BACKGROUND: While diagnostic, therapeutic, and vaccine development in the COVID-19 pandemic has proceeded at unprecedented speed, critical gaps in our understanding of the immune response to SARS-CoV-2 remain unaddressed by current diagnostic strategies. METHODS: A statistical classifier for identifying prior SARS-CoV-2 infection was trained using >4000 SARS-CoV-2-associated TCRβ sequences identified by comparing 784 cases and 2447 controls from 5 independent cohorts. The T-Detect™ COVID assay applies this classifier to TCR repertoires sequenced from blood samples to yield a binary assessment of past infection. Assay performance was assessed in 2 retrospective (n = 346; n = 69) and 1 prospective cohort (n = 87) to determine positive percent agreement (PPA) and negative percent agreement (NPA). PPA was compared to 2 commercial serology assays, and pathogen cross-reactivity was evaluated. RESULTS: T-Detect COVID demonstrated high PPA in individuals with prior RT-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 2 commercial serology tests, and no evidence of pathogen cross-reactivity. CONCLUSION: T-Detect COVID is a novel T-cell immunosequencing assay demonstrating high clinical performance for identification of recent or prior SARS-CoV-2 infection from blood samples, with implications for clinical management, risk stratification, surveillance, and understanding protective immunity and long-term sequelae.
BACKGROUND: While diagnostic, therapeutic, and vaccine development in the COVID-19 pandemic has proceeded at unprecedented speed, critical gaps in our understanding of the immune response to SARS-CoV-2 remain unaddressed by current diagnostic strategies. METHODS: A statistical classifier for identifying prior SARS-CoV-2 infection was trained using >4000 SARS-CoV-2-associated TCRβ sequences identified by comparing 784 cases and 2447 controls from 5 independent cohorts. The T-Detect™ COVID assay applies this classifier to TCR repertoires sequenced from blood samples to yield a binary assessment of past infection. Assay performance was assessed in 2 retrospective (n = 346; n = 69) and 1 prospective cohort (n = 87) to determine positive percent agreement (PPA) and negative percent agreement (NPA). PPA was compared to 2 commercial serology assays, and pathogen cross-reactivity was evaluated. RESULTS: T-Detect COVID demonstrated high PPA in individuals with prior RT-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 2 commercial serology tests, and no evidence of pathogen cross-reactivity. CONCLUSION: T-Detect COVID is a novel T-cell immunosequencing assay demonstrating high clinical performance for identification of recent or prior SARS-CoV-2 infection from blood samples, with implications for clinical management, risk stratification, surveillance, and understanding protective immunity and long-term sequelae.
Authors: Mikhail V Pogorelyy; Elisa Rosati; Anastasia A Minervina; Robert C Mettelman; Alexander Scheffold; Andre Franke; Petra Bacher; Paul G Thomas Journal: Cell Rep Med Date: 2022-07-01
Authors: Rachel M Gittelman; Enrico Lavezzo; Thomas M Snyder; H Jabran Zahid; Cara L Carty; Rebecca Elyanow; Sudeb Dalai; Ilan Kirsch; Lance Baldo; Laura Manuto; Elisa Franchin; Claudia Del Vecchio; Monia Pacenti; Caterina Boldrin; Margherita Cattai; Francesca Saluzzo; Andrea Padoan; Mario Plebani; Fabio Simeoni; Jessica Bordini; Nicola I Lorè; Dejan Lazarević; Daniela M Cirillo; Paolo Ghia; Stefano Toppo; Jonathan M Carlson; Harlan S Robins; Andrea Crisanti; Giovanni Tonon Journal: JCI Insight Date: 2022-05-23
Authors: Rebecca Elyanow; Thomas M Snyder; Sudeb C Dalai; Rachel M Gittelman; Jim Boonyaratanakornkit; Anna Wald; Stacy Selke; Mark H Wener; Chihiro Morishima; Alexander L Greninger; Michael Gale; Tien-Ying Hsiang; Lichen Jing; Michael R Holbrook; Ian M Kaplan; H Jabran Zahid; Damon H May; Jonathan M Carlson; Lance Baldo; Thomas Manley; Harlan S Robins; David M Koelle Journal: JCI Insight Date: 2022-05-23
Authors: Martin J Scurr; Wioleta M Zelek; George Lippiatt; Michelle Somerville; Stephanie E A Burnell; Lorenzo Capitani; Kate Davies; Helen Lawton; Thomas Tozer; Tara Rees; Kerry Roberts; Mererid Evans; Amanda Jackson; Charlotte Young; Lucy Fairclough; Paddy Tighe; Mark Wills; Andrew D Westwell; B Paul Morgan; Awen Gallimore; Andrew Godkin Journal: Immunology Date: 2021-12-06 Impact factor: 7.215
Authors: Robert L Murphy; Eustache Paramithiotis; Scott Sugden; Todd Chermak; Bruce Lambert; Damien Montamat-Sicotte; John Mattison; Steve Steinhubl Journal: Front Immunol Date: 2022-09-20 Impact factor: 8.786