Potential Target Genes in the Development of Atrial Fibrillation: A Comprehensive Bioinformatics Analysis

Background

Atrial fibrillation (AF) is the most prevalent arrhythmia worldwide. Although it is not life-threatening, the accompanying rapid and irregular ventricular rate can lead to hemodynamic deterioration and obvious symptoms, especially the risk of cerebrovascular embolism. Our study aimed to identify novel and promising genes that could explain the underlying mechanism of AF development.

Material/Methods

Expression profiles GSE41177, GSE79768, and GSE14975 were acquired from the Gene Expression Omnibus Database. R software was used for identifying differentially expressed genes (DEGs), and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were subsequently performed. A protein–protein interaction network was constructed in Cytoscape software. Next, a least absolute shrinkage and selection operator (LASSO) model was constructed and receiver-operating characteristic curve analysis was conducted to assess the specificity and sensitivity of the key genes.

Results

We obtained 204 DEGs from the datasets. The DEGs were mostly involved in immune response and cell communication. The primary pathways of the DEGs were related to the course or maintenance of autoimmune and chronic inflammatory diseases. The top 20 hub genes (high scores in cytoHubba) were selected in the PPI network. Finally, we identified 6 key genes (FCGR3B, CLEC10A, FPR2, IGSF6, S100A9, and S100A12) via the LASSO model.

Conclusions

We present 6 target genes that are potentially involved in the molecular mechanisms of AF development. In addition, these genes are likely to serve as potential therapeutic targets.

The relationship between preoperative serum vitamin D deficiency and postoperative atrial fibrillation: A systematic review and meta-analysis

Postoperative atrial fibrillation (POAF) is the most common arrhythmia seen in the first days following cardiac surgeries. Recently, there is a growing discussion regarding the link between vitamin D deficiency and POAF development. This systematic review and meta-analysis of the observational studies aimed at evaluating the association between preoperative vitamin D deficiency and Postoperative atrial fibrillation. In this study, using PubMed, Scopus, Google Scholar, EMBASE, Web of Science, and Cochrane Libraries, we searched for records published before July 2020. Two reviewers screened for studies that examined the relationship between preoperative vitamin D levels and the generation of POAF. Data regarding study design, patient characteristics, definition of atrial fibrillation (AF), type of surgery, vitamin D levels, and measurement methods were extracted. Five studies were included in the meta-analysis. Our primary analysis showed a significant relationship between preoperative levels of vitamin D and POAF development (mean differences (MD) = -2.851, 95% confidence interval (CI) =-5.506 to -0.195; P value 0.035). Our meta-analysis suggested serum vitamin D deficiency is associated with an increased risk of POAF development. Further large scale interventional studies are needed to explore whether vitamin D supplementation will prevent POAF.

Predictors of recurrent atrial fibrillation following catheter ablation

INTRODUCTION

Atrial fibrillation (AF) is a complex and multi-factorial rhythm disorder. Catheter ablation is widely used for the management of AF. However, it is limited by relapse of the arrhythmia necessitating repeat procedures.

AREAS COVERED

This review aims to discuss the predictors of post-ablation recurrent AF including age, gender, genetic predisposition, AF type and duration, comorbidities, lifestyle factors, echocardiographic parameters of heart chambers, left atrial fibrosis and ablation strategies and targets. An extensive literature search was undertaken on PubMed and Google Scholar to obtain full texts of relevant AF-related articles.

EXPERT OPINION

Maintenance of stable sinus rhythm is the main intended outcome of AF ablation. Therefore, it is very crucial to identify the risk factors that may influence the ablation success. Most of these predictors such as comorbidities, ablation strategy and targets and lifestyle factors are either reversible or modifiable. Thus, not only the awareness of these known risk factors by both patients and their physicians but also future research to identify the unknown predictors are critical to optimize care in this multi-faceted morbidity.

Predicting major bleeding among hospitalized patients using oral anticoagulants for atrial fibrillation after discharge

Aim

Real-world predictors of major bleeding (MB) have been well-studied among warfarin users, but not among all direct oral anticoagulant (DOAC) users diagnosed with atrial fibrillation (AF). Thus, our goal was to build a predictive model of MB for new users of all oral anticoagulants (OAC) with AF.

