Region-specific gene expression profiles in the left atria of patients with valvular atrial fibrillation

FCER1G as a novel immune-associated blood biomarker in cardiogenic stroke

Background

Cardioembolic stroke (CE) exhibits the highest recurrence rate and mortality rate among all subtypes of cerebral ischemic stroke (CIS), yet its pathogenesis remains uncertain. The immune system plays a pivotal role in the progression of CE. Growing evidence indicates that several immune-associated blood biomarkers may inform the causes of stroke. The study aimed to identify new immune-associated blood biomarkers in patients with CE and create an online predictive tool in distinguishing CE from noncardioembolic stroke (non-CE) in CIS.

Methods

Gene expression profiles that were publicly available were obtained from the Gene Expression Omnibus (GEO). The identification of differentially expressed genes (DEGs) was conducted using the Limma package. The hub module and hub genes were identified through the application of weighted gene coexpression network analysis (WGCNA). In order to identify potential diagnostic biomarkers for CE, both the random forest (RF) model and least absolute shrinkage and selection operator (LASSO) regression analysis were employed. Concurrently, the CIBERSORT algorithm was employed to evaluate the infiltration of immune cells in CE samples and examine the correlation between the biomarkers and the infiltrating immune cells. The diagnostic gene expression in blood samples was confirmed using qRT-PCR in a self-constructed dataset. Univariate and multiple logistic regression analyses were used to identify the risk factors for CE. Subsequently, the mathematical model of the nomogram was employed via Java's "Spring Boot" framework to develop the corresponding online tool, which was then deployed on a cloud server utilizing "nginx".

Results

Eleven differentially expressed genes (DEGs) that were upregulated and seven DEGs that were downregulated were identified. Through bioinformatics analysis and clinical sample verification, it was discovered that Fc Fragment of IgE Receptor Ig (FCER1G) could serve as a novel potential blood biomarker for CE. FCER1G, along with other risk factors associated with CE, were utilized to develop a nomogram. The training and validation sets, which consisted of 65 CIS patients, yielded areas under the curve (AUCs) of 0.9722 and 0.9689, respectively. These results indicate a high level of precision in risk delineation by the nomogram. Furthermore, the associated online predictive platform has the potential to serve as a more efficacious and appropriate predictive instrument (https://www.origingenetic.com/CardiogenicStroke-FCER1G) for distinguishing between CE and non-CE.

Conclusion

Blood biomarker FCER1G has the potential to identify patients who are at a higher risk of cardioembolism and direct the search for occult AF.The utilization of this online tool is anticipated to yield significant implications in terms of distinguishing between CE and non-CE, as well as enhancing the optimization of treatment decision support.

Identification of atrial fibrillation-related genes through transcriptome data analysis and Mendelian randomization

Background

Atrial fibrillation (AF) is a common persistent arrhythmia characterized by rapid and chaotic atrial electrical activity, potentially leading to severe complications such as thromboembolism, heart failure, and stroke, significantly affecting patient quality of life and safety. As the global population ages, the prevalence of AF is on the rise, placing considerable strains on individuals and healthcare systems. This study utilizes bioinformatics and Mendelian Randomization (MR) to analyze transcriptome data and genome-wide association study (GWAS) summary statistics, aiming to identify biomarkers causally associated with AF and explore their potential pathogenic pathways.

Methods

We obtained AF microarray datasets GSE41177 and GSE79768 from the Gene Expression Omnibus (GEO) database, merged them, and corrected for batch effects to pinpoint differentially expressed genes (DEGs). We gathered exposure data from expression quantitative trait loci (eQTL) and outcome data from AF GWAS through the IEU Open GWAS database. We employed inverse variance weighting (IVW), MR-Egger, weighted median, and weighted model approaches for MR analysis to assess exposure-outcome causality. IVW was the primary method, supplemented by other techniques. The robustness of our results was evaluated using Cochran's Q test, MR-Egger intercept, MR-PRESSO, and leave-one-out sensitivity analysis. A "Veen" diagram visualized the overlap of DEGs with significant eQTL genes from MR analysis, referred to as common genes (CGs). Additional analyses, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and immune cell infiltration studies, were conducted on these intersecting genes to reveal their roles in AF pathogenesis.

Results

The combined dataset revealed 355 differentially expressed genes (DEGs), with 228 showing significant upregulation and 127 downregulated. Mendelian randomization (MR) analysis identified that the autocrine motility factor receptor (AMFR) [IVW: OR = 0.977; 95% CI, 0.956-0.998; P = 0.030], leucine aminopeptidase 3 (LAP3) [IVW: OR = 0.967; 95% CI, 0.934-0.997; P = 0.048], Rab acceptor 1 (RABAC1) [IVW: OR = 0.928; 95% CI, 0.875-0.985; P = 0.015], and tryptase beta 2 (TPSB2) [IVW: OR = 0.971; 95% CI, 0.943-0.999; P = 0.049] are associated with a reduced risk of atrial fibrillation (AF). Conversely, GTPase-activating SH3 domain-binding protein 2 (G3BP2) [IVW: OR = 1.030; 95% CI, 1.004-1.056; P = 0.024], integrin subunit beta 2 (ITGB2) [IVW: OR = 1.050; 95% CI, 1.017-1.084; P = 0.003], glutaminyl-peptide cyclotransferase (QPCT) [IVW: OR = 1.080; 95% CI, 1.010-0.997; P = 1.154], and tripartite motif containing 22 (TRIM22) [IVW: OR = 1.048; 95% CI, 1.003-1.095; P = 0.035] are positively associated with AF risk. Sensitivity analyses indicated a lack of heterogeneity or horizontal pleiotropy (P > 0.05), and leave-one-out analysis did not reveal any single nucleotide polymorphisms (SNPs) impacting the MR results significantly. GO and KEGG analyses showed that CG is involved in processes such as protein polyubiquitination, neutrophil degranulation, specific and tertiary granule formation, protein-macromolecule adaptor activity, molecular adaptor activity, and the SREBP signaling pathway, all significantly enriched. The analysis of immune cell infiltration demonstrated associations of CG with various immune cells, including plasma cells, CD8T cells, resting memory CD4T cells, regulatory T cells (Tregs), gamma delta T cells, activated NK cells, activated mast cells, and neutrophils.

Conclusion

By integrating bioinformatics and MR approaches, genes such as AMFR, G3BP2, ITGB2, LAP3, QPCT, RABAC1, TPSB2, and TRIM22 are identified as causally linked to AF, enhancing our understanding of its molecular foundations. This strategy may facilitate the development of more precise biomarkers and therapeutic targets for AF diagnosis and treatment.

Evaluation of Toll-like Receptor 4 (TLR4) Involvement in Human Atrial Fibrillation: A Computational Study

In the present study, we have explored the involvement of Toll-like Receptor 4 (TLR4) in atrial fibrillation (AF), by using a meta-analysis of publicly available human transcriptomic data. The meta-analysis revealed 565 upregulated and 267 downregulated differentially expressed genes associated with AF. Pathway enrichment analysis highlighted a significant overrepresentation in immune-related pathways for the upregulated genes. A significant overlap between AF differentially expressed genes and TLR4-modulated genes was also identified, suggesting the potential role of TLR4 in AF-related transcriptional changes. Additionally, the analysis of other Toll-like receptors (TLRs) revealed a significant association with TLR2 and TLR3 in AF-related gene expression patterns. The examination of MYD88 and TICAM1, genes associated with TLR4 signalling pathways, indicated a significant yet nonspecific enrichment of AF differentially expressed genes. In summary, this study offers novel insights into the molecular aspects of AF, suggesting a pathophysiological role of TLR4 and other TLRs. By targeting these specific receptors, new treatments might be designed to better manage AF, offering hope for improved outcomes in affected patients.

Antiarrhythmic effects of metformin

Atrial fibrillation/flutter (AF) is a major public health problem and is associated with stroke, heart failure, dementia, and death. It is estimated that 20%-30% of Americans will develop AF at some point in their life. Current medications to prevent AF have limited efficacy and significant adverse effects. Newer and safer therapies to prevent AF are needed. Ventricular arrhythmias are less prevalent than AF but may have significant consequences including sudden cardiac death. Metformin is the most prescribed, first-line medication for treatment of diabetes mellitus (DM). It decreases hepatic glucose production but also reduces inflammation and oxidative stress. Experimental studies have shown that metformin improves metabolic, electrical, and histologic risk factors associated with AF and ventricular arrhythmias. Furthermore, in large clinical observational studies, metformin has been associated with a reduced risk of AF in people with DM. These data suggest that metformin may have antiarrhythmic properties and may be a candidate to be repurposed as a medication to prevent cardiac arrhythmias. In this article, we review the clinical observational and experimental evidence for the association between metformin and cardiac arrhythmias. We also discuss the potential antiarrhythmic mechanisms underlying this association. Repurposing a well-tolerated, safe, and inexpensive medication to prevent cardiac arrhythmias has significant positive public health implications.

