SARS-CoV-2–Specific Antibody Detection for Seroepidemiology: A Multiplex Analysis Approach Accounting for Accurate Seroprevalence

  1. Gerco den Hartog
  2. Rutger M Schepp
  3. Marjan Kuijer
  4. Corine GeurtsvanKessel
  5. Josine van Beek
  6. Nynke Rots
  7. Marion P G Koopmans
  8. Fiona R M van der Klis
  9. Robert S van Binnendijk

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Abstract

Background

The COVID-19 pandemic necessitates better understanding of the kinetics of antibody production induced by infection with SARS-CoV-2. We aimed to develop a high-throughput multiplex assay to detect antibodies to SARS-CoV-2 to assess immunity to the virus in the general population.

Methods

Spike protein subunits S1 and receptor binding domain, and nucleoprotein were coupled to microspheres. Sera collected before emergence of SARS-CoV-2 (n = 224) and of non-SARS-CoV-2 influenza-like illness (n = 184), and laboratory-confirmed cases of SARS-CoV-2 infection (n = 115) with various severities of COVID-19 were tested for SARS-CoV-2–specific IgG concentrations.

Results

Our assay discriminated SARS-CoV-2–induced antibodies and those induced by other viruses. The assay specificity was 95.1%–99.0% with sensitivity 83.6%–95.7%. By merging the test results for all 3 antigens a specificity of 100% was achieved with a sensitivity of at least 90%. Hospitalized COVID-19 patients developed higher IgG concentrations and the rate of IgG production increased faster compared to nonhospitalized cases.

Conclusions

The bead-based serological assay for quantitation of SARS-CoV-2–specific antibodies proved to be robust and can be conducted in many laboratories. We demonstrated that testing of antibodies against multiple antigens increases sensitivity and specificity compared to single-antigen–specific IgG determination.

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  1. Version published to 10.1093/infdis/jiaa479
  2. ScreenIT

    SciScore for 10.1101/2020.06.18.20133660: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethical approval was obtained from the Erasmus MC Medical Ethical Committee (MEC-2015-306) to anonymously analyze the used ILI and COVID-19 samples.
    Consent: Informed consent and voluntary informed consent was provided where applicable.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    MFI was converted to arbitrary units (AU/mL) by interpolation from a five-parameter logistic standard curve, using Bioplex Manager 6.2 (Bio-Rad Laboratories) software and exported to MS Excel.
    Bioplex
    suggested: (BioPlex, RRID:SCR_016144)
    Bio-Rad Laboratories
    suggested: (Bio-Rad Laboratories, RRID:SCR_008426)
    Antibody kinetics was fitted using a non-linear 4-parameter least square fit in Graphpad Prism 8.4.1.
    Graphpad Prism
    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.

  3. Version published to 10.1101/2020.06.18.20133660v1 on medRxiv