Disturbances in Metabolic Pathways and the Identification of a Potential Biomarker Panel for Early Cartilage Degeneration in a Rabbit Anterior Cruciate Ligament Transection Model

Objective: This study aimed to assess the association between synovial fluid (SF) metabolites and magnetic resonance imaging (MRI) measurements of cartilage biochemical composition to identify potential SF biomarkers for detecting the early onset of cartilage degeneration in a rabbit model.

Methods: Both knees of 12 New Zealand White rabbits were used. The anterior cruciate ligament transection (ACLT) model was performed on right knees, and the sham surgery on left knees. MRI UTE-T2* scanning and SF sample collection were performed on ACLT knees at 4 and 8 weeks postsurgery and on sham surgery knees at 4 weeks postsurgery. Ultra-performance liquid chromatography-mass spectrometry and multivariate statistical analysis were used to distinguish samples in three groups. Pathway and receiver operating characteristic analyses were utilized to identify potential metabolite biomarkers.

Results: There were 12 knees in sham surgery models, 11 in ACLT models at 4 weeks postsurgery, and 10 in ACLT models at 8 weeks postsurgery. UTE-T2* values for the lateral tibia cartilage showed significant decreases over the study period. Levels of 103 identified metabolites in SF were markedly different among three groups. Furthermore, 24 metabolites were inversely correlated with UTE-T2* values of the lateral tibia cartilage, while hippuric acid was positively correlated with UTE-T2* values of the lateral tibia cartilage. Among 25 potential markers, N1-acetylspermidine, 2-amino-1,3,4-octadecanetriol, l-phenylalanine, 5-hydroxy-l-tryptophan, and l-tryptophan were identified as potential biomarkers with high area under the curve values and Pearson correlation coefficients.

Conclusion: Five differential metabolites in SF were found as potential biomarkers for the early detection of cartilage degeneration in the rabbit ACLT model.

Keywords: biomarker; cartilage; degeneration; magnetic resonance imaging; metabolomics.