Why the study?
Potential molecular mechanisms and candidate biomarkers in the left atrial regions for the diagnosis and treatment of valvular atrial fibrillation needed to be identified.
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Population
Left atrial tissue from patients with atrial fibrillation and normal rhythm controls
Comparison
AF patients vs normal rhythm group
Design
Bioinformatics study using microarray and DNA methylation analysis
This study is aimed at identifying potential molecular mechanisms and candidate biomarkers in the left atrial regions for the diagnosis and treatment of valvular atrial fibrillation (VAF). Multibioinformatics methods, including linear models for microarray analysis (LIMMA), an SVA algorithm, CIBERSORT immune infiltration, and DNA methylation analysis, were employed. In addition, the protein‐protein interaction (PPI) network, Gene Ontology (GO), and molecular pathways of differentially expressed genes (DEGs) or differential methylation regions were constructed. In all, compared with the normal rhythm group, 243 different mRNAs (29 downregulated and 214 upregulated) and 26 different lncRNAs (3 downregulated and 23 upregulated) were detected in the left atrium (LA) of atrial fibrillation (AF) patients, and the neutrophil and CD8 + T cell were infiltrated. Additionally, 199 different methylation sites (107 downregulated and 92 upregulated) were also identified based on DNA methylation analysis. After integration, ELOVL2, CCR2, and WEE1 were detected for differentially methylated and differentially transcribed genes. Among them, WEE1 was also a core gene identified by the competing endogenous RNA (ceRNA) network that included WEE1‐KRBOX1‐AS1‐hsa‐miR‐17‐5p, in VAF left atrial tissue. We combined the DNA methylation and transcriptional expression differential analysis and found that WEE1 (cg13365543) may well be a candidate gene regulated by DNA methylation modification. Moreover, KRBOX1‐AS1 and WEE1 can compete endogenously and may mediate myocardial tissue infiltration into CD8 + T cells and participate in the AF process.
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Wu et al. (2020) studied this question.
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