Shared Risk Genes and Common Molecular Pathways Between PCOS and RPL by Integrated Transcriptomic Analysis and Machine Learning

Background Polycystic ovary syndrome (PCOS) is an endocrine-related factor contributing to recurrent pregnancy loss (RPL). PCOS and RPL may share common risk genes and potential pathological mechanisms. Methods Three PCOS and three RPL datasets were obtained from the GEO database. Weighted gene co-expression network analysis (WGCNA), differential expression analysis, and three external immune gene datasets were used to identify shared immunological genes. Enrichr analysis, Gene-TF-miRNA, and Gene-pro networks suggested potential pathogenic mechanisms. Machine learning algorithms were then applied to identify the key risk gene. ROC curves and RT-qPCR tested the performance of the key gene in validation datasets for both PCOS and RPL. Gene Set Enrichment Analysis (GSEA) validated pathway changes, and immune infiltration analysis identified immune cells involved in both diseases. Conclusions This study highlighted the association of the NF-κB pathway by involvement of 19 shared immunological genes and one key risk gene, IL1RN in RPL with PCOS . It might provide a novel understanding of the molecular pathology for RPL with PCOS.