Soluble PILRα: A novel plasma biomarker for atrial fibrillation progression and recurrence after catheter ablation

BACKGROUND

We aimed to identify plasma biomarkers of atrial fibrillation (AF) progression and recurrence after catheter ablation.

METHODS

Using AF gene profiling data from GEO database, a weighted gene co-expression network analysis (WGCNA) was conducted to determine the most significant module and hub genes associated with AF. Subsequently, 318 consecutively admitted patients who had undergone radiofrequency catheter ablation were enrolled in this study.

RESULTS

WGCNA results revealed that paired immunoglobulin-like type 2 receptor alpha (PILRA) was the only black module gene highly correlated with clinical traits. Plasma soluble PILRα (sPILRα) levels were elevated in patients with AF and significantly elevated in patients with persistent versus paroxysmal AF (4.64 ± 2.74 vs. 3.04 ± 1.56 ng/mL, p < 0.001). Elevated sPILRα level was an independent risk factor for AF progression even after adjusting for traditional factors (adjusted odds ratio: 3.06, 95 % confidence interval [CI]: 1.88-5.27, p < 0.001) and AF recurrence after catheter ablation in patients with persistent AF (adjusted hazards ratio: 4.41, 95 % CI: 1.22-15.92, p = 0.023).

CONCLUSIONS

WGCNA screening of GEO microarray gene profiling data showed PILRA expression levels to be correlated with AF progression and recurrence after catheter ablation in patients with persistent AF.

Identification and validation of genes associated with aging-related cardiovascular disease

Aging is acknowledged as the most significant risk factor for cardiovascular disease (CVD). This study sought to identify and validate potential aging-related genes associated with CVD by using bioinformatics. The confluence of the limma test, weighted correlation network analysis (WGCNA), and 2129 aging and senescence-associated genes led to the identification of aging-related differential expression genes (ARDEGs). By using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), potential biological roles and pathways of ARDEGs were identified. To find the significantly different functions between CVD and non-cardiovascular disease (nCVD) and to reckon the processes score, enrichment analysis of all genes was carried out using gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). By using GO and KEGG, potential biological roles and pathways of ARDEGs were identified. To evaluate the immune cell composition of the immune microenvironment, we performed an immune infiltration analysis on the dataset from the training group. We were able to acquire four ARDEGs (PTGS2, MMP9, HBEGF, and FN1). Aging, cellular senescence, and nitric oxide signal transduction were selected for biological function analysis. The diagnostic value of the four ARDEGs in distinguishing CVD from nCVD samples was deemed to be favorable. This research identified four ARDEGs that are associated with CVD. This study provides insight into prospective novel biomarkers for aging-related CVD diagnosis and progression monitoring.

Identification and validation of aging-related genes in atrial fibrillation

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in the clinic. Aging plays an essential role in the occurrence and development of AF. Herein, we aimed to identify the aging-related genes associated with AF using bioinformatics analysis. Transcriptome profiles of AF were obtained from the GEO database. Differential expression analysis was performed to identify AF-specific aging-related genes. GO and KEGG enrichment analyses were performed. Subsequently, the LASSO, SVM-RFE, and MCC algorithms were applied to screen aging-related genes. The mRNA expression of the screened genes was validated in the left atrial samples of aged rapid atrial pacing-induced AF canine models and their counterparts. The ROC curves of them were drawn to evaluate their diagnostic potential. Moreover, CIBERSORT was used to estimate immune infiltration. A correlation analysis between screened aging-related genes and infiltrating immune cells was performed. A total of 24 aging-related genes were identified, which were found to be mainly involved in the FoxO signaling pathway, PI3K-Akt signaling pathway, longevity regulating pathway, and peroxisome according to functional enrichment analysis. LASSO, SVM-RFE, and MCC algorithms identified three genes (HSPA9, SOD2, TXN). Furthermore, the expression levels of HSPA9 and SOD2 were validated in aged rapid atrial pacing-induced AF canine models. HSPA9 and SOD2 could be potential diagnostic biomarkers for AF, as evidenced by the ROC curves. Immune infiltration and correlation analysis revealed that HSPA9 and SOD2 were related to immune cell infiltrates. Collectively, these findings provide novel insights into the potential aging-related genes associated with AF. HSPA9 and SOD2 may play a significant role in the occurrence and development of AF.

PILRA is associated with immune cells infiltration in atrial fibrillation based on bioinformatics and experiment validation

Background and aims

inflammation plays an important role in atrial fibrillation (AF). In this study, we investigated the significance of immune cell infiltration in AF and identified the potential Hub genes involved in the regulation of immune cell infiltration in AF.

Methods

we obtained AF datasets from the GEO database and analyzed them for obtaining differentially expressed genes (DEGs) by R software. Then, we performed GO, KEGG, and GSEA enrichment analyses of DEGs. The Hub genes of AF were determined by least absolute shrinkage selection operator (LASSO) regression analysis and weighted gene co-expression network analysis (WGCNA). Their validation was verified by using quantitative polymerase chain reaction (qPCR) in the AF rat model. Finally, we used a single sample GSEA (ssGSEA) to analyze immune cell infiltration and its relationship with hub genes.

Results

We obtained 298 DGEs from the heatmap and found that DGEs were closely related to inflammation, immunity, and cytokine interactions by enrichment analyses. We obtained 10 co-expression modules by WGCNA. Among them, the module including CLEC4A, COTL1, EVI2B, FCER1G, GAPT, HCST, NCF2, PILRA, TLR8, and TYROBP had the highest correlation with AF. Four Hub genes (PILRA, NCF2, EVI2B, GAPT) were obtained further by LASSO analysis. The results suggested that the expression level of PILRA was significantly elevated in the rats with AF by qPCR, compared to the rats without AF. The results revealed that the infiltration of neutrophils, macrophages, monocytes, mast cells, immature B cells, myeloid-derived suppressor cell (MDSC), dendritic cell, and T cells and their partial subpopulations were closely related to AF by ssGSEA analysis, and PILRA was positively correlated with immature B cell, monocyte, macrophage, mast cell, dendritic cell, and T cells and their partial subpopulations by Spearman correlation analysis.

Conclusions

PILRA was closely related to multiple types of immune cell infiltration, which may be associated with AF. PILRA may be a novel target of intervention for AF.

Identification and cross-validation of autophagy-related genes in cardioembolic stroke

Objective

Cardioembolic stroke (CE stroke, also known as cardiogenic cerebral embolism, CCE) has the highest recurrence rate and fatality rate among all subtypes of ischemic stroke, the pathogenesis of which was unclear. Autophagy plays an essential role in the development of CE stroke. We aim to identify the potential autophagy-related molecular markers of CE stroke and uncover the potential therapeutic targets through bioinformatics analysis.

Methods

The mRNA expression profile dataset GSE58294 was obtained from the GEO database. The potential autophagy-related differentially expressed (DE) genes of CE stroke were screened by R software. Protein-protein interactions (PPIs), correlation analysis, and gene ontology (GO) enrichment analysis were applied to the autophagy-related DE genes. GSE66724, GSE41177, and GSE22255 were introduced for the verification of the autophagy-related DE genes in CE stroke, and the differences in values were re-calculated by Student's t-test.

Results

A total of 41 autophagy-related DE genes (37 upregulated genes and four downregulated genes) were identified between 23 cardioembolic stroke patients (≤3 h, prior to treatment) and 23 healthy controls. The KEGG and GO enrichment analysis of autophagy-related DE genes indicated several enriched terms related to autophagy, apoptosis, and ER stress. The PPI results demonstrated the interactions between these autophagy-related genes. Moreover, several hub genes, especially for CE stroke, were identified and re-calculated by Student's t-test.

Conclusion

We identified 41 potential autophagy-related genes associated with CE stroke through bioinformatics analysis. SERPINA1, WDFY3, ERN1, RHEB, and BCL2L1 were identified as the most significant DE genes that may affect the development of CE stroke by regulating autophagy. CXCR4 was identified as a hub gene of all types of strokes. ARNT, MAPK1, ATG12, ATG16L2, ATG2B, and BECN1 were identified as particular hub genes for CE stroke. These results may provide insight into the role of autophagy in CE stroke and contribute to the discovery of potential therapeutic targets for CE stroke treatment.

