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Background Osteoarthritis (OA) is a common, heterogeneous whole-joint disease contributing to significant morbidity with variable trajectories of symptom progression. Early detrimental joint changes may be identified using molecular biomarkers in serum or synovial fluid. When measuring the former, biomarkers are at risk of systemic dilution, with the latter technically challenging with increased associated risks. In addition, biomarker concentrations are also potentially influenced by extrinsic factors, including exercise. This case-control pilot study aims to understand the influence of sampling location and sub-maximal exercise on serum biomarker concentrations. Methods Recruited participants either had a recent lower-limb musculoskeletal injury (INJ), established knee OA (KOA) or were controls (CON). Serum was taken from their antecubital fossa (ACF, ‘Arm 1’), their great saphenous vein local to their ipsilateral knee (‘Knee’), and after a ten-minute non-weight-bearing exercise, their ACF again (‘Arm 2’). Serum biomarker assays were performed, with results analysed for differences between condition (CON v KOA v INJ), location (Arm 1 v Knee) and pre-post exercise (Arm 1 v Arm 2). Results Thirty-two participants were recruited (CON n=12, KOA n=10, INJ n=10), 81% male, median age 28 (IQR: 25-43) and BMI 23.9 (IQR: 22.5-26.3). Interleukin-(IL)-1β concentration was lower in the KOA group (p=0.004). IL-6 (1.65 and 0.96 ng/L) and leptin (12.65 and 7.01 ug/L) were higher in the Knee sample than Arm 1 (both p<0.001). COMP (173.06 and 190.27 ug/L, p=0.005) and CTX-II (0.68 and 0.83 ug/L, p=0.02) increased following exercise. Further differences were noted when the location and exercise intervention analyses were stratified by condition. Conclusions These novel sampling techniques and easy, accessible 10-minute exercise protocol are suitable for a wide range of settings. Both sampling location and precedent non-weight-bearing sub-maximal exercise influenced serum biomarker concentrations in this pilot case-control study. Optimising these sampling variables could improve the sensitivity of biomarker analysis following validation in a larger population.

Original publication

DOI

10.12688/f1000research.159928.1

Type

Journal

F1000Research

Publisher

F1000 Research Ltd

Publication Date

04/04/2025

Volume

14

Pages

395 - 395