Serum cytokine profiling differentiates underlying diseases in cytokine storm syndrome

Arthritis Rheumatol. 2025 Aug 8. doi: 10.1002/art.43349. Online ahead of print.

Abstract

Objective: Cytokine storm syndrome (CSS), commonly associated with hemophagocytic lymphohistiocytosis (HLH), is a fatal hyperinflammatory syndrome. Differentiating the underlying diseases responsible for CSS is essential for timely therapeutic decisions. This study explored the clinical usefulness of serum cytokine profiling in distinguishing underlying diseases in patients with CSS.

Methods: Serum samples were collected from 143 adult and pediatric patients with CSS and 22 healthy controls. The cohort included patients with various diagnoses of primary and secondary HLH, and Kawasaki disease (KD)-like hyperinflammatory syndromes. Serum levels of 48 cytokines were analyzed in 97 patients using a bead-based multiplex immunoassay (Luminex assay). Serum levels of IFN-α, IL-18, IL-6, CXCL9, and sTNF-RII were measured in 165 participants using enzyme-linked immunosorbent assay (ELISA).

Results: Luminex assay categorized patients with CSS into five clusters based on serum cytokine patterns. ELISA revealed distinct cytokine patterns, wherein patients with histiocytic necrotizing lymphadenitis-associated HLH and systemic lupus erythematosus-associated-MAS showed elevated IFN-α; systemic juvenile idiopathic arthritis- and adult-onset Still's disease-associated MAS, XIAP deficiency with HLH, and NLRC4-associated autoinflammatory disorder exhibited higher IL-18 levels. Additionally, KD shock syndrome had higher IL-6 levels than the other groups. CXCL9 was significantly elevated in patients with virus-associated HLH, familial HLH, malignant lymphoma-associated HLH, and KD-MAS. Multisystem inflammatory syndrome in children and toxic shock syndrome also showed moderate elevations of CXCL9 and IL-6 levels.

Conclusion: Serum cytokine profiling effectively differentiates CSS subtypes, facilitating better diagnosis and personalized treatment strategies based on specific disease backgrounds.