Construction and integrated analysis of the ceRNA network hsa_circ_0000672/miR-516a-5p/TRAF6 and its potential function in atrial fibrillation

Atrial fibrosis is a crucial contributor to initiation and perpetuation of atrial fibrillation (AF). This study aimed to identify a circRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) regulatory network related to atrial fibrosis in AF, especially to validate hsa_circ_0000672/hsa_miR-516a-5p/TRAF6 ceRNA axis in AF preliminarily. The circRNA-miRNA-mRNA ceRNA network associated with AF fibrosis was constructed using bioinformatic tools and literature reviews. Left atrium (LA) low voltage was used to represent LA fibrosis by using LA voltage matrix mapping. Ten controls with sinus rhythm (SR), and 20 patients with persistent AF including 12 patients with LA low voltage and 8 patients with LA normal voltage were enrolled in this study. The ceRNA regulatory network associated with atrial fibrosis was successfully constructed, which included up-regulated hsa_circ_0000672 and hsa_circ_0003916, down-regulated miR-516a-5p and five up-regulated hub genes (KRAS, SMAD2, TRAF6, MAPK11 and SMURF1). In addition, according to the results of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, these hub genes were clustered in TGF-beta and MAPK signaling pathway. In the patients with persistent AF, hsa_circ_0000672 expression in peripheral blood monocytes was significantly higher than those in controls with SR by quantitative real-time polymerase chain reaction (p-value < 0.001). Furthermore, hsa_circ_0000672 expression was higher in peripheral blood monocytes of persistent AF patients with LA low voltage than those with LA normal voltage (p-value = 0.002). The dual-luciferase activity assay confirmed that hsa_circ_0000672 exerted biological functions as a sponge of miR-516a-5p to regulate expression of its target gene TRAF6. Hsa_circ_0000672 expression in peripheral blood monocytes may be associated with atrial fibrosis. The hsa_circ_0000672 may be involved in atrial fibrosis by indirectly regulating TRAF6 as a ceRNA by sponging miR-516a-5p.

Integrated genomic analysis defines molecular subgroups in dilated cardiomyopathy and identifies novel biomarkers based on machine learning methods

Aim: As the most common cardiomyopathy, dilated cardiomyopathy (DCM) often leads to progressive heart failure and sudden cardiac death. This study was designed to investigate the molecular subgroups of DCM. Methods: Three datasets of DCM were downloaded from GEO database (GSE17800, GSE79962 and GSE3585). After log2-transformation and background correction with "limma" package in R software, the three datasets were merged into a metadata cohort. The consensus clustering was conducted by the "Consensus Cluster Plus" package to uncover the molecular subgroups of DCM. Moreover, clinical characteristics of different molecular subgroups were compared in detail. We also adopted Weighted gene co-expression network analysis (WGCNA) analysis based on subgroup-specific signatures of gene expression profiles to further explore the specific gene modules of each molecular subgroup and its biological function. Two machine learning methods of LASSO regression algorithm and SVM-RFE algorithm was used to screen out the genetic biomarkers, of which the discriminative ability of molecular subgroups was evaluated by receiver operating characteristic (ROC) curve. Results: Based on the gene expression profiles, heart tissue samples from patients with DCM were clustered into three molecular subgroups. No statistical difference was found in age, body mass index (BMI) and left ventricular internal diameter at end-diastole (LVIDD) among three molecular subgroups. However, the results of left ventricular ejection fraction (LVEF) statistics showed that patients from subgroup 2 had a worse condition than the other group. We found that some of the gene modules (pink, black and grey) in WGCNA analysis were significantly related to cardiac function, and each molecular subgroup had its specific gene modules functions in modulating occurrence and progression of DCM. LASSO regression algorithm and SVM-RFE algorithm was used to further screen out genetic biomarkers of molecular subgroup 2, including TCEAL4, ISG15, RWDD1, ALG5, MRPL20, JTB and LITAF. The results of ROC curves showed that all of the genetic biomarkers had favorable discriminative effectiveness. Conclusion: Patients from different molecular subgroups have their unique gene expression patterns and different clinical characteristics. More personalized treatment under the guidance of gene expression patterns should be realized.

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 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.

C1QC, VSIG4, and CFD as Potential Peripheral Blood Biomarkers in Atrial Fibrillation-Related Cardioembolic Stroke

Atrial fibrillation (AF) is a major risk factor for ischemic stroke. We aimed to identify novel potential biomarkers with diagnostic value in patients with atrial fibrillation-related cardioembolic stroke (AF-CE).Publicly available gene expression profiles related to AF, cardioembolic stroke (CE), and large artery atherosclerosis (LAA) were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified and then functionally annotated. The support vector machine recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO) regression analysis were conducted to identify potential diagnostic AF-CE biomarkers. Furthermore, the results were validated by using external data sets, and discriminability was measured by the area under the ROC curve (AUC). In order to verify the predictive results, the blood samples of 13 healthy controls, 20 patients with CE, and 20 patients with LAA stroke were acquired for RT-qPCR, and the correlation between biomarkers and clinical features was further explored. Lastly, a nomogram and the companion website were developed to predict the CE-risk rate. Three feature genes (C1QC, VSIG4, and CFD) were selected and validated in the training and the external datasets. The qRT-PCR evaluation showed that the levels of blood biomarkers (C1QC, VSIG4, and CFD) in patients with AF-CE can be used to differentiate patients with AF-CE from normal controls (P < 0.05) and can effectively discriminate AF-CE from LAA stroke (P < 0.05). Immune cell infiltration analysis revealed that three feature genes were correlated with immune system such as neutrophils. Clinical impact curve, calibration curves, ROC, and DCAs of the nomogram indicate that the nomogram had good performance. Our findings showed that C1QC, VSIG4, and CFD can potentially serve as diagnostic blood biomarkers of AF-CE; novel nomogram and the companion website can help clinicians to identify high-risk individuals, thus helping to guide treatment decisions for stroke patients.

Insulin resistance and heart failure with preserved ejection fraction. Pathogenetic and therapeutic crossroads

Insulin resistance, which is a fundamental pathogenetic factor of prediabetes, is closely associated with abdominal obesity on the one hand and the development of cardiovascular diseases, heart failure (HF), on the other. The pathogenetic role of insulin resistance is multifaceted and consists in the acceleration of atherosclerosis, the formation of left ventricular myocardial hypertrophy, including through mechanisms that do not depend on blood pressure, as well as the development of its diastolic dysfunction. The latter is the starting point for starting HF with preserved ejection fraction (HFpEF).

Compared with patients with HF with reduced ejection fraction, the presence of HFpEF determines a higher frequency of hospitalizations not due to decompensation of heart failure, but due to concomitant diseases, such as destabilization of the course of arterial hypertension, decompensation of type 2 diabetes mellitus, curation of which, in general, has a greater impact in terms of improving prognosis. Thus, in patients with prediabetes and HFpEF, the correction of insulin resistance as the underlying cause and trigger of cardiometabolic disorders can potentially improve not only insulin-glucose homeostasis, but also the parameters of myocardial diastolic function. This literature review is devoted to the accumulated experience of using metformin as a «strategic» antidiabetic drug in HFpEF and considering potential new points of its application as a protector of the cardiovascular system.

Prediction of herbal medicines based on immune cell infiltration and immune- and ferroptosis-related gene expression levels to treat valvular atrial fibrillation

Inflammatory immune response is apparently one of the determinants of progressive exacerbation of valvular atrial fibrillation(VAF). Ferroptosis, an iron-dependent modality of regulated cell death, is involved in the immune regulation of cardiovascular disease. However, the relevant regulatory mechanisms of immune infiltration and ferroptosis in VAF have been less studied. In the current study, a highly efficient system for screening immunity- and ferroptosis-related biomarkers and immunomodulatory ability of herbal ingredients has been developed with the integration of intelligent data acquisition, data mining, network pharmacology, and computer-assisted target fishing. VAF patients showed higher infiltration of neutrophils and resting stage dendritic cells, while VSR patients showed higher infiltration of follicular helper T cells. In addition, six (e.g., PCSK2) and 47 (e.g., TGFBR1) ImmDEGs and one (SLC38A1) and four (TGFBR1, HMGB1, CAV1, and CD44) FerDEGs were highly expressed in patients with valvular sinus rhythm (VSR) and VAF, respectively. We further identified a core subnetwork containing 34 hub genes, which were intersected with ImmDEGs and FerDEGs to obtain the key gene TGFBR1. Based on TGFBR1, 14 herbs (e.g., Fructus zizyphi jujubae, Semen Juglandis, and Polygonum cuspidatum) and six herbal ingredients (curcumin, curcumine, D-glucose, hexose, oleovitamin A, and resveratrol) were predicted. Finally, TGFBR1 was found to dock well with curcumin and resveratrol, and it was further verified that curcumin and resveratrol could significantly reduce myocardial fibrosis. We believe that herbs rich in curcumin and resveratrol such as Rhizoma curcumae longae and Curcuma kwangsiensis, mitigate myocardial fibrosis to improve VAF by modulating the TGFβ/Smad signaling pathway. This strategy provides a prospective approach systemically characterizing phenotype-target-herbs relationships based on the tissue-specific biological functions in VAF and brings us new insights into the searching lead compounds from Chinese herbs.

Hub Genes Identification, Small Molecule Compounds Prediction for Atrial Fibrillation and Diagnostic Model Construction Based on XGBoost Algorithm

Background

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and engenders significant global health care burden. The underlying mechanisms of AF is remained to be revealed and current treatment options for AF have limitations. Besides, a detection system can help identify those at risk of developing AF and will enable personalized management.

