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Bioinformatics analysis of differentially expressed genes in subchondral bone in early experimental osteoarthritis using microarray data

BACKGROUND: Osteoarthritis (OA) is the most common arthritic disease in humans, affecting the majority of individuals over 65 years of age. The aim of this study is to identify the gene expression profile specific to subchondral bone in OA by comparing the different expression profiles in experiment...

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Autores principales: Wang, Zhao, Ji, Yong, Bao, Hong-wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7414553/
https://www.ncbi.nlm.nih.gov/pubmed/32771051
http://dx.doi.org/10.1186/s13018-020-01839-8
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author Wang, Zhao
Ji, Yong
Bao, Hong-wei
author_facet Wang, Zhao
Ji, Yong
Bao, Hong-wei
author_sort Wang, Zhao
collection PubMed
description BACKGROUND: Osteoarthritis (OA) is the most common arthritic disease in humans, affecting the majority of individuals over 65 years of age. The aim of this study is to identify the gene expression profile specific to subchondral bone in OA by comparing the different expression profiles in experimental and sham-operation groups. METHODS: Gene expression profile GSE30322 was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained by limma package. And Database for Annotation, Visualization and Integrated Discovery (DAVID) databases were further used to identify the potential gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Furthermore, a protein–protein interaction (PPI) network was constructed and significant modules were extracted. RESULTS: Totally, 588 DEGs were identified including 199 upregulated DEGs and 389 downregulated DEGs screened in OA and sham-operation. GO showed that DEGs were significantly enhanced for ribosomal subunit export from nucleus and molting cycle. KEGG pathway analysis revealed that target genes were enriched in thiamine metabolism. CONCLUSION: These key candidate DEGs that affect the progression of OA, and these genes might serve as potential therapeutic targets for OA.
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spelling pubmed-74145532020-08-10 Bioinformatics analysis of differentially expressed genes in subchondral bone in early experimental osteoarthritis using microarray data Wang, Zhao Ji, Yong Bao, Hong-wei J Orthop Surg Res Research Article BACKGROUND: Osteoarthritis (OA) is the most common arthritic disease in humans, affecting the majority of individuals over 65 years of age. The aim of this study is to identify the gene expression profile specific to subchondral bone in OA by comparing the different expression profiles in experimental and sham-operation groups. METHODS: Gene expression profile GSE30322 was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained by limma package. And Database for Annotation, Visualization and Integrated Discovery (DAVID) databases were further used to identify the potential gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Furthermore, a protein–protein interaction (PPI) network was constructed and significant modules were extracted. RESULTS: Totally, 588 DEGs were identified including 199 upregulated DEGs and 389 downregulated DEGs screened in OA and sham-operation. GO showed that DEGs were significantly enhanced for ribosomal subunit export from nucleus and molting cycle. KEGG pathway analysis revealed that target genes were enriched in thiamine metabolism. CONCLUSION: These key candidate DEGs that affect the progression of OA, and these genes might serve as potential therapeutic targets for OA. BioMed Central 2020-08-08 /pmc/articles/PMC7414553/ /pubmed/32771051 http://dx.doi.org/10.1186/s13018-020-01839-8 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Wang, Zhao
Ji, Yong
Bao, Hong-wei
Bioinformatics analysis of differentially expressed genes in subchondral bone in early experimental osteoarthritis using microarray data
title Bioinformatics analysis of differentially expressed genes in subchondral bone in early experimental osteoarthritis using microarray data
title_full Bioinformatics analysis of differentially expressed genes in subchondral bone in early experimental osteoarthritis using microarray data
title_fullStr Bioinformatics analysis of differentially expressed genes in subchondral bone in early experimental osteoarthritis using microarray data
title_full_unstemmed Bioinformatics analysis of differentially expressed genes in subchondral bone in early experimental osteoarthritis using microarray data
title_short Bioinformatics analysis of differentially expressed genes in subchondral bone in early experimental osteoarthritis using microarray data
title_sort bioinformatics analysis of differentially expressed genes in subchondral bone in early experimental osteoarthritis using microarray data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7414553/
https://www.ncbi.nlm.nih.gov/pubmed/32771051
http://dx.doi.org/10.1186/s13018-020-01839-8
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