A Rapid Saliva Test for Monitoring Immune Protection against SARS -CoV-2 and its Variants

  1. Victoria SA. Momyer
  2. Samantha Dixon
  3. Q. John Liu
  4. Brian Wee
  5. Tiffany Y. Chen
  6. Anna Petropoulos
  7. L. Jessica Sang

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Abstract

Given the ongoing transmission and emergence of SARS-Cov-2 variants globally, it is critical to have a timely assessment on individuals’ immune responses as well as population immunity. Important questions such as the durability of COVID-19 immunity or the efficacy of vaccines require large datasets to generate meaningful insights. However, due to the complexity and relatively high-cost of many immunity assays and the needs for blood-drawing specialists, these assays were mostly limited to small-scale clinical studies. Our work demonstrated the potential of a non-invasive, inexpensive and data-driven solution for large-scale immunity surveillance and for predictive modeling of vaccine efficacy. Combining a proprietary saliva processing method and an ultra-sensitive digital detection technology, we were able to rapidly gather information regarding personalized immune response following infection or vaccination, monitor temporal evolution, and optimize predictive models for variant protection.

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  1. ScreenIT

    SciScore for 10.1101/2021.07.09.21260224: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Clinical Study: Study subjects were consented and enrolled in the study with approval from the Biomedical Research Alliance of New York Institutional Review Board (BRANY IRB # A20-08-597-840).
    Field Sample Permit: Sample collection and processing: Whole saliva was collected from a subject without any stimulation.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    To establish a standard curve, varying concentrations of anti-SARS-Cov-2 Spike IgG antibodies (Sino Biological) were spiked into a negative saliva sample and assayed using the TiMES automation system.
    anti-SARS-Cov-2 Spike IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Tests were performed using the TiMES system.
    TiMES
    suggested: (Lab Times, RRID:SCR_000657)

    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:
    Some of the limitations of this study include a relatively small dataset, a predictive algorithm based on analyzing aggregated data from clinical trials and using a published but unverified data model (11). In the future, the predictive algorithm can be further improved with larger datasets, which can be readily collected with the TiMES digital platform. Another limitation of the current study was to focus on immunity monitoring based on neutralizing antibodies alone. A number of studies have suggested that memory B cells and T cells may also contribute to long-term immunity and the protection against future infections (23-26). While the current study did not address B-cell or T-cell responses, the TiMES digital system has allowed us to rapidly develop a number of assays to investigate the immune response mediated by cytokines as well as other B-cell and T-cell biomarkers (18,19, 27). Together they will provide a more complete understanding of the SARS-CoV-2 immunity, inform vaccination strategy, and better prepare us for future outbreaks.

    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 10.1101/2021.07.09.21260224v1 on medRxiv