Evidence map›Paper›PMID 39221422›Full record

ArticleFrontiers in cardiovascular medicine2024

Identification of miR-1 and miR-499 in chronic atrial fibrillation by bioinformatics analysis and experimental validation.

Xinpei Chen, Yu Zhang, He Meng, Guiying Chen, Yongjiang Ma, Jian Li, Saizhe Liu, Zhuo Liang, Yinuo Xie, Ying Liu and 3 more

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. International journal of molecular sciences · 2025
    Article
  3. Review
  4. 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

13 authors.

Xinpei Chen *Munich Medical Research School, Ludwig-Maximilians University Munich, Munich, Germany.
Yu Zhang *Department of Cardiology, Beijing Anzhen Hospital, Beijing, China.
He MengDepartment of Cardiology, Tianjin Chest Hospital, Tianjin, China.
Guiying ChenDepartment of Pneumology, Tianjin Chest Hospital, Tianjin, China.
Yongjiang MaDepartment of Cardiology, The Sixth Medical Center of PLA General Hospital, Beijing, China.
Jian LiMunich Medical Research School, Ludwig-Maximilians University Munich, Munich, Germany.
Saizhe LiuMunich Medical Research School, Ludwig-Maximilians University Munich, Munich, Germany.
Zhuo LiangDepartment of Cardiology, Beijing Anzhen Hospital, Beijing, China.
Yinuo XieMunich Medical Research School, Ludwig-Maximilians University Munich, Munich, Germany.
Ying LiuDepartment of Cardiology, Beijing Jing Mei Group General Hospital, Beijing, China.
Hongyang GuoMunich Medical Research School, Ludwig-Maximilians University Munich, Munich, Germany.
Yutang WangDepartment of Geriatric Cardiology, Chinese PLA General Hospital, Beijing, China.
Zhaoliang ShanMunich Medical Research School, Ludwig-Maximilians University Munich, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Atrial fibrillation (AF) is one of the most prevalent arrhythmias and is characterized by a high risk of heart failure and embolic stroke, yet its underlying mechanism is unclear. The primary goal of this study was to establish a miRNA-mRNA network and identify the miRNAs associated with chronic AF by bioinformatics and experimental validation. Methods: The GSE79768 dataset was collected from the Gene Expression Omnibus(GEO) database to extract data from patients with or without persistent AF. Differentially expressed genes (DEGs) were identified in left atrial appendages (LAAs). The STRING platform was utilized for protein-protein interaction (PPI) network analysis. The target miRNAs for the top 20 hub genes were predicted by using the miRTarBase Web tool. The miRNA-mRNA network was established and visualized using Cytoscape software. The key miRNAs selected for verification in the animal experiment were confirmed by miRwalk Web tool. We used a classic animal model of rapid ventricular pacing for chronic AF. Two groups of animals were included in the experiment, namely, the ventricular pacing group (VP group), where ventricular pacing was maintained at 240-280 bpm for 2 weeks, and the control group was the sham-operated group (SO group). Finally, we performed reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to validate the expression of miR-1 and miR-499 in LAA tissues of the VP group and the SO group. Left atrial fibrosis and apoptosis were evaluated by Masson staining and caspase-3 activity assays, respectively. Results: The networks showed 48 miRNAs in LAA tissues. MiR-1 and miR-499 were validated using an animal model of chronic AF. The expression level of miR-1 was increased, and miR-499 was decreased in VP group tissues compared to SO group tissues in LAAs ( Conclusion: This study provides a better understanding of the alterations in miRNA-1 and miR-499 in chronic AF from the perspective of the miRNA-mRNA network and corroborates findings through experimental validation. These findings may offer novel potential therapeutic targets for AF in the future.

Indexed as

atrial fibrillationbioinformaticsdifferentially expressed genesmicroRNAs (miRNAs)miRNA-mRNA regulatory network

Identifiers

PMID39221422
PMCPMC11361948

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.