Synovium is a sensitive tissue for mapping the negative effects of systemic iron overload in osteoarthritis: identification and validation of two potential targets

Abstract

Abstract Background The prevention and treatment of osteoarthritis (OA) pose a major challenge in its research. The synovium is a critical tissue in the systematic treatment of OA. The present study aimed to investigate potential target genes and their correlation with iron overload in OA patients. Methods The internal datasets for analysis included the microarray datasets GSE46750, GSE55457, and GSE56409, while the external datasets for validation included GSE12021 and GSE55235. The GSE176308 dataset was used to generate single-cell RNA sequencing profiles. To investigate the expression of the target genes in synovial samples, quantitative reverse transcription-PCR, western blotting, and immunohistochemical assay were conducted. ELISA was used to detect the levels of ferritin and Fe2+ in both serum and synovium. Results JUN and ZFP36 were screened from the differentially expressed genes, and their mRNA were significantly reduced in the OA synovium compared to that in normal synovium. Subsequently, complex and dynamically evolving cellular components were observed in the OA synovium. The mRNA level of JUN and ZFP36 differed across various cell clusters of OA synovium and correlated with immune cell infiltration. Moreover, ferritin and Fe2+ were significantly increased in the serum and synovium of OA patients. Further, we found that JUN elevated and ZFP36 decreased at protein level. Conclusions The synovium is a sensitive tissue for mapping the adverse effects of systemic iron overload in OA. JUN and ZFP36 represent potential target genes for attenuating iron overload during OA treatment. Some discrepancies between the transcription and protein levels of JUN suggest that post-transcriptional modifications may be implicated. Future studies should also focus on the roles of JUN and ZFP36 in inducing changes in cellular components in the synovium during OA pathogenesis.

Keywords

• Bioinformatics analysis
• Iron overload
• Osteoarthritis
• Single-cell RNA-seq analysis
• Synovium
• Validation experiments