Multiomics analyses reveal key circadian rhythm genes implicated in Premature ovarian insufficiency

Background Premature ovarian insufficiency (POI), defined as the loss of ovarian function before the age of 40 years, severely disrupts reproductive and endocrine health. While circadian rhythm disruption has been implicated in reproductive aging, its mechanistic contribution to POI remains largely unexplored in humans. Methods We performed an integrative multiomics analysis combining single-nucleus RNA sequencing (snRNA-seq), bulk RNA-seq, genome-wide association studies (GWAS), and expression quantitative trait locus (eQTL) data. Co-expression networks were constructed via weighted gene coexpression network analysis (WGCNA), while cell-cell communication and trajectory analyses were conducted via CellChat and Monocle. Regulatory networks were inferred via SCENIC, and causality was assessed via summary-data-based Mendelian randomization (SMR). Candidate hub genes were prioritized through machine learning and validated via in vitro assays assessing rhythmicity and gene expression. Results snRNA-seq identified a granulosa cell subpopulation (GC1) with the highest circadian rhythm score, suggesting a pivotal role in regulating the ovarian clock. WGCNA and SCENIC analyses revealed age-associated downregulation of the core circadian regulators CLOCK and ARNTL, accompanied by disruptions in lipid metabolism and stress response pathways. SMR analysis revealed 120 circadian-related genes associated with POI risk, 30 of which were enriched in GC1-specific modules. CLOCK, CRY1, APOE, and GSTA1 emerged as key regulators on the basis of machine learning prioritization. Functional assays confirmed impaired rhythmicity and altered gene expression in KGN cells and senescent mouse granulosa cells. CLOCK knockdown increased P16 and P21 expression, underscoring its role in preserving granulosa cell homeostasis. Conclusions Our findings implicate circadian rhythm disruption as a hallmark and potential driver of ovarian aging. CLOCK, BMAL1, CRY1, APOE, and GSTA1 may serve as early biomarkers and therapeutic targets for POI.