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Comparison of molecular mechanisms of rheumatoid arthritis and osteoarthritis using gene microarrays
The present study aimed to compare the molecular mechanisms of rheumatoid arthritis (RA) and osteoarthritis (OA). The microarray dataset no. GSE29746 was downloaded from Gene Expression Omnibus. After data pre-processing, differential expression analysis between the RA group and the control, as well...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4878540/ https://www.ncbi.nlm.nih.gov/pubmed/27082252 http://dx.doi.org/10.3892/mmr.2016.5144 |
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author | LI, HONGQIANG HAO, ZHENYONG ZHAO, LIQIANG LIU, WEI HAN, YANLONG BAI, YUNXING WANG, JIAN |
author_facet | LI, HONGQIANG HAO, ZHENYONG ZHAO, LIQIANG LIU, WEI HAN, YANLONG BAI, YUNXING WANG, JIAN |
author_sort | LI, HONGQIANG |
collection | PubMed |
description | The present study aimed to compare the molecular mechanisms of rheumatoid arthritis (RA) and osteoarthritis (OA). The microarray dataset no. GSE29746 was downloaded from Gene Expression Omnibus. After data pre-processing, differential expression analysis between the RA group and the control, as well as between the OA group and the control was performed using the LIMMA package in R and differentially expressed transcripts (DETs) with |log(2)fold change (FC)|>1 and P<0.01 were identified. DETs screened from each disease group were then subjected to functional annotation using DAVID. Next, DETs from each group were used to construct individual interaction networks using the BIND database, followed by sub-network mining using clusterONE. Significant functions of nodes in each sub-network were also investigated. In total, 19 and 281 DETs were screened from the RA and OA groups, respectively, with only six common DETs. DETs from the RA and OA groups were enriched in 8 and 130 gene ontology (GO) terms, respectively, with four common GO terms, of which to were associated with phospholipase C (PLC) activity. In addition, DETs screened from the OA group were enriched in immune response-associated GO terms, and those screened from the RA group were largely associated with biological processes linked with the cell cycle and chromosomes. Genes involved in PLC activity and its regulation were indicated to be altered in RA as well as in OA. Alterations in the expression of cell cycle-associated genes were indicated to be linked with the occurrence of OA, while genes participating in the immune response were involved in the occurrence of RA. |
format | Online Article Text |
id | pubmed-4878540 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-48785402016-05-25 Comparison of molecular mechanisms of rheumatoid arthritis and osteoarthritis using gene microarrays LI, HONGQIANG HAO, ZHENYONG ZHAO, LIQIANG LIU, WEI HAN, YANLONG BAI, YUNXING WANG, JIAN Mol Med Rep Articles The present study aimed to compare the molecular mechanisms of rheumatoid arthritis (RA) and osteoarthritis (OA). The microarray dataset no. GSE29746 was downloaded from Gene Expression Omnibus. After data pre-processing, differential expression analysis between the RA group and the control, as well as between the OA group and the control was performed using the LIMMA package in R and differentially expressed transcripts (DETs) with |log(2)fold change (FC)|>1 and P<0.01 were identified. DETs screened from each disease group were then subjected to functional annotation using DAVID. Next, DETs from each group were used to construct individual interaction networks using the BIND database, followed by sub-network mining using clusterONE. Significant functions of nodes in each sub-network were also investigated. In total, 19 and 281 DETs were screened from the RA and OA groups, respectively, with only six common DETs. DETs from the RA and OA groups were enriched in 8 and 130 gene ontology (GO) terms, respectively, with four common GO terms, of which to were associated with phospholipase C (PLC) activity. In addition, DETs screened from the OA group were enriched in immune response-associated GO terms, and those screened from the RA group were largely associated with biological processes linked with the cell cycle and chromosomes. Genes involved in PLC activity and its regulation were indicated to be altered in RA as well as in OA. Alterations in the expression of cell cycle-associated genes were indicated to be linked with the occurrence of OA, while genes participating in the immune response were involved in the occurrence of RA. D.A. Spandidos 2016-06 2016-04-15 /pmc/articles/PMC4878540/ /pubmed/27082252 http://dx.doi.org/10.3892/mmr.2016.5144 Text en Copyright: © Li 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 LI, HONGQIANG HAO, ZHENYONG ZHAO, LIQIANG LIU, WEI HAN, YANLONG BAI, YUNXING WANG, JIAN Comparison of molecular mechanisms of rheumatoid arthritis and osteoarthritis using gene microarrays |
title | Comparison of molecular mechanisms of rheumatoid arthritis and osteoarthritis using gene microarrays |
title_full | Comparison of molecular mechanisms of rheumatoid arthritis and osteoarthritis using gene microarrays |
title_fullStr | Comparison of molecular mechanisms of rheumatoid arthritis and osteoarthritis using gene microarrays |
title_full_unstemmed | Comparison of molecular mechanisms of rheumatoid arthritis and osteoarthritis using gene microarrays |
title_short | Comparison of molecular mechanisms of rheumatoid arthritis and osteoarthritis using gene microarrays |
title_sort | comparison of molecular mechanisms of rheumatoid arthritis and osteoarthritis using gene microarrays |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4878540/ https://www.ncbi.nlm.nih.gov/pubmed/27082252 http://dx.doi.org/10.3892/mmr.2016.5144 |
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