Clinical correlations of SARS-CoV-2 antibody responses in patients with COVID-19 infection

  1. Mia DeSimone
  2. Daimon P Simmons
  3. Nicole Tolan
  4. Stacy Melanson
  5. Athena Petrides
  6. Milenko Tanasijevic
  7. Peter Schur

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Abstract

Coronavirus disease 19 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Understanding the clinical correlations of antibodies produced by infected individuals will be critical for incorporating antibody results into clinical management. This study was an observational cohort study to evaluate antibody responses in individuals with PCR-confirmed COVID-19, including 48 hospitalized patients diagnosed with COVID-19 by real-time polymerase chain reaction (RT-PCR) at a large tertiary care medical center. Serum samples were obtained from patients at various time points during the disease course and tested for IgM and IgG antibodies against SARS-CoV-2. Medical records were reviewed, and antibody levels were compared with clinical and laboratory findings. Patients did not have high levels of antibodies within one week of symptoms, but most had detectable IgM and IgG antibodies between 8 and 29 days after onset of symptoms. Some individuals did not develop measurable levels of IgM or IgG antibodies. IgM antibodies were associated with elevated ALT, but there were no other significant associations. We did not observe significant associations of SARS-CoV-2 antibodies with clinical outcomes, including intubation and death. SARS-CoV-2 IgM and IgG antibodies were unlikely to be detected in the first week of infection or in severely immunocompromised individuals. Although we did not observe associations with clinical outcomes, IgM antibodies were associated with higher ALT levels. Antibody production reflects the virus-specific immune response, which is important for immunity but also drives pathology, and antibody levels may be important for guiding treatment of individuals with COVID-19.

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  1. ScreenIT

    SciScore for 10.1101/2020.10.22.20213207: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Data analysis was performed by D.P.S. and M.D. Ethical Considerations: This study was reviewed and approved by the Brigham and Women’s Hospital Institutional Review Board (Boston, MA, USA).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Reagents/Antibody Measurement: IgM and IgG antibodies against SARS-CoV-2 were detected in serum samples using enzyme-linked immunosorbent assay (ELISA) kits (Epitope Diagnostics, San Diego, CA) and performed according to the manufacturer’s instructions.
    SARS-CoV-2
    suggested: None
    This assay uses nucleocapsid antigens to detect IgM and IgG antibodies that bind SARS-CoV-2.
    IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Graphical and statistical analysis was performed in Microsoft Excel 16.36 (Microsoft) and Prism 6.0.h (GraphPad).
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    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 10.1101/2020.10.22.20213207v2 on medRxiv
  3. Version published to 10.1101/2020.10.22.20213207v1 on medRxiv