Identification and validation of senescence-related genes in polycystic ovary syndrome

• Main Authors: Danni Jiang (Author), Yang Xu (Author), Lin Yang (Author), Pengfei Li (Author), Xiaojuan Han (Author), Qianni Li (Author), Yang Yang (Author), Lan Chao (Author)
• Format: Book
• Published: BMC, 2024-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s13048-023-01338-4; 1757-2215
• Keywords: Polycystic ovary syndrome; Aging; Gene; Bioinformatics; Gynecology and obstetrics; RG1-991
• Source: Journal of Ovarian Research, Vol 17, Iss 1, Pp 1-18 (2024)

Abstract Background Polycystic ovary syndrome (PCOS) is an exceedingly intractable issue affecting female endocrine and reproductive health. However, the etiology and intricate pathological mechanisms of PCOS remain unclear. Nowadays, aging was found to share multiple common pathological mechanisms with PCOS, which causes probing into the pathogenesis of PCOS from senescence. However, no bioinformatics analyses have specifically focused on connection between PCOS and ovarian aging. Methods Differentially expressed aging-related genes in PCOS were identified and then analyzed using function enrichment method. Hub genes were determined based on multiple algorithms, and expression validation of hub genes was performed in both datasets and experiments (human granulosa-like tumor cell line, KGN; human Granulosa Cell, hGCs). Finally, a transcription factor-miRNA-gene network of hub genes was constructed. Results Here, we identified 73 aging-related differential expression genes (ARDEGs) by intersecting DEGs in PCOS and senescence-related gene set. Furthermore, we performed biological functions and potential pathways of ARDEGs and potential hub genes were also screened by multiple algorithms. From the perspective of immune dysfunction, we analyzed the correlation between PCOS and immune cells. Finally, TF-miRNA-gene networks were constructed. Finally, TF-miRNA-gene networks were constructed. Conclusions Our work aimed to elucidate the relation between PCOS and cellular senescence based on bioinformatics strategy, deepening the understanding of mechanisms and to seek for novel therapy strategies for improving reproductive lifespan and female health. Exploring the potential molecular mechanism of cell aging in PCOS is expected to bring a new breakthrough for PCOS diagnosis and therapy strategies. And this, might deepen our understanding about intricate mechanisms of ovarian aging.