Year: 2026
Type: article
Study design: Observational Study
Abstract: Background: Kawasaki Disease (KD) is an acute inflammatory disease that primarily affects children. Without timely treatment, it may lead to severe cardiovascular complications. Currently, the lack of specific biomarkers complicates its early diagnosis. Methods: This study focuses on investigating the diagnostic value of C-C motif chemokine ligand 23 (CCL23) protein in distinguishing KD from other similar diseases through gene expression profiling analysis and biomarker detection. Firstly, methods such as differentially expressed genes (DEGs) analysis, protein-protein interaction (PPI) network construction, and pathway enrichment analysis are employed to identify relevant Hub genes. Subsequently, Western blot technology is used to detect the expression of CCL23 protein in plasma, so as to externally validate the diagnostic value of the aforementioned relevant Hub genes in differentiating Kawasaki disease from other similar diseases. Results: We identified 11 significant hub genes and found that the concentration of CCL23 in the KD group was significantly higher than that in the febrile control group and the healthy control group. Further receiver operating characteristic (ROC) analysis showed that CCL23 exhibited good sensitivity and specificity in distinguishing Kawasaki Disease from other diseases. Meanwhile, pathway enrichment analysis revealed that CCL23 was upregulated in the cytokine-cytokine receptor interaction pathway, suggesting that it may play an important role in immune-inflammatory responses. Conclusions: Although this study has limitations such as insufficient sample size and lack of long-term follow-up, the results provide new insights into CCL23 as a potential biomarker for KD. Future studies should further validate these findings and explore their application in clinical practice to improve the early diagnosis rate of KD.
Source: Frontiers in Immunology
Authors: Lifen Rao, Jinwen Liao, Xin Guo, Qiuming Miu, Yinbi Zheng, Weiping Xun
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7130333571