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Updated: Jan 15, 2026

Multiplex Cytokine Profiling of Stimulated Mouse Splenocytes Using a Cytometric Bead-based Immunoassay Platform
Published on: November 9, 2017
Serum Levels of 54 Cytokines and Chemokines Reveal Distinct Inflammatory Signatures in Ankylosing Spondylitis
Huan Li1,2,3,4, Ting Wang1,2,3, Mingze Li1,2,3
1Department of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Background:
Ankylosing spondylitis (AS) is a chronic autoimmune inflammatory disorder predominantly involving the axial skeleton. Understanding the cytokine and chemokine signatures in AS is crucial for elucidating disease mechanisms and identifying potential diagnostic biomarkers.
Methods:
Serum samples from 31 AS patients and 20 age-matched healthy controls (HCs) were analyzed. The concentrations of 54 cytokines, chemokines, and angiogenesis-related factors were measured using a Meso Scale Discovery (MSD) electrochemiluminescence immunoassay. Data analysis included statistical comparison of serum cytokine levels, heatmap clustering, principal component analysis (PCA), and receiver operating characteristic (ROC) curve analysis. Validation was performed using peripheral blood mononuclear cells (PBMCs) from SKG mice, a spontaneous animal model of AS, through quantitative real-time PCR.
Results:
Compared with HCs, AS patients showed significantly higher serum concentrations of 12 cytokines (TNF-α, TNF-β, IL-17A, IL-17D, VEGFA, ICAM1, SAA, IP-10/CXCL10, MIP-3α/CCL20, sFlt-1/VEGFR-1, CRP, and MCP-4/CCL13) and significantly lower concentrations of nine cytokines (IL-4, IL-8, IL-17C, MIP-1α/CCL3, eotaxin-3/CCL26, PlGF, VEGF-C, VEGF-D, and bFGF) (all p < 0.05). Heatmap clustering and PCA demonstrated a clear separation between AS patients and HCs. ROC curve analysis showed excellent diagnostic accuracy for IP-10/CXCL10 (AUC = 1.00), VEGF-D (AUC = 0.98), IL-17A (AUC = 0.87), TNF-α (AUC = 0.85), and ICAM1 (AUC = 0.84). Positive correlations were observed between IL-17A and MIP-3α/CCL20, and between VEGFA and sFlt-1, indicating coordinated inflammatory and angiogenic pathways. Validation experiments in SKG mice confirmed elevated IP-10/CXCL10 and reduced VEGF-D expression, supporting cross-species relevance.
Conclusions:
This study identified distinct cytokine and chemokine profiles in AS patients. IP-10/CXCL10 and VEGF-D emerged as promising diagnostic biomarkers with high discriminatory power. Several previously unreported immune mediators were also highlighted. These findings provide new insights into AS pathogenesis and suggest potential targets for future therapeutic interventions.
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