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Identifying ceRNA Networks Associated With the Susceptibility and Persistence of Atrial Fibrillation Through Weighted Gene Co-Expression Network Analysis.

ABSTRACT: Background: Atrial fibrillation (AF) is the most common arrhythmia. We aimed to construct competing endogenous RNA (ceRNA) networks associated with the susceptibility and persistence of AF by applying the weighted gene co-expression network analysis (WGCNA) and prioritize key genes using the random walk with restart on multiplex networks (RWR-M) algorithm. Methods: RNA sequencing results from 235 left atrial appendage samples were downloaded from the GEO database. The top 5,000 lncRNAs/mRNAs with the highest variance were used to construct a gene co-expression network using the WGCNA method. AF susceptibility- or persistence-associated modules were identified by correlating the module eigengene with the atrial rhythm phenotype. Using a module-specific manner, ceRNA pairs of lncRNA-mRNA were predicted. The RWR-M algorithm was applied to calculate the proximity between lncRNAs and known AF protein-coding genes. Random forest classifiers, based on the expression value of key lncRNA-associated ceRNA pairs, were constructed and validated against an independent data set. Results: From the 21 identified modules, magenta and tan modules were associated with AF susceptibility, whereas turquoise and yellow modules were associated with AF persistence. ceRNA networks in magenta and tan modules were primarily involved in the inflammatory process, whereas ceRNA networks in turquoise and yellow modules were primarily associated with electrical remodeling. A total of 106 previously identified AF-associated protein-coding genes were found in the ceRNA networks, including 16 that were previously implicated in the genome-wide association study. Myocardial infarction-associated transcript (MIAT) and LINC00964 were prioritized as key lncRNAs through RWR-M. The classifiers based on their associated ceRNA pairs were able to distinguish AF from sinus rhythm with respective AUC values of 0.810 and 0.940 in the training set and 0.870 and 0.922 in the independent test set. The AF-related single-nucleotide polymorphism rs35006907 was found in the intronic region of LINC00964 and negatively regulated the LINC00964 expression. Conclusion: Our study constructed AF susceptibility- and persistence-associated ceRNA networks, linked genetics with epigenetics, identified MIAT and LINC00964 as key lncRNAs, and constructed random forest classifiers based on their associated ceRNA pairs. These results will help us to better understand the mechanisms underlying AF from the ceRNA perspective and provide candidate therapeutic and diagnostic tools.

SUBMITTER: Liu Y

PROVIDER: S-EPMC8261127 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Atrial fibrillation (AF) is the most common form of cardiac arrhythmia and significantly increases the risks of morbidity, mortality and health care expenditure; however, treatment for AF remains unsatisfactory due to the complicated and incompletely understood underlying mechanisms. In the present study, weighted gene co‑expression network analysis (WGCNA) was conducted to identify key modules and hub genes to determine their potential associations with AF. WGCNA was performed in an AF dataset GSE79768 obtained from the Gene Expression Omnibus, which contained data from paired left and right atria in cardiac patients with persistent AF or sinus rhythm. Differentially expressed gene (DEG) analysis was used to supplement and validate the results of WGCNA. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were also performed. Green and magenta modules were identified as the most critical modules associated with AF, from which 6 hub genes, acetyl‑CoA Acetyltransferase 1, death domain‑containing protein CRADD, gypsy retrotransposon integrase 1, FTX transcript, XIST regulator, transcription elongation factor A like 2 and minichromosome maintenance complex component 3 associated protein, were hypothesized to serve key roles in the pathophysiology of AF due to their increased intramodular connectivity. Functional enrichment analysis results demonstrated that the green module was associated with energy metabolism, and the magenta module may be associated with the Hippo pathway and contain multiple interactive pathways associated with apoptosis and inflammation. In addition, the blue module was identified to be an important regulatory module in AF with a higher specificity for the left atria, the genes of which were primarily correlated with complement, coagulation and extracellular matrix formation. These results suggest that may improve understanding of the underlying mechanisms of AF, and assist in identifying biomarkers and potential therapeutic targets for treating patients with AF.

Project description:BACKGROUND:Ablation is a widely used therapy for atrial fibrillation (AF); however, arrhythmia recurrence and repeat procedures are common. Studies examining surrogate markers of genetic susceptibility to AF, such as family history and individual AF susceptibility alleles, suggest these may be associated with recurrence outcomes. Accordingly, the aim of this study was to test the association between AF genetic susceptibility and recurrence after ablation using a comprehensive polygenic risk score for AF. METHODS:Ten centers from the AF Genetics Consortium identified patients who had undergone de novo AF ablation. AF genetic susceptibility was measured using a previously described polygenic risk score (N=929 single-nucleotide polymorphisms) and tested for an association with clinical characteristics and time-to-recurrence with a 3 month blanking period. Recurrence was defined as >30 seconds of AF, atrial flutter, or atrial tachycardia. Multivariable analysis adjusted for age, sex, height, body mass index, persistent AF, hypertension, coronary disease, left atrial size, left ventricular ejection fraction, and year of ablation. RESULTS:Four thousand two hundred seventy-six patients were eligible for analysis of baseline characteristics and 3259 for recurrence outcomes. The overall arrhythmia recurrence rate between 3 and 12 months was 44% (1443/3259). Patients with higher AF genetic susceptibility were younger (P<0.001) and had fewer clinical risk factors for AF (P=0.001). Persistent AF (hazard ratio [HR], 1.39 [95% CI, 1.22-1.58]; P<0.001), left atrial size (per cm: HR, 1.32 [95% CI, 1.19-1.46]; P<0.001), and left ventricular ejection fraction (per 10%: HR, 0.88 [95% CI, 0.80-0.97]; P=0.008) were associated with increased risk of recurrence. In univariate analysis, higher AF genetic susceptibility trended towards a higher risk of recurrence (HR, 1.08 [95% CI, 0.99-1.18]; P=0.07), which became less significant in multivariable analysis (HR, 1.06 [95% CI, 0.98-1.15]; P=0.13). CONCLUSIONS:Higher AF genetic susceptibility was associated with younger age and fewer clinical risk factors but not recurrence. Arrhythmia recurrence after AF ablation may represent a genetically different phenotype compared to AF susceptibility.

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Identifying ceRNA Networks Associated With the Susceptibility and Persistence of Atrial Fibrillation Through Weighted Gene Co-Expression Network Analysis.

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