International journal of women's health · 2026
Integrative eQTL and Multi-Omics Analysis Reveals the Role of N6-Methyladenosine Modification in Polycystic Ovary Syndrome and Predictive Model Construction.
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Jin Mengqi, Xi Sujuan, Ma Lin
Аннотация
OBJECTIVE: Polycystic ovary syndrome (PCOS) is a heterogeneous disorder with incompletely understood epigenetic regulation. We investigated the role of N6-methyladenosine (m6A)-related single nucleotide polymorphisms (m6A-SNPs) in PCOS.
METHODS: Bulk RNA sequencing (RNA-seq) data from the GSE277906 dataset, comprising 23 PCOS patients and 17 healthy controls, was analyzed for differential expression. m6A-SNPs with significant expression quantitative trait locus (eQTL) signals were obtained by integrating eQTLGen and RMVar. Gene Ontology, KEGG, and Reactome supported enrichment analyses. Immune infiltration was estimated with CIBERSORT. Logistic-regression models were built based on the entire cohort without data splitting and evaluated using receiver operating characteristic (ROC) curves.
RESULTS: A total of 362 differentially expressed genes and 45 PCOS-related candidate m6A-SNPs were identified. Enrichment analysis revealed that these genes were mainly involved in cell cycle dysregulation and interferon-α/β signaling pathways. Immune infiltration analysis showed no extensive remodeling of the overall immune landscape in PCOS, but correlation analysis identified significant associations between key genes and specific immune subsets, including monocytes, dendritic cells, and M2 macrophages. The predictive model integrating gene expression and immune cell infiltration achieved the highest diagnostic value (AUC = 0.836), outperforming models based on single features. Moreover, genomic annotation of the core gene SECTM1 indicated an open chromatin state and potential regulation by a complex transcriptional network.
CONCLUSION: m6A-SNPs likely contribute to PCOS pathogenesis via gene-regulatory effects. The integrative model shows high diagnostic promise, and SECTM1 emerges as a potential candidate for further functional validation and diagnostic exploration.
METHODS: Bulk RNA sequencing (RNA-seq) data from the GSE277906 dataset, comprising 23 PCOS patients and 17 healthy controls, was analyzed for differential expression. m6A-SNPs with significant expression quantitative trait locus (eQTL) signals were obtained by integrating eQTLGen and RMVar. Gene Ontology, KEGG, and Reactome supported enrichment analyses. Immune infiltration was estimated with CIBERSORT. Logistic-regression models were built based on the entire cohort without data splitting and evaluated using receiver operating characteristic (ROC) curves.
RESULTS: A total of 362 differentially expressed genes and 45 PCOS-related candidate m6A-SNPs were identified. Enrichment analysis revealed that these genes were mainly involved in cell cycle dysregulation and interferon-α/β signaling pathways. Immune infiltration analysis showed no extensive remodeling of the overall immune landscape in PCOS, but correlation analysis identified significant associations between key genes and specific immune subsets, including monocytes, dendritic cells, and M2 macrophages. The predictive model integrating gene expression and immune cell infiltration achieved the highest diagnostic value (AUC = 0.836), outperforming models based on single features. Moreover, genomic annotation of the core gene SECTM1 indicated an open chromatin state and potential regulation by a complex transcriptional network.
CONCLUSION: m6A-SNPs likely contribute to PCOS pathogenesis via gene-regulatory effects. The integrative model shows high diagnostic promise, and SECTM1 emerges as a potential candidate for further functional validation and diagnostic exploration.