Immune remodeling and atrial fibrillation

Bioinformatics analysis of circular RNAs associated with atrial fibrillation and their evaluation as predictive biomarkers

BACKGROUND

Circular noncoding RNAs (circRNAs) are implicated in many human diseases, but their role in atrial fibrillation (AF) is poorly understood. In this study, we performed bioinformatics analysis of circRNA sequencing data to identify AF-related circRNAs.

METHODS

Left atrial appendage (LAA) samples were obtained from patients with valvular heart disease and were categorised into the sinus rhythm (SR; n = 4) and AF (n = 4) groups. CircRNA sequencing analysis was performed to identify differentially expressed (DE) circRNAs in AF patients. Functional enrichment analysis of DE circRNAs was performed to identify enriched Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.

RESULTS

We identified 3338 DE circRNAs, including 2147 upregulated and 1191 downregulated circRNAs, in AF patients. A ceRNA network of 16 DE circRNAs, 11 DE miRNAs, and 15 DE mRNAs was constructed. Functional enrichment analyses revealed that the AF-related DE circRNAs were enriched in response to vitamin D, the potassium channel complex, delayed rectifier potassium channel activity, osteoclast differentiation, primary immunodeficiency, endocrine and other factor-regulated calcium reabsorption and other processes. ROC curve analysis identified circRNA_00324, circRNA_17225, circRNA_16305, circRNA_10233, circRNA_05499, circRNA_03183, circRNA_14211, and circRNA_18422 as potential predictive biomarkers for distinguishing AF patients from SR patients, with AUC values of 0.9138, 0.7370, 0.8526, 0.6803, 0.8163, 0.8662, 0.7664, and 0.9320, respectively.

CONCLUSIONS

In this study, we constructed an AF-related ceRNA network and identified eight circRNAs as potential predictive biomarkers of AF.

Pharmacovigilance study on the reporting frequency of atrial fibrillation with immune checkpoint inhibitors: insights from FDA Adverse Event Reporting System

Background

Immune checkpoint inhibitors (ICIs) have transformed cancer therapy but are linked with immune-related adverse events (irAEs), including cardiac events.

Objective

This study aims to assess the reporting frequency of atrial fibrillation with ICIs using data from the Food and Drug Administration Adverse Event Reporting System (FAERS).

Design

It is an observational, retrospective, pharmacovigilance study.

Methods

Individual Case Safety Reports (ICSRs) were retrieved from FAERS up to September 24, 2024. Cases reporting one or more ICIs (atezolizumab, avelumab, cemiplimab, dostarlimab, durvalumab, ipilimumab, nivolumab, pembrolizumab, and tremelimumab) and atrial fibrillation were selected. Disproportionality analyses were performed by applying the reporting odds ratio (ROR) and the Informational Component (IC) with a 95% confidence interval (95% CI).

Results

A total of 1228 ICSRs were retrieved, of which 218 (17.75%) were related to combinations of ICIs. Most ICSRs (N = 812; 66.1%) referred to male patients and the age group most represented was ⩾65 years (N = 772; 62.9%). Atrial fibrillation was serious in 99.3% (N = 1220) of cases and had a fatal outcome (N = 248; 20.3%). Atezolizumab, avelumab, durvalumab, nivolumab, and pembrolizumab were associated with a statistically significant higher reporting frequency of atrial fibrillation compared to all other drugs (ROR: 1.90, IC: 0.91; ROR: 1.94, IC: 0.92; ROR: 1.52, IC: 0.60; ROR: 1.30, IC: 0.38; ROR: 1.66, IC: 0.72, respectively). The anti-CTLA-4 ipilimumab showed a statistically significant lower reporting frequency of atrial fibrillation compared to all other drugs (ROR: 0.69, IC: -0.53) and to all other ICIs (ROR: 0.45, IC: -1.02). Moreover, anti-PD-L1 (ROR: 2.60, IC: 0.47) and anti-PD-1 (ROR: 2.12, IC: 0.16) were associated with a higher reporting of atrial fibrillation compared to anti-CTLA-4.

Conclusion

ICI-induced atrial fibrillation was serious and had severe outcomes. The anti-CTLA-4 showed a lower likelihood of reporting atrial fibrillation, while higher reporting was found with anti-PD-1 and anti-PD-L1. Further studies are needed to confirm this safety aspect.

Senescent CD8+ T cells: a novel risk factor in atrial fibrillation

AIMS

Immune cell alterations may play a role in the development of atrial fibrillation (AF). Our objective was to comprehensively characterize immune cells in AF, and investigate the potential mechanisms.

METHODS AND RESULTS

Single-cell RNA sequencing and multicolour flow cytometry revealed that T cells constituted the most significant subset alterations in AF, and senescent CD8+ T cells were AF-associated subset. Senescent CD8+ T cells increased in both peripheral veins (P < 0.0001) and the left atria (P < 0.05) in patients with AF compared to non-AF control. Senescent CD8+ T cells were independently associated with AF prevalence (odds ratio = 2.876, P < 0.05) and postprocedural recurrence (hazard ratio = 22.955, P < 0.0001) using a cross-sectional study and a subsequent prospective cohort study. Senescent CD8+ T cells secreted an increased amount of interferon (IFN)-γ, which induces Ca2+ handling abnormalities in human induced pluripotent stem cell-derived atrial cardiomyocytes, and translated into an increased susceptibility to AF assessed by heart optical mapping.

