Evidence map›Paper›PMID 33741890›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2021

Potential Target Genes in the Development of Atrial Fibrillation: A Comprehensive Bioinformatics Analysis.

Liang Liu, Yun Yu, Long-Long Hu, Quan-Bin Dong, Feng Hu, Ling-Juan Zhu, Qian Liang, Ling-Ling Yu, Hui-Hui Bao, Xiao-Shu Cheng

Open access · hybridAbstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.2field-weighted citation impact, top 11% of its field
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

11 citing papers in PubMed, 15 citations in OpenAlex.

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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

10 authors at 2 institutions in 1 country.

Liang LiuDepartment of Cardiology, Second Affiliated Hospital, and Research Institute of Cardiovascular Diseases, Nanchang University, Nanchang, Jiangxi, China (mainland).
Yun YuDepartment of Cardiology, Second Affiliated Hospital, and Research Institute of Cardiovascular Diseases, Nanchang University, Nanchang, Jiangxi, China (mainland).
Long-Long HuDepartment of Cardiology, Second Affiliated Hospital, and Research Institute of Cardiovascular Diseases, Nanchang University, Nanchang, Jiangxi, China (mainland).
Quan-Bin DongDepartment of Cardiology, Second Affiliated Hospital, and Research Institute of Cardiovascular Diseases, Nanchang University, Nanchang, Jiangxi, China (mainland).
Feng HuDepartment of Cardiology, Second Affiliated Hospital, and Research Institute of Cardiovascular Diseases, Nanchang University, Nanchang, Jiangxi, China (mainland).
Ling-Juan ZhuDepartment of Cardiology, Second Affiliated Hospital, and Research Institute of Cardiovascular Diseases, Nanchang University, Nanchang, Jiangxi, China (mainland).
Qian LiangDepartment of Cardiology, Second Affiliated Hospital, and Research Institute of Cardiovascular Diseases, Nanchang University, Nanchang, Jiangxi, China (mainland).
Ling-Ling YuDepartment of Cardiology, Second Affiliated Hospital, and Research Institute of Cardiovascular Diseases, Nanchang University, Nanchang, Jiangxi, China (mainland).
Hui-Hui BaoDepartment of Cardiology, Second Affiliated Hospital, and Research Institute of Cardiovascular Diseases, Nanchang University, Nanchang, Jiangxi, China (mainland).
Xiao-Shu ChengDepartment of Cardiology, Second Affiliated Hospital, and Research Institute of Cardiovascular Diseases, Nanchang University, Nanchang, Jiangxi, China (mainland).
Second Affiliated Hospital of Nanchang University · CNNanchang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND Atrial fibrillation (AF) is the most prevalent arrhythmia worldwide. Although it is not life-threatening, the accompanying rapid and irregular ventricular rate can lead to hemodynamic deterioration and obvious symptoms, especially the risk of cerebrovascular embolism. Our study aimed to identify novel and promising genes that could explain the underlying mechanism of AF development. MATERIAL AND METHODS Expression profiles GSE41177, GSE79768, and GSE14975 were acquired from the Gene Expression Omnibus Database. R software was used for identifying differentially expressed genes (DEGs), and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were subsequently performed. A protein-protein interaction network was constructed in Cytoscape software. Next, a least absolute shrinkage and selection operator (LASSO) model was constructed and receiver-operating characteristic curve analysis was conducted to assess the specificity and sensitivity of the key genes. RESULTS We obtained 204 DEGs from the datasets. The DEGs were mostly involved in immune response and cell communication. The primary pathways of the DEGs were related to the course or maintenance of autoimmune and chronic inflammatory diseases. The top 20 hub genes (high scores in cytoHubba) were selected in the PPI network. Finally, we identified 6 key genes (FCGR3B, CLEC10A, FPR2, IGSF6, S100A9, and S100A12) via the LASSO model. CONCLUSIONS We present 6 target genes that are potentially involved in the molecular mechanisms of AF development. In addition, these genes are likely to serve as potential therapeutic targets.

Indexed as

Atrial FibrillationBiomarkers, TumorComputational BiologyDatabases, GeneticGene Expression ProfilingGene Expression Regulation, NeoplasticGene OntologyGene Regulatory NetworksHumansMicroRNAsProtein Interaction MappingProtein Interaction MapsSoftwareTranscriptomeBiomarkers, TumorMicroRNAs

Identifiers

PMID33741890
PMCPMC7989062
OpenAlexW3133080148

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.