Materials and Methods

In this study, we utilized the robust rank aggregation method to integrate six AF microarray datasets from the Gene Expression Omnibus database, and identified a set of differentially expressed genes between patients with AF and controls. Potential compounds were identified by mining the Connectivity Map database. Functional modules and closely-interacted clusters were identified using weighted gene co-expression network analysis and protein–protein interaction network, respectively. The overlapped hub genes were further filtered. Subsequent analyses were performed to analyze the function, biological features, and regulatory networks. Moreover, a reliable Machine Learning-based diagnostic model was constructed and visualized to clarify the diagnostic features of these genes.

Results

A total of 156 upregulated and 34 downregulated genes were identified, some of which had not been previously investigated. We showed that mitogen-activated protein kinase and epidermal growth factor receptor inhibitors were likely to mitigate AF based on Connectivity Map analysis. Four genes, including CXCL12, LTBP1, LOXL1, and IGFBP3, were identified as hub genes. CXCL12 was shown to play an important role in regulation of local inflammatory response and immune cell infiltration. Regulation of CXCL12 expression in AF was analyzed by constructing a transcription factor-miRNA-mRNA network. The Machine Learning-based diagnostic model generated in this study showed good efficacy and reliability.

Conclusion

Key genes involving in the pathogenesis of AF and potential therapeutic compounds for AF were identified. The biological features of CXCL12 in AF were investigated using integrative bioinformatics tools. The results suggested that CXCL12 might be a biomarker that could be used for distinguishing subsets of AF, and indicated that CXCL12 might be an important intermediate in the development of AF. A reliable Machine Learning-based diagnostic model was constructed. Our work improved understanding of the mechanisms of AF predisposition and progression, and identified potential therapeutic avenues for treatment of AF.

The Four Key Genes Participated in and Maintained Atrial Fibrillation Process via Reprogramming Lipid Metabolism in AF Patients

Atrial fibrillation (AF) is always in high incidence in the population, which can lead to serious complications. The structural and electrical remodeling of atrial muscle induced by inflammatory reaction or oxidative stress was considered as the major mechanism of AF. The treatment effect is not ideal based on current mechanisms. Recent studies demonstrated that lipid metabolism disorder of atrial muscle played an important role in the occurrence of AF. What key genes are involved is unclear. The purpose of the present study was to explore the lipid metabolism mechanism of AF. With the GEO database and the genomics of AF patients, metabolic related pathways and the key genes were analyzed. At the same time, the rat model of cecal ligation and puncture (CLP) was used to confirm the results. GSE 31821 and GSE 41177 were used as data sources, and the merged differentially expressed genes (DEGs) analysis showed that a total of 272 DEGs were found. GO annotation, KEGG, and gene set enrichment analysis (GSEA) showed that the fatty acid metabolism and the lipid biosynthetic process were involved in AF. Cholesterol biosynthesis, arachidonic acid metabolism, and the lipid droplet pathway were obviously increased in AF. Further analysis showed that four key genes, including ITGB1, HSP90AA1, CCND1, and HSPA8 participated in pathogenesis of AF regulating lipid biosynthesis. In CLP rats, metabolic profiling in the heart showed that the pyrimidine metabolism, the biosynthesis of unsaturated fatty acid metabolism, arginine and proline metabolism, and the fatty acid biosynthesis were involved. The four key genes were confirmed increased in the heart of CLP rats (p < 0.05 or 0.01). The results suggest that the lipid metabolism disorder participates in the occurrence of AF. ITGB1, HSP90AA1, CCND1, and HSPA8 are the key genes involved in the regulation of lipid biosynthesis.

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.

Analysis of potential genetic biomarkers using machine learning methods and immune infiltration regulatory mechanisms underlying atrial fibrillation

Objective

We aimed to screen out biomarkers for atrial fibrillation (AF) based on machine learning methods and evaluate the degree of immune infiltration in AF patients in detail.

Methods

Two datasets (GSE41177 and GSE79768) related to AF were downloaded from Gene expression omnibus (GEO) database and merged for further analysis. Differentially expressed genes (DEGs) were screened out using “limma” package in R software. Candidate biomarkers for AF were identified using machine learning methods of the LASSO regression algorithm and SVM-RFE algorithm. Receiver operating characteristic (ROC) curve was employed to assess the diagnostic effectiveness of biomarkers, which was further validated in another independent validation dataset of GSE14975. Moreover, we used CIBERSORT to study the proportion of infiltrating immune cells in each sample, and the Spearman method was used to explore the correlation between biomarkers and immune cells.

Results

129 DEGs were identified, and CYBB, CXCR2, and S100A4 were identified as key biomarkers of AF using LASSO regression and SVM-RFE algorithm. Both in the training dataset and the validation dataset, CYBB, CXCR2, and S100A4 showed favorable diagnostic effectiveness. Immune infiltration analysis indicated that, compared with sinus rhythm (SR), the atrial samples of patients with AF contained a higher T cells gamma delta, neutrophils and mast cells resting, whereas T cells follicular helper were relatively lower. Correlation analysis demonstrated that CYBB, CXCR2, and S100A4 were significantly correlated with the infiltrating immune cells.

Conclusions

In conclusion, this study suggested that CYBB, CXCR2, and S100A4 are key biomarkers of AF correlated with infiltrating immune cells, and infiltrating immune cells play pivotal roles in AF.

Research Progress of LncRNAs in Atrial Fibrillation

Atrial fibrillation (AF) is one of the most common arrhythmias in adults, with high morbidity and increased mortality risk. In recent years, the clinical diagnosis, treatment, and mechanistic research of AF have increased exponentially, and regulation based on the potential molecular mechanism of AF is a research hotspot. Long noncoding RNAs (LncRNAs), usually refer to noncoding RNA transcripts greater than 200 nucleotides in length, have been shown to play a role in cardiovascular diseases such as coronary artery disease, heart failure, and myocardial fibrosis through various regulatory methods. An increasing number of researchers have begun to pay attention to the identification and function of LncRNAs in AF. This article reviews changes in the expression of related LncRNAs detected in AF and describes the LncRNAs that play a regulatory role in AF-related processes, to explore the potential of LncRNAs as new biomarkers and therapeutic targets in AF.

Impact of genetically predicted atrial fibrillation on cancer risks: A large cardio-oncology Mendelian randomization study using UK biobank

Background

Increasing incidences of both atrial fibrillation (AF) and cancer have been observed in recent years. However, the casual association of both serious conditions has been scarcely evaluated and is considered to be a blank slate in cardio-oncology. Thus, we introduced Mendelian randomization (MR) methods to estimate the effects of AF on cancer risks.

Methods

We performed univariable and multivariable two-sample MR analyses to evaluate the effects of AF on the risk of 19 site-specific types of cancer. This MR study was conducted based on 111 independent AF-associated genetic instruments from genome-wide association studies and summarized-level data from corresponding cancer consortia. Multiple sensitivity analyses, including the leave-one-out analysis, MR-Egger regression, and MR-PRESSO tests, were further performed to examine the potential directional pleiotropic effects. Functional annotation was performed for common differentially expressed genes of AF and prostate cancer (PCA).

Results

A total of 6,777,155 European-descent people, including 533,725 cases and 6,243,430 controls, were included in the present MR analysis. Univariable MR analyses demonstrated a causal effect of AF on the incidence of PCA [odds ratio (OR): 0.96; 95% confidence interval (CI) 0.92-0.99, p = 0.01], and the causal effect remained significant (OR: 0.65; 95% CI 0.47-0.90, p = 0.01) after adjusting for potential confounders through the multivariable MR approach. However, no casual associations between AF and the other 18 site-specific cancer risks were observed (all p-values were > 0.05). The consistency of outcomes across complementary sensitivity MR methods further supported the causality. The functional analysis emphasized the essential role of antioxidant and xenobiotic catabolic processes in AF and PCA.

Conclusion

Contrary to the findings of several previous observational studies, our comprehensive MR analyses did not corroborate a causal role for AF in increasing the risk of various types of cancer. They did, however, demonstrate that AF may decrease the risk of PCA. Studies from larger sample sizes and individuals with different ethnic backgrounds are required to further support our conclusions.

The Construction and Comprehensive Analysis of a ceRNA Immunoregulatory Network and Tissue-Infiltrating Immune Cells in Atrial Fibrillation

Background

At present, the mechanisms behind atrial fibrillation (AF) pathogenesis are still unclear. We construct a ceRNA immunoregulatory network to further understand the mechanism of AF.

Methods

Four AF mRNA datasets from the Gene Expression Omnibus (GEO) database were integrated by SVA method. AF-related immune genes (AF-IRGs) were selected via combining ImmPort database with the genes in the module most associated with AF obtained by a weighted gene coexpression network analysis (WGCNA). Then, circRNA and miRNA expressions from the GEO database were extracted and mapped with related databases. Next, an immune-related circRNA-miRNA-mRNA ceRNA network was constructed and hub genes were filtered from a protein–protein interaction (PPI) network, and the differentially expressed (DE) hub genes in AF were further screened. Additionally, immune infiltration was investigated in AF by using CIBERSORT. Subsequently, the relationships between DE hub genes and AF-related infiltrating immune cells were performed by using Pearson correlation coefficients. Ulteriorly, the immune-cells-related ceRNA subnetwork in AF was built.