CONCLUSIONS

An increased amount of senescent CD8+ T cells may be a hallmark of the immune senescence phenotype in AF and potentially serve as a valid biomarker for assessing prevalence and postprocedural recurrence of AF. By connecting immune senescence with electrophysiological disturbances in AF, this research provides a potential mechanism for the involvement of senescent CD8+ T cells in proarrhythmic calcium disorders and suggests novel avenues for developing new immune-modulatory and senolytic therapies for AF.

Transcriptomics, Proteomics and Bioinformatics in Atrial Fibrillation: A Descriptive Review

Atrial fibrillation (AF) is the most frequent cardiac arrhythmia, with an estimated five million cases globally. This condition increases the likelihood of developing cardiovascular complications such as thromboembolic events, with a fivefold increase in risk of both heart failure and stroke. Contemporary challenges include a better understanding AF pathophysiology and optimizing therapeutical options due to the current lack of efficacy and adverse effects of antiarrhythmic drug therapy. Hence, the identification of novel biomarkers in biological samples would greatly impact the diagnostic and therapeutic opportunities offered to AF patients. Long noncoding RNAs, micro RNAs, circular RNAs, and genes involved in heart cell differentiation are particularly relevant to understanding gene regulatory effects on AF pathophysiology. Proteomic remodeling may also play an important role in the structural, electrical, ion channel, and interactome dysfunctions associated with AF pathogenesis. Different devices for processing RNA and proteomic samples vary from RNA sequencing and microarray to a wide range of mass spectrometry techniques such as Orbitrap, Quadrupole, LC-MS, and hybrid systems. Since AF atrial tissue samples require a more invasive approach to be retrieved and analyzed, blood plasma biomarkers were also considered. A range of different sample preprocessing techniques and bioinformatic methods across studies were examined. The objective of this descriptive review is to examine the most recent developments of transcriptomics, proteomics, and bioinformatics in atrial fibrillation.

Exploring the Axis of Gut Microbiota-Inflammatory Cytokine-Atrial Fibrillation in the Pathogenesis of Atrial Fibrillation

A relationship may exist between the gut microbiota, inflammatory factors and atrial fibrillation (AF); however, the precise biological mechanisms linking these components remain uncertain.In this study, 211 single-nucleotide polymorphisms associated with the gut microbiota were collected from the MiBioGen consortium. Summary data for AF were sourced from large-scale genome-wide association studies. Two-step Mendelian randomization (MR) was applied to estimate the possible mediating effect of inflammatory cytokines on the causality between the gut microbiota and AF. MR confirmed the effects of class Lentisphaeria, family Bifidobacteriaceae, family XIII, genus Anaerostipes, genus Howardella, genus Intestinibacter, genus Lachnospiraceae (NK4A136 group), genus Odoribacter, genus Ruminococcus gnavus, order Bifidobacteriales, order Victivallales and phylum Lentisphaerae on AF prevention. Moreover, MR revealed the role of Fms-related tyrosine kinase 3 ligand, interleukin-6, interleukin-7, leukaemia inhibitory factor receptor, sulfotransferase 1A1 and tumour necrosis factor ligand superfamily member 12 in protecting against AF. Fibroblast growth factor 5, interleukin-2 receptor subunit β, and tumour necrosis factor had a causal effect, increasing AF risk. The mediation exploration indicated that the indirect effect of genus Rikenellaceae (RC9 gut group) (id.11191) on AF mediated by interleukin-6 was OR 1.011 (95% confidence interval 1.002–1.024; mediation proportion=23.913%). This study supplies genetic insights into the potential causal association between the gut microbiota and AF. These causal associations and mediating effects are useful for managing AF through manipulation of the gut microbiota.

Possible Risk Factors Contributing to Atrial Fibrillation Occurrence in Heart Failure With Mildly Reduced Ejection Fraction

Background

Heart failure (HF) is often accompanied by atrial fibrillation (AF), which significantly worsens the outcome of both diseases. Half of individuals with HF has AF, and HF occurs in more than one-third of individuals with AF. Thus, HF and AF are commonly encountered together and are closely interrelated with similar risk factors. The aim of this study was to investigate the impact of potential risk factors on the occurrence of paroxysmal/persistent AF in patients with heart failure with moderately reduced ejection fraction (HFmrEF).

Methods

The study included 193 patients with HFmrEF and nonvalvular paroxysmal/persistent AF after successful cardioversion. As a control group the similar 76 patients without AF were examined. All patients underwent the examination, including electrocardiography (ECG), echocardiography, ambulatory blood pressure monitoring and Holter ECG monitoring. Levels of inflammatory markers, such as high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α) and the fibrotic marker transforming growth factor-β1 (TGF-β1) were measured using the enzyme-linked immunosorbent assay (ELISA) method. The obtained results were modeled using binary logistic regression using the odds ratio (OR).

Results

It was shown that frequent episodes of hypertensive crisis (HC) and increased body mass index (BMI) were possible risk factors for paroxysmal/persistent AF. An increased OR of diastolic and systolic parameters of the left ventricle was associated with significant atrial and ventricular remodeling. Statistically, higher OR of inflammatory markers levels, such as hs-CRP, IL-6 and TNF-α were associated with an increased risk of paroxysmal/persistent AF occurrence in HFmrEF patients compared to similar patients without AF. An increase of the fibrosis marker TGF-β1 OR was statistically significant in patients with persistent AF.

