Assessing Immunity by Quantitative Measurement of SARS-CoV-2 IgG Antibodies in Fingerstick Samples

  1. Javier T. Garza
  2. Jacob Quick
  3. Dev Chatterjee
  4. Robert P. Garr
  5. Atul Varadhachary
  6. Leo Linbeck

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Abstract

COVID-19 has affected billions of people around the world directly or indirectly. The response to the pandemic has focused on preventing the spread of the disease and improving treatment options. Diagnostic technologies have played a key role in this response since the beginning of the pandemic. As vaccines and other treatments have been developed and deployed, interest in understanding and measuring the individual level of immune protection has increased. Historically, use of antibody titers to measure systemic immunity has been constrained by an incomplete understanding of the relationship between antibodies and immunity, the lack of international standards for antibody concentration to enable cross-study comparisons, and insufficient clinical data to allow for the development of robust antibody-immunity models.

However, these constraints have recently shifted. With a deeper understanding of antibodies, the promulgation of WHO antibody standards, and the development of immunity models using datasets from multiple COVID-19 vaccine trials, certain types of quantitative antibody tests may now provide a way to monitor individual or community immunity against COVID-19. Specifically, tests that quantitate the concentration of anti-RBD IgG –antibodies that target the receptor binding domain of the S1 spike protein component of the SARS-CoV-2 virus – show promise as a useful and scalable measure of the COVID-19 immunity of both individuals and communities. However, to fulfill this promise, a rapid and easy-to-administer test is needed.

To address this important clinical need, Brevitest deployed its point-of-care-capable technology platform that can run a rapid (<15 minute), quantitative antibody test with a sample of 10 μl of whole blood from a fingerstick. The test we validated on this platform measures the concentration of anti-RBD IgG in Binding Antibody Units per milliliter (BAU/mL) per WHO Reference Standard NIBSC 20/136.

In this paper, we present studies used to characterize the Brevitest anti-RBD IgG assay and evaluate its clinical performance, lower limits of measurement, precision, linearity, interference, and cross-reactivity. The results demonstrate the ability of this assay to measure a patient’s anti-RBD IgG concentration. This information, together with models developed from recent COVID-19 vaccine clinical trials, can provide a means of assessing the current level of immune protection of an individual or community against COVID-19 infection.

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  1. ScreenIT

    SciScore for 10.1101/2021.12.21.21268075: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Samples were collected from subjects according to an IRB-approved protocol after consent with an IRB-approved informed consent form.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The cartridge is not a microfluidic device, as there is no movement of reagents within the cartridge; rather, the key ELISA components – antigen, capture antibody, and tracer antibody – are bound to magnetic microspheres that are moved between reagent wells.
    antigen,
    suggested: None
    Cross-reactivity and Interference: To test for cross-reactivity on the Brevitest assay, a panel of samples known to be negative for SARS-CoV-2 and positive for IgG antibodies to the following viruses were obtained from BioIVT: influenza A, influenza B, HBV, HCV, HIV, Haemophilus influenzae, alpha coronaviruses 229E and NL63, beta coronaviruses OC43 and HKU1, RSV, Parainfluenza, and Mycoplasma pneumoniae.
    IgG
    suggested: (Virostat Cat# 3862, RRID:AB_2889989)
    NL63
    suggested: (Virostat Cat# 3879, RRID:AB_2889994)
    HKU1
    suggested: None

    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.

    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.

  2. Version published to 10.1101/2021.12.21.21268075 on medRxiv