Methods

We identified patients hospitalized for any cause and discharged alive in the community from 2011 to 2017 with a primary or secondary diagnosis of AF in Quebec’s RAMQ and Med-Echo administrative databases. Cohort entry occurred at the first OAC claim. Patients were categorized according to OAC type. Outcomes were incident MB, gastrointestinal bleeding (GIB), non-GI extracranial bleeding (NGIB) and intracranial bleeding within 1 year of follow-up. Covariates included age, sex, co-morbidities (within 3 years before cohort entry) and medication use (within 2 weeks before cohort entry). We used logistic-LASSO and adaptive logistic-LASSO regressions to identify MB predictors among OAC users. Discrimination and calibration were assessed for each model and a global model was selected. Subgroup analyses were performed for MB subtypes and OAC types.

Results

Our cohort consisted of 14,741 warfarin, 3,722 dabigatran, 6,722 rivaroxaban and 11,196 apixaban users aged 70–86 years old. The important MB predictors were age, prior MB and liver disease with ORs ranging from 1.37–1.64. The final model had a c-statistic of 0.63 (95% CI 0.60–0.65) with adequate calibration. The GIB and NGIB models had similar c-statistics of 0.65 (95% CI 0.63–0.66) and 0.67 (95% CI 0.64–0.70), respectively.

Conclusions

MB and MB subtype predictors were similar among DOAC and warfarin users. The predictors selected by our models and their discriminative potential are concordant with published data. Thus, these models can be useful tools for future pharmacoepidemiologic studies involving older oral anticoagulant users with AF.

Prognostic value of troponin I in atrial fibrillation

OBJECTIVE

To evaluate whether circulating cardiac troponin I (cTnI) levels are associated with worst outcomes in patients with atrial fibrillation (AF).

METHODS

Consecutive patients visiting the emergency room (ER) with a new episode of a previously diagnosed AF or a new diagnosis of AF during ER admission between January 1st, 2010 and December 31st, 2015, were enrolled in the study (n = 2617). After applying exclusion criteria and eliminating repeated episodes, 2013 patients were finally included. Of these, 1080 patients with at least one cTnI measurement in the ER were selected and classified into 4 groups according to cTnI quartiles: Q1 (n = 147) cTnI <10 ng/L (Group 1); Q2 (n = 254): 10-19 ng/L (Group 2); Q3 (n = 409): 20-40 ng/L (Group 3); and Q4 (n = 270): cTnI >40 ng/L (Group 4). The median follow-up period was 47.8 ± 32.8 months. The primary endpoint was all-cause death during the follow-up.

RESULTS

A higher mortality was found in group 4 compared with the other groups (58.9% vs. 28.5%, respectively, p < 0.001), along with, hospitalizations (40.4% vs. 30.7%, p = 0.004), and readmissions due to decompensated heart failure (26.7% vs. 2.5%, p = 0.002). The probability of survival without AF recurrences was lower in the Q4 (p = 0.045). Moreover, cTnI levels >40 ng/L (Q4) were an independent risk factor of death (HR, 2.03; 95% CI, 1.64-2.51; p < 0.001).

CONCLUSION

The assessment of cTnI at ER admission could be a useful strategy for risk stratification of patients diagnosed with AF by identifying a subgroup with medium-term to long-term increased risk of adverse events and mortality.

Very Low Prevalence and Incidence of Atrial Fibrillation among Bolivian Forager-Farmers

Background

Atrial fibrillation is the most common arrhythmia in post-industrialized populations. Older age, hypertension, obesity, chronic inflammation, and diabetes are significant atrial fibrillation risk factors, suggesting that modern urban environments may promote atrial fibrillation.

Objective

Here we assess atrial fibrillation prevalence and incidence among tropical horticulturalists of the Bolivian Amazon with high levels of physical activity, a lean diet, and minimal coronary atherosclerosis, but also high infectious disease burden and associated inflammation.

Methods

Between 2005-2019, 1314 Tsimane aged 40-94 years (52% female) and 534 Moseten Amerindians aged 40-89 years (50% female) underwent resting 12-lead electrocardiograms to assess atrial fibrillation prevalence. For atrial fibrillation incidence assessment, 1059 (81% of original sample) Tsimane and 310 Moseten (58%) underwent additional ECGs (mean time to follow up 7.0, 1.8 years, respectively).