Conclusions

It could be considered that frequency of HC, BMI, atrial and ventricular remodeling, as well as an increase of inflammation markers were possible risk factors for the occurrence of paroxysmal/persistent AF in HFmrEF patients. Moreover, fibrosis factor level significantly increased the likelihood of persistent AF in these patients.

[Pathogenesis and potential diagnostic biomarkers of atrial fibrillation in Chinese population: a study based on bioinfor-matics]

OBJECTIVES

To explore the pathogenesis and potential biomarkers of atrial fibrillation based on bioinformatics.

METHODS

Differentially expressed genes and module genes related to atrial fibrillation were obtained from GSE41177 and GSE79768 datasets (Chinese-origin tissue samples) through differential expression analysis and weighted gene co-expression network analysis. Candidate hub genes were obtained by taking intersections, and hub genes were obtained after gender stratification. Subsequently, functional enrichment analysis and immune infiltration analysis were performed. Four machine learning models were constructed based on the hub genes, and the optimal model was selected to construct a prediction nomogram. The prediction ability of the nomogram was verified using calibration curves and decision curves. Finally, potential therapeutic drugs for atrial fibrillation were screened from the DGIdb database.

RESULTS

A total of 67 differentially expressed genes and 65 module genes related to atrial fibrillation were identified. Functional enrichment analysis indicated that the pathogenesis of atrial fibrillation was closely related to inflammatory response, immune response, and immune and infectious diseases. Four common hub genes (TYROBP, FCER1G, EVI2B and SOD2), and two genes specifically expressed in male (PILRA and SLC35G3) and female (HLA-DRA and GATP) patients with atrial fibrillation were obtained after gender-segregated screening. The extreme gradient boosting model had satisfactory diagnostic efficiency, and the nomogram constructed based on the hub genes, male significant variables (PILRA, SLC35G3 and SOD2), and female significant variables (FCER1G, SOD2 and TYROBP) had satisfactory predictive ability. Immune infiltration analysis demonstrated a disturbed immune infiltration microenvironment in atrial fibrillation with a higher abundance of plasma cells, neutrophils, and γδT cells, with a higher abundance of neutrophils in males and resting mast cells in females. Two potential drugs for the treatment of atrial fibrillation, valproic acid and methotrexate, were obtained by database and literature screening.

CONCLUSIONS

The pathogenesis of atrial fibrillation is closely related to inflammation and immune response, and the microenvironment of immune cell infiltration of cardiomyocytes in the atrial tissue of patients with atrial fibrillation is disordered. TYROBP, FCER1G, EVI2B and SOD2 serve as potential diagnostic biomarkers of atrial fibrillation; PILRA and SLC35G3 serve as potential specific diagnostic biomarkers of atrial fibrillation in the male population, which can effectively predict the risk of atrial fibrillation development and are also potential targets for the treatment of atrial fibrillation.

The role of systemic inflammatory indices in predicting atrial fibrillation and its complications: a narrative review

Atrial fibrillation (AF) is associated with increased morbidity and mortality. Inflammation and oxidative stress play critical roles in AF occurrence and its complications. Therefore, evaluating the circulating levels of inflammatory and oxidative stress biomarkers and their possible applications in AF diagnosis and management have been the focus of many efforts. The monocyte-to-high-density lipoprotein cholesterol ratio (MHR) and neutrophil-to-lymphocyte ratio (NLR) are two non-invasive, available, and established markers that serve as indicators of inflammation and oxidative stress. This review summarizes the current literature regarding alterations in the NLR, MHR, and other composite markers of systemic inflammation in AF patients. Moreover, this review discusses the clinical performance of these markers in predicting AF occurrence, recurrence, and disease outcomes. The PubMed, Scopus, and ScienceDirect online databases were searched for relevant studies using appropriate keywords, including "atrial fibrillation", "monocyte to high-density lipoprotein cholesterol ratio", and "neutrophil to lymphocyte ratio". The results of this review revealed the association of elevated levels of systemic inflammatory markers, specifically the NLR and MHR with AF and its complications. This finding indicates the potential role of subclinical inflammation in the development of AF, emphasizing its consideration in both the prevention and treatment of AF and associated complications. Despite these promising findings, the utilization of these markers in routine clinical settings faces challenges, including low specificity and sensitivity and varying cut-off values across different studies.

Tissue-resident memory T cells in epicardial adipose tissue comprise transcriptionally distinct subsets that are modulated in atrial fibrillation

Atrial fibrillation (AF) is the most common sustained arrhythmia and carries an increased risk of stroke and heart failure. Here we investigated how the immune infiltrate of human epicardial adipose tissue (EAT), which directly overlies the myocardium, contributes to AF. Flow cytometry analysis revealed an enrichment of tissue-resident memory T (TRM) cells in patients with AF. Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-cell T cell receptor (TCR) sequencing identified two transcriptionally distinct CD8+ TRM cells that are modulated in AF. Spatial transcriptomic analysis of EAT and atrial tissue identified the border region between the tissues to be a region of intense inflammatory and fibrotic activity, and the addition of TRM populations to atrial cardiomyocytes demonstrated their ability to differentially alter calcium flux as well as activate inflammatory and apoptotic signaling pathways. This study identified EAT as a reservoir of TRM cells that can directly modulate vulnerability to cardiac arrhythmia.

