Identification and validation of hub m7G-related genes and infiltrating immune cells in osteoarthritis based on integrated computational and bioinformatics analysis.

Abstract

Background: Osteoarthritis (OA) is a joint disease closely associated with synovial tissue inflammation, with the severity of synovitis impacting disease progression. m7G RNA methylation is critical in RNA processing, metabolism, and function, but its role in OA synovial tissue is not well understood. This study explores the relationship between m7G methylation and immune infiltration in OA.

Methods: Data were obtained from the GEO database. Hub genes related to m7G were identified using differential expression and LASSO-Cox regression analysis, and a diagnostic model was developed. Functional enrichment, drug target prediction, and target gene-related miRNA prediction were performed for these genes. Immune cell infiltration was analyzed using the CIBERSORT algorithm, and unsupervised clustering analysis was conducted to examine immune infiltration patterns. RT-qPCR was used to validate hub gene expression.

Results: Seven m7G hub genes (SNUPN, RNMT, NUDT1, LSM1, LARP1, CYFIP2, and CYFIP1) were identified and used to develop a nomogram for OA risk prediction. Functional enrichment indicated involvement in mRNA metabolism and RNA transport. Differences in macrophage and T-cell infiltration were observed between OA and normal groups. Two distinct m7G immune infiltration patterns were identified, with significant microenvironment differences between clusters. RT-qPCR confirmed differential hub gene expression.

Conclusion: A diagnostic model based on seven m7G hub genes was developed, highlighting these genes as potential biomarkers and significant players in OA pathogenesis.