Your browser doesn't support javascript.
loading
Magnitude and Dynamics of the T-Cell Response to SARS-CoV-2 Infection at Both Individual and Population Levels
Thomas M Snyder; Rachel M Gittelman; Mark Klinger; Damon H May; Edward J Osborne; Ruth Taniguchi; H Jabran Zahid; Ian M Kaplan; Jennifer N Dines; Matthew N Noakes; Ravi Pandya; Xiaoyu Chen; Summer Elasady; Emily Svejnoha; Peter Ebert; Mitchell W Pesesky; Patricia De Almeida; Hope O'Donnell; Quinn DeGottardi; Gladys Keitany; Jennifer Lu; Allen Vong; Rebecca Elyanow; Paul Fields; Julia Greissl; Lance Baldo; Simona Semprini; Claudio Cerchione; Fabio Nicolini; Massimiliano Mazza; Ottavia M Delmonte; Kerry Dobbs; Rocio Laguna-Goya; Gonzalo Carreño-Tarragona; Santiago Barrio; Luisa Imberti; Alessandra Sottini; Eugenia Quiros-Roldan; Camillo Rossi; Andrea Biondi; Laura Rachele Bettini; Mariella D'Angio; Paolo Bonfanti; Miranda F Tompkins; Camille Alba; Clifton Dalgard; Vittorio Sambri; Giovanni Martinelli; Jason D Goldman; James R Heath; Helen C Su; Luigi D Notarangelo; Estela Paz-Artal; Joaquin Martinez-Lopez; Jonathan M Carlson; Harlan S Robins.
Afiliación
  • Thomas M Snyder; Adaptive Biotechnologies
  • Rachel M Gittelman; Adaptive Biotechnologies
  • Mark Klinger; Adaptive Biotechnologies
  • Damon H May; Adaptive Biotechnologies
  • Edward J Osborne; Adaptive Biotechnologies
  • Ruth Taniguchi; Adaptive Biotechnologies
  • H Jabran Zahid; Microsoft Research
  • Ian M Kaplan; Adaptive Biotechnologies
  • Jennifer N Dines; Adaptive Biotechnologies
  • Matthew N Noakes; Adaptive Biotechnologies
  • Ravi Pandya; Microsoft Research
  • Xiaoyu Chen; Adaptive Biotechnologies
  • Summer Elasady; Adaptive Biotechnologies
  • Emily Svejnoha; Adaptive Biotechnologies
  • Peter Ebert; Adaptive Biotechnologies
  • Mitchell W Pesesky; Adaptive Biotechnologies
  • Patricia De Almeida; Adaptive Biotechnologies
  • Hope O'Donnell; Adaptive Biotechnologies
  • Quinn DeGottardi; Adaptive Biotechnologies
  • Gladys Keitany; Adaptive Biotechnologies
  • Jennifer Lu; Adaptive Biotechnologies
  • Allen Vong; Adaptive Biotechnologies
  • Rebecca Elyanow; Adaptive Biotechnologies
  • Paul Fields; Adaptive Biotechnologies
  • Julia Greissl; Microsoft Research
  • Lance Baldo; Adaptive Biotechnologies
  • Simona Semprini; University of Bologna
  • Claudio Cerchione; Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS
  • Fabio Nicolini; Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS
  • Massimiliano Mazza; Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS
  • Ottavia M Delmonte; National Institute of Allergy and Infectious Diseases, National Institutes of Health
  • Kerry Dobbs; National Institute of Allergy and Infectious Diseases, National Institutes of Health
  • Rocio Laguna-Goya; Hospital 12 de Octubre, i+12, CNIO, Complutense University
  • Gonzalo Carreño-Tarragona; Hospital 12 de Octubre, i+12, CNIO, Complutense University
  • Santiago Barrio; Hospital 12 de Octubre, i+12, CNIO, Complutense University
  • Luisa Imberti; ASST Spedali Civili di Brescia and University of Brescia
  • Alessandra Sottini; ASST Spedali Civili di Brescia and University of Brescia
  • Eugenia Quiros-Roldan; ASST Spedali Civili di Brescia and University of Brescia
  • Camillo Rossi; ASST Spedali Civili di Brescia and University of Brescia
  • Andrea Biondi; MetabERN-University of Milano-Bicocca-Fondazione MBBM-Ospedale San Gerardo
  • Laura Rachele Bettini; MetabERN-University of Milano-Bicocca-Fondazione MBBM-Ospedale San Gerardo
  • Mariella D'Angio; MetabERN-University of Milano-Bicocca-Fondazione MBBM-Ospedale San Gerardo
