Exploring ferroptosis-associated immune characteristics in Kawasaki disease through bioinformatics

Abstract Kawasaki disease (KD), as a common pediatric inflammatory vasculitis, has an unclear pathogenesis. This study integrated bioinformatics and clinical data analysis to explore the characteristics of ferroptosis in KD. We used data from the Gene Expression Omnibus (GEO) database to identify fe...

Full description

Saved in:
Bibliographic Details
Main Authors: Wei Li, Yan Duan, Lingyun Zhang, Jialin Zou, Bin Liu, Jun Jiang, Dong Liu, Haiyan Liu, Gang Li
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-15182-7
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Abstract Kawasaki disease (KD), as a common pediatric inflammatory vasculitis, has an unclear pathogenesis. This study integrated bioinformatics and clinical data analysis to explore the characteristics of ferroptosis in KD. We used data from the Gene Expression Omnibus (GEO) database to identify ferroptosis-related genes, and variable selection was performed using Least Absolute Shrinkage and Selection Operator (LASSO) analysis. We employed seven machine learning methods to determine the optimal predictive model, revealing that the Support Vector Machine (SVM) model exhibited optimal performance in external validation. Unsupervised clustering based on FRGs stratified KD patients into high and low expression subtypes. The high expression subtype showed significantly elevated levels of monocyte immune infiltration, which was further validated by single-cell analysis. Clinical data analysis demonstrated that patients in the high-monocyte group not only had a higher incidence of incomplete KD presentations but also exhibited lower resistance to intravenous immunoglobulin (IVIG) therapy. These results suggest that ferroptosis may participate in the pathogenesis of KD by modulating monocyte levels, providing new insights into explaining clinical heterogeneity and differences in IVIG treatment responses.
ISSN:2045-2322