Results

A total of 95 AF-IRGs were detected, and an immune-related ceRNA network in AF was constructed with 12 circRNAs, 7 miRNAs and 50 mRNAs. The immune infiltration analysis indicated that a higher level of neutrophils, as well as a lower level of T cells regulatory (Tregs) and NK cells activated in AF. Four DE hub genes (CXCL12, IL7R, TNFSF13B, CD8A) were associated with Tregs or NK cells activated immune cells (P < 0.05). Tregs or NK cells activated immune cells-related ceRNA subnetwork including 5 circRNAs (has_circ_0001190, has_circ_0006725, has_circ_0079284, has_circ_0005299, and has_circ_0002103), 4 miRNAs (has-miR-198, has-miR-623, has-miR-1246, and has-miR-339-3p) and 4 DE hub genes was eventually constructed in AF.

Conclusion

Our results provide new insights into the molecular mechanisms governing AF progression from the perspective of immune-related ceRNA network.

Molecular Signatures of Human Chronic Atrial Fibrillation in Primary Mitral Regurgitation

Objectives

Transcriptomics of atrial fibrillation (AFib) in the setting of chronic primary mitral regurgitation (MR) remains to be characterized. We aimed to compare the gene expression profiles of patients with degenerative MR in AFib and sinus rhythm (SR) for a clearer picture of AFib pathophysiology.

Methods

After transcriptomic analysis and bioinformatics (n = 59), differentially expressed genes were defined using 1.5-fold change as the threshold. Additionally, independent datasets from GEO were included as meta-analyses.

Results

QRT-PCR analysis confirmed that AFib persistence was associated with increased expression molecular changes underlying a transition to heart failure (NPPB, P = 0.002; ANGPTL2, P = 0.002; IGFBP2, P = 0.010), structural remodeling including changes in the extracellular matrix and cellular stress response (COLQ, P = 0.003; COMP, P = 0.028; DHRS9, P = 0.038; CHGB, P = 0.038), and cellular stress response (DNAJA4, P = 0.038). Furthermore, AFib persistence was associated with decreased expression of the targets of structural remodeling (BMP7, P = 0.021) and electrical remodeling (CACNB2, P = 0.035; MCOLN3, P = 0.035) in both left and right atrial samples. The transmission electron microscopic analysis confirmed ultrastructural atrial remodeling and autophagy in human AFib atrial samples.

Conclusions

Atrial cardiomyocyte remodeling in persistent AFib is closely linked to alterations in gene expression profiles compared to SR in patients with primary MR. Study findings may lead to novel therapeutic targets. This trial is registered with ClinicalTrials.gov identifier: NCT00970034.

CXCL12/CXCR4 axis as a key mediator in atrial fibrillation via bioinformatics analysis and functional identification

Atrial fibrillation (AF) is an increasingly prevalent arrhythmia with significant health and socioeconomic impact. The underlying mechanism of AF is still not well understood. In this study, we sought to identify hub genes involved in AF, and explored their functions and underlying mechanisms based on bioinformatics analysis. Five microarray datasets in GEO were used to identify the differentially expressed genes (DEGs) by Robust Rank Aggregation (RRA), and hub genes were screened out using protein-protein interaction (PPI) network. AF model was established using a mixture of acetylcholine and calcium chloride (Ach-CaCl2) by tail vein injection. We totally got 35 robust DEGs that mainly involve in extracellular matrix formation, leukocyte transendothelial migration, and chemokine signaling pathway. Among these DEGs, we identified three hub genes involved in AF, of which CXCL12/CXCR4 axis significantly upregulated in AF patients stands out as one of the most potent targets for AF prevention, and its effect on AF pathogenesis and underlying mechanisms were investigated in vivo subsequently with the specific CXCR4 antagonist AMD3100 (6 mg/kg). Our results demonstrated an elevated transcription and translation of CXCL12/CXCR4 axis in AF patients and mice, accompanied with the anabatic atrial inflammation and fibrosis, thereby providing the substrate for AF maintenance. Blocking its signaling via AMD3100 administration in AF model mice reduced AF inducibility and duration, partly ascribed to decreased atrial inflammation and structural remodeling. Mechanistically, these effects were achieved by reducing the recruitment of CD3+ T lymphocytes and F4/80+ macrophages, and suppressing the hyperactivation of ERK1/2 and AKT/mTOR signaling in atria of AF model mice. In conclusion, this study provides new evidence that antagonizing CXCR4 prevents the development of AF, and suggests that CXCL12/CXCR4 axis may be a potential therapeutic target for AF.

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

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.

Functional genomics and epigenomics of atrial fibrillation

Atrial fibrillation is a progressive cardiac arrhythmia that increases the risk of hospitalization and adverse cardiovascular events. Despite years of study, we still do not have a full comprehension of the molecular mechanism responsible for the disease. The recent implementation of large-scale approaches in both patient samples, population studies and animal models has helped us to broaden our knowledge on the molecular drivers responsible for AF and on the mechanisms behind disease progression. Understanding genomic and epigenomic changes that take place during chronification of AF will prove essential to design novel treatments leading to improved patient care.

Comprehensive analysis of autophagy-related genes and patterns of immune cell infiltration in valvular atrial fibrillation

Background

The development of atrial fibrillation (AF) following valvular heart disease (VHD) remains a common disease and is associated with substantial adverse complications. However, valid molecular diagnostic and therapeutic tools for post-VHD AF have not been fully established. This study was conducted to discover the molecular mechanisms and immune microenvironment underlying AF following VHD.

Methods

Gene expression profiles of the GSE41177 dataset were assessed to construct a protein–protein interaction network, and then, autophagy-related hub genes were identified. In addition, to determine the functions of immune cell infiltration in valvular AF, we used the CIBERSORT algorithm to estimate the composition of 22 immune cell types in valvular heart disease. Finally, correlation analysis was carried out to identify the relationship between differentially expressed autophagy-related genes (DEARGs) and significant immune cell subpopulations to reveal potential regulatory pathways.

Results

A total of 153 DEARGs were identified in AF-VHD patients compared with controlled donors. Moreover, we screened the top ten hub nodes with the highest degrees through a network analysis. The ten hub nodes were considered hub genes related to AF genesis and progression. Then, we revealed six significant immune cell subpopulations through the CIBERSORT algorithm. Finally, correlation analysis was performed, and six DEARGs (BECN1, GAPDH, ATG7, MAPK3, BCL2L1, and MYC) and three immune cell subpopulations (T cells CD4 memory resting, T cells follicular helper, and neutrophils) were identified as the most significant potential regulators.

Conclusion

The DEARGs and immune cells identified in our study may be critical in AF development following VHD and provide potential predictive markers and therapeutic targets for determining a treatment strategy for AF patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-01939-1.

Meta-analysis of Transcriptomic Data Reveals Pathophysiological Modules Involved with Atrial Fibrillation

BACKGROUND

Atrial fibrillation (AF) is a complex disease and affects millions of people around the world. The biological mechanisms that are involved with AF are complex and still need to be fully elucidated. Therefore, we performed a meta-analysis of transcriptome data related to AF to explore these mechanisms aiming at more sensitive and reliable results.

METHODS

Ten public transcriptomic datasets were downloaded, analyzed for quality control, and individually pre-processed. Differential expression analysis was carried out for each dataset, and the results were meta-analytically aggregated using the rth ordered p value method. We analyzed the final list of differentially expressed genes through network analysis, namely topological and modularity analysis, and functional enrichment analysis.

RESULTS

The meta-analysis of transcriptomes resulted in 1197 differentially expressed genes, whose protein-protein interaction network presented 39 hubs-bottlenecks and four main identified functional modules. These modules were enriched for 39, 20, 64, and 10 biological pathways involved with the pathophysiology of AF, especially with the disease's structural and electrical remodeling processes. The stress of the endoplasmic reticulum, protein catabolism, oxidative stress, and inflammation are some of the enriched processes. Among hub-bottlenecks genes, which are highly connected and probably have a key role in regulating these processes, HSPA5, ANK2, CTNNB1, and MAPK1 were identified.

CONCLUSION

Our approach based on transcriptome meta-analysis revealed a set of key genes that demonstrated consistent overall changes in expression patterns associated with AF despite data heterogeneity related, among others, to type of tissue. Further experimental investigation of our findings may shed light on the pathophysiology of the disease and contribute to the identification of new therapeutic targets.

