Objective: Kawasaki disease (KD) is a childhood febrile vasculitis with unknown etiology. Epigenetic regulation in the gene expression dynamics has become increasingly important in KD. Thus, we performed an integrated analysis of DNA methylation and gene expression data to identify novel molecular mechanisms and key functional genes in KD.
Methods: DNA methylation (GSE84624) and gene expression (GSE68004) datasets were downloaded from Gene Expression Omnibus. Methylated-differentially expressed genes (mDEGs) were documented as the overlapping genes between the differentially methylated genes (DMGs) in GSE84624 and differentially expressed genes (DEGs) in GSE68004. Functional enrichment analyses of the mDEGs were conducted using DAVID database. Protein-protein interaction (PPI) network was then constructed to obtain the hub genes involved in KD using STRING database.
Results: A total of 1389 DMGs and 1362 DEGs were screened out between KD and control samples. Overlapping of them resulted in four hypermethylated/downregulated and 187 hypomethylated/upregulated genes. These mDEGs were mainly enriched in inflammation response, innate immune response, and blood coagulation, and signaling pathways such as platelet activation, osteoclast differentiation, and chemokine signaling pathway. PPI network analyses identified MAPK14 and PHLPP1 as the hub genes involved in KD, which could distinguish KD from other common pediatric febrile diseases. In addition, the methylation and expression levels of MAPK14 and PHLPP1 were validated in other independent datasets.
Conclusion: This study provides an integrated view of interactions among DNA methylation and gene expression in patients with KD. MAPK14 and PHLPP1 are the key genes influenced by methylation and may serve as candidate biomarkers for KD.
Keywords: DNA methylation; Kawasaki disease; bioinformatics; gene expression.
© 2019 Wiley Periodicals, Inc.