Binhu Hospital, Hefei First People's Hospital, Hefei, Anhui, China.
State Key Laboratory of Bioelectronics, Southeast University, Nanjing, China.
Front Endocrinol (Lausanne). 2023 Jul 24;14:1004245. doi: 10.3389/fendo.2023.1004245. eCollection 2023.
Natural menopause is an inevitable biological process with significant implications for women's health. However, the molecular mechanisms underlying menopause are not well understood. This study aimed to investigate the molecular and cellular changes occurring in the ovary before and after perimenopause.
Single-cell sequencing data from the GTEx V8 cohort (30-39: 14 individuals; 40-49: 37 individuals; 50-59: 61 individuals) and transcriptome sequencing data from ovarian tissue were analyzed. Seurat was used for single-cell sequencing data analysis, while harmony was employed for data integration. Cell differentiation trajectories were inferred using CytoTrace. CIBERSORTX assessed cell infiltration scores in ovarian tissue. WGCNA evaluated co-expression network characteristics in pre- and post-perimenopausal ovarian tissue. Functional enrichment analysis of co-expression modules was conducted using ClusterprofileR and Metascape. DESeq2 performed differential expression analysis. Master regulator analysis and signaling pathway activity analysis were carried out using MsViper and Progeny, respectively. Machine learning models were constructed using Orange3.
We identified the differentiation trajectory of follicular cells in the ovary as ARID5B+ Granulosa -> JUN+ Granulosa -> KRT18+ Granulosa -> MT-CO2+ Granulosa -> GSTA1+ Granulosa -> HMGB1+ Granulosa. Genes driving Granulosa differentiation, including RBP1, TMSB10, SERPINE2, and TMSB4X, were enriched in ATP-dependent activity regulation pathways. Genes involved in maintaining the Granulosa state, such as DCN, ARID5B, EIF1, and HSP90AB1, were enriched in the response to unfolded protein and chaperone-mediated protein complex assembly pathways. Increased contents of terminally differentiated HMGB1+ Granulosa and GSTA1+ Granulosa were observed in the ovaries of individuals aged 50-69. Signaling pathway activity analysis indicated a gradual decrease in TGFb and MAPK pathway activity with menopause progression, while p53 pathway activity increased. Master regulator analysis revealed significant activation of transcription factors FOXR1, OTX2, MYBL2, HNF1A, and FOXN4 in the 30-39 age group, and GLI1, SMAD1, SMAD7, APP, and EGR1 in the 40-49 age group. Additionally, a diagnostic model based on 16 transcription factors (Logistic Regression L2) achieved reliable performance in determining ovarian status before and after perimenopause.
This study provides insights into the molecular and cellular mechanisms underlying natural menopause in the ovary. The findings contribute to our understanding of perimenopausal changes and offer a foundation for health management strategies for women during this transition.
自然绝经是一个不可避免的生物学过程，对女性健康有重大影响。然而，绝经的分子机制尚不清楚。本研究旨在探讨绝经前和绝经后卵巢中发生的分子和细胞变化。
分析了 GTEx V8 队列的单细胞测序数据（30-39 岁：14 人；40-49 岁：37 人；50-59 岁：61 人）和卵巢组织的转录组测序数据。使用 Seurat 进行单细胞测序数据分析，使用 harmony 进行数据集成。使用 CytoTrace 推断细胞分化轨迹。使用 CIBERSORTX 评估卵巢组织中的细胞浸润评分。使用 WGCNA 评估绝经前和绝经后卵巢组织的共表达网络特征。使用 ClusterprofileR 和 Metascape 对共表达模块进行功能富集分析。使用 DESeq2 进行差异表达分析。使用 MsViper 和 Progeny 进行主调控因子分析和信号通路活性分析。使用 Orange3 构建机器学习模型。
我们确定了卵巢中卵泡细胞的分化轨迹为 ARID5B+颗粒细胞 -> JUN+颗粒细胞 -> KRT18+颗粒细胞 -> MT-CO2+颗粒细胞 -> GSTA1+颗粒细胞 -> HMGB1+颗粒细胞。驱动颗粒细胞分化的基因，包括 RBP1、TMSB10、SERPINE2 和 TMSB4X，在 ATP 依赖的活性调节途径中富集。维持颗粒细胞状态的基因，如 DCN、ARID5B、EIF1 和 HSP90AB1，在未折叠蛋白反应和伴侣介导的蛋白复合物组装途径中富集。在 50-69 岁人群的卵巢中，观察到终末分化的 HMGB1+颗粒细胞和 GSTA1+颗粒细胞含量增加。信号通路活性分析表明，随着绝经的进展，TGFb 和 MAPK 通路活性逐渐降低，而 p53 通路活性增加。主调控因子分析显示，在 30-39 岁年龄组中，FOXR1、OTX2、MYBL2、HNF1A 和 FOXN4 的转录因子显著激活，在 40-49 岁年龄组中，GLI1、SMAD1、SMAD7、APP 和 EGR1 的转录因子显著激活。此外，基于 16 个转录因子的诊断模型（Logistic Regression L2）在绝经前和绝经后卵巢状态的确定中表现出可靠的性能。
本研究提供了绝经过程中卵巢中分子和细胞机制的见解。这些发现有助于我们理解围绝经期的变化，并为女性在这一过渡时期的健康管理策略提供了基础。
