Aberrantly hydroxymethylated differentially expressed genes and the associated protein pathways in osteoarthritis

Yang Fang; Pingping Wang; Lin Xia; Suwen Bai; Yonggang Shen; Qing Li; Yang Wang; Jinhang Zhu; Juan Du; Bing Shen

doi:10.7717/peerj.6425

Aberrantly hydroxymethylated differentially expressed genes and the associated protein pathways in osteoarthritis

PeerJ. 2019 Feb 25:7:e6425. doi: 10.7717/peerj.6425. eCollection 2019.

Authors

Yang Fang¹, Pingping Wang¹, Lin Xia¹, Suwen Bai¹, Yonggang Shen², Qing Li³, Yang Wang¹, Jinhang Zhu¹, Juan Du¹, Bing Shen¹

Affiliations

¹ School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, China.
² Nursing Faculty, Anhui Health College, Chizhou, Anhui, China.
³ Central Laboratory of Medical Research Center, Anhui Provincial Hospital, Hefei, Anhui, China.

Abstract

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.

Keywords: Bioinformatics; Cartilage; Collagen; DNA hydroxymethylation; Expression profile.

Grants and funding

This work was supported by grants from the National Natural Science Foundation of China (Grant No. U1732157, 81570403, 81472018), the Anhui Provincial Natural Science Foundation (Grant No. 1708085MH187), the Natural Science Foundation of Anhui Province Department of Education (Grant No. KJ2018A0974); Anhui Medical University for Scientific Research (BSKY XJ201607), the Outstanding Young Investigator of Anhui Medical University, and the Science and Technology Research Project of Anhui Province (Grant No. 1501041147). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.