Comprehensive Analysis of Immune Cell Infiltration and M2-Like Macrophage Biomarker Expression Patterns in Atrial Fibrillation

Background

Macrophages play a crucial role in the progression of AF, closely linked to atrial inflammation and myocardial fibrosis. However, the functions and molecular mechanisms of different phenotypic macrophages in AF are not well understood. This study aims to analyze the infiltration characteristics of atrial immune cells in AF patients and further explore the role and molecular expression patterns of M2 macrophage-related genes in AF.

Methods

This study integrates single-cell and large-scale sequencing data to analyze immune cell infiltration and molecular characterization of the LAA in patients with AF, using SR as a control group. CIBERSORT assesses immune cell types in LAA tissues; WGCNA identifies signature genes; cell clustering analyzes cell types and subpopulations; cell communication explores macrophage interactions; hdWGCNA identifies M2 macrophage gene modules in AF. AF biomarkers are identified using LASSO and Random Forest, validated with ROC curves and RT-qPCR. Potential molecular mechanisms are inferred through TF-miRNA-mRNA networks and single-gene enrichment analyses.

Results

Myeloid cell subsets varied considerably between the AF and SR groups, with a significant increase in M2 macrophages in the AF group. Signals of inflammation and matrix remodeling were observed in AF. M2 macrophage-related genes IGF1, PDK4, RAB13, and TMEM176B were identified as AF biomarkers, with RAB13 and TMEM176B being novel markers. A TF-miRNA-mRNA network was constructed using target genes, which are enriched in the PPAR signaling pathway and fatty acid metabolism.

Conclusion

Over infiltration of M2 macrophages may be an important factor in the progression of AF. The M2 macrophage-related genes IGF1, RAB13, TMEM176B and PDK4 may regulate the progression of AF through the PPAR signaling pathway and fatty acid metabolism.

Deciphering mechanisms of cardiomyocytes and non-cardiomyocyte transformation in myocardial remodeling of permanent atrial fibrillation

INTRODUCTION

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia, and it significantly increases the risk of cardiovascular complications and morbidity, even with appropriate treatment. Tissue remodeling has been a significant topic, while its systematic transcriptional signature remains unclear in AF.

OBJECTIVES

Our study aims to systematically investigate the molecular characteristics of AF at the cellular-level.

METHODS

We conducted single-nuclei RNA-sequencig (snRNA-seq) analysis using nuclei isolated from the left atrial appendage (LAA) of AF patients and sinus rhythm. Pathological staining was performed to validate the key findings of snRNA-seq.

RESULTS

A total of 30 cell subtypes were identified among 80, 592 nuclei. Within the LAA of AF, we observed a specific subtype of dedifferentiated cardiomyocytes (CMs) characterized by reduced expression of cardiac contractile proteins (TTN and TRDN) and heightened expression of extracellular-matrix related genes (COL1A2 and FBN1). Transcription factor prediction analysis revealed that gene expression patterns in dedifferentiated CMs were primarily regulated by CEBPG and GISLI. Additionally, we identified a distinct subtype of endothelial progenitor cells (EPCs) demonstrating elevated expression of PROM1 and KDR, a population decreased within the LAA of AF. Epicardial adipocytes disclosed a reduced release of the anti-inflammatory and anti-fibrotic factor PRG4, and an augmented secretion of VEGF signals targeting CMs. Additionally, we noted accumulation of M2-like macrophages and CD8+ T cells with high pro-inflammatory score in LAA of AF. Furthermore, the analysis of intercellular communication revealed specific pathways related to AF, such as inflammation, extracellular matrix, and vascular remodeling signals.

CONCLUSIONS

This study has discovered the presence of dedifferentiated CMs, a decrease in endothelial progenitor cells, a shift in the secretion profile of adipocytes, and an amplified inflammatory response in AF. These findings could offer crucial insights for future research on AF and serve as valuable references for investigating novel therapeutic approaches for AF.

Analyses of lncRNA and mRNA profiles in recurrent atrial fibrillation after catheter ablation

BACKGROUND

Atrial fibrillation (AF) is the most common cardiac arrhythmia worldwide. Catheter ablation has become a crucial treatment for AF. However, there is a possibility of atrial fibrillation recurrence after catheter ablation. Our study sought to elucidate the role of lncRNA‒mRNA regulatory networks in late AF recurrence after catheter ablation.

METHODS

We conducted RNA sequencing to profile the transcriptomes of 5 samples from the presence of recurrence after AF ablation (P-RAF) and 5 samples from the absence of recurrence after AF ablation (A-RAF). Differentially expressed genes (DEGs) and long noncoding RNAs (DE-lncRNAs) were analyzed using the DESeq2 R package. The functional correlations of the DEGs were assessed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein‒protein interaction (PPI) network was constructed using STRING and Cytoscape. We also established a lncRNA‒mRNA regulatory network between DE-lncRNAs and DEGs using BEDTools v2.1.2 software and the Pearson correlation coefficient method. To validate the high-throughput sequencing results of the hub genes, we conducted quantitative real-time polymerase chain reaction (qRT‒PCR) experiments.

