학술논문
Development of a T cell-based immunodiagnostic system to effectively distinguish SARS-CoV-2 infection and COVID-19 vaccination status
Document Type
article
Author
Yu, Esther Dawen; Wang, Eric; Garrigan, Emily; Goodwin, Benjamin; Sutherland, Aaron; Tarke, Alison; Chang, James; Gálvez, Rosa Isela; Mateus, Jose; Ramirez, Sydney I; Rawlings, Stephen A; Smith, Davey M; Filaci, Gilberto; Frazier, April; Weiskopf, Daniela; Dan, Jennifer M; Crotty, Shane; Grifoni, Alba; Sette, Alessandro; da Silva Antunes, Ricardo
Source
Cell Host & Microbe. 30(3)
Subject
Language
Abstract
Both SARS-CoV-2 infections and COVID-19 vaccines elicit memory T cell responses. Here, we report the development of 2 pools of experimentally defined SARS-CoV-2 T cell epitopes that, in combination with spike, were used to discriminate 4 groups of subjects with different SARS-CoV-2 infection and COVID-19 vaccine status. The overall T cell-based classification accuracy was 89.2% and 88.5% in the experimental and validation cohorts. This scheme was applicable to different mRNA vaccines and different lengths of time post infection/post vaccination and yielded increased accuracy when compared to serological readouts. T cell responses from breakthrough infections were also studied and effectively segregated from vaccine responses, with a combined performance of 86.6% across all 239 subjects from the 5 groups. We anticipate that a T cell-based immunodiagnostic scheme to classify subjects based on their vaccination and natural infection history will be an important tool for longitudinal monitoring of vaccinations and for establishing SARS-CoV-2 correlates of protection.