Kawasaki disease (KD) is an acute febrile vasculitis and the leading cause of acquired heart disease in children. Despite decades of research, the etiology remains unknown and key mechanisms linking systemic inflammation to coronary artery lesions are incompletely defined. High-throughput technologies-including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and immunomics-have enabled systems-level profiling of KD and highlighted reproducible inflammatory and vascular pathways. Multiomics integration increasingly supports convergent mechanistic axes, particularly interleukin (IL-1/IL-6-neutrophil programs, Fcγ-receptor signaling related to intravenous immunoglobulin (IVIG) pharmacodynamics, Ca²+/nuclear factor of activated T cells-dependent T-cell activation, and endothelial/extracellular matrix remodeling associated with coronary outcomes. While these findings provide a robust framework for biomarker discovery and therapeutic hypothesis generation, most signatures remain investigational and require prospective validation, standardized sampling (pre-/post-IVIG), and clinically scalable assays before routine implementation. This review summarizes current multiomics applications in KD, prioritizes the most consistently supported pathways, and outlines a pragmatic roadmap toward clinically useful risk stratification, disease monitoring, and outcome prediction.
Ahn et al. (Wed,) studied this question.