RESULTS

A total of 28,528 mRNAs and 42,333 lncRNAs were detected. A total of 96 DEGs and 203 DE-lncRNAs were identified between the two groups. GO analysis revealed that the DEGs were enriched in the biological processes (BPs) of "regulation of immune response" and "regulation of immune system process", the cellular components (CCs) of "extracellular matrix" and "cell‒cell junction", and the molecular functions (MFs) of "signaling adaptor activity" and "protein-macromolecule adaptor activity". According to the KEGG analysis, the DEGs were associated with the "PI3K-Akt signaling pathway" and "MAPK signaling pathway." Nine hub genes (MMP9, IGF2, FGFR1, HSPG2, GZMB, PEG10, GNLY, COL6A1, and KCNE3) were identified through the PPI network. lncRNA-TMEM51-AS1-201 was identified as a core regulator in the lncRNA‒mRNA regulatory network, suggesting its potential impact on the recurrence of AF after catheter ablation through the regulation of COL6A1, FGFR1, HSPG2, and IGF2.

CONCLUSIONS

The recurrence of atrial fibrillation after catheter ablation may be associated with immune responses and fibrosis, with the extracellular matrix playing a crucial role. TMEM51-AS1-201 has been identified as a potential key target for AF recurrence after catheter ablation.

Early Detection of Atrial Fibrillation in Chronic Obstructive Pulmonary Disease Patients

Atrial fibrillation (AF) is an important medical problem, as it significantly affects patients' quality of life and prognosis. AF often complicates the course of chronic obstructive pulmonary disease (COPD), a widespread disease with heavy economic and social burdens. A growing body of evidence suggests multiple links between COPD and AF. This review considers the common pathogenetic mechanisms (chronic hypoxia, persistent inflammation, endothelial dysfunction, and myocardial remodeling) of these diseases and describes the main risk factors for the development of AF in patients with COPD. The most effective models based on clinical, laboratory, and functional indices are also described, which enable the identification of patients suffering from COPD with a high risk of AF development. Thus, AF in COPD patients is a frequent problem, and the search for new tools to identify patients at a high risk of AF among COPD patients remains an urgent medical problem.

The Role of Immune Cells Driving Electropathology and Atrial Fibrillation

Atrial fibrillation (AF) is the most common progressive cardiac arrhythmia worldwide and entails serious complications including stroke and heart failure. Despite decades of clinical research, the current treatment of AF is suboptimal. This is due to a lack of knowledge on the mechanistic root causes of AF. Prevailing theories indicate a key role for molecular and structural changes in driving electrical conduction abnormalities in the atria and as such triggering AF. Emerging evidence indicates the role of the altered atrial and systemic immune landscape in driving this so-called electropathology. Immune cells and immune markers play a central role in immune remodeling by exhibiting dual facets. While the activation and recruitment of immune cells contribute to maintaining atrial stability, the excessive activation and pronounced expression of immune markers can foster AF. This review delineates shifts in cardiac composition and the distribution of immune cells in the context of cardiac health and disease, especially AF. A comprehensive exploration of the functions of diverse immune cell types in AF and other cardiac diseases is essential to unravel the intricacies of immune remodeling. Usltimately, we delve into clinical evidence showcasing immune modifications in both the atrial and systemic domains among AF patients, aiming to elucidate immune markers for therapy and diagnostics.

Bioinformatics analysis reveals the potential common genes and immune characteristics between atrial fibrillation and periodontitis

BACKGROUND AND OBJECTIVE

Atrial fibrillation (AF) and periodontitis, both classified under chronic inflammatory diseases, share common etiologies, including genetic factors and immune pathways. However, the exact mechanisms are still poorly understood. This study aimed to explore the potential common genes and immune characteristics between AF and periodontitis.

METHODS

Gene expression datasets for AF and periodontitis were downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis was used to identify common genes in the training set. Functional analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, were conducted to elucidate the underlying mechanisms. Hub genes were further screened based on expression levels, receiver operating characteristic (ROC) curves, and least absolute shrinkage and selection operator (LASSO) regression. Then, based on the expression levels and ROC values of the hub genes in the validation set, the target genes were identified. Finally, immune cell infiltration analysis was performed on the AF and periodontitis datasets in the training set using the "CIBERSORT" R package. The relationships between target genes, infiltrating immune cells, and inflammatory factors were also investigated. In addition, AF susceptibility, atrial fibrosis, inflammatory infiltration, and RGS1 protein expression in rat models of periodontitis were assessed through in vivo electrophysiology experiments, Masson's trichrome staining, hematoxylin-eosin staining, immunohistochemistry, and western blotting, respectively.

RESULTS

A total of 21 common genes were identified between AF and periodontitis among the differentially expressed genes. After evaluating gene expression levels, ROC curves, and LASSO analysis, four significant genes between AF and periodontitis were identified, namely regulator of G-protein signaling 1 (RGS1), annexin A6 (ANXA6), solute carrier family 27 member 6 (SLC27A6), and ficolin 1 (FCN1). Further validation confirmed that RGS1 was the optimal shared target gene for AF and periodontitis. Immune cell infiltration analysis revealed that neutrophils and T cells play an important role in the pathogenesis of both diseases. RGS1 showed a significant positive correlation with activated memory CD4 T cells and gamma-delta T cells and a negative correlation with CD8 T cells and regulatory T cells in both training sets. Moreover, RGS1 was positively correlated with classical pro-inflammatory cytokines IL1β and IL6. In periodontitis rat models, AF susceptibility, atrial fibrosis, and inflammatory infiltration were significantly increased, and RGS1 expression in the atrial tissue was upregulated.

