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Article

Identification of potential target genes associated with the pathogenesis of osteoarthritis using microarray based analysis

  • Authors:
    • Meng Li
    • Liqiang Zhi
    • Zhi Zhang
    • Weiguo Bian
    • Yusheng Qiu
  • View Affiliations / Copyright

    Affiliations: Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
  • Pages: 2799-2806
    |
    Published online on: July 5, 2017
       https://doi.org/10.3892/mmr.2017.6928
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Abstract

The aim of the present study was to investigate the molecular circuitry of osteoarthritis (OA) and identify more potential target genes for OA treatment. Microarray data of GSE32317 was downloaded from the National Center for Biotechnology Information Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in samples of synovial membrane from patients with early stage of knee OA (OA_Early) and late stage of knee OA (OA_End) that were compared with healthy specimens. Bioinformatics analysis was applied to analyze the significant functions and pathways that were enriched by the common DEGs identified in OA_Early and OA_End samples. Furthermore, a protein‑protein interaction (PPI) network was constructed and significant modules were extracted. Transcription factors (TFs) that could regulate genes in the significant modules were identified. A total of 1,207 and 1,575 DEGs were identified in OA_Early and OA_End samples compared with healthy samples, respectively. A total of 740 genes were upregulated and 308 genes were downregulated across the OA_Early and OA_End samples. These common DEGs were enriched in different gene ontology terms and pathways, such as immune response. Angiotensinogen (AGT) and C‑X‑C motif chemokine ligand 12 (CXCL12) were identified to be hub proteins in the PPI network or in the selected module 1. In addition, the DEG lysine demethylase 2B (KDM2B) was identified as a TF that can regulate genes in the significant modules 2 and 3. In conclusion, the present study has identified AGT, CXCL12 and KDM2B as potentially essential genes associated with the pathogenesis of knee OA.
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Copy and paste a formatted citation
Spandidos Publications style
Li M, Zhi L, Zhang Z, Bian W and Qiu Y: Identification of potential target genes associated with the pathogenesis of osteoarthritis using microarray based analysis. Mol Med Rep 16: 2799-2806, 2017.
APA
Li, M., Zhi, L., Zhang, Z., Bian, W., & Qiu, Y. (2017). Identification of potential target genes associated with the pathogenesis of osteoarthritis using microarray based analysis. Molecular Medicine Reports, 16, 2799-2806. https://doi.org/10.3892/mmr.2017.6928
MLA
Li, M., Zhi, L., Zhang, Z., Bian, W., Qiu, Y."Identification of potential target genes associated with the pathogenesis of osteoarthritis using microarray based analysis". Molecular Medicine Reports 16.3 (2017): 2799-2806.
Chicago
Li, M., Zhi, L., Zhang, Z., Bian, W., Qiu, Y."Identification of potential target genes associated with the pathogenesis of osteoarthritis using microarray based analysis". Molecular Medicine Reports 16, no. 3 (2017): 2799-2806. https://doi.org/10.3892/mmr.2017.6928
Copy and paste a formatted citation
x
Spandidos Publications style
Li M, Zhi L, Zhang Z, Bian W and Qiu Y: Identification of potential target genes associated with the pathogenesis of osteoarthritis using microarray based analysis. Mol Med Rep 16: 2799-2806, 2017.
APA
Li, M., Zhi, L., Zhang, Z., Bian, W., & Qiu, Y. (2017). Identification of potential target genes associated with the pathogenesis of osteoarthritis using microarray based analysis. Molecular Medicine Reports, 16, 2799-2806. https://doi.org/10.3892/mmr.2017.6928
MLA
Li, M., Zhi, L., Zhang, Z., Bian, W., Qiu, Y."Identification of potential target genes associated with the pathogenesis of osteoarthritis using microarray based analysis". Molecular Medicine Reports 16.3 (2017): 2799-2806.
Chicago
Li, M., Zhi, L., Zhang, Z., Bian, W., Qiu, Y."Identification of potential target genes associated with the pathogenesis of osteoarthritis using microarray based analysis". Molecular Medicine Reports 16, no. 3 (2017): 2799-2806. https://doi.org/10.3892/mmr.2017.6928
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