Evidence map›Paper›PMID 40629599›Full record

ArticleMedicine2025

A causal relationship between functional connectivity of brain networks and cardiovascular disease: A Mendelian randomization study.

Haoxuan Chu, Xia Guo, Han Chi Xu, Shipeng Wang, Zhen Guo, Yulin Tian, Yushi Wang

Abstract read
In one paragraph

Article in Medicine, 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

7 authors.

Haoxuan ChuDepartment of Cardiovascular Medicine, The First Hospital of Jilin University, Changchun, China.
Xia Guo
Han Chi Xu
Shipeng Wang
Zhen Guo
Yulin Tian

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dysfunction in the brain's resting-state functional networks is strongly connected with mental illness and cognitive impairment, while cardiovascular disease (CVD) is accepted as a risk factor for cognitive dysfunction. Growing interest exists in the correlation between brain and heart diseases. However, the causality between resting-state functional networks and CVD remains uncertain. In this research, a two-sample Mendelian randomization (MR) approach was applied to explore the causal association between 191 resting-state functional magnetic resonance imaging (rsfMRI) traits and 10 CVDs. This MR study employed single nucleotide polymorphisms that are strongly associated with rsfMRI phenotypes, which were sourced from the Zenodo database. We aimed to determine the causal relationship between rsfMRI phenotypes, considered as the exposure, and CVD, defined as the outcome. We engaged inverse variance weighting as our primary analytical method and executed a comprehensive sensitivity analysis to assess the heterogeneity and dependability of the results. Additionally, to validate the robustness of the findings, the test thresholds were recalibrated using the Bonferroni correction method. Functional connectivity among the angular gyrus, precuneus, cingulate gyrus, and parietal lobe also increased the hazards of atrial fibrillation (ORIVW = 0.644, 95% CI: 0.527-0.788, P = 1.83 × 10-5). Moreover, MR analyses of brain network connectivity concerning other CVDs did not meet the Bonferroni-corrected P-value threshold. Changes in functional connectivity of brain networks may be an indicator of risk for the development of atrial fibrillation but are not associated with the development of other CVDs.

Indexed as

BrainCardiovascular DiseasesNerve NetFemaleHumansMagnetic Resonance ImagingMaleMendelian Randomization AnalysisPhenotypePolymorphism, Single Nucleotidebrain network functioncardiovascular diseasecausal inferenceMendelian randomizationnutrition

Identifiers

PMID40629599
PMCPMC12237397

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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 OpenQuestion graph.