Findings

Only one (male) of 1314 Tsimane (0.076%) and one (male) of 534 Moseten (0.187%) demonstrated atrial fibrillation at baseline. There was one new (female) Tsimane case in 7395 risk years for the 1059 participants with >1 ECG (incidence rate = 0.14 per 1,000 risk years). No new cases were detected among Moseten, based on 542 risk years.

Conclusion

Tsimane and Moseten show the lowest levels of atrial fibrillation ever reported, 1/20 to ~1/6 of rates in high-income countries. These findings provide additional evidence that a subsistence lifestyle with high levels of physical activity, and a diet low in processed carbohydrates and fat is cardioprotective, despite frequent infection-induced inflammation. Findings suggest that atrial fibrillation is a modifiable lifestyle disease rather than an inevitable feature of cardiovascular aging.

Utility estimations of health states of older Australian women with atrial fibrillation using SF-6D

PURPOSE

To estimate SF-6D utility scores for older women with atrial fibrillation (AF); calculate and compare mean utility scores for women with AF with various demographic, health behaviours, and clinical characteristics; and develop a multivariable regression model to determine factors associated with SF-6D utility scores.

METHODS

This study evaluated N = 1432 women diagnosed with AF from 2000 to 2015 of the old cohort (born 1921-26) of the Australian Longitudinal Study on Women's Health (ALSWH) who remained alive for at least 12 months post first recorded AF diagnosis. Self-reported data on demographics, health behaviours, health conditions, and SF-36 were obtained from the ALSWH surveys, corresponding to within three years of the date of the first record of AF diagnosis. Linked Pharmaceutical Benefits Scheme (PBS) data determined the use of oral anticoagulants and comorbid conditions, included in CHA₂DS₂-VA (Congestive heart failure, Hypertension, Age ≥ 75 years, Diabetes, Stroke or TIA, Vascular disease and Age 65-74 years) score calculation, were assessed using state-based hospital admissions data. Utility scores were calculated for every woman from their SF-36 responses using the SF-6D algorithm with Australian population norms. Mean utility scores were then calculated for women with various demographic, health behaviours, and clinical characteristics. Ordinary Least Square (OLS) regression modelling was performed to determine factors associated with these utility scores. Two different scenarios were used for the analysis: (1) complete-case, for women with complete data on all the SF-36 items required to estimate SF-6D (N = 584 women), and (2) Multiple Imputation (MI) for missing data, applied to missing values on SF-36 items (N = 1432 women). MI scenario was included to gauge the potential bias when using complete data only.

RESULTS

The mean health utility was estimated to be 0.638 ± 0.119 for the complete dataset and 0.642 ± 0.120 for the dataset where missing values were handled using MI. Using the MI technique, living in regional and remote areas ([Formula: see text]) and the use of oral anticoagulants ([Formula: see text] were positively associated with health utility compared to living in major cities and no use of anticoagulants, respectively. Difficulty to manage on available income [Formula: see text], no/low physical activity [Formula: see text], disability [Formula: see text], history of stroke ([Formula: see text] and history of arthritis [Formula: see text] were negatively associated with health utility.

CONCLUSION

This study presents health utility estimates for older women with AF. These estimates can be used in future clinical and economic research. The study also highlights better health utilities for women living in regional and remote areas, which requires further exploration.

Atrial fibrillation self screening, management and guideline recommended therapy (AF SELF SMART): A protocol for atrial fibrillation self-screening in general practice

BACKGROUND

Opportunistic screening for silent atrial fibrillation (AF) is recommended to reduce stroke, but screening rates are sub-optimal in general practice. We hypothesize that patient self-screening in the waiting room may improve screening and detection of AF.

METHODS AND ANALYSES

This proof-of-concept study tests a purpose-designed AF self-screening station and customised software which seamlessly integrates with general practice electronic medical records and workflow. The self-screening station records a lead-1 ECG. The software automatically (1) identifies eligible patients (aged ≥65 years, no AF diagnosis) from the practice appointment diary; (2) sends eligible patients an automated SMS reminder prior to their appointment; (3) creates individualised QR code to scan at self-screening station; and (4) imports the ECG and result directly into the patients' electronic medical record. Between 5 and 8 general practices in New South Wales, Australia, will participate with an aim of 1500 patients undertaking self-screening. The main outcome measures will be the proportion of eligible patients that undertook self-screening, incidence of newly-diagnosed AF, and patient and staff experience of the self-screening process. De-identified data will be collected using a clinical audit tool, and qualitative interviews will determine patient and staff acceptability.