CONCLUSION

A common gene between AF and periodontitis, RGS1 appears central in linking the two conditions. Immune and inflammatory responses may underlie the interaction between AF and periodontitis.

Identification and validation of potential biomarkers for atrial fibrillation based on integrated bioinformatics analysis

Background: Globally, the most common form of arrhythmias is atrial fibrillation (AF), which causes severe morbidity, mortality, and socioeconomic burden. The application of machine learning algorithms in combination with weighted gene co-expression network analysis (WGCNA) can be used to screen genes, therefore, we aimed to screen for potential biomarkers associated with AF development using this integrated bioinformatics approach. Methods: On the basis of the AF endocardium gene expression profiles GSE79768 and GSE115574 from the Gene Expression Omnibus database, differentially expressed genes (DEGs) between AF and sinus rhythm samples were identified. DEGs enrichment analysis and transcription factor screening were then performed. Hub genes for AF were screened using WGCNA and machine learning algorithms, and the diagnostic accuracy was assessed by the receiver operating characteristic (ROC) curves. GSE41177 was used as the validation set for verification. Subsequently, we identified the specific signaling pathways in which the key biomarkers were involved, using gene set enrichment analysis and reverse prediction of mRNA-miRNA interaction pairs. Finally, we explored the associations between the hub genes and immune microenvironment and immune regulation. Results: Fifty-seven DEGs were identified, and the two hub genes, hypoxia inducible factor 1 subunit alpha inhibitor (HIF1AN) and mitochondrial inner membrane protein MPV17 (MPV17), were screened using WGCNA combined with machine learning algorithms. The areas under the receiver operating characteristic curves for MPV17 and HIF1AN validated that two genes predicted AF development, and the differential expression of the hub genes was verified in the external validation dataset. Enrichment analysis showed that MPV17 and HIF1AN affect mitochondrial dysfunction, oxidative stress, gap junctions, and other signaling pathway functions. Immune cell infiltration and immunomodulatory correlation analyses showed that MPV17 and HIF1AN are strongly correlated with the content of immune cells and significantly correlated with HLA expression. Conclusion: The identification of hub genes associated with AF using WGCNA combined with machine learning algorithms and their correlation with immune cells and immune gene expression can elucidate the molecular mechanisms underlying AF occurrence. This may further identify more accurate and effective biomarkers and therapeutic targets for the diagnosis and treatment of AF.

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.

Inflammation and Coagulation are Two Interconnected Pathophysiological Pathways in Atrial Fibrillation Pathogenesis

Introduction

Atrial fibrillation (AF) is associated with elevated levels of clotting factors such as tissue factor (TF) and factor XII (FXII). Various inflammation markers, such as interleukin-6 (IL-6), tumor necrosis factor-α (TNF- α), and high-sensitive C-reactive protein (hs-CRP), have also been associated with AF. This study explores the relationship between inflammation markers and coagulation activity, including their impact on heart structural changes in these patients.

Methods

We observed 283 patients with nonvalvular AF who underwent a complete examination at admission, but only 183 patients have successful cardioversion. As a control group, similar patients without AF were examined. The markers of the coagulation and inflammation were studied by ELISA on the analyzer "Stat Fax 303 Plus". Studies were conducted using l statistical package SPSS 13.0.

Results

It was revealed that patients with AF had significantly higher levels of hs-CRP, IL-6, and TNF-α and had elevated levels of TF and FXII compared with control group. The moderate correlations were observed between IL-6 and left atrial diameter (LAD), IL-6 and LA stiffness, hs-CRP and left atrial volume (LAV), TF and LAV.

Conclusion

We have demonstrated that patients with AF have the relationship between elevated levels of inflammatory markers and coagulation activity, which contributes to structural atrial remodeling.

[mRNA Expression Profile Changes in Angiotensin-Ⅱ-Induced Atrial Myocardial Fibrosis in Rats]

Objective

To study the differences between the mRNA expression profile in angiotensin Ⅱ (Ang Ⅱ)-induced fibrotic cardiomyocytes and that of normal cardiomyocytes and the relevant signaling pathways.

Methods

Six 8-week-old male Sprague-Dawley (SD) rats were randomly assigned to a control group and an Ang Ⅱ group, with 3 rats in each group. Rats in the control group were injected via caudal vein with 0.9% normal saline at 2 mg/kg per day, while rats in the Ang Ⅱ group were injected with Ang Ⅱ via caudal vein at 2 mg/kg per day. The medications were continuously administered in the two groups for 14 days. The degree of myocardial fibrosis was determined by Masson's Trichrome staining and the content of collagen Ⅰ was determined by immunohistochemistry. High throughput sequencing was performed to measure the mRNA expression of rat cardiomyocytes in the two groups and to screen for differentially-expressed mRNAs. The differentially-expressed mRNAs were analyzed by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.

Results

Compared with those of the control group, the degree of myocardial fibrosis and the content of collagen Ⅰ in Ang Ⅱ group were significantly higher ( P<0.05). Through sequencing, 313 differentially-expressed mRNAs were identified, with 201 being up-regulated and 112 being down-regulated. Go and KEGG analyses showed that these differentially-expressed mRNA were involved in a variety of biological regulatory functions and pathways of myocardial fibrosis.

