Evidence map›Paper›PMID 40123755›Full record

ArticleInternational journal of women's health2025

Dissecting Causal Relationships Between Immune Cells, Plasma Metabolites, and PCOS: Evidence From Mediating Mendelian Randomization Analysis.

Xia-Li Wang, Yi-Fang He, Shi-Kun Chen, Jing Cheng, Xiu-Ming Wu

Abstract read
In one paragraph

Article in International journal of women's health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Xia-Li Wang *Department of Clinical Medicine, Quanzhou Medical College, Quanzhou, 362000, People's Republic of China.
Yi-Fang He *Department of Ultrasound, Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, People's Republic of China.
Shi-Kun ChenDepartment of Clinical Laboratory, Quanzhou Taiwan Investment Zone Disease Prevention and Control Center, Quanzhou, 362000, People's Republic of China.
Jing ChengQuanzhou Science and Technology Center, Quanzhou Medical College, Quanzhou, 362000, People's Republic of China.
Xiu-Ming WuDepartment of Ultrasound, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, 362000, People's Republic of China.ORCID 0009-0002-4795-6029

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The relationship between Polycystic ovary syndrome (PCOS) and immune dysregulation, along with metabolic disturbances, remains unclear. This study used Mendelian Randomization (MR) to investigate causal relationships between immune cells, PCOS, and possible metabolite mediators. Methods: We explored the genetic-level relationship between immune cells and PCOS, focusing on metabolites as potential mediators. Data from genome-wide association studies (GWAS) included 731 immune cell types (n=3757), 1400 plasma metabolites (n=8299), and PCOS cases (n=797) versus controls (n=140,558). Bidirectional MR analysis examined immune-PCOS relationships, while two-step MR and mediation analysis identified metabolites as potential mediators. The inverse variance-weighted (IVW) method was used for primary causal assessment, with sensitivity analysis validating results. Results: We identified a total of 33 immune cells that were associated with increased or decreased risk of PCOS ( Conclusion: This study highlights 12 immune cells impacting PCOS through 17 metabolites, advancing the understanding of immune mechanisms in PCOS risk and suggesting potential therapeutic approaches targeting immune modulation.

Indexed as

immunitymediating rolemetabolitesMR analysisPCOS

Identifiers

PMID40123755
PMCPMC11928329

What Socratic holds

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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.