Evidence map›Paper›PMID 41204358›Full record

ArticleJournal of ovarian research2025

Association between plasma extracellular vesicles LncRNAs and metabolic syndrome in polycystic ovary syndrome.

Yan-Zhen Wu, Lei-Lei Mao

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Yan-Zhen WuDepartment of gynecology and obstetrics, Wenzhou Central Hospital, Wenzhou, China.
Lei-Lei MaoDepartment of gynecology and obstetrics, Wenzhou Central Hospital, Wenzhou, China. 18868266648@163.com.

Funding

Wenzhou scientific research project Y20240607
6 · The paper itself

Abstract

backgroundThis case-control study aimed to investigate the relationship between plasma EVs LncRNAs, specifically Xist, MALAT1, and NEAT1, and MetS in PCOS patients, to identify a novel biomarker for early MetS diagnosis in these patients.

methodsThe levels of Xist, MALAT1, and NEAT1 in PCOS patients with and without MetS were quantified using qRT-PCR and then compared. Generalized linear regression and trend regression analyses were utilized to examine the association between three LncRNAs and MetS. ROC curve, DCA, AIC assessment, and importance ranking were applied to assess the clinical value of the three LncRNAs for MetS in PCOS patients.

resultsThe study included 220 newly diagnosed PCOS patients, with 82 (37.273%) having MetS. The expression levels of Xist, MALAT1, and NEAT1 were lower in PCOS patients with MetS compared to those without MetS (all P < 0.001). Further, significant independent associations between the three LncRNAs and MetS occurrence were found (all P < 0.05), with a negative relationship. Among three LncRNAs, MALAT1 had the superior performance (AUC = 0.801) in discriminative the occurrence of MetS in PCOS patients. In addition, MALAT1 also showed the highest importance for the risk of MetS.

conclusionThe low expressions of Xist, MALAT1, and NEAT1 were associated with the high risk of MetS in PCOS patients, with MALAT1 potentially serving as a preferred molecular marker for discriminative MetS in PCOS.

Indexed as

Extracellular VesiclesMetabolic SyndromePolycystic Ovary SyndromeRNA, Long NoncodingAdultBiomarkersCase-Control StudiesFemaleHumansROC CurveBiomarkersMALAT1 long non-coding RNA, humanNEAT1 long non-coding RNA, humanRNA, Long NoncodingXIST non-coding RNALncRNAsMALAT1MetSNEAT1PCOS

Identifiers

PMID41204358
PMCPMC12595885

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.