Performance of cytokine models in predicting SLE activity

Area of Science:

• Immunology
• Rheumatology
• Biomarker Discovery

Background:

• Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease.
• Identifying universal biomarkers for SLE flares remains challenging due to disease variability.
• Existing biomarkers for predicting lupus flares show inconsistent validation data.

Purpose of the Study:

• To identify sensitive and specific biomarkers for predicting SLE flares.
• To evaluate the predictive value of serum cytokines for SLE disease activity.

Main Methods:

• 124 SLE patients were prospectively followed.
• Disease activity assessed using SLE disease activity index (SLEDAI-2K).
• Serum cytokines measured via multiplex bead-based flow cytometry; correlation and logistic regression analyses performed.

Main Results:

• IFN-α, MCP-1, IL-6, IL-8, and IL-18 levels were elevated in active SLE and correlated with SLEDAI.
• IL-18 demonstrated the highest positive likelihood ratios for active SLE.
• IL-6, IL-8, and IL-18 predicted active SLE at baseline; C3 and IL-18 predicted active SLE at 12 weeks. IL-18 and IL-6 showed higher predictive accuracy than anti-dsDNA and C3.

Conclusions:

• Cytokine monitoring enhances sensitivity and specificity for SLE disease activity assessment.
• IL-18 predicts renal SLE flares, while IL-6 and IL-8 predict non-renal flares.
• Serum IL-18, IL-6, and IL-8 are proposed as clinical tools for monitoring SLE disease activity.