Serology characteristics of SARS-CoV-2 infection after exposure and post-symptom onset

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Abstract

Timely diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a prerequisite for treatment and prevention. The serology characteristics and complement diagnosis value of the antibody test to RNA test need to be demonstrated.

Method

Serial sera of 80 patients with PCR-confirmed coronavirus disease 2019 (COVID-19) were collected at the First Affiliated Hospital of Zhejiang University, Hangzhou, China. Total antibody (Ab), IgM and IgG antibodies against SARS-CoV-2 were detected, and the antibody dynamics during the infection were described.

Results

The seroconversion rates for Ab, IgM and IgG were 98.8%, 93.8% and 93.8%, respectively. The first detectible serology marker was Ab, followed by IgM and IgG, with a median seroconversion time of 15, 18 and 20 days post exposure (d.p.e.) or 9, 10 and 12 days post onset (d.p.o.), respectively. The antibody levels increased rapidly beginning at 6 d.p.o. and were accompanied by a decline in viral load. For patients in the early stage of illness (0–7 d.p.o), Ab showed the highest sensitivity (64.1%) compared with IgM and IgG (33.3% for both; p<0.001). The sensitivities of Ab, IgM and IgG increased to 100%, 96.7% and 93.3%, respectively, 2 weeks later. When the same antibody type was detected, no significant difference was observed between enzyme-linked immunosorbent assays and other forms of immunoassays.

Conclusions

A typical acute antibody response is induced during SARS-CoV-2 infection. Serology testing provides an important complement to RNA testing in the later stages of illness for pathogenic-specific diagnosis and helpful information to evaluate the adapted immunity status of patients.

Article activity feed

  1. SciScore for 10.1101/2020.03.23.20041707: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was reviewed and approved by the Medical Ethical Committee of the first affiliated hospital of Zhejiang University (approval number 2020-IIT-47).
    Consent: Written informed consent was obtained from each enrolled subject.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Antibody measurement: The total antibody (Ab), IgM antibody and IgG antibody against SARS-CoV-2 in plasma samples were tested using three enzyme linked immunosorbent assays (ELISA-Ab, ELISA-IgM and ELISA-IgG), three colloidal-gold lateral-flow immunoassays (LFIA-Ab, LFIA-IgM and LFIA-IgG) and two chemiluminescence microparticle immunoassays (CMIA-Ab and CMIA-IgM), respectively.
    LFIA-IgG
    suggested: None
    The total antibody detection was based on double-antigens sandwich immunoassay and the IgM antibody detection were based on μ-chain capture immunoassay.
    IgM
    suggested: None
    Software and Algorithms
    SentencesResources
    All statistical analysis was conducted by SAS 9.4 (SAS Institute, Cary, NC, USA).
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    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 limitations of the study included: 1) only symptomatic infections were enrolled, therefore if the antibody response to asymptomatic infection follows similar features remains to be determined; 2) most blood samples were all collected with one month post onset so the lasting time of antibodies cannot be estimated; 3) the antibody levels had not been exactly titrated. Future studies are needed to better understand the antibody response profile of SARS-CoV-2 infection and to precisely interpret the clinical meaning of serology findings. In conclusion, typical acute antibody response is induced during the SARS-CoV-2 infection. The serology testing provides important complementation to RNA test for pathogenic specific diagnosis and helpful information to evaluate the adapted immunity status of patient. It should be strongly recommended to apply well-validated antibody tests in the clinical management and public health practice to improve the control of Covid-19 infection.

    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 10.1101/2020.03.23.20041707: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementThis study was reviewed and approved by the Medical Ethical Committee of the first affiliated hospital of Zhejiang University ( approval number 2020-IIT-47) .Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variableThe median age of patients was 55 years ( IQR , 45-64 years ) and 38.7 % were females .Cell Line Authentication[ 6 ] However , the clinical and laboratory findings of Covid-19 infection are not distinguishable from pneumonia caused by infection of some common respiratory tract pathogens such as influenza virus , streptococcus pneumoniae and mycoplasma pneumoniae.

    Table 2: Resources

    Antibodies
    SentencesResources
    Serial plasma of COVID-19 patients and were collected and total antibody ( Ab) , IgM and IgG antibody against SARS-CoV-2 were detected.
    total antibody ( Ab) , IgM and IgG
    suggested: None
          <div style="margin-bottom:8px">
            <div><b>SARS-CoV-2</b></div>
            <div>suggested: None</div>
          </div>
        </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Antibody measurement The total antibody ( Ab) , IgM antibody and IgG antibody against SARS-CoV-2 in 7 plasma samples were tested using three enzyme linked immunosorbent assays ( ELISA-Ab , ELISA-IgM and ELISA-IgG) , three colloidal-gold lateral-flow immunoassays ( LFIA-Ab , LFIA-IgM and LFIA-IgG ) and two chemiluminescence microparticle immunoassays ( CMIA-Ab and CMIA-IgM) , respectively .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
          <div style="margin-bottom:8px">
            <div><b>IgM</b></div>
            <div>suggested: None</div>
          </div>
        
          <div style="margin-bottom:8px">
            <div><b>LFIA-IgG</b></div>
            <div>suggested: None</div>
          </div>
        </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">It can detect any types of antibodies including IgM, IgG and IgA in principle.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
          <div style="margin-bottom:8px">
            <div><b>IgM, IgG</b></div>
            <div>suggested: None</div>
          </div>
        </td></tr><tr><td style="min-width:100px;text-align:center; padding-top:4px;" colspan="2"><b>Software and Algorithms</b></td></tr><tr><td style="min-width:100px;text=align:center"><i>Sentences</i></td><td style="min-width:100px;text-align:center"><i>Resources</i></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">All statistical analysis was conducted by SAS 9.4 ( SAS Institute , Cary , NC , USA) .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
          <div style="margin-bottom:8px">
            <div><b>SAS Institute</b></div>
            <div>suggested: (Statistical Analysis System, <a href="https://scicrunch.org/resources/Any/search?q=SCR_008567">SCR_008567</a>)</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.