Can Non-Conventional Blood Biomarkers Improve Running Performance Prediction? A Proof of Concept.

Conventional measures such as maximal oxygen uptake (V˙O(2)max), although widely regarded as the gold standard, do not fully capture endurance performance. Therefore, this study investigated whether a 2.4 km Cooper test elicits measurable changes in blood-based biomarkers (decorin, hypoxanthine, N-terminal pro-B-type natriuretic peptide (NT-proBNP), brain-derived neurotrophic factor (BDNF)) and whether integrating these markers may improve performance prediction in a heterogeneous sample of runners. In this cross-sectional observational proof-of-concept study, thirty-three participants completed the 2.4 km Cooper test, with venous blood samples collected at baseline and post-test. Non-parametric statistical tests were used to assess biomarker changes (α = 0.05), with exploratory correlations evaluated using Spearman's ρ. To examine whether blood-based biomarkers provide information beyond conventional field-based predictors, Ridge regression with leave-one-out cross-validation (LOOCV) was applied to predict 10 km race time in a subsample of 24 participants who completed a 10 km race two weeks later. The Cooper test elicited significant post-test changes in decorin, hypoxanthine, and BDNF (all p < 0.001). Higher post-test decorin (ρ = -0.44, p = 0.010) and hypoxanthine (ρ = -0.37, p = 0.034) were associated with faster Cooper test performance. In Ridge regression analysis, adding post-test decorin to conventional predictors resulted in a minor reduction of 10 km race time prediction error. This study suggests that decorin may provide complementary information to a conventional field-based test in heterogeneous recreational runners. Post-test decorin marginally contributed to 10 km race performance prediction beyond established predictors, though external validation and comparison with directly measured V˙O(2)max are needed before practical application can be recommended.