Bioinformatics analysis of Rho-signal transduction genes in postmenopausal osteoporosis and periodontitis

Postmenopausal osteoporosis (PMOP) increases the risk of periodontitis (PD), yet the shared mechanisms remain unclear. Rho-signal transduction genes may play a role due to their involvement in bone remodeling. This study aimed to explore Rho-related genes as potential biomarkers linking PMOP and PD. Public transcriptomic datasets of PMOP and PD were analyzed. After PCA-based outlier removal, differentially expressed genes were identified using limma, followed by intersection analysis, KEGG enrichment, PPI network construction, and Rho pathway screening. Machine learning (Lasso, SVM-RFE) and Wilcoxon tests identified CTNNAL1 and MERTK as candidate biomarkers. GSEA, ssGSEA, and immune infiltration analyses were performed, along with construction of lncRNA/circRNA-miRNA-mRNA regulatory networks. Subcellular localization, chromosomal mapping, disease association, and molecular docking analyses were also conducted. An ovariectomy plus periodontitis (OP+PD) mouse model was used for in vivo validation. CTNNAL1 and MERTK were consistently dysregulated in both PMOP and PD datasets. They were enriched in MYC-targets-V1, allograft rejection, heme metabolism, and oxidative phosphorylation. Immune analysis revealed altered levels of CD56^bright NK cells and immature dendritic cells. Regulatory networks implicated lncRNAs such as XIST, GAS5, and NEAT1. Molecular docking indicated interactions with pinosylvin and glycitein. In vivo validation confirmed significant changes in CTNNAL1 and MERTK expression and increased bone loss and inflammation in OP+PD mice. CTNNAL1 and MERTK were identified as potential Rho-associated biomarkers showing consistent dysregulation in both PMOP and PD datasets. These biomarkers may serve as risk indicators or therapeutic candidates, warranting further validation.