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In silico Identification of 10 Hub Genes and an miRNA–mRNA Regulatory Network in Acute Kawasaki Disease
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) regula...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044791/ https://www.ncbi.nlm.nih.gov/pubmed/33868359 http://dx.doi.org/10.3389/fgene.2021.585058 |
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author | Ma, Jin Gui, Huan Tang, Yunjia Ding, Yueyue Qian, Guanghui Yang, Mengjie Wang, Mei Song, Xiudao Lv, Haitao |
author_facet | Ma, Jin Gui, Huan Tang, Yunjia Ding, Yueyue Qian, Guanghui Yang, Mengjie Wang, Mei Song, Xiudao Lv, Haitao |
author_sort | Ma, Jin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8044791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80447912021-04-15 In silico Identification of 10 Hub Genes and an miRNA–mRNA Regulatory Network in Acute Kawasaki Disease Ma, Jin Gui, Huan Tang, Yunjia Ding, Yueyue Qian, Guanghui Yang, Mengjie Wang, Mei Song, Xiudao Lv, Haitao Front Genet Genetics 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. Frontiers Media S.A. 2021-03-25 /pmc/articles/PMC8044791/ /pubmed/33868359 http://dx.doi.org/10.3389/fgene.2021.585058 Text en Copyright © 2021 Ma, Gui, Tang, Ding, Qian, Yang, Wang, Song and Lv. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Ma, Jin Gui, Huan Tang, Yunjia Ding, Yueyue Qian, Guanghui Yang, Mengjie Wang, Mei Song, Xiudao Lv, Haitao In silico Identification of 10 Hub Genes and an miRNA–mRNA Regulatory Network in Acute Kawasaki Disease |
title | In silico Identification of 10 Hub Genes and an miRNA–mRNA Regulatory Network in Acute Kawasaki Disease |
title_full | In silico Identification of 10 Hub Genes and an miRNA–mRNA Regulatory Network in Acute Kawasaki Disease |
title_fullStr | In silico Identification of 10 Hub Genes and an miRNA–mRNA Regulatory Network in Acute Kawasaki Disease |
title_full_unstemmed | In silico Identification of 10 Hub Genes and an miRNA–mRNA Regulatory Network in Acute Kawasaki Disease |
title_short | In silico Identification of 10 Hub Genes and an miRNA–mRNA Regulatory Network in Acute Kawasaki Disease |
title_sort | in silico identification of 10 hub genes and an mirna–mrna regulatory network in acute kawasaki disease |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044791/ https://www.ncbi.nlm.nih.gov/pubmed/33868359 http://dx.doi.org/10.3389/fgene.2021.585058 |
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