Serum IgA, IgM, and IgG responses in COVID-19

  1. Huan Ma
  2. Weihong Zeng
  3. Hongliang He
  4. Dan Zhao
  5. Dehua Jiang
  6. Peigen Zhou
  7. Linzhao Cheng
  8. Yajuan Li
  9. Xiaoling Ma
  10. Tengchuan Jin

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Abstract

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  1. ScreenIT

    SciScore for 10.1101/2020.04.17.20064907: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Patients and clinical samples: This study was approved by the Medical Ethical Committee of the First Affiliated Hospital of USTC and the First Affiliated Hospital of Anhui Medical University.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    A second antibody that recognizes IgA, IgM or IgG conjugated with acridinium (which can react with substrates to generate a strong chemiluminescence) was used for detecting the IgA, IgM or IgG caught by antigen, respectively.
    IgM
    suggested: None
    IgA , IgM or IgG caught by antigen , respectively .
    suggested: None
    RBD-specific Antibody standards preparation: SARS-CoV-2 RBD was immobilized to agarose beads by using CNBr-activated Sepharose™ 4B reagent (GE Healthcare), then column filled with the RBD coupled agarose beads were employed to purify RBD-specific IgA, IgM and IgG antibodies from a serum pool of recovering patients (a manuscript in preparation).
    IgA , IgM and IgG
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    The SARS-CoV-2 RBD protein was expressed using HEK293 cell and purified from cell supernatant using Protein A column.
    HEK293
    suggested: CLS Cat# 300192/p777_HEK293, RRID:CVCL_0045)
    Software and Algorithms
    SentencesResources
    Statistical analysis: Receiver operating characteristic (ROC) analysis was conducted using MedCalc software to determine the optimal cut-off value (criterion) and evaluate the diagnostic value of NP- or RBD-specific IgA, IgM and IgG detection.
    MedCalc
    suggested: (MedCalc, RRID:SCR_015044)

    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. Serum samples were not available every day for each patient, the earliest serum was collected at the 4th day, and last one was at the 41th day after self-reported illness onset. There are only 17 cases of serum samples collected within the first 10 days after illness onset; which consequently influenced the accuracy of early. Similarly, there were only 23 cases of serum samples taken after 30 days post illness onset, hampering an analysis of long-term antibody levels in recovered patients. Most patients enrolled in this study were with clinically moderate symptoms (56/87, 64.4%). There were 17 severe and 5 critical cases, respectively. There were also few cases of mild COVID-19 patients. Therefore, this study of the correlation between antibody levels and disease severity warrants further investigation. In summary, this study reports a novel serological test for detecting SARS-CoV-2 RBD-specific IgA as well as IgM and IgG for clinical diagnosis of COVID-19. Due to its high specificity and sensitivity, this approach could sensitively and quantitatively measure levels of the three types of antibody in blood and other tissues. The serological study also provides valuable information for monitoring SARS-CoV-2 infection, understanding of COVID-19 pathogenesis and improving strategies for preventing, treating and vaccine development of this pandemic disease.

    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 10.1038/s41423-020-0474-z
  3. Version published to 10.1101/2020.04.17.20064907 on medRxiv