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Updated: Jul 1, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Identification of hub genes and pathogenesis in Kawasaki disease based on bioinformatics analysis
Min Cao1, Zhenhu Zhang2, Qian Liu3
1Department of Clinical Laboratory, Shanghai Songjiang District Central Hospital, Shanghai, China.
Background:
The aim of this study was to explore new biomarkers of Kawasaki disease (KD) and provide evidence for clinical diagnosis and treatment.
Materials And Methods:
Gene Expression Omnibus (GEO) datasets GSE68004 and GSE73461 were downloaded, and the differentially expressed genes (DGEs) were taken, along with DEGs enrichment analysis and protein interaction network. Finally, five algorithms in CytoHubba plug-in were applied to obtain hub genes.
Results:
In this study, 32 Co-DEGs were identified, and these genes mainly participated in neutrophil degranulation, neutrophil activation involved in immune response, and negative regulation of cytokine production involved in immune response; meanwhile, they were primarily enriched in starch and sucrose metabolism, fatty acid metabolism, autophagy and apoptosis, ferroptosis, and other pathways. Combined with the results of PPI and CytoHubba, 13 key genes were selected as follows: S100A12, HK3, HP, MMP9, MCEMP1, PYGL, ARG1, HIST2H2AA, ANXA3, HIST2H2AC, HIST2H2AA3, GYG1, DYSF.
Conclusions:
These 13 key genes may mediate the occurrence and development of KD through various processes such as immune regulation, inflammatory response, glucose metabolism, autophagy, and apoptosis, which provide valuable references for the diagnosis and treatment of KD.
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