Identification of Differentially Expressed Genes in Kawasaki Disease Patients as Potential Biomarkers for IVIG Sensitivity by Bioinformatics Analysis

Identification and validation of autophagy-related genes in Kawasaki disease

BACKGROUND

Kawasaki disease (KD) is a systemic vasculitis of unknown etiology affecting mainly children. Studies have shown that the pathogenesis of KD may be related to autophagy. Using bioinformatics analysis, we assessed the significance of autophagy-related genes (ARGs) in KD.

METHODS

Common ARGs were identified from the GeneCards Database, the Molecular Signatures Database (MSigDB), and the Gene Expression Omnibus (GEO) database. ARGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein-protein interaction (PPI) network analysis. Furthermore, related microRNAs (miRNAs), transcription factors (TFs), and drug interaction network were predicted. The immune cell infiltration of ARGs in tissues was explored. Finally, we used receiver operating characteristic (ROC) curves and quantitative real-time PCR (qRT-PCR) to validate the diagnostic value and expression levels of ARGs in KD.

RESULTS

There were 20 ARGs in total. GO analysis showed that ARGs were mainly rich in autophagy, macro-autophagy, and GTPase activity. KEGG analysis showed that ARGs were mainly rich in autophagy-animal and the collecting duct acid secretion pathway. The expression of WIPI1, WDFY3, ATP6V0E2, RALB, ATP6V1C1, GBA, C9orf72, LRRK2, GNAI3, and PIK3CB is the focus of PPI network. A total of 72 related miRNAs and 130 related TFs were predicted by miRNA and TF targeting network analyses. Ten pairs of gene-drug interaction networks were also predicted; immune infiltration analysis showed that SH3GLB1, ATP6V0E2, PLEKHF1, RALB, KLHL3, and TSPO were closely related to CD8 + T cells and neutrophils. The ROC curve showed that ARGs had good diagnostic value in KD. qRT-PCR showed that WIPI1 and GBA were significantly upregulated.

CONCLUSION

Twenty potential ARGs were identified by bioinformatics analysis, and WIPI1 and GBA may be used as potential drug targets and biomarkers.

Identifying differentially expressed genes and miRNAs in Kawasaki disease by bioinformatics analysis

Kawasaki disease (KD) is an acute systemic immune vasculitis caused by infection, and its etiology and underlying mechanisms are not completely clear. This study aimed to identify differentially expressed genes (DEGs) with diagnostic and treatment potential for KD using bioinformatics analysis. In this study, three KD datasets (GSE68004, GSE73461, GSE18606) were downloaded from the Gene Expression Omnibus (GEO) database. Identification of DEGs between normal and KD whole blood was performed using the GEO2R online tool. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis of DEGs was undertaken with Metascape. Analysis and visualization of protein-protein interaction networks (PPI) were carried out with STRING and Cytoscape. Lastly, miRNA-genes regulatory networks were built by Cytoscape to predict the underlying microRNAs (miRNAs) associated with DEGs. Overall, 269 DEGs were identified, including 230 up-regulated and 39 down-regulated genes. The enrichment functions and pathways of DEGs involve regulation of defense response, inflammatory response, response to bacterium, and T cell differentiation. KEGG analysis indicates that the genes were significantly enriched in Neutrophil extracellular trap formation, TNF signaling pathway, Cytokine-cytokine receptor interaction, and Primary immunodeficiency. After combining the results of the protein-protein interaction (PPI) network and CytoHubba, 9 hub genes were selected, including TLR8, ITGAX, HCK, LILRB2, IL1B, FCGR2A, S100A12, SPI1, and CD8A. Based on the DEGs-miRNAs network construction, 3 miRNAs including mir-126-3p, mir-375 and mir-146a-5p were determined to be potential key miRNAs. To summarize, a total of 269 DEGs, 9 hub genes and 3 miRNAs were identified, which could be considered as KD biomarkers. However, further studies are needed to clarify the biological roles of these genes in KD.