Identification of Key Genes and Underlying Mechanisms in Acute Kawasaki Disease Based on Bioinformatics Analysis
Side Gao, Wenjian Ma, Xuze Lin, Sizhuang Huang, Mengyue Yu
Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (mainland)
Med Sci Monit 2021; 27:e930547
Available online: 2021-04-08
Kawasaki disease (KD) is a systemic vasculitis that predominantly occurs in children, but the pathogenesis of KD remains unclear. Here, we explored key genes and underlying mechanisms potentially involved in KD using bioinformatic analyses.
MATERIAL AND METHODS: The shared differentially expressed genes (DEGs) in KD compared to control samples were identified using the microarray data from the Gene Expression Omnibus Series (GSE) 18606, GSE68004, and GSE73461. Analyses of the functional annotation, protein-protein interaction (PPI) network, microRNA-target DEGs regulatory network, and immune cell infiltration were performed. The expression of hub genes before and after intravenous immunoglobulin (IVIG) treatment in KD was further verified using GSE16797.
RESULTS: A total of 195 shared DEGs (164 upregulated and 31 downregulated genes) were identified between KD and healthy controls. These shared DEGs were mainly enriched in immune and inflammatory responses. Ten upregulated hub genes (ITGAX, SPI1, LILRB2, MMP9, S100A12, C3AR1, RETN, MAPK14, TLR5, MYD88) and the most significant module were identified in the PPI network. There were 309 regulatory relationships detected within 70 predicted microRNAs and 193 target DEGs. The immune cell infiltration analysis showed that monocytes, neutrophils, activated mast cells, and activated natural killer cells had relatively high proportions and were significantly more infiltrated in KD samples. Six hub genes of ITGAX, LILRB2, C3AR1, MAPK14, TLR5, and MYD88 were markedly downregulated after IVIG treatment for KD.
CONCLUSIONS: Our study identified the candidate genes and associated molecules that may be related to the KD process, and provided new insights into potential mechanisms and therapeutic targets for KD.
Keywords: Databases, Genetic, Diagnosis, Mucocutaneous Lymph Node Syndrome