Bioinformatic analysis for the identification of potential gene interactions and therapeutic targets in atrial fibrillation

Yu, Shandong

doi:10.1101/2020.05.18.101972

Cited by 7 publications

(7 citation statements)

References 28 publications

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“…The current consensus is that electrical remodeling, inflammation, fibrosis as well as genetics are the major substrate for AF (34,35). In our analysis, these m6A-SNPs are involved in biological regulation and signaling, which may regulate the electrical remodeling, inflammation, fibrosis (36).…”

Section: Figurementioning

confidence: 79%

Genome-wide detection of m6A-associated SNPs in atrial fibrillation pathogenesis

Huang

Tan

Yuán

et al. 2023

Front. Cardiovasc. Med.

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ObjectiveN6-Methyladenosine (m6A) modification is of great importance in both the pathological conditions and physiological process. The m6A single nucleotide polymorphisms (SNPs) are associated with cardiovascular diseases including coronary artery disease, heart failure. However, it is unclear whether m6A-SNPs are involved in atrial fibrillation (AF). Here, we aimed to explore the relationship between m6A-SNPs and AF.MethodThe relationship between m6A-SNPs and AF was evaluated by analyzing the AF genome-wide association study (GWAS) and m6A-SNPs annotated by the m6AVar database. Further, eQTL and gene differential expression analysis were performed to confirm the association between these identified m6A-SNPs and their target genes in the development of AF. Moreover, we did the GO enrichment analysis to figure out the potential functions of these m6A-SNPs affected genes.ResultTotally, 105 m6A-SNPs were identified to be significantly associated with AF (FDR < 0.05), among which 7 showed significant eQTL signals on local genes in the atrial appendage. By using four public AF gene expression datasets, we identified genes SYNE2, USP36, and THAP9 containing SNPs rs35648226, rs900349, and rs1047564 were differentially expressed in AF population. Further, SNPs rs35648226 and rs1047564 are potentially associated with AF by affecting m6A modification and both of them might have an interaction with RNA-binding protein, PABPC1.ConclusionIn summary, we identified m6A-SNPs associated with AF. Our study provided new insights into AF development as well as AF therapeutic target.

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Section: Figurementioning

confidence: 79%

Genome-wide detection of m6A-associated SNPs in atrial fibrillation pathogenesis

Huang

Tan

Yuán

et al. 2023

Front. Cardiovasc. Med.

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“…To explore the function of differential genes, the online bioinformatics tools Database for Annotation, Visualization, and Integrated Discovery (DAVID) were used to annotate the functions of GO and KEGG pathway enrichment analysis [20][21][22] .…”

Section: Gene Ontology (Go) and Kyoto Encyclopedia Of Genes Genomes (...mentioning

confidence: 99%

Screening and Analysis of Aortic Dissection Based on Bioinformatics Methods Related Key Genes and Early Prevention and Treatment

Xin,

Liu,

et al. 2024

IJPS

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To Explore Potential Biomarkers in the Development of Aortic DissectionAortic dissection is a serious cardiovascular emergency with a very high early mortality rate, so it is particularly important to develop new targeted therapies to reduce prevalence and improve survival, and we hope to explore potential biomarkers involved in the development of aortic dissection and available pharmaceutical components sensitive to therapeutic targets through bioinformatics technology. First, download the gene expression omnibus dataset (GSE190635), use the affy software package of the R software for data standardization, the limma software package to screen the differential genes, and use the relevant software package to draw the volcano map and heat map of the differential gene; then database for annotation, visualization, and integrated discovery software was used for gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analysis. Next, the protein-protein interaction network was further constructed, and the STRING exported data was visualized using Cytoscape software, and finally the hub gene was extracted using cytoHubba and MCODE plugins. Finally, the Coremine medical information retrieval platform was used to screen for possible therapeutic drugs. Through differentially expressed genes analysis, 45 up-regulated differentially expressed genes and 132 down-regulated differentially expressed genes were successfully distinguished from the GSE79768. They are mainly enriched in positive regulation of urine volume, cell activation, extracellular region, lipopeptide binding and nucleotide oligomerization domain-like receptor signaling pathway, etc. Through protein-protein interaction, the top 7 hub genes were ranked, including early growth response protein 1, C-X-C motif chemokine ligand 8, fructo-oligosaccharides, filamin C, toll-like receptor 2, identified integrin alpha 7, myosin light chain-2. Coremine medical was used to retrieve a variety of related drugs, among which recombinant interleukin-6, recombinant tumor necrosis factor family protein, lipopolysaccharide and tyrosine co-regulated the above genes. In this study, 7 differentially expressed genes were identified as potential biomarkers for aortic dissection patients, which may provide new targets for aortic dissection therapy. But this is just the beginning, and we need to carry out experiments to verify the accuracy and feasibility of these results in the future.

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“…These pathways can also be used to target genes that might be involved in pathogenesis of atrial fibrillation and can be used as therapeutic targets and potential biomarkers. Biomarkers for atrial fibrillation are already being identified [ 129 , 130 ] and could be useful in clinical risk assessment and outcomes for individuals with atrial fibrillation.…”

Section: Conclusion Challenges and Future Directionsmentioning

confidence: 99%

Are Interactions between Epicardial Adipose Tissue, Cardiac Fibroblasts and Cardiac Myocytes Instrumental in Atrial Fibrosis and Atrial Fibrillation?

Krishnan

Chilton

Raman

et al. 2021

Cells

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Atrial fibrillation is very common among the elderly and/or obese. While myocardial fibrosis is associated with atrial fibrillation, the exact mechanisms within atrial myocytes and surrounding non-myocytes are not fully understood. This review considers the potential roles of myocardial fibroblasts and myofibroblasts in fibrosis and modulating myocyte electrophysiology through electrotonic interactions. Coupling with (myo)fibroblasts in vitro and in silico prolonged myocyte action potential duration and caused resting depolarization; an optogenetic study has verified in vivo that fibroblasts depolarized when coupled myocytes produced action potentials. This review also introduces another non-myocyte which may modulate both myocardial (myo)fibroblasts and myocytes: epicardial adipose tissue. Epicardial adipocytes are in intimate contact with myocytes and (myo)fibroblasts and may infiltrate the myocardium. Adipocytes secrete numerous adipokines which modulate (myo)fibroblast and myocyte physiology. These adipokines are protective in healthy hearts, preventing inflammation and fibrosis. However, adipokines secreted from adipocytes may switch to pro-inflammatory and pro-fibrotic, associated with reactive oxygen species generation. Pro-fibrotic adipokines stimulate myofibroblast differentiation, causing pronounced fibrosis in the epicardial adipose tissue and the myocardium. Adipose tissue also influences myocyte electrophysiology, via the adipokines and/or through electrotonic interactions. Deeper understanding of the interactions between myocytes and non-myocytes is important to understand and manage atrial fibrillation.

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Bioinformatic analysis for the identification of potential gene interactions and therapeutic targets in atrial fibrillation

Cited by 7 publications

References 28 publications

Genome-wide detection of m6A-associated SNPs in atrial fibrillation pathogenesis

Genome-wide detection of m6A-associated SNPs in atrial fibrillation pathogenesis

Screening and Analysis of Aortic Dissection Based on Bioinformatics Methods Related Key Genes and Early Prevention and Treatment

Are Interactions between Epicardial Adipose Tissue, Cardiac Fibroblasts and Cardiac Myocytes Instrumental in Atrial Fibrosis and Atrial Fibrillation?

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