Heat inactivation of serum interferes with the immunoanalysis of antibodies to SARS‐CoV‐2

This article has been Reviewed by the following groups

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Abstract

Background

The detection of serum antibodies to the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is emerging as a new tool for the coronavirus disease 2019 (COVID‐19) diagnosis. Since many coronaviruses are sensitive to heat, heating inactivation of samples at 56°C prior to testing is considered a possible method to reduce the risk of transmission, but the effect of heating on the measurement of SARS‐CoV‐2 antibodies is still unclear.

Methods

By comparing the levels of SARS‐CoV‐2 antibodies before and after heat inactivation of serum at 56°C for 30 minutes using a quantitative fluorescence immunochromatographic assay

Results

We showed that heat inactivation significantly interferes with the levels of antibodies to SARS‐CoV‐2. The IgM levels of all the 34 serum samples (100%) from COVID‐19 patients decreased by an average level of 53.56%. The IgG levels were decreased in 22 of 34 samples (64.71%) by an average level of 49.54%. Similar changes can also be observed in the non–COVID‐19 disease group (n = 9). Of note, 44.12% of the detected IgM levels were dropped below the cutoff value after heating, suggesting heat inactivation can lead to false‐negative results of these samples.

Conclusion

Our results indicate that heat inactivation of serum at 56°C for 30 minutes interferes with the immunoanalysis of antibodies to SARS‐CoV‐2. Heat inactivation prior to immunoanalysis is not recommended, and the possibility of false‐negative results should be considered if the sample was pre‐inactivated by heating.

Article activity feed

  1. SciScore for 10.1101/2020.03.12.20034231: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: A total of 34 serum samples with positive SARS-CoV-2 antibody results from patients with COVID-19 infections and 9 serum form non-COVID-19 diseases were collected form Hankou Hospital, Wuhan city with approval of the ethics committee (hkyy2020-004).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The immunoassay quantitatively measures IgM and IgG antibodies to SARS-CoV-2.
    IgG
    suggested: None
    SARS-CoV-2
    suggested: None

    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. SciScore for 10.1101/2020.03.12.20034231: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementMethods A total of 34 serum samples with positive SARS-CoV-2 antibody results from patients with COVID-19 infections and 9 serum form non-COVID-19 diseases were collected form Hankou Hospital, Wuhan city with approval of the ethics committee (hkyy2020-004).Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The immunoassay quantitatively measures IgM and IgG antibodies to SARS-CoV-2.
    IgG
    suggested: None
          <div style="margin-bottom:8px">
            <div><b>SARS-CoV-2</b></div>
            <div>suggested: None</div>
          </div>
        </td></tr></table>
    

    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).


    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, please follow this link.