Evidence map›Paper›PMID 41079183›Full record

ArticleFrontiers in endocrinology2025

Shared senescence-associated gene networks in PCOS and T2DM: biomarker identification and functional validation.

Mingyue Kong, Kun Lou, Dan Liu, Ziqi Dai, Tianjiao Li, Yihan Yang, Xuesong Zhang, Xin Chen

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Mingyue Kong *College of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, Jilin, China.
Kun Lou *Changchun Orthopedics Hospital, Changchun, Jilin, China.
Dan LiuAffiliated Hospital of Changchun University of Chinese Medicine, Changchun, Jilin, China.
Ziqi DaiChangchun University of Chinese Medicine, Changchun, Jilin, China.
Tianjiao LiChangchun University of Chinese Medicine, Changchun, Jilin, China.
Yihan YangChangchun University of Chinese Medicine, Changchun, Jilin, China.
Xuesong ZhangChangchun University of Chinese Medicine, Changchun, Jilin, China.
Xin ChenChangchun University of Chinese Medicine, Changchun, Jilin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Polycystic ovary syndrome (PCOS) and type 2 diabetes mellitus (T2DM) are two prevalent and interrelated disorders that pose an increasingly significant global health burden. Cellular senescence may represent a pivotal process driving the progression of both conditions. Senescent cells, through the senescence-associated secretory phenotype (SASP), can induce chronic inflammation, which is highly likely to exacerbate the pathological progression of PCOS and T2DM. However, the molecular pathways linking cellular senescence to PCOS and T2DM have not yet been systematically elucidated. Methods: The transcriptome datasets of PCOS (GSE54248) and T2DM (GSE23561) were obtained from the GEO database, and differentially expressed genes (DEGs) were screened using the limma package. Age-related DEGs (ARDEGs) were obtained by intersecting DEGs with age-related genes, and the protein-protein interaction (PPI) network was constructed based on the STRING database. Hub genes with diagnostic value were determined via the Wilcoxon rank sum test and receiver operating characteristic (ROC) curve. CIBERSORT was used to analyze the infiltration characteristics of immune cells, and the functions of the hub gene were analyzed by gene set enrichment analysis (GSEA). Single-cell sequencing was used to locate gene expression patterns, and qRT-PCR was used to verify the expression of candidate genes in clinical samples. Results: 80 DEGs between PCOS and T2DM samples were obtained, and 15 ARDEGs were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that they were related to inflammatory response and immune response, and were involved in specific functions and pathways. Four hub genes were identified: TUBA4A, RTN1, G6PD, and HP. qRT-PCR experimental results showed that HP, G6PD, TUBA4A, and RTN1 were highly expressed in the peripheral blood of PCOS and T2DM patients, compared to healthy people. Discussion: This study revealed the potential connections between PCOS, T2DM, and aging-related molecular networks and signaling pathways and discovered multiple potential therapeutic targets. It provides new intervention directions for clinicians, especially based on aging mechanisms.

Indexed as

BiomarkersCellular SenescenceDiabetes Mellitus, Type 2Gene Regulatory NetworksPolycystic Ovary SyndromeFemaleGene Expression ProfilingHumansProtein Interaction MapsTranscriptomeBiomarkersbioinformatics analysishub genesmolecular interaction networkspolycystic ovary syndromesenescence-associated secretory phenotypetype 2 diabetes

Identifiers

PMID41079183
PMCPMC12507634

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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 OpenQuestion graph.