Effect of TFAM on ATP content in tachypacing primary cultured cardiomyocytes and atrial fibrillation patients

Atrial fibrillation (AF) is one of the most common types of arrhythmia worldwide; although a number of theories have been proposed to explain the mechanisms of AF, the treatment of AF is far from satisfactory. Energy metabolism is associated with the development of AF. Mitochondrial transcription factor A (TFAM) serves a role in the maintenance and transcription of mitochondrial DNA. The present study aimed to investigate the association between TFAM and AF and the effect of TFAM on ATP content in cardiomyocytes. Left atrial appendage tissues were collected from 20 patients with normal sinus rhythm (SR) and 20 patients with AF, and the expression levels of TFAM in SR and AF tissues were evaluated. In addition, a tachypacing model of primary cultured cardiomyocytes was constructed to assess ATP content, cell viability and expression levels of TFAM, mitochondrially encoded (MT)-NADH dehydrogenase 1 (ND1), MT-cytochrome c oxidase 1 (CO1), NADH ubiquinone oxidoreductase core subunit 1 (NDUFS1) and cytochrome c oxidase subunit 6C (COX6C). Finally, the effects of overexpression and inhibition of TFAM on ATP content, cell viability and the expression levels of MT-ND1 and MT-CO1 were investigated. The expression levels of TFAM were decreased in AF tissues compared with SR tissues (P<0.05). The ATP content, cell viability and expression levels of TFAM, MT-ND1 and MT-CO1 were decreased in tachypacing cardiomyocytes compared with non-pacing cardiomyocytes (P<0.05), whereas the expression levels of NDUFS1 and COX6C were not changed (P>0.05). Overexpression of TFAM increased ATP content, cell viability and expression levels of MT-ND1 and MT-CO1 (P<0.05). The inhibition of TFAM decreased ATP content, cell viability and expression levels of MT-ND1 and MT-CO1 (P<0.05). In summary, the results of the present study demonstrated that the expression levels of TFAM were decreased in AF tissues and tachypacing cardiomyocytes and that the restoration of TFAM increased the ATP content by upregulating the expression levels of MT-ND1 and MT-CO1 in tachypacing cardiomyocytes. Thus, TFAM may be a novel beneficial target for treatment of patients with AF.

Comprehensive Analysis of Differential Immunocyte Infiltration and Potential ceRNA Networks Involved in the Development of Atrial Fibrillation

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.

Genetic Susceptibility to Atrial Fibrillation Is Associated With Atrial Electrical Remodeling and Adverse Post-Ablation Outcome

OBJECTIVES

This study sought to assess the atrial electrophysiological properties and post-ablation outcomes in patients with atrial fibrillation (AF) with and without the rs2200733 single nucleotide variant.

BACKGROUND

The phenotype associated with chromosome 4q25 of the AF-susceptibility locus remains unknown.

METHODS

In this study, 102 consecutive patients (ages 61 ± 9 years, 64% male) with paroxysmal or persistent AF were prospectively recruited prior to ablation. Patients were genotyped for rs2200733 and high-density left atrial (LA) electroanatomic maps were created using a multipolar catheter during distal coronary sinus (CS) pacing at 600 ms. Voltage, conduction velocity (CV), CV heterogeneity, and fractionated signals of 6 LA segments were determined. Arrhythmia recurrence was assessed by continuous device (51%) and Holter monitoring.

RESULTS

Overall, 41 patients (40%) were single nucleotide variant carriers (38 heterozygous, 3 homozygous). A mean of 2,239 ± 852 points per patient were collected. Carriers had relatively increased CV heterogeneity (45.7 ± 7.5% vs. 35.9 ± 2.3%; p < 0.001), complex signals (9.4 ± 2.9% vs 6.0 ± 1.2%; p = 0.008), regional LA slowing, or conduction block (31.7 ± 8.2% vs. 17.9 ± 1.9%; p = 0.013) particularly in the posterior and lateral walls. There were no differences in CV, voltage, atrial refractoriness, or sinus node function. At follow-up (median: 27 months; range 19 to 31 months), carriers had lower arrhythmia-free survival (51% vs. 80%; p = 0.003). On multivariable analysis, carrier status was independently associated with CV heterogeneity (p = 0.001), complex signals (p = 0.002), and arrhythmia recurrence (p = 0.019).

CONCLUSIONS

These data provide the first evidence that the rs2200733-tagged haplotype alters LA electrical remodeling and is a determinant of long-term outcome following AF ablation. The molecular mechanisms underpinning these changes warrant further investigation.

Ubiquitin Pathway Is Associated with Worsening Left Ventricle Function after Mitral Valve Repair: A Global Gene Expression Study

The molecular mechanism for worsening left ventricular (LV) function after mitral valve (MV) repair for chronic mitral regurgitation remains unknown. We wished to assess the LV transcriptome and identify determinants associated with worsening LV function post-MV repair. A total of 13 patients who underwent MV repair for chronic primary mitral regurgitation were divided into two groups, preserved LV function (N = 8) and worsening LV function (N = 5), for the study. Specimens of LV from the patients taken during surgery were used for the gene microarray study. Cardiomyocyte cell line HL-1 cells were transfected with gene-containing plasmids and further evaluated for mRNA and protein expression, apoptosis, and contractile protein degradation. Of 67,258 expressed sequence tags, microarrays identified 718 genes to be differentially expressed between preserved-LVF and worsening-LVF, including genes related to the protein ubiquitination pathway, bone morphogenetic protein (BMP) receptors, and regulation of eIF4 and p70S6K signaling. In addition, worsening-LVF was associated with altered expressions of genes pathologically relevant to heart failure, such asdownregulated apelin receptors and upregulated peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PPARGC1A). HL-1 cardiomyocyte cells transfected with ubiquitination-related genes demonstrated activation of the protein ubiquitination pathwaywith an increase in the ubiquitin activating enzyme E1 (UAE-E1). It also led to increased apoptosis, downregulated and ubiquitinated X-linked inhibitor of apoptosis protein (XIAP), and reduced cell viability. Overexpression of ubiquitination-related genes also resulted in degradation and increased ubiquitination of α-smooth muscle actin (SMA). In conclusion, worsening-LVF presented differential gene expression profiles from preserved-LVF after MV repair. Upregulation of protein ubiquitination-related genes associated with worsening-LVF after MV repair may exert adverse effects on LV through increased apoptosis and contractile protein degradation.

Insight into atrial fibrillation through analysis of the coding transcriptome in humans

Atrial fibrillation is the most common sustained cardiac arrhythmia in humans, and its prevalence continues to increase because of the aging of the world population. Much still needs to be learned about the molecular pathways involved in the development and the persistence of the disease. Analysis of the transcriptome of cardiac tissue has provided valuable insight into diverse aspects of atrial remodeling, in particular concerning electrical remodeling-related to ion channels-and structural remodeling identified by dysregulation of processes linked to inflammation, fibrosis, oxidative stress, and thrombogenesis. The huge amount of data produced by these studies now represents a valuable source for the identification of novel potential therapeutic targets. In addition, the shift from cardiac tissue to peripheral blood as a substrate for transcriptome analysis revealed this strategy as a promising tool for improved diagnosis and therefore better patient care.

SNX17 (Sorting Nexin 17) Mediates Atrial Fibrillation Onset Through Endocytic Trafficking of the Kv1.5 (Potassium Voltage-Gated Channel Subfamily A Member 5) Channel

BACKGROUND

Kv1.5 (Potassium voltage-gated channel subfamily A member 5) has been regarded as a promising target of interventions for atrial fibrillation (AF). SNX17 (sorting nexin 17), a member of the SNXs (sorting nexin family), regulates the intracellular trafficking of membrane proteins through its FERM (four-point-one, ezrin, radixin, moesin) domain. However, whether SNX17 regulates the trafficking process of Kv1.5 remains unknown.

METHODS

A SNX17 knockout rat line was generated to test the role of SNX17 in atrial electrophysiology. The protein expression of SNX17 and membrane ion channels was detected by Western blotting. Electrophysiology changes in the atrial tissue and myocytes were analyzed by optical mapping and patch clamp, respectively. Acetylcholine and electrical stimulation were used to induce AF, and ECG recording was adopted to assess the influence of SNX17 deficiency on AF susceptibility. The spatial relationship between Kv1.5 and SNX17 was evaluated by immunostaining and confocal scanning, and the functional region of SNX17 regulating Kv1.5 trafficking was identified using plasmids with truncated SNX17 domains.

RESULTS

Embryonic death occurred in homozygous SNX17 knockout rats. SNX17 heterozygous rats survived, and the level of the SNX17 protein in the atrium was decreased by ≈50%. SNX17 deficiency increased the membrane expression of Kv1.5 and atria-specific ultrarapid delayed rectifier outward potassium current ( I_Kur) density, resulting in a shortened action potential duration, and eventually contributing to AF susceptibility. Mechanistically, SNX17 facilitated the endocytic sorting of Kv1.5 from the plasma membrane to early endosomes via the FERM domain.

CONCLUSIONS

SNX17 mediates susceptibility to AF by regulating endocytic sorting of the Kv1.5 channel through the FERM domain. SNX17 could be a potential target for the development of new drugs for AF.

