Integrated Multi-Omics Analysis and Experimental Validation Identify Acetylation-Related Genes as Potential Regulators in Osteoarthritis.

Background

Osteoarthritis (OA) is a prevalent degenerative joint disease with a complex molecular basis. This study aims to identify key molecules involved in OA pathogenesis, focusing on the role of acetylation-related gene expression.

Methods

Public microarray datasets GSE82107 and GSE169077 were integrated to construct a differential expression landscape between OA patients and healthy controls. Acetylation-linked differentially expressed genes (acetylation-DEGs, ARDEGs) were extracted by intersecting DEGs with a curated set of acetyltransferases, deacetylases and acetylation substrates. A protein-protein interaction (PPI) network was built and subjected to LASSO-penalized regression to prioritise hub genes. Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Gene Set Variation Analysis (GSVA) were performed to characterize biological themes. Immune infiltration was quantified with CIBERSORTx and single-sample Gene Set Enrichment Analysis (ssGSEA). Single-cell RNA-seq data (GSE216651) were employed for orthogonal validation. For experimental corroboration, synovial tissue was collected from OA patients undergoing arthroplasty; mRNA and protein levels of hub genes were determined by qRT-PCR, Western blot and immunofluorescence. The destabilisation of the medial meniscus (DMM) mouse model was used for in vivo verification.

Results

Twenty-one high-confidence ARDEGs were identified. Analysis of the PPI network yielded ten hub nodes, six of which (EGR1, PFKFB3, HDAC4, MMP13, PDK4 and ACADL) retained non-zero coefficients in the least absolute shrinkage and selection operator (LASSO) model. Enrichment analyses implicated these genes in embryonic development, collagen-containing extracellular matrix remodeling and PI3K-Akt signaling. Immune infiltration analysis showed potential differences in immune cell abundance between OA and healthy controls. Single-cell dataset analysis verified the expression patterns of key genes in different cell types. Concordant dysregulation of EGR1, PFKFB3, HDAC4, MMP13 and PDK4 was observed at both mRNA and protein levels in human OA synovium and DMM mouse joints.

Conclusion

This comprehensive analysis identified acetylation-related genes and analyzed their potential biological roles in OA. The identified ARDEGs may provide new insights into OA diagnosis and treatment.