Conclusion

Ang Ⅱ can cause myocardial fibrosis in rats. There are significant differences in mRNA expression between fibrotic cardiomyocytes and normal cardiomyocytes. The differentially expressed mRNAs may play an important role in biological processes, including immune response, cell remodeling, and extracellular matrix deposition.

Metabolic Syndrome and Atrial Fibrillation: Different Entities or Combined Disorders

Obesity, hypertension, insulin resistance, and dyslipidemia are all clusters of an entity called "Metabolic Syndrome". The global trends of this syndrome's incidence/prevalence continue to increase reciprocally, converting it into a massive epidemic problem in the medical community. Observing the risk factors of atrial fibrillation, a medical condition that is also converted to a scourge, almost all parts of the metabolic syndrome are encountered. In addition, several studies demonstrated a robust correlation between metabolic syndrome and the occurrence of atrial fibrillation. For atrial fibrillation to develop, a combination of the appropriate substrate and a trigger point is necessary. The metabolic syndrome affects the left atrium in a multifactorial way, leading to atrial remodeling, thus providing both the substrate and provoking the trigger needed, which possibly plays a substantial role in the progression of atrial fibrillation. Due to the remodeling, treatment of atrial fibrillation may culminate in pernicious sequelae, such as repeated catheter ablation procedures. A holistic approach of the patient, with simultaneous treatment of both entities, is suggested in order to ensure better outcomes for the patients.

TNFSF14/LIGHT promotes cardiac fibrosis and atrial fibrillation vulnerability via PI3Kγ/SGK1 pathway-dependent M2 macrophage polarisation

BACKGROUND

Tumour necrosis factor superfamily protein 14 (TNFSF14), also called LIGHT, is an important regulator of immunological and fibrosis diseases. However, its specific involvement in cardiac fibrosis and atrial fibrillation (AF) has not been fully elucidated. The objective of this study is to examine the influence of LIGHT on the development of myocardial fibrosis and AF.

METHODS

PCR arrays of peripheral blood mononuclear cells (PBMCs) from patients with AF and sinus rhythm was used to identify the dominant differentially expressed genes, followed by ELISA to evaluate its serum protein levels. Morphological, functional, and electrophysiological changes in the heart were detected in vivo after the tail intravenous injection of recombinant LIGHT (rLIGHT) in mice for 4 weeks. rLIGHT was used to stimulate bone marrow-derived macrophages (BMDMs) to prepare a macrophage-conditioned medium (MCM) in vitro. Then, the MCM was used to culture mouse cardiac fibroblasts (CFs). The expression of relevant proteins and genes was determined using qRT-PCR, western blotting, and immunostaining.

RESULTS

The mRNA levels of LIGHT and TNFRSF14 were higher in the PBMCs of patients with AF than in those of the healthy controls. Additionally, the serum protein levels of LIGHT were higher in patients with AF than those in the healthy controls and were correlated with left atrial reverse remodelling. Furthermore, we demonstrated that rLIGHT injection promoted macrophage infiltration and M2 polarisation in the heart, in addition to promoting atrial fibrosis and AF inducibility in vivo, as detected with MASSON staining and atrial burst pacing respectively. RNA sequencing of heart samples revealed that the PI3Kγ/SGK1 pathway may participate in these pathological processes. Therefore, we confirmed the hypothesis that rLIGHT promotes BMDM M2 polarisation and TGB-β1 secretion, and that this process can be inhibited by PI3Kγ and SGK1 inhibitors in vitro. Meanwhile, increased collagen synthesis and myofibroblast transition were observed in LIGHT-stimulated MCM-cultured CFs and were ameliorated in the groups treated with PI3Kγ and SGK1 inhibitors.

CONCLUSION

LIGHT protein levels in peripheral blood can be used as a prognostic marker for AF and to evaluate its severity. LIGHT promotes cardiac fibrosis and AF inducibility by promoting macrophage M2 polarisation, wherein PI3Kγ and SGK1 activation is indispensable.

Inflammatory bowel disease and atrial fibrillation: a contemporary overview

Atrial fibrillation is the most common arrhythmia in clinical practice and it is associated with increased morbidity and mortality. Atrial fibrillation is linked with inflammatory signaling while inflammation and oxidative stress promote atrial remodeling promoting the development and perpetuation of the arrhythmia. On the other hand, inflammatory bowel disease (IBD) is considered a chronic inflammatory condition with flares and remissions. IBD has been associated with an increased risk of atherosclerotic cardiovascular disease but its relationship with atrial fibrillation has not been studied well. Recent epidemiological evidence indicates an association between IBD and atrial fibrillation, especially during flares/hospitalizations. This brief review provides a concise overview of all available data regarding the association between IBD and atrial fibrillation including the predictive role of electrocardiographic and echocardiographic markers. Several unresolved issues including the thromboembolic risk in this setting and the potential role of antiinflammatory interventions are also discussed.

Analyses of m6A regulatory genes and subtype classification in atrial fibrillation

Objective

To explore the role of m6A regulatory genes in atrial fibrillation (AF), we classified atrial fibrillation patients into subtypes by two genotyping methods associated with m6A regulatory genes and explored their clinical significance.

