Aberrantly hydroxymethylated differentially expressed genes and the associated protein pathways in osteoarthritis
Background The elderly population is at risk of osteoarthritis (OA), a common, multifactorial, degenerative joint disease. Environmental, genetic, and epigenetic (such as DNA hydroxymethylation) factors may be involved in the etiology, development, and pathogenesis of OA. Here, comprehensive bioinfo...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2019-02-01
|
| Series: | PeerJ |
| Subjects: | |
| Online Access: | https://peerj.com/articles/6425.pdf |
| _version_ | 1797418693446074368 |
|---|---|
| author | Yang Fang Pingping Wang Lin Xia Suwen Bai Yonggang Shen Qing Li Yang Wang Jinhang Zhu Juan Du Bing Shen |
| author_facet | Yang Fang Pingping Wang Lin Xia Suwen Bai Yonggang Shen Qing Li Yang Wang Jinhang Zhu Juan Du Bing Shen |
| author_sort | Yang Fang |
| collection | DOAJ |
| description | Background The elderly population is at risk of osteoarthritis (OA), a common, multifactorial, degenerative joint disease. Environmental, genetic, and epigenetic (such as DNA hydroxymethylation) factors may be involved in the etiology, development, and pathogenesis of OA. Here, comprehensive bioinformatic analyses were used to identify aberrantly hydroxymethylated differentially expressed genes and pathways in osteoarthritis to determine the underlying molecular mechanisms of osteoarthritis and susceptibility-related genes for osteoarthritis inheritance. Methods Gene expression microarray data, mRNA expression profile data, and a whole genome 5hmC dataset were obtained from the Gene Expression Omnibus repository. Differentially expressed genes with abnormal hydroxymethylation were identified by MATCH function. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the genes differentially expressed in OA were performed using Metascape and the KOBAS online tool, respectively. The protein–protein interaction network was built using STRING and visualized in Cytoscape, and the modular analysis of the network was performed using the Molecular Complex Detection app. Results In total, 104 hyperhydroxymethylated highly expressed genes and 14 hypohydroxymethylated genes with low expression were identified. Gene ontology analyses indicated that the biological functions of hyperhydroxymethylated highly expressed genes included skeletal system development, ossification, and bone development; KEGG pathway analysis showed enrichment in protein digestion and absorption, extracellular matrix–receptor interaction, and focal adhesion. The top 10 hub genes in the protein–protein interaction network were COL1A1, COL1A2, COL2A1, COL3A1, COL5A1, COL5A2, COL6A1, COL8A1, COL11A1, and COL24A1. All the aforementioned results are consistent with changes observed in OA. Conclusion After comprehensive bioinformatics analysis, we found aberrantly hydroxymethylated differentially expressed genes and pathways in OA. The top 10 hub genes may be useful hydroxymethylation analysis biomarkers to provide more accurate OA diagnoses and target genes for treatment of OA. |
| first_indexed | 2024-03-09T06:37:39Z |
| format | Article |
| id | doaj.art-d6385c1a07a74554899a16693b4d32d6 |
| institution | Directory Open Access Journal |
| issn | 2167-8359 |
| language | English |
| last_indexed | 2024-03-09T06:37:39Z |
| publishDate | 2019-02-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ |
| spelling | doaj.art-d6385c1a07a74554899a16693b4d32d62023-12-03T10:56:24ZengPeerJ Inc.PeerJ2167-83592019-02-017e642510.7717/peerj.6425Aberrantly hydroxymethylated differentially expressed genes and the associated protein pathways in osteoarthritisYang Fang0Pingping Wang1Lin Xia2Suwen Bai3Yonggang Shen4Qing Li5Yang Wang6Jinhang Zhu7Juan Du8Bing Shen9School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, ChinaSchool of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, ChinaSchool of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, ChinaSchool of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, ChinaNursing Faculty, Anhui Health College, Chizhou, Anhui, ChinaCentral Laboratory of Medical Research Center, Anhui Provincial Hospital, Hefei, Anhui, ChinaSchool of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, ChinaSchool of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, ChinaSchool of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, ChinaSchool of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, ChinaBackground The elderly population is at risk of osteoarthritis (OA), a common, multifactorial, degenerative joint