ArticleTranslational pediatrics2026
Identification of potential biomarkers of tryptophan metabolism in Kawasaki disease and exploration of potential mechanisms.
Article in Translational pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Kawasaki disease (KD) is an acute febrile illness, primarily affecting children under 5 years old. The relationship between tryptophan metabolism (TM) and KD is unclear. In this study, we identified biomarkers associated with TM-related genes in KD, and explore their potential biological roles. Methods: Differentially expressed genes (DEGs) were identified that intersected with key module genes from a weighted gene co-expression network analysis. We used three algorithms to obtain key genes. Biomarkers were described as characteristic genes with an area under the curve (AUC) above 0.7 in the GSE68004 and GSE73461 datasets. The pathways associated with biomarkers were probed using gene set enrichment analysis, whereas immune infiltration analysis revealed their correlations with immune cells. Furthermore, the N Results: A total of 906 DEGs and 1,194 key module genes overlapped, which resulted in 234 key genes. Based on three machine-learning algorithms, Conclusions: Four biomarkers associated with TM in KD were identified, and their mechanisms were further examined. The results provide mechanistic insight for the improved diagnosis and treatment of KD.
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