Preliminary insights into salivary proteomic versus targeted biomarker profiles associated with acute physical fatigue

Introduction Physical fatigue is a key determinant of operational readiness in tactical athletes. Hormonal, immune, and enzymatic biomarkers have been proposed for fatigue assessment, but reliability can be affected by external factors. Therefore, this study aimed to compare targeted stress-related biomarkers versus proteins identified via untargeted salivary proteomics for classifying acute physical fatigue.

Ten recreationally active adults (6M, 4F) completed a fatiguing protocol within a 3-day sample collection window. Saliva samples were analyzed for targeted biomarkers via commercial immunoassays and proteins via untargeted liquid chromatography-mass spectrometry. Support vector machine models classified pre-versus post-fatigue state and were extended to predict fatigue probabilities across the full protocol. Pathway enrichment analysis characterized systems-level biological processes represented by fatigue-associated proteins, and Spearman correlations were computed between protein abundance changes and composite performance decline.

The protein panel achieved 90% classification accuracy versus 80% by the targeted biomarkers, with superior sensitivity and higher predicted fatigue probability immediately post-fatigue. Models displayed divergent recovery trajectories, suggesting the two panels capture different biological timescales of the fatigue response. Pathway enrichment identified immune activation as the dominant systems-level signal with secondary clusters reflecting cytoskeletal remodeling and protein trafficking, while three proteins showed significant inverse correlations with performance decline.

Salivary proteins identified through untargeted proteomics demonstrated greater sensitivity for detecting acute physical fatigue than traditional stress-related biomarkers. These findings support non-invasive proteomic monitoring of fatigue in tactical settings. Future studies should validate these findings in larger, more diverse populations and assess applicability for chronic fatigue monitoring. Competing Interest Statement The authors have declared no competing interest. Footnotes The analytical approach has been changed to address all time points and not only pre/post fatigue.