Gene expression analysis in Kawasaki disease; bioinformatics and experimental approach

Rahmati, Yazdan; Mollanoori, Hasan; Kakavandi, Naser; Nateghian, Alireza; Sayyahfar, Shirin; Babaei, Vahid; Esmaeili, Sajjad; Teimourian, Shahram

doi:10.1016/j.imu.2020.100423

Cited by 6 publications

(3 citation statements)

References 45 publications

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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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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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“…Since bioinformatics is a well-known approach for the assessment of high throughput data, gene expression analysis is tied to bioinformatics and network analysis. [7][8][9][10] A large number of dysregulated genes are organized in the interacted unit as a network, and each gene will interact with the related neighbors in a certain mode. The PPI network is a strong tool for screening the assessed genes.…”

Section: Introductionmentioning

confidence: 99%

Efficacy Evaluation of Human Skin Treatment with Photodynamic Therapy in Actinic Keratoses Patients

Razzaghi,

Arjmand,

Hamzeloo-Moghadam

et al. 2023

J Lasers Med Sci

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Introduction: Photodynamic therapy (PDT) is a combined method of light and light-activated chemicals that are called photosensitizers (PSs). PDT is recommended as a high cure rate method with fewer side effects and a noninvasive tool to treat cancer. This study aimed to evaluate PDT efficacy as a therapeutic method against actinic keratoses in patients via protein-protein interaction (PPI) network analysis by using the gene expression profiles of Gene Expression Omnibus (GEO). Methods: Twenty-one gene expression profiles were extracted from GEO and analyzed by GEO2R to determine the significant differentially expressed genes (DEGs). The significant DEGs were included in PPI networks via Cytoscape software. The networks were analyzed by the "Network Analyzer", and the elements of the main connected components were assessed. Results: There were three main connected components for the compared sets of the gene expression profiles including the lesional region of skin before (Before set) and after (After set) PDT versus healthy (healthy set) skin and before versus after. The before-health comparison showed a partial similarity with the After-Healthy assessment. The before-after evaluation indicated that there were not considerable differences between the gene expression profile of the lesional region before and after PDT. Conclusion: In conclusion, PDT was unable to return the gene expression pattern of the actinic keratoses skin to a healthy condition completely.

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“…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%

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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Gene expression analysis in Kawasaki disease; bioinformatics and experimental approach

Cited by 6 publications

References 45 publications

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

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

Efficacy Evaluation of Human Skin Treatment with Photodynamic Therapy in Actinic Keratoses Patients

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

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