Bulk and single-cell multiomics insights into theca cell and granulosa cell dysfunction in polyendocrine metabolic ovarian syndrome

Abstract

Abstract Polyendocrine metabolic ovarian syndrome (PMOS) is a heterogeneous disorder marked by a variety of clinical, hormonal, and metabolic disorders of an endocrine nature, affecting women of reproductive age and causing anovulatory infertility, metabolic dysfunction and hormonal disorders of a heterogeneous nature. Because of its complicated etiology and varied clinical presentation, PMOS’s underlying processes are still poorly understood despite its high incidence. There is a growing body of literature that attributes the multifactorial nature of PMOS to genetic predisposition, epigenetic modifications, environmental variables, and metabolic abnormalities, which result in dysregulation of multiple cellular pathways associated with ovarian function. Ovarian theca and granulosa cells are crucial to the pathophysiology of PMOS because alterations in their activity result in aberrant steroidogenesis, follicular arrest, reduced oocyte development, and disrupted endocrine signalling. Recent advances in high-throughput multiomics technology have greatly advanced our understanding of the molecular landscape of PMOS. Recent advances in multiomics technologies, including genomics, epigenomics, transcriptomics, proteomics and metabolomics, have revolutionised our understanding of PMOS by allowing the integrated exploration of these molecular alterations. Genomic studies identified PMOS susceptibility loci, whereas epigenomic and transcriptomic studies revealed abnormal gene regulation and miRNA regulation. Proteomic and metabolomic profiling further elucidated functional disruption in protein networks and metabolic pathways, particularly in theca and granulosa cells. Bulk multiomics approaches have substantially advanced our understanding of PMOS through the identification of genetic, epigenetic, transcriptomic, proteomic, and metabolic alterations associated with disease pathogenesis. Cellular function and heterogeneity are largely governed by complex gene regulatory networks (GRNs) and dynamic cell-to-cell communication mechanisms. Recent advances in single-cell multiomics approaches have enabled the identification of cell-specific molecular signatures and improved the understanding of the complex interactions between ovarian cell populations. Integration of bulk and single-cell multiomics datasets offers a more nuanced perspective on disease mechanisms. By integrating multiomics data, the present review aims to provide a more detailed understanding of the PMOS, thereby facilitating the identification of clinically significant biomarkers, the clarification of key regulatory pathways, and the identification of potential treatment targets. Collectively, these findings provide a framework for future translational research to improve the diagnosis and management of PMOS.