disease. Environmental, genetic, and epigenetic (such as DNA hydroxymethylation) factors may be involved in the etiology, development, and pathogenesis of OA. Here, comprehensive bioinformatic analyses were used to identify aberrantly hydroxymethylated differentially expressed genes and pathways in osteoarthritis to determine the underlying molecular mechanisms of osteoarthritis and susceptibility-related genes for osteoarthritis inheritance. Methods Gene expression microarray data, mRNA expression profile data, and a whole genome 5hmC dataset were obtained from the Gene Expression Omnibus repository. Differentially expressed genes with abnormal hydroxymethylation were identified by MATCH function. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the genes differentially expressed in OA were performed using Metascape and the KOBAS online tool, respectively. The protein–protein interaction network was built using STRING and visualized in Cytoscape, and the modular analysis of the network was performed using the Molecular Complex Detection app. Results In total, 104 hyperhydroxymethylated highly expressed genes and 14 hypohydroxymethylated genes with low expression were identified. Gene ontology analyses indicated that the biological functions of hyperhydroxymethylated highly expressed genes included skeletal system development, ossification, and bone development; KEGG pathway analysis showed enrichment in protein digestion and absorption, extracellular matrix–receptor interaction, and focal adhesion. The top 10 hub genes in the protein–protein interaction network were COL1A1, COL1A2, COL2A1, COL3A1, COL5A1, COL5A2, COL6A1, COL8A1, COL11A1, and COL24A1. All the aforementioned results are consistent with changes observed in OA. Conclusion After comprehensive bioinformatics analysis, we found aberrantly hydroxymethylated differentially expressed genes and pathways in OA. The top 10 hub genes may be useful hydroxymethylation analysis biomarkers to provide more accurate OA diagnoses and target genes for treatment of OA.https://peerj.com/articles/6425.pdfDNA hydroxymethylationExpression profileBioinformaticsCartilageCollagen |
| spellingShingle | Yang Fang Pingping Wang Lin Xia Suwen Bai Yonggang Shen Qing Li Yang Wang Jinhang Zhu Juan Du Bing Shen Aberrantly hydroxymethylated differentially expressed genes and the associated protein pathways in osteoarthritis PeerJ DNA hydroxymethylation Expression profile Bioinformatics Cartilage Collagen |
| title | Aberrantly hydroxymethylated differentially expressed genes and the associated protein pathways in osteoarthritis |
| title_full | Aberrantly hydroxymethylated differentially expressed genes and the associated protein pathways in osteoarthritis |
| title_fullStr | Aberrantly hydroxymethylated differentially expressed genes and the associated protein pathways in osteoarthritis |
| title_full_unstemmed | Aberrantly hydroxymethylated differentially expressed genes and the associated protein pathways in osteoarthritis |
| title_short | Aberrantly hydroxymethylated differentially expressed genes and the associated protein pathways in osteoarthritis |
| title_sort | aberrantly hydroxymethylated differentially expressed genes and the associated protein pathways in osteoarthritis |
| topic | DNA hydroxymethylation Expression profile Bioinformatics Cartilage Collagen |
| url | https://peerj.com/articles/6425.pdf |
| work_keys_str_mv | AT yangfang aberrantlyhydroxymethylateddifferentiallyexpressedgenesandtheassociatedproteinpathwaysinosteoarthritis AT pingpingwang aberrantlyhydroxymethylateddifferentiallyexpressedgenesandtheassociatedproteinpathwaysinosteoarthritis AT linxia aberrantlyhydroxymethylateddifferentiallyexpressedgenesandtheassociatedproteinpathwaysinosteoarthritis AT suwenbai aberrantlyhydroxymethylateddifferentiallyexpressedgenesandtheassociatedproteinpathwaysinosteoarthritis AT yonggangshen aberrantlyhydroxymethylateddifferentiallyexpressedgenesandtheassociatedproteinpathwaysinosteoarthritis AT qingli aberrantlyhydroxymethylateddifferentiallyexpressedgenesandtheassociatedproteinpathwaysinosteoarthritis AT yangwang aberrantlyhydroxymethylateddifferentiallyexpressedgenesandtheassociatedproteinpathwaysinosteoarthritis AT jinhangzhu aberrantlyhydroxymethylateddifferentiallyexpressedgenesandtheassociatedproteinpathwaysinosteoarthritis AT juandu aberrantlyhydroxymethylateddifferentiallyexpressedgenesandtheassociatedproteinpathwaysinosteoarthritis AT bingshen aberrantlyhydroxymethylateddifferentiallyexpressedgenesandtheassociatedproteinpathwaysinosteoarthritis |