Evidence map›Paper›PMID 41316481›Full record

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.

Mengying Bai, Liujuan Zhang, Wenbo Wu, Ruoxin Weng, Haifeng Wu, Yuan Li, Shuyi Ling, Yuehui Zheng

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Mengying Bai *Reproductive Health Department, The Fourth Clinical Medical College of Guangzhou University of Traditional Chinese Medicine, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, 518033, Guangdong, China.
Liujuan Zhang *Reproductive Health Department, The Fourth Clinical Medical College of Guangzhou University of Traditional Chinese Medicine, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, 518033, Guangdong, China.
Wenbo Wu *Reproductive Health Department, The Fourth Clinical Medical College of Guangzhou University of Traditional Chinese Medicine, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, 518033, Guangdong, China.
Ruoxin WengReproductive Health Department, The Fourth Clinical Medical College of Guangzhou University of Traditional Chinese Medicine, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, 518033, Guangdong, China.
Haifeng WuReproductive Health Department, The Fourth Clinical Medical College of Guangzhou University of Traditional Chinese Medicine, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, 518033, Guangdong, China.
Yuan LiReproductive Health Department, The Fourth Clinical Medical College of Guangzhou University of Traditional Chinese Medicine, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, 518033, Guangdong, China. liyuan042711@126.com.
Shuyi LingReproductive Health Department, The Fourth Clinical Medical College of Guangzhou University of Traditional Chinese Medicine, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, 518033, Guangdong, China. ling_shuyi@163.com.
Yuehui ZhengReproductive Health Department, The Fourth Clinical Medical College of Guangzhou University of Traditional Chinese Medicine, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, 518033, Guangdong, China. yuehuizheng@163.com.

Funding

Basic Research Scheme of Shenzhen Science and Technology Innovation Commission (JCYJ20220531092208018, JCYJ20230807094815031, JCYJ20240813152305008)National Natural Science Foundation of China (No.82474232)The 2024 Guangzhou University of Chinese Medicine "Jie-bang Gua-shuai" Graduate Innovation Capacity Enhancement Program A3-0317-24-429-015
6 · The paper itself

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.

Indexed as

AgingBiomarkersOvaryProteomicsAnimalsCyclophosphamideDisease Models, AnimalFemaleMiceMice, Inbred C57BLProtein Interaction MapsBiomarkersCyclophosphamideIndicator predictionModel evaluationOvarian agingProteomicsTherapeutic targets

Identifiers

PMID41316481
PMCPMC12661719

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.