Development of a T cell-based immunodiagnostic system to effectively distinguish SARS-CoV-2 infection and COVID-19 vaccination status

开发一种基于T细胞的免疫诊断系统,以有效区分SARS-CoV-2感染和COVID-19疫苗接种状态

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作者:Esther Dawen Yu ,Eric Wang ,Emily Garrigan ,Benjamin Goodwin ,Aaron Sutherland ,Alison Tarke ,James Chang ,Rosa Isela Gálvez ,Jose Mateus ,Sydney I Ramirez ,Stephen A Rawlings ,Davey M Smith ,Gilberto Filaci ,April Frazier ,Daniela Weiskopf ,Jennifer M Dan ,Shane Crotty ,Alba Grifoni ,Alessandro Sette ,Ricardo da Silva Antunes

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.

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