Mapping the key players in Kawasaki disease; role of inflammatory genes and protein-protein interactions

Abstract

Background

Kawasaki disease (KD) is a complex acquired condition characterized by systemic blood vessel inflammation that primarily affects children under five years of age. It is clinically diagnosed as a syndrome, making it susceptible to misdiagnoses. Severe complications such as myocardial damage and coronary artery abnormalities can be fatal; thus, early diagnosis is critical for preventing disease progression. Currently, no specific diagnostic test can distinguish KD from viral or bacterial infections. Additionally, the molecular mechanisms underlying the disease remain unclear, hindering the development of targeted therapies.

Objective

This study aimed to identify the genetic patterns and molecular mechanisms associated with KD using a comprehensive gene expression analysis.

Methods

RNA sequencing and microarray genomic datasets were retrieved from the NCBI Gene Expression Omnibus (GEO). Four datasets (GSE68004, GSE63881, GSE73461, and GSE73463) were used for the final analysis. These datasets compared patients with KD to healthy controls, and patients with acute KD to convalescent patients. Differentially expressed genes (DEGs) were identified in the datasets. Enrichment analysis was conducted, followed by protein-protein interaction (PPI) network analysis to identify hub genes. Heatmaps were generated to visualize gene expression patterns.

Results

Eighteen hub genes were identified in the KD versus control comparison, whereas 20 hub genes were identified in the acute versus convalescent analysis. These genes play key roles in inflammation, cytokine storm, innate immune modulation, and endothelial damage.

Conclusion

This study provides valuable insights into the molecular mechanisms underlying KD, and identifies potential diagnostic biomarkers and therapeutic targets.