4.6 Article

Exploration of Potential Biomarker Genes and Pathways in Kawasaki Disease: An Integrated in-Silico Approach

Journal

FRONTIERS IN GENETICS
Volume 13, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2022.849834

Keywords

bioinformatics; biomarkers; hub genes; in-silico analysis; Kawasaki disease; microarray; transcriptomics analysis

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This study aimed to elucidate the underlying pathogenesis of Kawasaki disease (KD) by re-analyzing transcriptome data. The findings identified genes related to neutrophil degranulation as important factors in KD. Additionally, the study revealed a strong interplay between immunological and genetic factors in the pathogenesis of KD.
Kawasaki disease (KD) is a common childhood systemic vasculitis with a special predilection for coronary arteries. Even after more than five decades of the initial description of the disease, the etiology of KD remains an enigma. This transcriptome data re-analysis study aimed to elucidate the underlying pathogenesis of KD using a bioinformatic approach to identify differentially expressed genes (DEGs) to delineate common pathways involved in KD. Array datasets from the Gene Expression Omnibus database were extracted and subjected to comparative meta-analysis for the identification of prominent DEGs. Fifteen hub genes with high connectivity were selected from these DEGs (IL1B, ITGAM, TLR2, CXCL8, SPI1, S100A12, MMP9, PRF1, TLR8, TREM1, CD44, UBB, FCER1G, IL7R, and FCGR1A). Of these 15 genes, five genes (CXCL8, FCGR1A, IL1B, TLR2, and TLR8) were found to be involved in neutrophil degranulation. To gain further insight into the molecular mechanism, a protein-protein network was established. Significantly enriched pathways based on the above-mentioned genes were mainly centered on biological regulation and signaling events. In addition, the pathway analysis also indicated that the majority of the DEGs in KD were enriched in systemic lupus erythematosus, suggesting a strong interplay between immunological and genetic factors in the pathogenesis of KD. These findings could significantly aid in identifying therapeutic targets and understanding KD biosignatures to design a biomarker panel for early diagnosis and severity of the disease.

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