Evidence map›Paper›PMID 42109721›Full record

ReviewFrontiers in endocrinology2026

Gut microbiota in perimenopausal atherosclerosis: the estrogen-gut-vascular axis and personalized cardiovascular prevention.

Yiying Zhu, Yanhua Li

Abstract readReview
In one paragraph

Review in Frontiers in endocrinology, 2026. 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. Review
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.

Yiying ZhuThe Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China.
Yanhua LiDepartment of General Practice, The Second Affiliated Hospital of Zhejiang Chinese Medical University (Xinhua Hospital of Zhejiang Province), Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The risk of atherosclerosis rises markedly in perimenopausal women. The observed discrepancy between the traditional "estrogen cardioprotection hypothesis" and the complex effects of hormone replacement therapy in clinical practice suggests the existence of intermediary mechanisms that are not yet fully understood. Recent research indicates that the gut microbiota may play a pivotal role in this "estrogen paradox". By integrating current evidence, this review systematically elucidates the core driving function of the "estrogen-gut-vascular axis" in disease progression: declining estrogen levels lead to intestinal barrier dysfunction and associated imbalances in microbial metabolites (e.g. reduced short-chain fatty acids and increased pro-inflammatory metabolites), collectively accelerating atherogenesis. Targeting this axis through dietary modification, microbial therapeutics, and precision hormone interventions may break this pathological cycle. Notably, effective nutritional strategies must consider food matrix, individual microbial metabolic capacity, and timing of intervention. Furthermore, building on extensive research into age-related shifts in gut microbiota, this review proposes the novel concept of 'gut microbial age' based on functional metabolic profiles, to quantify the functional state of host-microbiome interactions. This concept aims to provide new perspectives and tools for personalized cardiovascular risk assessment and precise intervention in perimenopausal women.

Indexed as

AtherosclerosisCardiovascular DiseasesEstrogensGastrointestinal MicrobiomePerimenopauseAnimalsFemaleHumansPrecision MedicineEstrogensatherosclerosisestrogengut microbiotaperimenopausetreatment

Identifiers

PMID42109721
PMCPMC13152738

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.