Systematic Analysis of Differential Expression Profile in Rheumatoid Arthritis Chondrocytes Using Next-Generation Sequencing and Bioinformatics Approaches

Int J Med Sci. 2018 Jul 13;15(11):1129-1142. doi: 10.7150/ijms.27056. eCollection 2018.


Cartilage destruction in rheumatoid arthritis (RA) occurs primarily in the pannus-cartilage interface. The close contact of the synovium-cartilage interface implicates crosstalk between synovial fibroblasts and chondrocytes. The aim of this study is to explore the differentially expressed genes and novel microRNA regulations potentially implicated in the dysregulated cartilage homeostasis in joint destruction of RA. Total RNAs were extracted from human primary cultured normal and RA chondrocytes for RNA and small RNA expression profiling using next-generation sequencing. Using systematic bioinformatics analyses, we identified 463 differentially expressed genes in RA chondrocytes were enriched in biological functions related to altered cell cycle process, inflammatory response and hypoxic stimulation. Moreover, fibroblast growth factor 9 (FGF9), kynureninase (KYNU), and regulator of cell cycle (RGCC) were among the top dysregulated genes identified to be potentially affected in the RA joint microenvironment, having similar expression patterns observed in arrays of clinical RA synovial tissues from the Gene Expression Omnibus database. Additionally, among the 31 differentially expressed microRNAs and 10 candidate genes with potential microRNA-mRNA interactions in RA chondrocytes, the novel miR-140-3p-FGF9 interaction was validated in different microRNA prediction databases, and proposed to participate in the pathogenesis of joint destruction through dysregulated cell growth in RA. The findings provide new perspectives for target genes in the management of cartilage destruction in RA.

Keywords: bioinformatics.; cell cycle; chondrocytes; next-generation sequencing; rheumatoid arthritis.

MeSH terms

  • Arthritis, Rheumatoid / metabolism*
  • Cells, Cultured
  • Chondrocytes / metabolism*
  • Computational Biology
  • Fibroblasts
  • High-Throughput Nucleotide Sequencing*
  • Humans