SARS-CoV-2 Convalescent Sera Binding and Neutralizing Antibody Concentrations Compared with COVID-19 Vaccine Efficacy Estimates against Symptomatic Infection

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

Although COVID-19 vaccine efficacy (VE) studies have estimated antibody concentrations that correlate with protection from COVID-19, how these estimates compare to those generated in response to SARS-CoV-2 infection is unclear. We assessed quantitative neutralizing and binding antibody concentrations using standardized assays on serum specimens collected from COVID-19-unvaccinated persons with detectable antibodies.

Article activity feed

  1. SciScore for 10.1101/2021.11.24.21266812: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Informed consent was waived, as all data were deidentified.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Sera were tested [17] for anti-SARS-CoV-2 antibodies using one of the following three qualitative assays issued emergency use authorization by the FDA that were in use in the clinical laboratories: 1) Architect™ SARS-CoV-2 IgG Assay (nucleocapsid (N) protein; Abbott, Chicago, IL), 2) VITROS® Anti-SARS-CoV-2 IgG Assay (S protein; Ortho-Clinical Diagnostics, Raritan, NJ), and 3) Elecsys® Anti-SARS-CoV-2 Assay (N protein; Roche, Indianapolis, IN) (Supplementary figure 3).
    Anti-SARS-CoV-2 IgG
    suggested: None
    Among 84,683 total serum samples collected during July 27, 2020-August 27, 2020 identified as anti-SARS-CoV-2 antibody positive and had linked age and sex information (as part of the larger serosurveillance study) [17], 3067 serum specimens were selected by convenience sampling for reflex testing with anti-SARS-CoV-2 quantitative IgG and neutralizing antibody assays.
    anti-SARS-CoV-2
    suggested: None
    anti-SARS-CoV-2 quantitative IgG
    suggested: None
    Calibration of the PhenoSense CoV Neutralizing Antibody Assay® with the First WHO International Standard for Anti-SARS-CoV-2 Immunoglobulin (20/136, National Institute for Biological Standards and Controls, UK) [9] allowed us to generate a calibration factor of 0.0653 (S protein containing G614) and convert NT50 values from titers to international units per mL (IU/mL) by multiplying by the calibration factor.
    Anti-SARS-CoV-2 Immunoglobulin (20/136
    suggested: None
    Comparison of Study Antibody Data to Antibody Concentrations Associated with COVID-19 VE: Of the COVID-19 vaccines in use around the world currently, serological correlates of protection thresholds associated with VE have been estimated for ChAdOx1 [11] and mRNA-1273 [12] using the First WHO International Standard for Anti-SARS-CoV-2 Immunoglobulin.
    Anti-SARS-CoV-2 Immunoglobulin.
    suggested: None
    Post-hoc Tukey’s tests were performed to identify previous qualitative antibody tests and age categories with significantly different anti-SARS-CoV-2 RBD IgG and NT50 concentrations; p-values were adjusted to account for multiple comparisons.
    anti-SARS-CoV-2 RBD IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Sera were tested [17] for anti-SARS-CoV-2 antibodies using one of the following three qualitative assays issued emergency use authorization by the FDA that were in use in the clinical laboratories: 1) Architect™ SARS-CoV-2 IgG Assay (nucleocapsid (N) protein; Abbott, Chicago, IL), 2) VITROS® Anti-SARS-CoV-2 IgG Assay (S protein; Ortho-Clinical Diagnostics, Raritan, NJ), and 3) Elecsys® Anti-SARS-CoV-2 Assay (N protein; Roche, Indianapolis, IN) (Supplementary figure 3).
    Abbott
    suggested: (Abbott, RRID:SCR_010477)
    Statistical Analyses: Data management tasks, and statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC) and GraphPad Prism 9.0.0 (GraphPad Software, San Diego, CA).
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    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: We detected the following sentences addressing limitations in the study:
    Our study has several limitations. First, due to the absence of information on whether persons had symptoms or if testing had been done or, if so, the date of COVID-19 symptom onset and/or a positive SARS-CoV-2 qRT-PCR or antigen test, we were unable to calculate the number of days that had elapsed between infection and collection of serum for antibody testing and thus the measurements might not reflect peak antibody concentrations. The ChAdOx1 and mRNA-1273 VE trials measured serum antibody concentrations 28 days after the second vaccine dose, presumably at the peak of the measurable humoral immune response to the vaccine. Therefore, if the sera used in this study were collected >28 days after SARS-CoV-2 infection, it is possible that the percentage of persons with antibody concentrations meeting or exceeding those concentrations associated with 70% and 90% COVID-19 VE were underestimated. However, as a result of the sharp rise in COVID-19 cases in the United States in mid-June 2020 (Supplementary Figure 2) [21], >50% of cases reported in the country prior to July 27, 2020 (date first specimens used in this study were collected) occurred after June 15, 2020. This indicates that the majority of sera in this study were likely to have been collected within 73 days of SARS-CoV-2 infection, a time before IgG antibody concentrations would be expected to have significantly waned from peak post-infection levels [22]. Second, 13.6% of persons had anti-RBD IgG concentrations below the...

    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.

    Results from scite Reference Check: We found no unreliable references.


    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.