Identification of potential core genes in Kawasaki disease using bioinformatics analysis

Wu, Wenbin; You, Keyou; Zhong, Jinchan; Ruan, Zhanwei; Wang, Bubu

doi:10.1177/0300060519862057

Cited by 8 publications

(9 citation statements)

References 25 publications

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“…ITGAM , also known as CD11b , belongs to the integrin family and is involved in the regulation of neutrophils, monocyte activation, adhesion, and migration to damaged endothelium associated extracellular matrix. Moreover, studies have shown increased ITGAM levels in peripheral blood and upregulated protein expression in patients with KD ( Reindel et al, 2013 ; Wu et al, 2019 ).…”

Section: Discussionmentioning

confidence: 99%

“…This hypothesis was validated in the mice model by Lau et al (2008) . Studies have shown that serum levels of MMP-9 are elevated in KD patients and were found to play an important role in the development of CAAs ( Takeshita et al, 2001 ; Chua et al, 2003 ; Gavin et al, 2003 ; Wu et al, 2019 ). Perforin-1 ( PRF1 ) is one of the major cytolytic proteins of cytolytic granules.…”

Section: Discussionmentioning

confidence: 99%

“…To date, quite a number of genes have been examined in KD, which were usually selected based on information regarding their function in inflammation, immune response, and other biological mechanisms. Recently, gene expression profiling studies have been conducted to understand the pathophysiology of KD ( Hoang et al, 2014 ; Dietz et al, 2017 ; Wu et al, 2019 ; Rahmati et al, 2020 ; Gao et al, 2021 ); however, the prognostic power of identified genes still remains unclear. Therefore, understanding the pathogenesis of KD is essential for identifying novel pathways that can be targeted for therapy.…”

Section: Introductionmentioning

confidence: 99%

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Exploration of Potential Biomarker Genes and Pathways in Kawasaki Disease: An Integrated in-Silico Approach

et al. 2022

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Kawasaki disease (KD) is a common childhood systemic vasculitis with a special predilection for coronary arteries. Even after more than five decades of the initial description of the disease, the etiology of KD remains an enigma. This transcriptome data re-analysis study aimed to elucidate the underlying pathogenesis of KD using a bioinformatic approach to identify differentially expressed genes (DEGs) to delineate common pathways involved in KD. Array datasets from the Gene Expression Omnibus database were extracted and subjected to comparative meta-analysis for the identification of prominent DEGs. Fifteen hub genes with high connectivity were selected from these DEGs (IL1B, ITGAM, TLR2, CXCL8, SPI1, S100A12, MMP9, PRF1, TLR8, TREM1, CD44, UBB, FCER1G, IL7R, and FCGR1A). Of these 15 genes, five genes (CXCL8, FCGR1A, IL1B, TLR2, and TLR8) were found to be involved in neutrophil degranulation. To gain further insight into the molecular mechanism, a protein–protein network was established. Significantly enriched pathways based on the above-mentioned genes were mainly centered on biological regulation and signaling events. In addition, the pathway analysis also indicated that the majority of the DEGs in KD were enriched in systemic lupus erythematosus, suggesting a strong interplay between immunological and genetic factors in the pathogenesis of KD. These findings could significantly aid in identifying therapeutic targets and understanding KD biosignatures to design a biomarker panel for early diagnosis and severity of the disease.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Exploration of Potential Biomarker Genes and Pathways in Kawasaki Disease: An Integrated in-Silico Approach

et al. 2022

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“…Despite these treatments, the role of gene alteration in the pathogenesis of KD remains to be elucidated. Recently, microarray technology coupled with bioinformatics tools has been used to identify the novel genes associated with the pathogenesis, diagnosis and treatment of KD (Wu et al, 2019;Yazdan et al, 2020). Herein, we have used mRNA expression profile data of GSE18606 to identify hub genes in whole blood that are associated with acute KD.…”

Section: Discussionmentioning

confidence: 99%

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

Gui

Tang

et al. 2021

Front. Genet.

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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.

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“…Many recent studies found novel immunobiological pathways involved in KD and allowed to identify potential therapeutic targets for KD, they are listed in Table 3 (15,37,(136)(137)(138)(139)(140)(141)(142)(143)(144)(145)(146)(147). Literature data indicate that researchers focused especially on JAK / STAT pathway in the context of vasculitis, thus it could be regarded as a most promising potential target.…”

Section: Potential Therapeutic Targetmentioning

confidence: 99%

Anti-inflammatory Treatment of Kawasaki Disease: Comparison of Current Guidelines and Perspectives

Buda

Friedman-Gruszczyńska

Książyk

2021

Front. Med.

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Kawasaki disease (KD), an acute, generalized vasculitis, is associated with an increased risk of coronary heart disease and is the most common cause of acquired heart disease in childhood. The incidence of KD is increasing worldwide. There are numerous international treatment guidelines. Our study aims to perform the first one so far comparison of them. While the gold standard therapy remains still the same (intravenous immunoglobulins and aspirin), there is currently a lack of evidence for choosing optimal treatment for high-risk patients and refractory KD. In this review, we also discuss the treatment of complications of KD and Kawasaki-like phenotypes, present an anti-inflammatory treatment in the light of new scientific data, and present novel potential therapeutic targets for KD.

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Identification of potential core genes in Kawasaki disease using bioinformatics analysis

Cited by 8 publications

References 25 publications

Exploration of Potential Biomarker Genes and Pathways in Kawasaki Disease: An Integrated in-Silico Approach

Exploration of Potential Biomarker Genes and Pathways in Kawasaki Disease: An Integrated in-Silico Approach

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

Anti-inflammatory Treatment of Kawasaki Disease: Comparison of Current Guidelines and Perspectives

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