Identification and validation of cell senescence genes in recurrent spontaneous abortion via multiple bioinformatics algorithms.

Recurrent spontaneous abortion (RSA) represents a significant challenge in reproductive obstetrics, affecting approximately 5% of couples globally. Despite various treatments, the effectiveness of these interventions remains highly contentious. Emerging evidence suggests that cellular senescence plays a critical role in the pathogenesis of multiple diseases, potentially implicating its involvement in RSA as well. This study integrated two RNA sequencing datasets and employed Weighted Gene Co-Expression Network Analysis (WGCNA) alongside five machine learning algorithms (XGBoost, Boruta, LASSO, SVM-RFE, and Random Forest) to identify cellular senescence genes linked to RSA. Gene expression was validated at both the transcriptome and protein levels using qPCR, Western blot, and immunofluorescence techniques. An Artificial Neural Network (ANN) model was implemented to evaluate their diagnostic value. Additionally, functional enrichment and single-cell RNA sequencing analyses were conducted to investigate the biological functions of these genes. Three cellular senescence genes-TBX2, SRSF3, and TNRC6B-were identified and found to be upregulated in RSA patients. Functional enrichment analysis revealed these genes' involvement in the MAPK signaling pathway, ECM-receptor interaction, and cell-cell communication. Single-cell RNA sequencing demonstrated the distribution of these genes across various cell types, underscoring their significance in RSA. Furthermore, drug sensitivity analysis identified potential small molecule therapeutics for RSA. Cellular senescence may play a central role in the pathology of RSA, with TBX2, SRSF3, and TNRC6B emerging as potential diagnostic biomarkers. This research enhances our understanding of the molecular mechanisms underlying RSA and lays the groundwork for new diagnostic and therapeutic strategies. Nonetheless, further experimental studies are required to elucidate the specific roles and mechanisms of these genes in RSA, with the ultimate goal of achieving precise prevention and personalized treatment.