ETHICS AND DISSEMINATION

Ethics approval was received from the University of Sydney Human Research Ethics Committee in June 2019 (Project no: 2019/382) and the University of Notre Dame Human Research Ethics Committee (Project no: 019145S) in October 2019. Results will be disseminated through various forums, including peer-reviewed publication and conference presentations.Trial registration numberACTRN12620000233921.

The association of fracture risk in atrial fibrillation patients and long-term anticoagulant therapy category: a systematic review and meta-analysis

OBJECTIVE

Our study aimed to assess the risk of all fractures and hip fractures in patients with atrial fibrillation (AF) who took non-vitamin K antagonist oral anticoagulants (NOACs) compared to warfarin.

METHODS

We searched PubMed, Embase, and Cochrane Library and Clinical Trials.gov Website. Reviewed related researches up to January 31, 2020, to identify studies with more than 12 months of follow-up data. The protocol for this systematic review and meta-analysis has been registered in the International Prospective Register of Systematic Reviews (PROSPERO Number: CRD42020156893).

RESULTS

We included five RCT studies, and five observational studies that contained a total of 326,846 patients in our meta-analysis. Our meta-analysis showed that patients taken NOACs had no significant all fracture risk (RR = 0.91, 95% CI [0.81-1.01]) and hip fracture risk (RR = 0.92, 95% CI [0.82-1.03]) compared with those taken warfarin. Subanalysis showed that the risk of all fractures and hip fractures treated by NOACs were significant lower compared with warfarin in observational studies compared with RCT studies. Also, a subanalysis across the duration of anticoagulation showed the NOACs users have lower all fracture risk than warfarin users when the duration of anticoagulation ≤2 years (RR = 0.89, 95% CI [0.80-0.99]). Further analysis, significant lower all fracture risk in the rivaroxaban therapy (RR = 0.81; 95% CI [0.76-0.86]) compared with warfarin but no statistical significance in hip fracture. There were no significant difference of all fracture risk and hip fracture risk in dabigatran, apixaban, and edoxaban therapy compared with warfarin.

CONCLUSION

The meta-analysis demonstrated that NOACs associated with a significantly lower all fracture risk compared with warfarin when the duration of anticoagulation more than 2 years. Rivaroxaban users had lower risk of all fracture than warfarin users in AF patients. But there was no evidence to verify apixaban, edoxaban, and dabigatranin could decrease all fracture and hip fracture risk compared with warfarin.

Predicting All-Cause Mortality Risk in Atrial Fibrillation Patients: A Novel LASSO-Cox Model Generated From a Prospective Dataset

Background: Although mortality remains high in patients with atrial fibrillation (AF), there have been limited studies exploring machine learning (ML) models on mortality risk prediction in patients with AF. Objectives: This study sought to develop an ML model that captures important variables in order to predict all-cause mortality in AF patients. Methods: In this single center prospective study, an ML-based mortality prediction model was developed and validated using a dataset of 2,012 patients who experienced AF from November 2018 to February 2020 at the First Affiliated Hospital of Shantou University Medical College. The dataset was randomly divided into a training set (70%, n = 1,223) and a validation set (30%, n = 552). A total of 122 features were collected for variable selection. Least absolute shrinkage and selection operator (LASSO) and random forest (RF) algorithms were used for variable selection. Ten ML models were developed using variables selected by LASSO or RF. The best model was selected and compared with conventional risk scores. A nomogram and user-friendly online tool were developed to facilitate the mortality predictions and management recommendations. Results: Thirteen features were selected by the LASSO regression algorithm. The LASSO-Cox model achieved an area under the curve (AUC) of 0.842 in the training dataset, and 0.854 in the validation dataset. A nomogram based on eight independent features was developed for the prediction of survival at 30, 180, and 365 days following discharge. Both the time dependent receiver operating characteristic (ROC) and decision curve analysis (DCA) showed better performances of the nomogram compared to the CHA₂DS₂-VASc and HAS-BLED models. Conclusions: The LASSO-Cox mortality predictive model shows potential benefits in death risk evaluation for AF patients over the 365-day period following discharge. This novel ML approach may also provide physicians with personalized management recommendations.

