Distinguishing COVID-19 infection and vaccination history by T cell reactivity
Yu, E. D.; Wang, E.; Garrigan, E.; Goodwin, B.; Sutherland, A.; Chang, J.; Galvez, R. I.; Mateus, J.; Rawlings, S. A.; Smith, D. M.; Frazier, A.; Weiskopf, D.; Dan, J. M.; Crotty, S.; Grifoni, A.; Sette, A.; da Silva Antunes, R.
Show abstract
SARS-CoV-2 infection and COVID-19 vaccines elicit memory T cell responses. Here, we report the development of two new pools of Experimentally-defined T cell epitopes derived from the non-spike Remainder of the SARS-CoV-2 proteome (CD4RE and CD8RE). The combination of T cell responses to these new pools and Spike (S) were used to discriminate four groups of subjects with different SARS-CoV-2 infection and COVID-19 vaccine status: non-infected, non-vaccinated (I-V-); infected and non-vaccinated (I+V-); infected and then vaccinated (I+V+); and non-infected and vaccinated (I-V+). The overall classification accuracy based on 30 subjects/group was 89.2% in the original cohort and 88.5% in a validation cohort of 96 subjects. The T cell classification scheme was applicable to different mRNA vaccines, and different lengths of time post-infection/post-vaccination. T cell responses from breakthrough infections (infected vaccinees, V+I+) were also effectively segregated from the responses of vaccinated subjects using the same classification tool system. When all five groups where combined, for a total of 239 different subjects, the classification scheme performance was 86.6%. We anticipate that a T cell-based immunodiagnostic scheme able to classify subjects based on their vaccination and natural infection history will be an important tool for longitudinal monitoring of vaccination and aid in establishing SARS-CoV-2 correlates of protection.
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