Atrial fibrillation and its arrhythmogenesis associated with insulin resistance

Background

Insulin resistance (IR) is considered as a risk factor for atrial fibrillation (AF) even before diabetes develops. The pathophysiology and underlying mechanism are largely unclear.

Methods

We investigated the corresponding mechanism in two IR models of rats fed 15-week high-fat (HFa) and high-fructose/cholesterol (HFr) diets. AF was evaluated and induced by burst atrial pacing. Isolated atrial myocytes were used for whole-cell patch clamp and calcium assessment. Ex vivo whole heart was used for optical mapping. Western blot and immunofluorescence were used for quantitative protein evaluation.

Results

Both HFa and HFr rat atria were vulnerable to AF evaluated by burst atrial pacing. Isolated atrial myocytes from HFa and HFr rats revealed significantly increased sarcoplasmic reticulum calcium content and diastolic calcium sparks. Whole-heart mapping showed prolonged calcium transient duration, conduction velocity reduction, and repetitive ectopic focal discharge in HFa and HFr atria. Protein analysis revealed increased TGF-β1 and collagen expression; increased superoxide production; abnormal upregulation of calcium-homeostasis-related proteins, including oxidized CaMKIIδ, phosphorylated-phospholamban, phosphorylated-RyR-2, and sodium-calcium exchanger; and increased Rac1 activity in both HFa and HFr atria. We observed that inhibition of CaMKII suppressed AF in both HF and HFr diet-fed rats. In vitro palmitate-induced IR neonatal cardiomyocytes and atrial fibroblasts expressed significantly more TGF-β1 than did controls, suggesting paracrine and autocrine effects on both myocytes and fibroblasts.

Conclusions

IR engenders both atrial structural remodeling and abnormal intracellular calcium homeostasis, contributing to increased AF susceptibility. The inhibition of CaMKII may be a potential therapeutic target for AF in insulin resistance.

Identification of optimal reference genes for transcriptomic analyses in normal and diseased human heart

Aims

Quantitative real-time RT-PCR (RT-qPCR) has become the method of choice for mRNA quantification, but requires an accurate normalization based on the use of reference genes showing invariant expression across various pathological conditions. Only few data exist on appropriate reference genes for the human heart. The objective of this study was to determine a set of suitable reference genes in human atrial and ventricular tissues, from right and left cavities in control and in cardiac diseases.

Methods and results

We assessed the expression of 16 reference genes (ACTB, B2M, GAPDH, GUSB, HMBS, HPRT1, IPO8, PGK1, POLR2A, PPIA, RPLP0, TBP, TFRC, UBC, YWHAZ, 18S) in tissues from: right and left ventricles from healthy controls and heart failure (HF) patients; right-atrial tissue from patients in sinus rhythm with (SRd) or without (SRnd) atrial dilatation, patients with paroxysmal (pAF) or chronic (cAF) atrial fibrillation or with HF; and left-atrial tissue from patients in SR or cAF. Consensual analysis (by geNorm and Normfinder algorithms, BestKeeper software tool and comparative delta-Ct method) of the variability scores obtained for each reference gene expression shows that the most stably expressed genes are: GAPDH, GUSB, IPO8, POLR2A, and YWHAZ when comparing either right and left ventricle or ventricle from healthy controls and HF patients; GAPDH, IPO8, POLR2A, PPIA, and RPLP0 when comparing either right and left atrium or right atria from all pathological groups. ACTB, TBP, TFRC, and 18S genes were identified as the least stable.

Conclusions

The overall most stable reference genes across different heart cavities and disease conditions were GAPDH, IPO8, POLR2A and PPIA. YWHAZ or GUSB could be added to this set for some specific experiments. This study should provide useful guidelines for reference gene selection in RT-qPCR studies in human heart.

Identification of functional lncRNAs in atrial fibrillation by integrative analysis of the lncRNA-mRNA network based on competing endogenous RNAs hypothesis

A mounting body of evidence has suggested that long noncoding RNAs (lncRNAs) play critical roles in human diseases by acting as competing endogenous RNAs (ceRNAs). However, the functions and ceRNA mechanisms of lncRNAs in atrial fibrillation (AF) remain to date unclear. In this study, we constructed an AF-related lncRNA-mRNA network (AFLMN) based on ceRNA theory, by integrating probe reannotation pipeline and microRNA (miRNA)-target regulatory interactions. Two lncRNAs with central topological properties in the AFLMN were first obtained. By using bidirectional hierarchical clustering, we identified two modules containing four lncRNAs, which were significantly enriched in many known pathways of AF. To elucidate the ceRNA interactions in certain disease or normal condition, the dysregulated lncRNA-mRNA crosstalks in AF were further analyzed, and six hub lncRNAs were obtained from the network. Furthermore, random walk analysis of the AFLMN suggested that lncRNA RP11-296O14.3 may function importantly in the pathological process of AF. All these eight lncRNAs that were identified from previous steps (RP11-363E7.4, GAS5, RP11-410L14.2, HAGLR, RP11-421L21.3, RP11-111K18.2, HOTAIRM1, and RP11-296O14.3) exhibited a strong diagnostic power for AF. The results of our study provide new insights into the functional roles and regulatory mechanisms of lncRNAs in AF, and facilitate the discovery of novel diagnostic biomarkers or therapeutic targets.

Distinct patterns of atrial electrical and structural remodeling in angiotensin II mediated atrial fibrillation

Atrial fibrillation (AF) is prevalent in hypertension and elevated angiotensin II (Ang II); however, the mechanisms by which Ang II leads to AF are poorly understood. Here, we investigated the basis for this in mice treated with Ang II or saline for 3 weeks. Ang II treatment increased susceptibility to AF compared to saline controls in association with increases in P wave duration and atrial effective refractory period, as well as reductions in right and left atrial conduction velocity. Patch-clamp studies demonstrate that action potential (AP) duration was prolonged in right atrial myocytes from Ang II treated mice in association with a reduction in repolarizing K⁺ currents. In contrast, APs in left atrial myocytes from Ang II treated mice showed reductions in upstroke velocity and overshoot, as well as greater prolongations in AP duration. Ang II reduced Na⁺ current (I_Na) in the left, but not the right atrium. This reduction in I_Na was reversible following inhibition of protein kinase C (PKC) and PKCα expression was increased selectively in the left atrium in Ang II treated mice. The transient outward K⁺ current (I_to) showed larger reductions in the left atrium in association with a shift in the voltage dependence of activation. Finally, Ang II caused fibrosis throughout the atria in association with changes in collagen expression and regulators of the extracellular matrix. This study demonstrates that hypertension and elevated Ang II cause distinct patterns of electrical and structural remodeling in the right and left atria that collectively create a substrate for AF.

Proteomics and transcriptomics in atrial fibrillation

Atrial fibrillation (AF) is the most common tachyarrhythmia. AF, due to substantial remodeling processes initiated in the atria, is a typically self-sustaining and progressive disease. Atrial remodeling has been intensively investigated at the molecular level in recent decades. Although the application of "omics" technologies has already significantly contributed to our current understanding of the pathophysiology of AF, the complexity of the latter and the large heterogeneity of AF patients remained a major limitation. With the advent of novel "omics" and by applying integrative approaches, it will be possible to extract more information and push boundaries. The present review will summarize the contribution of transcriptomics and proteomics to our understanding of the pathophysiology of AF.

Chloride Channels are Involved in the Development of Atrial Fibrillation - A Transcriptomic and proteomic Study

Electrical and structural remodeling processes are contributors to the self-perpetuating nature of atrial fibrillation (AF). However, their correlation has not been clarified. In this study, human atrial tissues from the patients with rheumatic mitral valve disease in either sinus rhythm or persistent AF were analyzed using a combined transcriptomic and proteomic approach. An up-regulation in chloride intracellular channel (CLIC) 1, 4, 5 and a rise in type IV collagen were revealed. Combined with the results from immunohistochemistry and electron microscope analysis, the distribution of type IV collagen and effects of fibrosis on myocyte membrane indicated the possible interaction between CLIC and type IV collagen, confirmed by protein structure prediction and co-immunoprecipitation. These results indicate that CLICs play an important role in the development of atrial fibrillation and that CLICs and structural type IV collagen may interact on each other to promote the development of AF in rheumatic mitral valve disease.

An integrated anti-arrhythmic target network of a Chinese medicine compound, Wenxin Keli, revealed by combined machine learning and molecular pathway analysis

Deciphering the compound Wenxin Keli's anti-arrhythmic pharmacological mechanism by integrating network pharmacology and experimental verification methods.

