In silico Identification of 10 Hub Genes and an miRNA–mRNA Regulatory Network in Acute Kawasaki Disease

Abstract

Kawasaki disease (KD) causes acute systemic vasculitis and has unknown etiology. Since the acute stage of KD is the most relevant, the aim of the present study was to identify hub genes in acute KD by bioinformatics analysis. We also aimed at constructing microRNA (miRNA)–messenger RNA (mRNA) regulatory networks associated with acute KD based on previously identified differentially expressed miRNAs (DE-miRNAs). DE-mRNAs in acute KD patients were screened using the mRNA expression profile data of GSE18606 from the Gene Expression Omnibus. The functional and pathway enrichment analysis of DE-mRNAs were performed with the DAVID database. Target genes of DE-miRNAs were predicted using the miRWalk database and their intersection with DE-mRNAs was obtained. From a protein–protein interaction (PPI) network established by the STRING database, Cytoscape software identified hub genes with the two topological analysis methods maximal clique centrality and Degree algorithm to construct a miRNA-hub gene network. A total of 1,063 DE-mRNAs were identified between acute KD and healthy individuals, 472 upregulated and 591 downregulated. The constructed PPI network with these DE-mRNAs identified 38 hub genes mostly enriched in pathways related to systemic lupus erythematosus, alcoholism, viral carcinogenesis, osteoclast differentiation, adipocytokine signaling pathway and tumor necrosis factor signaling pathway. Target genes were predicted for the up-regulated and down-regulated DE-miRNAs, 10,203, and 5,310, respectively. Subsequently, 355, and 130 overlapping target DE-mRNAs were obtained for upregulated and downregulated DE-miRNAs, respectively. PPI networks with these target DE-mRNAs produced 15 hub genes, six down-regulated and nine upregulated hub genes. Among these, ten genes (ATM, MDC1, CD59, CD177, TRPM2, FCAR, TSPAN14, LILRB2, SIRPA, and STAT3) were identified as hub genes in the PPI network of DE-mRNAs. Finally, we constructed the regulatory network of DE-miRNAs and hub genes, which suggested potential modulation of most hub genes by hsa-miR-4443 and hsa-miR-6510-5p. SP1 was predicted to potentially regulate most of DE-miRNAs. In conclusion, several hub genes are associated with acute KD. An miRNA–mRNA regulatory network potentially relevant for acute KD pathogenesis provides new insights into the underlying molecular mechanisms of acute KD. The latter may contribute to the diagnosis and treatment of acute KD.

In-depth systems biological evaluation of bovine alveolar macrophages suggests novel insights into molecular mechanisms underlying Mycobacterium bovis infection

“…Therefore, several steps were performed to identify these key dysregulated genes, including identification of intramodular hub genes in the non-preserved modules, integration of co-expressed hub genes with PPI networks, and identification of the hub-central genes in the bTB-specific co-expressed hub genes-based PPI networks through MCC topological algorithm. Noteworthy, in parallel with the current study, the MCC algorithm has been used as an objective criterion for measuring node centrality and identifying important genes/proteins in candidate networks in disease-based system biology studies ( Bai et al, 2020 ; Yang et al, 2020 ; Ma et al, 2021 ; Wang Y. et al, 2021 ). Finally, a total of 260 hub-central genes were found in the 7 bTB-specific non-preserved modules that these genes were hubs in their co-expression networks and also played a central role in the respective co-expressed hub genes-based PPI networks (so-called double centrality) which were as critical targets in related to the promotion of the bTB establishment.…”

Using bioinformatics analysis to screen abnormal methylated differentially expressed hub genes of Kawasaki disease and construct diagnostic model

“…PPI analysis showed that three hypomethylated, high expression hub genes were CD177, IL1RN, and MYL9. CD177 is a neutrophil surface molecule, many studies have proved that there is a close relationship between CD177 and KD [ 33 , 34 , 35 ]. Huang et al.…”

Human microRNA-4433 (hsa-miR-4443) Targets 18 Genes to be a Risk Factor of Neurodegenerative Diseases

“…In the present study, hsa-miR-4443 (miRbase accession MI0016786, http://www.mirbase.org/cgibin/mirna_entry.pl?acc=MI0016786 ) was the only 1 co-differently expressed microRNA identified in this study. Hsa-miR-4443 was reported to be involved in several types of cancer and in the biology of the immune system, such as participating in the malignancy of breast cancer [ 36 , 37 ], tumors of glial origin [ 38 , 39 ] and head and neck squamous cell carcinoma [ 40 ], suppressing invasiveness of ovarian cancer [ 41 ] and colon cancer [ 42 ], promoting the resistance of non-small cell lung cancer cells to epirubicin [ 43 , 44 ], downregulated in hepatocellular carcinoma [ 45 ] peripheral blood mononuclear cells of non-segmental vitiligo (NSV) patients [ 46 ] and acute Kawasaki disease [ 47 , 48 ], and regulating T cell-mediated inflammatory processes [ 49 ] and monocyte activation [ 50 ]. Although no studies on the roles of hsa-miR-4443 in neurodegenerative diseases have been reported yet, the effects of hsa-miR-4443 on tumors of glial origin [ 38 , 39 ] and immune cells [ 49 , 50 ] indicated hsa-miR-4443 regulating glial cells and neuroimmunity to participate in occurrence of neurodegenerative diseases.…”