnosis is the detection of viral RNA by reverse transcription (RT)-PCR. Additional diagnostic methods enabling the detection of current or past SARS-CoV-2 infection would be highly beneficial to ensure the timely diagnosis of all infected and recovered patients. Here, we investigated several serological tools, i.e., two immunochromatographic lateral flow assays (LFA-1 (Biosynex COVID-19 BSS) and LFA-2 (COVID-19 Sign IgM/IgG)) and two enzyme-linked immunosorbent assays (ELISAs) detecting IgA (ELISA-1 Euroimmun), IgM (ELISA-2 EDI) and/or IgG (ELISA-1 and ELISA-2) based on well-characterized panels of serum samples from patients and healthcare workers with PCR-confirmed COVID-19 and from SARS-CoV-2-negative patients. A total of 272 serum samples were used, including 62 serum samples from hospitalized patients (panel 1 and panel 3), 143 serum samples from healthcare workers (panel 2) diagnosed with COVID-19 and 67 serum samples from negative controls. Diagnostic performances of each assay were assessed according to days after symptom onset (dso) and the antigenic format used by manufacturers. We found overall sensitivities ranging from 69% to 93% on panels 1 and 2 and specificities ranging from 83% to 98%. The clinical sensitivity varied greatly according to the panel tested and the dso. The assays we tested showed poor mutual agreement. A thorough selection of serological assays for the detection of ongoing or past infections is advisable.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.16.156166: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethical approval was granted by the local institutional review board (CE-2020-34).
    Consent: All patients provided written informed consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Another 27 serum samples were used to study cross-reactivity, including 20 samples from patients infected with four other human coronaviruses two to three months before sampling (HCoV-229E, HCoV-HKU1, HCoV-NL63, and HCoV-OC43), two from patients previously infected with influenza A virus, one from a patient previously infected with human rhinovirus, two containing rheumatoid factor, and two positive for antinuclear antibodies.
    antinuclear
    suggested: None
    Enzyme-linked Immunosorbent Assay (IgA, IgM and IgG): The following ELISA diagnostic kits were used for the detection of anti-SARS-CoV-2 IgA, IgM and IgG antibodies according to the manufacturer’s instructions: (1) ELISA-1: ELISA anti-SARS-CoV-2 IgA and IgG (Euroimmun, Lübeck, Germany) and (2) ELISA-2: EDI™ novel coronavirus COVID-19 IgM and IgG (Epitope Diagnostics, San Diego, CA, USA).
    IgA, IgM
    suggested: None
    anti-SARS-CoV-2 IgA, IgM
    suggested: None
    IgG antibodies according to the manufacturer’s instructions: (1) ELISA-1: ELISA anti-SARS-CoV-2 IgA and IgG (Euroimmun, Lübeck, Germany) and (2) ELISA-2: EDI™ novel coronavirus COVID-19 IgM and IgG (Epitope Diagnostics, San Diego, CA, USA)
    suggested: None
    the manufacturer’s instructions: (1) ELISA-1: ELISA
    suggested: None
    IgA and IgG (Euroimmun, Lübeck, Germany)
    suggested: None
    Software and Algorithms
    SentencesResources
    Analyses were conducted using GraphPad (San Diego, CA, USA) Prism 6 software.
    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: 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.

  2. Version published to 10.1101/2020.06.16.156166 on bioRxiv