Clinical Validation of a Novel T-cell Receptor Sequencing Assay for Identification of Recent or Prior SARS-CoV-2 Infection

  1. Sudeb C. Dalai
  2. Jennifer N. Dines
  3. Thomas M. Snyder
  4. Rachel M. Gittelman
  5. Tera Eerkes
  6. Pashmi Vaney
  7. Sally Howard
  8. Kipp Akers
  9. Lynell Skewis
  10. Anthony Monteforte
  11. Pam Witte
  12. Cristina Wolf
  13. Hans Nesse
  14. Megan Herndon
  15. Jia Qadeer
  16. Sarah Duffy
  17. Emily Svejnoha
  18. Caroline Taromino
  19. Ian M. Kaplan
  20. John Alsobrook
  21. Thomas Manley
  22. Lance Baldo

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Abstract

Background

While diagnostic, therapeutic, and vaccine development in the COVID-19 pandemic has proceeded at unprecedented speed and scale, critical gaps remain in our understanding of the immune response to SARS-CoV-2. Current diagnostic strategies, including serology, have numerous limitations in addressing these gaps. Here we describe clinical performance of T- Detect™ COVID, the first reported assay to determine recent or prior SARS-CoV-2 infection based on T-cell receptor (TCR) sequencing and immune repertoire profiling from whole blood samples.

Methods

Methods for high-throughput immunosequencing of the TCRβ gene from blood specimens have been described 1 . We developed a statistical classifier showing high specificity for identifying prior SARS-CoV-2 infection 2 , utilizing >4,000 SARS-CoV-2-associated TCR sequences from 784 cases and 2,447 controls across 5 independent cohorts. The T-Detect COVID Assay comprises immunosequencing and classifier application to yield a qualitative positive or negative result. Several retrospective and prospective cohorts were enrolled to assess assay performance including primary and secondary Positive Percent Agreement (PPA; N=205, N=77); primary and secondary Negative Percent Agreement (NPA; N=87, N=79); PPA compared to serology (N=55); and pathogen cross-reactivity (N=38).

Results

T-Detect COVID demonstrated high PPA in subjects with prior PCR-confirmed SARS-CoV-2 infection (97.1% 15+ days from diagnosis; 94.5% 15+ days from symptom onset), high NPA (∼100%) in presumed or confirmed SARS-CoV-2 negative cases, equivalent or higher PPA than two commercial EUA serology tests, and no evidence of pathogen cross-reactivity.

Conclusion

T-Detect COVID is a novel T-cell immunosequencing assay demonstrating high clinical performance to identify recent or prior SARS-CoV-2 infection from standard blood samples. This assay can provide critical insights on the SARS-CoV-2 immune response, with potential implications for clinical management, risk stratification, surveillance, assessing protective immunity, and understanding long-term sequelae.

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  2. Rapid Reviews Infectious Diseases

    Carolina Scagnolari

    Review of "Clinical Validation of a Novel T-cell Receptor Sequencing Assay for Identification of Recent or Prior SARS-CoV-2 Infection"

    Reviewer: Carolina Scagnolari (Sapienza University of Rome) | 📗📗📗📗◻️ 

  3. ScreenIT

    SciScore for 10.1101/2021.01.06.21249345: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics: All samples were collected pursuant to an Institutional Review Board (IRB)-approved clinical study protocol.
    Consent: For residual samples collected under prospective study protocols, informed consent was obtained from participants.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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:
    However, the limitations of serologic testing, including high variability in test performance across platforms and antibody isotypes tested18, waning or loss of antibody signal over time11,13,14, and absence of detectable antibodies in up to 10% of individuals including those with immunocompromising conditions25,26, expose unmet clinical and public health needs for immunologic testing strategies for SARS-CoV-2 that are consistent, durable, and more informative. Using TCR gene sequencing from whole blood samples, we describe a sequence-based assay to identify recent or prior SARS-CoV-2 infection which demonstrates high PPA (>97% beyond 15 days following diagnosis), high NPA in presumed or confirmed negative SARS-CoV-2 infection (∼100%), equivalent or higher PPA compared to commercially available EUA serology tests, and lack of cross reactivity with a number of viral and/or respiratory tract pathogens. This performance was consistent across several retrospective and prospective cohorts and longitudinal sampling timeframes. Utilizing this approach in a real-world setting, we have shown previously that robust T-cell signals are persistent at least 6 months after primary SARS-CoV-2 infection42, consistent with other reports44. In the SARS-CoV-1 pandemic, detectable virus-specific T-cell responses were observed in recovered individuals up to 17 years later21. In direct real-world comparisons with serologic testing, we have observed up to a 20% lower sensitivity of commercially avai...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04583982CompletedImmuneSense™ COVID-19 Study
    NCT04494893RecruitingImmuneRACE - Immune Response Action to COVID-19 Events

    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.
    • Thank you for including a protocol registration statement.

    About SciScore

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  4. Version published to 10.1101/2021.01.06.21249345v1 on medRxiv