Methods

We downloaded datasets from the Gene Expression Omnibus (GEO) database. The m6A regulatory gene expression levels were extracted. We constructed and compared random forest (RF) and support vector machine (SVM) models. Feature genes were selected to develop a nomogram model with the superior model. We identified m6A subtypes based on significantly differentially expressed m6A regulatory genes and identified m6A gene subtypes based on m6A-related differentially expressed genes (DEGs). Comprehensive evaluation of the two m6A modification patterns was performed.

Results

The data of 107 samples from three datasets, GSE115574, GSE14975 and GSE41177, were acquired from the GEO database for training models, comprising 65 AF samples and 42 sinus rhythm (SR) samples. The data of 26 samples from dataset GSE79768 comprising 14 AF samples and 12 SR samples were acquired from the GEO database for external validation. The expression levels of 23 regulatory genes of m6A were extracted. There were correlations among the m6A readers, erasers, and writers. Five feature m6A regulatory genes, ZC3H13, YTHDF1, HNRNPA2B1, IGFBP2, and IGFBP3, were determined (p < 0.05) to establish a nomogram model that can predict the incidence of atrial fibrillation with the RF model. We identified two m6A subtypes based on the five significant m6A regulatory genes (p < 0.05). Cluster B had a lower immune infiltration of immature dendritic cells than cluster A (p < 0.05). On the basis of six m6A-related DEGs between m6A subtypes (p < 0.05), two m6A gene subtypes were identified. Both cluster A and gene cluster A scored higher than the other clusters in terms of m6A score computed by principal component analysis (PCA) algorithms (p < 0.05). The m6A subtypes and m6A gene subtypes were highly consistent.

Conclusion

The m6A regulatory genes play non-negligible roles in atrial fibrillation. A nomogram model developed by five feature m6A regulatory genes could be used to predict the incidence of atrial fibrillation. Two m6A modification patterns were identified and evaluated comprehensively, which may provide insights into the classification of atrial fibrillation patients and guide treatment.

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.

Combining bioinformatics and machine learning to identify common mechanisms and biomarkers of chronic obstructive pulmonary disease and atrial fibrillation

Background

Patients with chronic obstructive pulmonary disease (COPD) often present with atrial fibrillation (AF), but the common pathophysiological mechanisms between the two are unclear. This study aimed to investigate the common biological mechanisms of COPD and AF and to search for important biomarkers through bioinformatic analysis of public RNA sequencing databases.

Methods

Four datasets of COPD and AF were downloaded from the Gene Expression Omnibus (GEO) database. The overlapping genes common to both diseases were screened by WGCNA analysis, followed by protein-protein interaction network construction and functional enrichment analysis to elucidate the common mechanisms of COPD and AF. Machine learning algorithms were also used to identify key biomarkers. Co-expression analysis, “transcription factor (TF)-mRNA-microRNA (miRNA)” regulatory networks and drug prediction were performed for key biomarkers. Finally, immune cell infiltration analysis was performed to evaluate further the immune cell changes in the COPD dataset and the correlation between key biomarkers and immune cells.

Results

A total of 133 overlapping genes for COPD and AF were obtained, and the enrichment was mainly focused on pathways associated with the inflammatory immune response. A key biomarker, cyclin dependent kinase 8 (CDK8), was identified through screening by machine learning algorithms and validated in the validation dataset. Twenty potential drugs capable of targeting CDK8 were obtained. Immune cell infiltration analysis revealed the presence of multiple immune cell dysregulation in COPD. Correlation analysis showed that CDK8 expression was significantly associated with CD8+ T cells, resting dendritic cell, macrophage M2, and monocytes.

Conclusions

This study highlights the role of the inflammatory immune response in COPD combined with AF. The prominent link between CDK8 and the inflammatory immune response and its characteristic of not affecting the basal expression level of nuclear factor kappa B (NF-kB) make it a possible promising therapeutic target for COPD combined with AF.

Causal association of peripheral immune cell counts and atrial fibrillation: A Mendelian randomization study

Background

Atrial fibrillation (AF) is the most common and persistent form of arrhythmia. Recently, increasing evidence has shown a link between immune responses and atrial fibrillation. However, whether the immune response is a cause or consequence of AF remains unknown. We aimed to determine whether genetically predicted peripheral immunity might have a causal effect on AF.

Methods

First, we performed Mendelian randomization (MR) analyses using genetic variants strongly associated with neutrophil, eosinophil, basophil, lymphocyte, and monocyte cell counts as instrumental variables (IVs). Lymphocyte counts were then subjected to further subgroup analysis. The effect of immune cell counts on AF risk was measured using summary statistics from genome-wide association studies (GWAS).

Results

Two-sample MR analysis revealed that a higher neutrophil count, basophil count and lymphocyte count had a causal effect on AF [Odds ratio (OR), 1.06, 95% confidence interval (CI), 1.01-1.10, P = 0.0070; OR, 1.10; 95% CI, 1.04-1.17; P = 0.0015; OR, 0.96; 95% CI, 0.93-0.99; P = 0.0359]. In addition, in our further analysis, genetically predicted increases in CD4 + T-cell counts were also associated with an increased risk of AF (OR, 1.04; 95% CI, 1.0-.09; P = 0.0493).

Conclusion

Our MR analysis provided evidence of a genetically predicted causal relationship between higher peripheral immune cell counts and AF. Subgroup analysis revealed the key role of peripheral lymphocytes in AF, especially the causal relationship between CD4 + T cell count and AF. These findings are beneficial for future exploration of the mechanism of AF.