Aims. To investigate the correlations among cytokines and regulatory T cells (T-regs) in ankylosing spondylitis (AS) patients, and their changes after anti-tumour necrosis factor-α (TNF-α) treatment. Methods. We included 72 AS patients with detailed medical records, disease activity score (Bath Ankylosing Spondylitis Disease Activity Index), functional index (Bath Ankylosing Spondylitis Functional Index), and laboratory data (interleukin (IL)-2, IL-4, IL-10, TNF-α, interferon (IFN)-γ, transforming growth factor (TGF)-β, ESR, and CRP). Their peripheral blood mononuclear cells (PBMCs) were marked with anti-CD4, anti-CD25, and anti-FoxP3 antibodies, and triple positive T cells were gated by flow cytometry as T-regs. Their correlations were calculated and the changes after anti-TNF-α therapy were compared. Results. The frequency of T-regs in PBMCs was positively correlated to ESR and CRP in AS (r = 0.35 and 0.43; p = 0.032 and 0.027, respectively), and there was also a significant correlation between serum level of TNF-α and CRP (p = 0.041). The frequency of T-regs in PBMCs positively correlated to serum levels of TNF-α, IL-10, and TGF-β, while IL-2, IL-4, and IFN-γ showed opposite results. After anti-TNF-α treatment, there were significantly lower serum levels of TNF-α, IL-10, TGF-β, and frequency of T-regs in PBMCs among these AS patients (p = 0.026, 0.032, 0.029, and 0.037, respectively). Conclusion. In AS patients, proinflammatory cytokine may give positive feedback to induce more T-reg production and anti-inflammatory cytokine secretion to suppress this inflammatory status, and they can be reversed by anti-TNF-α therapy. However, the detailed interactions among T-regs and complex cytokine networks in autoinflammatory diseases still need more studies and further functional assay. Cite this article: Bone Joint Res 2023;12(2):133–137

Aims

Metabolic profiling is a top-down method of analysis looking at metabolites, which are the intermediate or end products of various cellular pathways. Our primary objective was to perform a systematic review of the published literature to identify metabolites in human synovial fluid (HSF), which have been categorized by metabolic profiling techniques. A secondary objective was to identify any metabolites that may represent potential biomarkers of orthopaedic disease processes.