  • Paolo Bonfanti; University of Milano-Bicocca-Ospedale San Gerardo
  • Miranda F Tompkins; Uniformed Services University of the Health Sciences
  • Camille Alba; Uniformed Services University of the Health Sciences
  • Clifton Dalgard; Uniformed Services University of the Health Sciences
  • Vittorio Sambri; University of Bologna
  • Giovanni Martinelli; Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS
  • Jason D Goldman; Swedish Medical Center, and University of Washington
  • James R Heath; Institute for Systems Biology
  • Helen C Su; National Institute of Allergy and Infectious Diseases, National Institutes of Health
  • Luigi D Notarangelo; National Institute of Allergy and Infectious Diseases, National Institutes of Health
  • Estela Paz-Artal; Hospital 12 de Octubre, i+12, CNIO, Complutense University
  • Joaquin Martinez-Lopez; Hospital 12 de Octubre, i+12, CNIO, Complutense University
  • Jonathan M Carlson; Microsoft Research
  • Harlan S Robins; Adaptive Biotechnologies
Preprint en En | PREPRINT-MEDRXIV | ID: ppmedrxiv-20165647
Artículo de revista
Un artículo publicado en revista científica está disponible y probablemente es basado en este preprint, por medio del reconocimiento de similitud realizado por una máquina. La confirmación humana aún está pendiente.
Ver artículo de revista
ABSTRACT
T cells are involved in the early identification and clearance of viral infections and also support the development of antibodies by B cells. This central role for T cells makes them a desirable target for assessing the immune response to SARS-CoV-2 infection. Here, we combined two high-throughput immune profiling methods to create a quantitative picture of the T-cell response to SARS-CoV-2. First, at the individual level, we deeply characterized 3 acutely infected and 58 recovered COVID-19 subjects by experimentally mapping their CD8 T-cell response through antigen stimulation to 545 Human Leukocyte Antigen (HLA) class I presented viral peptides (class II data in a forthcoming study). Then, at the population level, we performed T-cell repertoire sequencing on 1,815 samples (from 1,521 COVID-19 subjects) as well as 3,500 controls to identify shared "public" T-cell receptors (TCRs) associated with SARS-CoV-2 infection from both CD8 and CD4 T cells. Collectively, our data reveal that CD8 T-cell responses are often driven by a few immunodominant, HLA-restricted epitopes. As expected, the T-cell response to SARS-CoV-2 peaks about one to two weeks after infection and is detectable for at least several months after recovery. As an application of these data, we trained a classifier to diagnose SARSCoV-2 infection based solely on TCR sequencing from blood samples, and observed, at 99.8% specificity, high early sensitivity soon after diagnosis (Day 3-7 = 85.1% [95% CI = 79.9-89.7]; Day 8-14 = 94.8% [90.7-98.4]) as well as lasting sensitivity after recovery (Day 29+/convalescent = 95.4% [92.1-98.3]). These results demonstrate an approach to reliably assess the adaptive immune response both soon after viral antigenic exposure (before antibodies are typically detectable) as well as at later time points. This blood-based molecular approach to characterizing the cellular immune response has applications in clinical diagnostics as well as in vaccine development and monitoring.
Licencia
cc_by_nc_nd
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Diagnostic_studies / Experimental_studies / Prognostic_studies Idioma: En Año: 2020 Tipo del documento: Preprint
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Diagnostic_studies / Experimental_studies / Prognostic_studies Idioma: En Año: 2020 Tipo del documento: Preprint