Analysis of gene expression and methylation datasets identified ADAMTS9, FKBP5, and PFKBF3 as biomarkers for osteoarthritis.

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  • Additional Information
    • Source:
      Publisher: Wiley-Liss Country of Publication: United States NLM ID: 0050222 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-4652 (Electronic) Linking ISSN: 00219541 NLM ISO Abbreviation: J Cell Physiol Subsets: MEDLINE
    • Publication Information:
      Publication: New York, NY : Wiley-Liss
      Original Publication: Philadelphia, Wistar Institute of Anatomy and Biology.
    • Subject Terms:
      ADAMTS9 Protein/*metabolism ; Gene Expression Regulation/*physiology ; Osteoarthritis/*metabolism ; Phosphofructokinase-2/*metabolism ; Tacrolimus Binding Proteins/*metabolism; ADAMTS9 Protein/genetics ; Biomarkers ; DNA Methylation ; Databases, Genetic ; Humans ; Phosphofructokinase-2/genetics ; Tacrolimus Binding Proteins/genetics ; Transcriptome
    • Abstract:
      Background: Osteoarthritis (OA) is a kind of chronic osteoarthropathy and degenerative joint disease. Epigenetic regulation in the gene expression dynamics has become increasingly important in OA. We performed a combined analysis of two types of microarray datasets (gene expression and DNA methylation) to identify methylation-based key biomarkers to provide a better understanding of molecular biological mechanisms of OA.
      Methods: We obtained two expression profiling datasets (GSE55235, GSE55457) and one DNA methylation profiling data set (GSE63695) from the Gene Expression Omnibus. First, differentially expressed genes (DEGs) between patients with OA and controls were identified using the Limma package in R(v3.4.4). Then, function enrichment analysis of DEGs was performed using a DAVID database. For DNA methylation datasets, ChAMP methylation analysis package was used to identify differential methylation genes (DMGs). Finally, a comprehensive analysis of DEGs and DMGs was conducted to identify genes that exhibited differential expression and methylation simultaneously.
      Results: We identified 112 DEGs and 2,896 DMGs in patients with OA compared with controls. Functional analysis of DEGs obtained that inflammatory responses, immune responses, and positive regulation of apoptosis, tumor necrosis factor (TNF) signaling pathway, and osteoclast differentiation may be involved in the pathogenesis of OA. Cross-analysis revealed 26 genes that exhibited differential expression and methylation in OA. Among them, ADAMTS9, FKBP5, and PFKBF3 were identified as valuable methylation-based biomarkers for OA.
      Conclusion: In summary, our study identified different molecular features between patients with OA and controls. This may provide new clues for clarifying the pathogenetic mechanisms of OA.
      (© 2018 Wiley Periodicals, Inc.)
    • Contributed Indexing:
      Keywords: DNA methylation; bioinformatics; gene expression; osteoarthritis (OA)
    • Accession Number:
      0 (Biomarkers)
      EC 2.7.1.105 (PFKFB3 protein, human)
      EC 2.7.1.105 (Phosphofructokinase-2)
      EC 3.4.24.- (ADAMTS9 Protein)
      EC 3.4.24.- (ADAMTS9 protein, human)
      EC 5.2.1.- (Tacrolimus Binding Proteins)
      EC 5.2.1.8 (tacrolimus binding protein 5)
    • Publication Date:
      Date Created: 20181015 Date Completed: 20200417 Latest Revision: 20200417
    • Publication Date:
      20231215
    • Accession Number:
      10.1002/jcp.27557
    • Accession Number:
      30317616