J Clin Immunol. 2026 Apr 21. doi: 10.1007/s10875-026-02025-x. Online ahead of print.
ABSTRACT
Kawasaki disease (KD) remains the leading cause of acquired heart disease in children. While intravenous immunoglobulin (IVIG) represents standard therapy, approximately 10-20% of patients exhibit treatment refractoriness associated with significantly elevated coronary artery lesion risk. Current risk stratification relies on clinical parameters-fever duration or nonspecific inflammatory markers-which fail to capture distinct immunopathological features associated with treatment failure. To bridge this gap, we employed a convergent strategy integrating transcriptomic discovery from two independent cohorts with prospective protein-level and cellular validation in a clinical cohort. Three machine learning models-LASSO regression, Random Forest, and XGBoost-independently identified TREM1 (Triggering Receptor Expressed on Myeloid cells-1) as a core resistance predictor. Prospective validation in 117 KD patients demonstrated that plasma soluble TREM-1 (sTREM-1) was markedly elevated in IVIG-resistant cases (median 1247 vs. 856 pg/mL, P < 0.001) and effectively differentiated KD from other febrile illnesses. Mechanistically, sTREM-1 elevation showed a moderate positive correlation with myeloperoxidase-DNA complexes (ρ = 0.612, P < 0.001), indicating that TREM-1-associated neutrophil hyperactivation is associated with excessive neutrophil extracellular trap (NET) formation and vascular injury. External validation (GSE63881) confirmed TREM1 upregulation (2.1-fold) in resistant patients. Incorporating sTREM-1 into a multivariable prediction model achieved area under curve 0.884 using Firth’s penalized logistic regression (optimism-corrected AUC 0.871) in this derivation cohort, significantly outperforming traditional clinical scores. These findings suggest TREM-1-associated NETosis as a potential contributor to the pathobiology of IVIG resistance. As a TRIPOD Type 1b derivation study, external clinical validation in independent multi-center cohorts is required prior to clinical implementation.
PMID:42010185 | DOI:10.1007/s10875-026-02025-x