SARS-CoV-2 Serologic Assays in Control and Unknown Populations Demonstrate the Necessity of Virus Neutralization Testing

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Abstract

Background

To determine how serologic antibody testing outcome links with virus neutralization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we evaluated individuals for SARS-CoV-2 antibody level and viral neutralization.

Methods

We compared serum Ig levels across platforms of viral antigens and antibodies with 15 positive and 30 negative SARS-CoV-2 controls followed by viral neutralization assessment. We then applied these platforms to a clinically relevant cohort of 114 individuals with unknown histories of SARS-CoV-2 infection.

Results

In controls, the best-performing virus-specific antibody detection platforms were SARS-CoV-2 receptor binding domain (RBD) IgG (sensitivity 87%, specificity 100%, positive predictive value [PPV] 100%, negative predictive value [NPV] 94%), spike IgG3 (sensitivity 93%, specificity 97%, PPV 93%, NPV 97%), and nucleocapsid protein (NP) IgG (sensitivity 93%, specificity 97%, PPV 93%, NPV 97%). Neutralization of positive and negative control sera showed 100% agreement. Twenty individuals with unknown history had detectable SARS-CoV-2 antibodies with 16 demonstrating virus neutralization. Spike IgG3 provided the highest accuracy for predicting serologically positive individuals with virus neutralization activity (misidentified 1/20 unknowns compared to 2/20 for RBD and NP IgG).

Conclusions

The coupling of virus neutralization analysis to a spike IgG3 antibody test is optimal to categorize patients for correlates of SARS-CoV-2 immune protection status.

Article activity feed

  1. SciScore for 10.1101/2020.08.18.20177196: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Statistics: Human participants: The institutional review board at the University of Washington reviewed and approved our human subjects study prior to enrollment of any subjects.
    Consent: To enroll in the study each subject was required to provide verbal understanding and written consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Consistent historical negative samples and the positive control spike-binding antibody CR3022 (Abcam, ab273073) were included on plates with total IgG antibody binding for specific viral antigen and antibody combinations.
    total IgG
    suggested: None
    Following a 2hr incubation and washes, the following anti-human secondary antibodies conjugated to HRP were diluted 1:3000 and added to plates: IgG (Thermofisher 31410), IgG1 (Southern Biotech 9054), IgG3 (Southern Biotech 9210), IgM (Sigma A6907), IgA (Sigma A0295).
    anti-human secondary
    suggested: (Thermo Fisher Scientific Cat# 31410, RRID:AB_228269)
    IgG1
    suggested: (SouthernBiotech Cat# 9054-04, RRID:AB_2796626)
    IgG3
    suggested: (SouthernBiotech Cat# 9210-04, RRID:AB_2687998)
    Experimental Models: Cell Lines
    SentencesResources
    The virus plasma mixture was then added in duplicate, along with virus only and mock controls, to Vero cells (ATCC) in a 12-well plate and incubated for 1hr at 37 degrees.
    Vero
    suggested: None
    Software and Algorithms
    SentencesResources
    OD values for each sample dilution were plotted and the area under the curve (AUC) was calculated using Prism.
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    R2 values were determined using a nonlinear regression fit in Prism. University of Washington NP Assay: Abbott SARS-CoV-2 IgG Testing Serum samples were run on the Abbott Architect instrument using the Abbott SARS-CoV-2 IgG assay after FDA notification following manufacturer’s instructions.
    Abbott
    suggested: (Abbott, RRID:SCR_010477)

    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:
    Across the ELISA platforms we investigated, our data supports the use of spike-reactive IgG3 as the best initial screening test to predict neutralization but with the important caveat of our limited sample size. Many of the parameters of test performance were similar for RBD IgG, spike IgG3, and NP IgG. However, spike IgG3 edged out both NP and RBD IgG with the ability to predict neutralization (% PRNT agreement and misidentification columns in Table 1). Expanded studies comparing these three platforms with larger sample sizes would very beneficial to assess if spike IgG3 continues to outperform the other two platforms. RBD and NP IgG platforms already have FDA emergency approval, with the NP IgG platform having the highest specificity and most comprehensive validation(4). Spike IgG3 platforms have not been developed but represent a highly promising platform for development given the knowledge that IgG3 isotypes are known as the most effective at viral neutralization compared to other IgG subtypes(10, 20). The NP IgG assay is likely to be limited in its ability to predict neutralization due to its localization within the virion: the NP protein is hidden beneath the viral envelope and it is therefore unlikely to be an effective target for neutralizing antibodies, unlike the spike proteins(27). However coupling the existing NP IgG Abott ELISA detection assay with neutralization would be a rapid and practical way to address this possible issue. Classic PRNTs are expensive and ti...

    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.