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Screening of gene signatures for rheumatoid arthritis and osteoarthritis based on bioinformatics analysis

The current study aimed to identify gene signatures during rheumatoid arthritis (RA) and osteoarthritis (OA), and used these to elucidate the underlying modular mechanisms. Using the Gene Expression Omnibus database, the present study obtained the GSE7669 mRNA expression microarray data from RA and...

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Autores principales: He, Peiheng, Zhang, Ziji, Liao, Weiming, Xu, Dongliang, Fu, Ming, Kang, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4940106/
https://www.ncbi.nlm.nih.gov/pubmed/27356888
http://dx.doi.org/10.3892/mmr.2016.5423
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author He, Peiheng
Zhang, Ziji
Liao, Weiming
Xu, Dongliang
Fu, Ming
Kang, Yan
author_facet He, Peiheng
Zhang, Ziji
Liao, Weiming
Xu, Dongliang
Fu, Ming
Kang, Yan
author_sort He, Peiheng
collection PubMed
description The current study aimed to identify gene signatures during rheumatoid arthritis (RA) and osteoarthritis (OA), and used these to elucidate the underlying modular mechanisms. Using the Gene Expression Omnibus database, the present study obtained the GSE7669 mRNA expression microarray data from RA and OA synovial fibroblasts (n=6 each). The differentially expressed genes (DEGs) in RA synovial samples compared with OA samples were identified using the Linear Models for Microarray Analysis package. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the Database for Annotation Visualization and Integrated Discovery. A protein-protein interaction network was constructed and the modules were further analyzed using the Molecular Complex Detection plugin of Cytoscape. A total of 181 DEGs were identified by comparing RA and OA synovial samples (96 up- and 85 downregulated genes). The significant DEGs in module 1, including collagen, type I, α 1 (COL1A1), COL3A1, COL4A1 and COL11A1, were predominantly enriched in the extracellular matrix (ECM)-receptor interaction and focal adhesion pathways. Additionally, significant DEGs in module 2, including radical S-adenosyl methionine domain containing 2 (RSAD2), 2′-5′-oligoadenylate synthetase 2 (OAS2), myxovirus (influenza virus) resistance 1 (MX1) and ISG15 ubiquitin-like modifier (ISG15), were predominantly associated with immune function pathways. In conclusion, the present study indicated that RSAD2, OAS2, MX1 and ISG15 may be notable gene signatures in RA development via regulation of the immune response. COL3A1, COL4A1, COL1A1 and COL11A1 may be important gene signatures in OA development via involvement in the pathways of ECM-receptor interactions and focal adhesions.
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spelling pubmed-49401062016-07-21 Screening of gene signatures for rheumatoid arthritis and osteoarthritis based on bioinformatics analysis He, Peiheng Zhang, Ziji Liao, Weiming Xu, Dongliang Fu, Ming Kang, Yan Mol Med Rep Articles The current study aimed to identify gene signatures during rheumatoid arthritis (RA) and osteoarthritis (OA), and used these to elucidate the underlying modular mechanisms. Using the Gene Expression Omnibus database, the present study obtained the GSE7669 mRNA expression microarray data from RA and OA synovial fibroblasts (n=6 each). The differentially expressed genes (DEGs) in RA synovial samples compared with OA samples were identified using the Linear Models for Microarray Analysis package. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the Database for Annotation Visualization and Integrated Discovery. A protein-protein interaction network was constructed and the modules were further analyzed using the Molecular Complex Detection plugin of Cytoscape. A total of 181 DEGs were identified by comparing RA and OA synovial samples (96 up- and 85 downregulated genes). The significant DEGs in module 1, including collagen, type I, α 1 (COL1A1), COL3A1, COL4A1 and COL11A1, were predominantly enriched in the extracellular matrix (ECM)-receptor interaction and focal adhesion pathways. Additionally, significant DEGs in module 2, including radical S-adenosyl methionine domain containing 2 (RSAD2), 2′-5′-oligoadenylate synthetase 2 (OAS2), myxovirus (influenza virus) resistance 1 (MX1) and ISG15 ubiquitin-like modifier (ISG15), were predominantly associated with immune function pathways. In conclusion, the present study indicated that RSAD2, OAS2, MX1 and ISG15 may be notable gene signatures in RA development via regulation of the immune response. COL3A1, COL4A1, COL1A1 and COL11A1 may be important gene signatures in OA development via involvement in the pathways of ECM-receptor interactions and focal adhesions. D.A. Spandidos 2016-08 2016-06-23 /pmc/articles/PMC4940106/ /pubmed/27356888 http://dx.doi.org/10.3892/mmr.2016.5423 Text en Copyright: © He et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
He, Peiheng
Zhang, Ziji
Liao, Weiming
Xu, Dongliang
Fu, Ming
Kang, Yan
Screening of gene signatures for rheumatoid arthritis and osteoarthritis based on bioinformatics analysis
title Screening of gene signatures for rheumatoid arthritis and osteoarthritis based on bioinformatics analysis
title_full Screening of gene signatures for rheumatoid arthritis and osteoarthritis based on bioinformatics analysis
title_fullStr Screening of gene signatures for rheumatoid arthritis and osteoarthritis based on bioinformatics analysis
title_full_unstemmed Screening of gene signatures for rheumatoid arthritis and osteoarthritis based on bioinformatics analysis
title_short Screening of gene signatures for rheumatoid arthritis and osteoarthritis based on bioinformatics analysis
title_sort screening of gene signatures for rheumatoid arthritis and osteoarthritis based on bioinformatics analysis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4940106/
https://www.ncbi.nlm.nih.gov/pubmed/27356888
http://dx.doi.org/10.3892/mmr.2016.5423
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