Coordinating immune responses - humoral and cellular - is vital for protection against severe Covid-19. Our study evaluates a multicytokine CD4+T cell signature's predictive for post-vaccinal serological and CD8+T cell responses. A cytokine signature composed of four cytokines (IL-2, TNF-α, IP10, IL-9) excluding IFN-γ, and generated through machine learning, effectively predicted the CD8+T cell response following mRNA-1273 or BNT162b2 vaccine administration. Its applicability extends to murine vaccination models, encompassing diverse immunization routes (such as intranasal) and vaccine platforms (including adjuvanted proteins). Notably, we found correlation between CD4+T lymphocyte-produced IL-21 and the humoral response. Consequently, we propose a test that offers a rapid overview of integrated immune responses. This approach holds particular relevance for scenarios involving immunocompromised patients because they often have low cell counts (lymphopenia) or pandemics. This study also underscores the pivotal role of CD4+T cells during a vaccine response and highlights their value in vaccine immunomonitoring.
Keywords: Health sciences; Immunity; Machine learning; Mathematical biosciences; Virology.
© 2024 The Authors.