The Nine RNA Methylation Regulatory Gene Signature Is Associated with the Pathogenesis of Atrial Fibrillation by Modulating the Immune Microenvironment in the Atrial Tissues

Background. Atrial fibrillation (AF) is the most common type of cardiac arrhythmias and a major cause of cardiovascular disease (CVD)-related deaths globally. RNA methylation is the most frequent posttranscriptional modification in the eukaryotic RNAs. Previous studies have demonstrated close associ...

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Bibliographic Details
Published in:Disease markers 2023, Vol.2023, p.1-16
Main Authors: Wang, Qiuyu, Zhang, Shuaipeng, Xu, Xiruo, Liu, Jianguo, Tan, Pengjin, Wang, Chunbo, Wang, Jing, Li, Xin, Shang, Lihua
Format: Article
Language:English
Subjects:
Ablation
Algorithms
Atrophy
Biomarkers
Cardiac arrhythmia
Cardiovascular diseases
Catheters
Datasets
Diagnostic systems
DNA methylation
Fibrillation
Functional analysis
Gene expression
Heart diseases
Lymphocytes
Machine learning
Methylation
Microenvironments
Pathogenesis
Patients
Post-transcription
Regression analysis
Ribonucleic acid
Risk
RNA
Sample size
Statistical analysis
Therapeutic targets
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Summary:Background. Atrial fibrillation (AF) is the most common type of cardiac arrhythmias and a major cause of cardiovascular disease (CVD)-related deaths globally. RNA methylation is the most frequent posttranscriptional modification in the eukaryotic RNAs. Previous studies have demonstrated close associations between the status of RNA methylation and CVD. Methods. We comprehensively evaluated the relationship between RNA methylation and AF. Least absolute shrinkage and selection operator (LASSO) logistic regression analysis was used to establish a risk score model in AF. Biological functional analysis was used to explore the relationship between RNA methylation related signatures and immune microenvironment characteristics. Machine learning was used to recognize the outstanding RNA methylation regulators in AF. Results. There was a significant variant of the mRNA expression of RNA methylation regulators in AF. RNA methylation related risk score could predict the onset of AF and closely associated with immune microenvironment features. XG-Boost algorithm and SHAP recognized that NSUN3 and DCPS might play a key role in the development of AF. Meanwhile, NSUN3 and DCPS had potential diagnostic value in AF. Conclusion. RNA methylation regulatory genes are associated with the onset of AF by modulating the immune microenvironment. The nine AF risk-related RNA methylation regulatory gene signature is a potential diagnostic biomarker and therapeutic target for AF.
ISSN:0278-0240
1875-8630
DOI:10.1155/2023/7277369