Longitudinal Assessment of TCR Repertoires in Recipients of Inactivated SARS-CoV-2 Vaccines: An Artificial Intelligence-Guided Study

T cells play a crucial role in mitigating disease severity during SARS-CoV-2 infection and in shaping long-term immune memory. However, the precise molecular immune response involving T-cell receptor (TCR) repertoire changes following full vaccination, and evaluating vaccine efficacy through TCR analysis, remains incompletely understood. In this study, we conducted a 10-month longitudinal investigation of individuals who received SARS-CoV-2 inactivated vaccines and developed a vaccine efficacy evaluation model. Through the advanced large language artificial intelligence method, we identified vaccine-specific TCR clones, 3 V genes, 20 V-J combinations, and 3 epitopes, and traced their longitudinal development. The vaccine-specific TCR clones expanded to peak levels after the second vaccine dose and remained detectable in most subjects at 10 months. Utilizing vaccine-specific TCRs as novel markers, we constructed a vaccine efficacy evaluation model that predicts antibody levels with a mean AUC of 0.96, highlighting the relationship between vaccine-specific TCRs and antibodies. Our findings reveal the longitudinal patterns of vaccine-specific TCR clones and the potential of the efficacy evaluation model built upon them.