Investigation of leukocyte RHO/ROCK gene expressions in patients with non-valvular atrial fibrillation

ROCK (RhoA/Rho Kinase) Activation in Atrial Fibrillation: Molecular Pathways and Clinical Implications

Among the complex mechanisms of AF pathogenesis, intracellular calcium overload and oxidative stress play a major role, both triggered by inflammatory processes. The additional basic event taking place in AF is atrial fibrotic remodeling, again triggered by oxidative stress, which is determined by connexins rearrangement and differentiation of fibroblasts into active collagensecreting myofibroblasts. RhoA/ROCK system is the final pathway of a wide spectrum of molecular effectors such as Angiotensin II, platelet-derived growth factor, connective tissue growth factor and transforming growth factor β, that overall determine calcium dysregulation and pro-fibrotic remodeling. Both in experimental and clinical studies, RhoA/ROCK activation has been linked to superoxide ion production, fibrotic remodeling and connexins rearrangement, with important consequences for AF pathogenesis. ROCK pathway inhibition may therefore be a therapeutic or preventive target for special AF subgroups of patients.

FAM201A, a long noncoding RNA potentially associated with atrial fibrillation identified by ceRNA network analyses and WGCNA

Background

Being the most common arrhythmia in clinic, atrial fibrillation (AF) causes various comorbidities to patients such as heart failure and stroke. LncRNAs were reported involved in pathogenesis of AF, yet, little is known about AF-associated lncRNAs. The present study aims to explore lncRNAs associated with AF susceptibility based on competing endogenous RNA (ceRNA) network analysis and weighted gene co-expression network analysis (WGCNA).

Methods

GSE41177 and GSE79768 datasets were obtained from the Gene Expression Omnibus (GEO) database. Competing endogenous RNA (ceRNA) network analysis was performed using GSE41177. Differentially expressed lncRNAs (DElncRNAs), mRNAs (DEmRNAs) between AF patients and patients with sinus rhythm (SR) were identified from GSE41177 using R software. Then, the ceRNA network was constructed based on DElncRNAs, the predicted target miRNAs and DEmRNAs. Weighted gene co-expression network analysis (WGCNA) was performed using GSE79768 to validate the AF-related lncRNAs identified from GSE41177. LncRNA modules and crucial lncRNAs relevant to AF and were identified.

Results

In summary, 18 DElncRNAs and 350 DEmRNAs were found between AF patients and SR patients. A total of 5 lncRNAs, 10 miRNAs, and 21 mRNAs were contained in the final ceRNA network. Taking into consideration both the ceRNA theory and inference scores from the comparative toxicogenomics database (CTD) database, the ceRNA axis FAM201A-miR-33a-3p-RAC3 was identified as mostly relevant to AF susceptibility. FAM201A (Gene significance, GS = − 0.62; Module membership, MM = 0.75) was also proved in the blue module, which was identified most highly relevant with AF by WGCNA.

Conclusions

These results demonstrated that decreased expression of FAM201A might be associated with susceptibility of AF. Working as the ceRNA to regulate RAC3 might be one function of FAM201A in AF susceptibility, which requires further exploration in future research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01232-w.

Multiomics Analysis of Genetics and Epigenetics Reveals Pathogenesis and Therapeutic Targets for Atrial Fibrillation

Objective

This study is aimed at understanding the molecular mechanisms and exploring potential therapeutic targets for atrial fibrillation (AF) by multiomics analysis.

Methods

Transcriptomics and methylation data of AF patients were retrieved from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) and differentially methylated sites between AF and normal samples were screened. Then, highly expressed and hypomethylated and lowly expressed and hypermethylated genes were identified for AF. Weighted gene coexpression network analysis (WGCNA) was presented to construct AF-related coexpression networks. 52 AF blood samples were used for whole exome sequence. The mutation was visualized by the maftools package in R. Key genes were validated in AF using independent datasets.

Results

DEGs were identified between AF and controls, which were enriched in neutrophil activation and regulation of actin cytoskeleton. RHOA, CCR2, CASP8, and SYNPO2L exhibited abnormal expression and methylation, which have been confirmed to be related to AF. PCDHA family genes had high methylation and low expression in AF. We constructed two AF-related coexpression modules. Single-nucleotide polymorphism (SNP) was the most common mutation type in AF, especially T > C. MUC4 was the most frequent mutation gene, followed by PHLDA1, AHNAK2, and MAML3. There was no statistical difference in expression of AHNAK2 and MAML3, for AF. PHLDA1 and MUC4 were confirmed to be abnormally expressed in AF.

Conclusion

Our findings identified DEGs related to DNA methylation and mutation for AF, which may offer possible therapeutic targets and a new insight into the pathogenesis of AF from a multiomics perspective.