Transcriptome Analysis Reveals the Mechanism of Natural Ovarian Ageing

Abstract

Background: The decline in the quantity and quality of oocytes due to ovarian ageing in women is now a significant threat to reproductive health today as the concept of delayed fertility becomes widespread. However, the molecular mechanisms of natural ovarian ageing have not been fully elucidated.

Method: Here, we used transcriptomic data from 180 normal ovarian tissues from GTEx V8 to analyze the expression profile of ovarian tissues from women with age segments of 20-29 (22 individuals), 30-39 (14 individuals), 40-49 (37 individuals), 50-59 (61 individuals), 60-69 (42 individuals), and 70-79 (4 individuals), respectively. XCELL was used to assess the infiltration score of 64 cell types of the ovary. WGCNA was used to characterize the co-expression network during the natural aging of the ovary. ClusterprofileR was used for functional enrichment analysis of co-expression modules. MsViper was used for master regulator analysis.

Results: The infiltration score of endothelial cells and activated antigen-presenting cells during natural ovarian ageing increased significantly at ages 30-39, 40-49, and then decreased, whereas CD4+ Tcm increased with age. WGCNA identified six co-expression modules from ovarian tissue transcriptomic data species. The red module was significantly and positively correlated with senescence and CD4+ Tcm, and the turquoise module was significantly and positively correlated with Endothelial Cells. We further explored ovarian tissue for women aged 20-29 and 30-39 years. The GSEA results showed that the Chemokine signaling pathway was significantly activated in the 30-39-year-old group, while Oocyte meiosis was significantly inhibited. Finally, the results of msviper found that transcription factors such as KDM1A, PRDM5, ZNF726, PPARG, FOXJ2, and GLI2 were mainly activated in the 20-29 years group, while VAV1, RUNX3, ZC3H12D, MYCL, and IRF5 were mainly activated in the 30-39 years group and that these transcription factor activities were diagnostic of natural ovarian ageing (AUC: 0.65-0.71).

Conclusion: Natural ageing of the ovary is significantly correlated with immune cell infiltration and activation of inflammation-related signaling pathways, with inflammation levels reaching a maximum during early ovarian ageing (30-39, 40-49) and then gradually decreasing after that. These studies provide a research basis for exploring the mechanisms of natural ovarian ageing.

Keywords: aging; inflammation; mechanism; ovary; reproduction.

Figure 1

WorkFlow.

Figure 2

Comparison of XCELL scores of ovarian tissues. (A) Cell types with significant differences. (B) Distribution of Endotheial cells, CD4+ Tcm, aDC in the six age groups. (C) Comparison of immune-inhibitory checkpoint gene expression. (D) Comparison of gene expression in immune-stimulatory checkpoints. *p < 0.05, **p < 0.01, ***p < 0.005, ****p < 0.001.

Figure 3

Weighted gene co-expression network analysis (WGCNA). (A, B) Selection of the best soft threshold. (C) Six co-expression modules were obtained for genes with fusion distance less than 0.25. Among them, the grey modules contained genes that could not be clustered. (D) Correlation of modules with phenotypes. (E) Functional enrichment analysis of Brown module hub genes (F) Functional enrichment analysis of Green module hub genes (G) Functional enrichment analysis of Turquoise module hub genes (H) Functional enrichment analysis of Yellow module hub genes (I) Functional enrichment analysis of Blue module hub genes (J) Functional enrichment analysis of Red Module hub genes functional enrichment analysis. The hub genes of each module are selected based on MM values greater than 0.7.

Figure 4

In-depth analysis of the Red module genes. (A) Correlation of Red module genes with the first principal component (B, C) Results of functional enrichment analysis. (D) PPI network and coregulatory modules.

Figure 5

Differential expression analysis of the 0-29 age group and the 30-39 age group. (A) Differential expression volcano plot (B) Signaling pathways enriched in the 30-39 age group (C) Signaling pathways enriched in the 20-29 age group. (D) Cell adhesion moleculars (CAMs) coregulated genes. (E) Chemokine signaling pathway coregulated gene. (F) Olfactory transduction coregulator gene (G) Oocyte meiosis coregulator gene.

Figure 6

Analysis of master regulators in the 20-29 age group vs. the 30-39 age group. (A) Top 20 transcription factors with differential protein activity enrichment (B–D) Significantly activated transcription factors in the 30-39 age group for the diagnosis of ovarian senescence in the reproductive years (VAV1, RUNX3, IRF5). (E–G) Significantly activated transcription factors in the 20-29 age group for the diagnosis of ovarian senescence in the reproductive age group (KDM1A, PRDM5, ZNF726). Act: TF activation; Exp: TF expression.