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Background Our understanding of the SARS-CoV-2 immune response has critical gaps that are inadequately addressed with available tools. We report the clinical performance of T-Detect COVID, the first T-cell assay to identify prior SARS-CoV-2 infection using T-cell receptor (TCR) sequencing and repertoire profiling from whole blood samples. Methods The T-Detect COVID assay combines high-throughput immunosequencing of the TCRß gene from blood samples with a statistical classifier demonstrating 99.8% specificity for identifying prior SARS-CoV-2 infection. The assay was employed in several retrospective and prospective cohorts to assess primary and secondary Positive Percent Agreement (PPA) with SARS-CoV-2 RT-PCR (N=205; N=77); primary and secondary Negative Percent Agreement (NPA; N=87; N=79); PPA compared to SARS-CoV-2 serology (N=55); and pathogen cross-reactivity (N=38). The real-world performance of the test was also evaluated in a retrospective review of test ordering (N=69) at a single primary care clinic in Park City, Utah. Results In validation studies, T-Detect COVID demonstrated high PPA (97.1% ≥15 days from diagnosis) in subjects with prior PCR-confirmed SARS-CoV-2 infection; high NPA (~100%) in SARS-CoV-2 negative cases; equivalent or higher PPA with RT-PCR compared to two commercial EUA antibody tests; and no evidence of pathogen cross-reactivity. Review of assay use in a single clinic showed 100% PPA with RT-PCR in individuals with past confirmed SARS-CoV-2 vs. 85.7% for antibody testing, 100% agreement with positive antibody results, and positive results in 2/4 convalescent subjects with seroreversion to a negative antibody. In addition, 12/69 (17.3%) individuals with absent or negative RT-PCR tested positive by T-Detect COVID, nearly all of whom had compatible symptoms and/or exposure. TCR positivity was observed up to 12+ months (median 118 days) from the date of positive RT-PCR. Conclusion A T-cell immunosequencing assay shows high clinical performance for identifying past SARS-CoV-2 infection from whole blood samples. This assay can provide additional insights on the SARS-CoV-2 immune response, with practical implications for clinical management, risk stratification, surveillance, assessing vaccine immunity, and understanding long-term sequelae. Disclosures Sudeb C. Dalai, MD, PhD, Adaptive Biotechnologies (Employee, Shareholder) Jennifer N. Dines, MD, Adaptive Biotechnologies (Employee, Shareholder) Thomas M. Snyder, PhD, Adaptive Biotechnologies (Employee, Shareholder) Rachel M. Gittelman, PhD, Adaptive Biotechnologies (Employee, Shareholder) Tera Eerkes, PhD, Adaptive Biotechnologies (Employee, Shareholder) Pashmi Vaney, PhD, Adaptive Biotechnologies (Employee, Shareholder) Sally Howard, PhD, Adaptive Biotechnologies (Employee, Shareholder) Kipp Akers, PhD, Adaptive Biotechnologies (Employee, Shareholder) Lynell Skewis, PhD, Adaptive Biotechnologies (Employee, Shareholder) Anthony Monteforte, PhD, Adaptive Biotechnologies (Employee, Shareholder) Pamela R. Witte, PhD, Adaptive Biotechnologies (Employee, Shareholder) Cristina Wolf, PhD, Adaptive Biotechnologies (Employee, Shareholder) Hans Nesse, PhD, Adaptive Biotechnologies (Employee, Shareholder) Jia Qadeer, PhD, Adaptive Biotechnologies (Employee, Shareholder) Sarah Duffy, PhD, Adaptive Biotechnologies (Employee, Shareholder) Emily Svejnoha, PhD, Adaptive Biotechnologies (Employee, Shareholder) Caroline Taromino, PhD, Adaptive Biotechnologies (Employee, Shareholder) Ian M. Kaplan, PhD, Adaptive Biotechnologies (Employee, Shareholder) John Alsobrook, MD, Adaptive Biotechnologies (Employee, Shareholder) Thomas Manley, MD, Adaptive Biotechnologies (Employee, Shareholder) Lance Baldo, MD, Adaptive Biotechnologies (Employee, Shareholder, Leadership Interest) |
