ArticleJournal of ovarian research2025
Quantitative proteomic analysis of pathological and physiological ovarian aging: model evaluation, molecular mechanisms, and identification of early biomarkers and therapeutic targets.
Article in Journal of ovarian research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Molecular characteristics of follicular fluid in advanced maternal age women with different ovarian reserves: a multi-omics study.BMC women's health · 2026Article
- Proteomic analysis reveals key genes and pathways involved in ovarian ageing of Qira Black sheep.Frontiers in veterinary science · 2026Article
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Authors and funding
8 authors.
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Abstract
objectivesOvarian aging is considered the "pacemaker" and "biological clock" of systemic female aging, with early manifestations that are often insidious. In this study, we analyzed the shared and distinct molecular signatures between physiological and pathological ovarian aging models using proteomic approaches, with the aim of identifying early predictive markers and therapeutic targets for ovarian aging, evaluating model fidelity, and elucidating underlying molecular mechanisms.
methodsOvarian tissue samples were collected from female C57/BL6 mice representing chemotherapeutic ovarian aging (8-week-old, Cyclophosphamide-Busulfan model) and natural ovarian aging (18-month-old). Initial validation of the models was conducted through histological assessment and serum hormone measurements. Quantitative proteomics was employed to profile protein expression. Differentially expressed proteins were subjected to GO, KEGG, and WikiPathways functional enrichment and clustering analyses, followed by validation of selected candidate genes using quantitative real-time polymerase chain reaction (RT-qPCR).
resultsThe cyclophosphamide-busulfan induced pathological ovarian aging model exhibited partial consistency with natural ovarian aging in terms of histological morphology, hormone levels, and proteomic profiles. protein-protein interaction (PPI) network construction and pathway enrichment analyses provided further evidence supporting the strong association between alterations in the subcortical maternal complex (SCMC) and ovarian dysfunction. Notably, Cyp17a1 and Lhcgr were identified as potential early biomarkers for ovarian aging. Additionally, 7 key molecular targets (pbk, sdhd, Gsta3, Gstm6, Nlrp5, Nlrp4f, and Nlrp14) closely related to chronic inflammation and oxidative stress were identified, some of which may reveal the close relationship between aging and tumors. Comparative analysis further revealed that pathological ovarian aging is predominantly characterized by DNA damage and cell cycle dysregulation, whereas physiological aging predominantly involved immune dysfunction, abnormal lipid metabolism, and chronic low-grade inflammation, underscoring the molecular heterogeneity between aging subtypes.
conclusionsThis study confirmed the validity of the cyclophosphamide-busulfan induced mouse model of ovarian senescence, highlighted both the shared and distinct molecular mechanisms of physiological and pathological ovarian aging, and identified promising early biomarkers and therapeutic intervention targets.
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