Biomarkers of Knee Joint Healing in Adolescents with Anterior Cruciate Ligament Injuries

Abstract

Objective: Anterior cruciate ligament (ACL) injuries are increasing in adolescents and increase the risk for early-onset knee osteoarthritis (OA). Biomarkers can be a non-invasive measure to assess physiological properties following knee injury or trauma. The objective of this thesis was to i) perform a systematic review to determine the most studied biomarkers of knee healing following ACL reconstruction (ACLR), and age of these patients, and ii) explore the feasibility of measuring these biomarkers in adolescents with ACL injuries. Design: Studies were included if i) participants underwent ACLR, and ii) at least one biomarker of healing was measured. Participant age, sample(s) collected, and biomarker(s) studied were recorded. Interleukin-6 (IL-6), c-terminal crosslinking telopeptide of type II collagen (CTX-II) and procollagen type II collagen propeptide (PIICP) were then measured using ELISA in adolescents prior to ACLR in urine (u) and synovial fluid (sf). Spearman’s Rho (rs) coefficients were calculated to determine the association between uCTX-II/sfCTX-II, and uIL-6/sfIL-6. A ratio of PIICP: CTX-II was calculated to represent the ratio of cartilage synthesis to degradation. Results: The review produced six studies evaluating healing following ACLR. IL-6 and CTX-II were the most studied (3/6 studies), and only one study included adolescents (age 19.6±4.5). Due to multiple undetectable biomarker levels, we could only report rs for uCTX-II/sfCTX-II (rs = -.200, p-value = .800, n=4). We also reported a ratio for sfPIICP: sfCTX-II (23.06 ±19.23). Conclusion: Exploring biomarkers in adolescents was motivated by their unique physiology due to puberty, and this was the first study to do so. The findings from this pilot study indicate that further analysis is required to determine optimal sample preparation. This will allow for reliable results while studying the feasibility of these biomarkers during ACLR recovery. This insight can ensure more informed decision making by clinicians clearing patients for return-to-activity.