| Multiomics approaches in Kawasaki disease: insights into pathogenesis and emerging directions for diagnosis and treatment |
Jong Gyun Ahn1,2,3 
, Insoo Kang3
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1Department of Pediatrics, Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea
2Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, Seoul, Korea
3Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA |
Correspondence:
Jong Gyun Ahn, Email: JGAHN@yuhs.ac
Insoo Kang, Email: insoo.kang@yale.edu
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Received: 9 December 2025 • Revised: 7 January 2026 • Accepted: 9 January 2026 |
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| Abstract |
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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. |
| Key Words:
Kawasaki disease, Multiomics, Biomarkers, Risk stratification |
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