Synovial Fluid Metabolites Differentiate between Septic and Nonseptic Joint Pathologies

Abstract

Osteoarthritis (OA), osteochondrosis (OC), and synovial sepsis in horses cause loss of function and pain. Reliable biomarkers are required to achieve accurate and rapid diagnosis, with synovial fluid (SF) holding a unique source of biochemical information. Nuclear magnetic resonance (NMR) spectroscopy allows global metabolite analysis of a small volume of SF, with minimal sample preprocessing using a noninvasive and nondestructive method. Equine SF metabolic profiles from both nonseptic joints (OA and OC) and septic joints were analyzed using 1D ¹H NMR spectroscopy. Univariate and multivariate statistical analyses were used to identify differential metabolite abundance between groups. Metabolites were annotated via ¹H NMR using 1D NMR identification software Chenomx, with identities confirmed using 1D ¹H and 2D ¹H ¹³C NMR. Multivariate analysis identified separation between septic and nonseptic groups. Acetate, alanine, citrate, creatine phosphate, creatinine, glucose, glutamate, glutamine, glycine, phenylalanine, pyruvate, and valine were higher in the nonseptic group, while glycylproline was higher in sepsis. Multivariate separation was primarily driven by glucose; however, partial-least-squares discriminant analysis plots with glucose excluded demonstrated the remaining metabolites were still able to discriminate the groups. This study demonstrates that a panel of synovial metabolites can distinguish between septic and nonseptic equine SF, with glucose the principal discriminator.

Keywords: equine; metabolomics; nuclear magnetic resonance; osteoarthritis; osteochondrosis; sepsis; synovial fluid.

Figure 1

Quantile plots of OA/OC (Non-Septic), sepsis, and all spectra depicting the median spectral plot (black line) and variation from the median within each group (yellow to red scale) for the full spectral range (9.0–0.5 ppm) and more detailed regions depicting selected peaks from three differentially abundant metabolites, glucose, glutamine, and alanine. Variation within the full spectra can most clearly be seen at 0.8 ppm.

Figure 2

Principal component analysis (PCA) scores plot of septic (blue) and nonseptic (red) SF samples. Samples with meniscal tear or hematogenous sepsis subdiagnoses for OA and sepsis, respectively, are highlighted in each group with a thick black outline, OC are distinguished from OA by highlight shade.

Figure 3

(a) PLS-DA plots of OA/OC versus sepsis using only metabolite annotated buckets: first two components shown out of a total of two components used to fit the model (R² = 0.85, Q² = 0.72). (b) VIP scores for the 25 most influential buckets of PLS-DA. (c) PLS-DA plots of OA/OCD versus sepsis using only metabolite annotated/identified buckets with all glucose buckets excluded: first two components shown. It should be noted that only one component was used to fit the model (R² = 0.70, Q² = 0.45). (d) VIP scores for the 25 most influential buckets of glucose-excluded PLS-DA.

Figure 4

Boxplots of key metabolites, shown as relative intensities corresponding to the most representative peak for each metabolite. t test: ∗ = p < 0.05, ∗∗ = p < 0.01, and ∗∗∗ = p < 0.001.