Transcriptome Profiling of the Anterior Cingulate Cortex in a CFA-Induced Inflammatory Pain Model Identifies ECM-Related Genes in a Model of Rheumatoid Arthritis.

BACKGROUND

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent joint inflammation and progressive bone destruction. However, its complex pathogenesis remains poorly understood, and effective therapeutic targets are still lacking.

OBJECTIVE

This study aimed to identify key genes associated with RA and elucidate their biological significance by integrating bioinformatic analysis with experimental validation.

METHODS

Whole-transcriptome data from the anterior cingulate cortex (ACC) of Complete Freund's Adjuvant (CFA)-induced inflammatory pain and control mice (GSE147216 dataset, GEO database) were collected from NCBI (National Center for Biotechnology Information). Differentially expressed genes (DEGs) were first identified. Subsequent analyses included Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, construction of a protein-protein interaction (PPI) network, and identification of hub genes using a Random Forest machine learning algorithm. Quantitative PCR (qPCR) was performed to validate gene expression levels.

RESULTS

A total of 76 DEGs were identified, including 64 upregulated and 12 downregulated genes. Among them, Fn1 (fibronectin 1), Bgn (biglycan), and Lum (lumican) were identified as hub genes. Functional enrichment analysis revealed inflammatory responses, extracellular matrix (ECM) remodeling, and the TGF-β signaling pathway. qPCR validation confirmed significant upregulation of Fn1, Bgn, and Lum mRNA in the CFA group.

CONCLUSIONS

This study highlights the potential roles of Fn1, Bgn, and Lum in the central sensitization associated with inflammatory pain, offering insights relevant to RA.