Single-cell RNA sequencing analysis reveals exercise-induced transcriptional dynamics in half-marathon runners

Previous studies in sports science suggested that regular exercise has a positive impact on human health. However, the effects of endurance sports and their underlying mechanisms are still not com-pletely understood. One of the main debates regards the modulation of immune dynamics in high-intensity exercise. As part of the "Run 4 Science" project in Verona, Italy, we conducted a single-cell RNA sequencing analysis on half-marathon amateur runners to investigate the transcriptional dynam-ics of peripheral blood mononuclear cells following endurance exercise. Blood samples were collected from 4 participants before and after running a half-marathon to carry out a comprehensive tran-scriptomic analysis of immune cells at the single-cell level. Our analysis revealed significant altera-tions in the transcriptional profiles following endurance physical exercise. Modulations in myeloid cells suggested the activation of stress response (6 related pathways, p-value < 0.04) and pathways related to viral processes (4 related pathways, p-value < 0.03), while in lymphoid cells they hinted to a shift towards immune activation (24 related pathways, p-value < 0.01). Additionally, transcriptional changes in platelets point to an activation of the coagulation process (5 related pathways, p-value < 0.005). Single-cell data was also analysed following a pseudo-bulk approach (i.e., simulating a bulk RNAseq experiment) to gain further biological insights. Our findings suggest that a pseudo-bulk analysis could offer complementary findings to classical single-cell analysis methods and demonstrate that endurance physical exercise, such as running a half-marathon, induces substantial changes in the transcriptional dynamics of immune cells. These insights contribute to a better understanding of the immune modulation mediated by endurance exercise and may inform future training routines or nutri-tional guidelines based on individual gene expression levels.