A Combined Linkage and Exome Sequencing Analysis for Electrocardiogram Parameters in the Erasmus Rucphen Family Study

Electrocardiogram (ECG) measurements play a key role in the diagnosis and prediction of cardiac arrhythmias and sudden cardiac death. ECG parameters, such as the PR, QRS, and QT intervals, are known to be heritable and genome-wide association studies of these phenotypes have been successful in identifying common variants; however, a large proportion of the genetic variability of these traits remains to be elucidated. The aim of this study was to discover loci potentially harboring rare variants utilizing variance component linkage analysis in 1547 individuals from a large family-based study, the Erasmus Rucphen Family Study (ERF). Linked regions were further explored using exome sequencing. Five suggestive linkage peaks were identified: two for QT interval (1q24, LOD = 2.63; 2q34, LOD = 2.05), one for QRS interval (1p35, LOD = 2.52) and two for PR interval (9p22, LOD = 2.20; 14q11, LOD = 2.29). Fine-mapping using exome sequence data identified a C > G missense variant (c.713C > G, p.Ser238Cys) in the FCRL2 gene associated with QT (rs74608430; P = 2.8 × 10^-4, minor allele frequency = 0.019). Heritability analysis demonstrated that the SNP explained 2.42% of the trait’s genetic variability in ERF (P = 0.02). Pathway analysis suggested that the gene is involved in cytosolic Ca²⁺ levels (P = 3.3 × 10^-3) and AMPK stimulated fatty acid oxidation in muscle (P = 4.1 × 10^-3). Look-ups in bioinformatics resources showed that expression of FCRL2 is associated with ARHGAP24 and SETBP1 expression. This finding was not replicated in the Rotterdam study. Combining the bioinformatics information with the association and linkage analyses, FCRL2 emerges as a strong candidate gene for QT interval.

Genetic Variants Associated With Susceptibility to Atrial Fibrillation in a Japanese Population

BACKGROUND

Atrial fibrillation (AF) affects millions of individuals worldwide. The genome-wide association studies have identified robust genetic associations with AF.

METHODS

We genotyped 5461 participants of Japanese ancestry for 11 AF-related loci and determined the effects of carrying different numbers of risk alleles on disease development and age at disease onset. The weighted genetic risk score (GRS) was calculated, and its ability to predict AF was determined.

RESULTS

Six single-nucleotide polymorphisms-rs593479 (1q24 in PRRX1), rs1906617 (4q25 near PITX2), rs11773845 (7q31 in CAV1), rs6584555 (10q25 in NEURL), rs6490029 (12q24 in CUX2), and rs12932445 (16q22 in ZFHX3) (P < 1.9 × 10^-5)-were confirmed as being associated with AF. Patients with a high total number of risk alleles (9-12) had a younger median age at onset of AF (58 years; 95% confidence interval [CI], 55-60 years) than those with a low total number (1-4) (63 years; 95% CI, 61-64 years) (P = 0.0015). We observed a 4.38-fold (95% CI, 3.69-5.19) difference in risk of AF between individuals with scores in the top and bottom quartiles of the GRS. Receiver operating characteristic analysis indicated an area under the curve of 0.641 (95% CI, 0.628-0.653; P < 0.0001).

CONCLUSIONS

Six loci were validated as associated with AF in a Japanese population. This study suggests that a combination of common genetic markers modestly facilitates discrimination of AF. This is the first report, to our knowledge, to demonstrate that the age of onset of AF is affected by common risk alleles.

Differential left-to-right atria gene expression ratio in human sinus rhythm and atrial fibrillation: Implications for arrhythmogenesis and thrombogenesis

BACKGROUND

Atrial fibrillation (AF) causes atrial remodeling, and the left atrium (LA) is the favored substrate for maintaining AF. It remains unclear if AF remodels both atria differently and contributes to LA arrhythmogenesis and thrombogenesis. Therefore, we wished to characterize the transcript profiles in the LA and right atrium (RA) in sinus rhythm (SR) and AF respectively.

METHODS

Paired LA and RA appendages acquired from patients receiving cardiac surgery were used for ion-channel- and whole-exome-based transcriptome analysis. The ultrastructure was evaluated by immunohistochemistry.

RESULTS

Twenty-two and twenty ion-channels and transporters were differentially expressed between the LA and RA in AF and SR, respectively. Among these, 15 genes were differentially expressed in parallel between AF and SR. AF was associated with increased LA/RA expression ratio in 9 ion channel-related genes, including genes related to calcium handling. In microarray, AF was associated with a differential LA/RA gene expression ratio in 309 genes, and was involved in atherosclerosis-related signaling. AF was associated with the upregulation of thrombogenesis-related genes in the LA appendage, including P2Y12, CD 36 and ApoE. Immunohistochemistry showed higher expressions of collagen-1, oxidative stress and TGF-β1 in the RA compared to the LA.

CONCLUSIONS

AF was associated with differential LA-to-RA gene expression related to specific ion channels and pathways as well as upregulation of thrombogenesis-related genes in the LA appendage. Targeting the molecular mechanisms underlying the LA-to-RA difference and AF-related remodeling in the LA appendage may help provide new therapeutic options in treating AF and preventing thromboembolism in AF.

Proinflammatory gene expression in patients undergoing mitral valve surgery and maze ablation for atrial fibrillation

OBJECTIVE

It is difficult to achieve rhythm control in patients with long-standing persistent atrial fibrillation (AF). The radiofrequency maze procedure is an effective means in curing AF with a variable recurrence rate depending on patient characteristics and AF duration. In these patients, the characteristics of the atrial substrate have not been well investigated. Because the inflammatory process has been shown to be important in the pathogenesis of AF, we sought to characterize the proinflammatory gene expression in left atria obtained from patients with AF undergoing mitral valve surgery combined with the maze procedure to distinguish the changes associated with AF and its recurrence after the surgical ablation.

METHODS

Left atrial appendages from 35 patients receiving mitral valve surgery were used for study. Ten patients had sinus rhythm (SR) and 25 patients had persistent AF for more than 1 year and underwent the maze procedure. Among the AF patients, 13 patients remained in SR (AF-SR) and 12 patients had recurrent AF during the 1-year clinical follow-up (AF-AF). The nCounter Human Inflammation Array (NanoString Technologies, Seattle, Wash) was used for evaluating proinflammatory gene expression. Quantitative polymerase chain reaction, Western blot, and immunohistochemistry were applied for studying messenger RNA and protein expression.

RESULTS

Of 144 expressed proinflammatory genes, the inflammation array analysis revealed that 32 genes were differentially expressed between AF (including AF-SR and AF-AF) and SR. Thirteen genes were differentially expressed between AF-SR and AF-AF. The array and quantitative polymerase chain reaction produced parallel results in analyzing the expression of particular genes. Concordant with the gene expression difference between AF and SR patients, rapid pacing increased the expressions of SHC1, RHOA, PDGFA, and TRAF2 in HL-1 myocytes, implicating a causative effect of tachyarrhythmia on these genes. Compared with AF-SR, AF-AF expressed more intense oxidative stress, upregulations of collagen, transforming growth factor beta 1, and intranuclear nuclear factor of activated T-cells. Regression analysis showed that increased left atrial diameter was associated with the expression of RHOA and STAT1.

CONCLUSIONS

Differential expression profiles of proflammatory genes were presented between SR and AF and between maintained SR and recurrent AF after the maze procedure. The identified inflammatory molecules associated with AF and failed surgical ablation may provide clues for developing new potential therapeutic targets to improve AF rhythm control.

MicroRNA profiling in the left atrium in patients with non-valvular paroxysmal atrial fibrillation

Background

We aimed to identify the miRNA expression profiles in left atrial appendage, with the intention of identifying miRNAs that were significantly associated with non-valvular paroxysmal AF.

Methods

The RNA samples were isolated from healthy controls (n = 5) and patients with atrial fibrillation (n = 8). To confirm the findings obtained by analyzing the miRNA profile, we measured the expression of selected miRNAs in the entire cohort by quantitative PCR.

Results

Ten specific miRNAs were found to be differentially expressed between atrial fibrillation and healthy controls with more than a 2-fold change (P < 0.05). Consistent with the data obtained for the profile, expression levels of miRNA-155, miRNA-146b-5p and miRNA-19b were significantly increased in patients with atrial fibrillation. Interestingly, levels of miRNA-146b-5p and miRNA-155, which are known to be associated with inflammation, were independently and positively associated with left atrium dimension, atrial fibrillation duration and high sensitivity C-reactive protein levels. By using four Databases (TargetScan, miRanda, Starbase Clip-seq and miRDB) to perform target gene prediction, there were four genes were related to the inflammatory response and fibrosis, and three others encoding cardiac ion channel proteins. As a result of TaqMan qPCR and Western analysis, the relative mRNA and protein expression level of three target genes (DIER-1, TIMP-4 and CACNA1C) were significantly lower in the atrial fibrillation group than that in the healthy control group.

Conclusions

Expression of inflammation-associated miRNAs is significantly up-regulated in the left atrial appendage of patients with non-valvular paroxysmal atrial fibrillation, which may play a significant role in electrical and structural remodeling.

Electronic supplementary material

The online version of this article (doi:10.1186/s12872-015-0085-2) contains supplementary material, which is available to authorized users.