Mobile health technology-supported atrial fibrillation screening and integrated care: A report from the mAFA-II trial Long-term Extension Cohort

BACKGROUND

In the mobile Atrial Fibrillation App (mAFA)-II trial, the use of mobile health (mHealth) technology, incorporating AF screening and integrated management strategy, was associated with improved short-term clinical outcomes. The aim of this study was to report adherence/persistence and long term (≥1 year) clinical outcomes of the mAFA-II trial, with mHealth-supported optimised stroke prevention, symptom control and comorbidity management.

METHODS

We studied an adult population screened for AF, where identified patients could enter a structured program of holistic and integrated care based on the ABC (Atrial fibrillation Better Care) pathway using mHealth with a mAFA intervention. In this cluster randomised trial, comparing mHeath intervention to usual care, the primary composite outcome was 'stroke/thromboembolism, all-cause death and rehospitalization'.

RESULTS

The 1261 subjects (mean age 67.0 years, 38.0% female) who were followed up over one year (mean follow-up 687 (standard deviation, SD 191) days) in the intervention arm, had a lower risk of the composite outcome of 'ischaemic stroke/systemic thromboembolism, death, and rehospitalization' (hazard ratio, HR 0.18, 95% confidence interval, CI: 0.13-0.25, P < 0.001), compared to usual care (1212 subjects, mean age 70.1 years, 42.1% female). Of 842 patients using their smart devices for 'Better symptom management', 70.8% had good management adherence (monitoring time/follow-up since initial monitoring ≥ 70%), with the persistence of use of 91.7%.

CONCLUSION

Amongst AF patients with long term use (≥1 year) of mHealth technology for optimising stroke prevention, symptom control and comorbidity management, adherence/persistence was good and associated with a reduction in adverse clinical outcomes.

Small and Intermediate Calcium Activated Potassium Channels in the Heart: Role and Strategies in the Treatment of Cardiovascular Diseases

Calcium-activated potassium channels are a heterogeneous family of channels that, despite their different biophysical characteristics, structures, and pharmacological signatures, play a role of transducer between the ubiquitous intracellular calcium signaling and the electric variations of the membrane. Although this family of channels was extensively described in various excitable and non-excitable tissues, an increasing amount of evidences shows their functional role in the heart. This review aims to focus on the physiological role and the contribution of the small and intermediate calcium-activated potassium channels in cardiac pathologies.

Does Catheter Ablation Lower the Long-Term Risk of Stroke and Mortality in Patients with Atrial Fibrillation? A Concise Review of the Current State of Knowledge

Atrial fibrillation (AF) is the most common cardiac arrhythmia worldwide and carries a significant risk of morbidity and mortality. Multiple trials have highlighted the benefit of catheter ablation over medical therapy in restoring sinus rhythm and improving quality of life. Whether it reduces long-term risk of stroke and mortality is still unclear.

We performed a literature search using the PubMed database to review the current state of knowledge regarding the long-term outcomes of stroke and mortality in ablated patients compared to patients who receive medical therapy. Our review mainly consisted of recent randomized controlled trials and large observational studies. 

Results from large observational studies show that catheter ablation significantly reduces the risk of stroke in high-risk patients and mortality compared to medical therapy. However, randomized controlled trials have only demonstrated a mortality benefit in patients with comorbid systolic heart failure. In patients with paroxysmal AF, ablation therapy significantly limits the progression to persistent AF and has a higher efficacy in restoring sinus rhythm. Maintenance of sinus rhythm is the most important factor associated with lower long term risk of stroke and mortality.

Large randomized controlled trials similar to the Catheter Ablation Versus Anti-arrhythmic Drug Therapy for Atrial Fibrillation (CABANA) trial are still needed to clarify whether catheter ablation is superior over medical therapy in improving the long-term outcomes of stroke and mortality.

Multi-scale Entropy Evaluates the Proarrhythmic Condition of Persistent Atrial Fibrillation Patients Predicting Early Failure of Electrical Cardioversion

Atrial fibrillation (AF) is nowadays the most common cardiac arrhythmia, being associated with an increase in cardiovascular mortality and morbidity. When AF lasts for more than seven days, it is classified as persistent AF and external interventions are required for its termination. A well-established alternative for that purpose is electrical cardioversion (ECV). While ECV is able to initially restore sinus rhythm (SR) in more than 90% of patients, rates of AF recurrence as high as 20-30% have been found after only a few weeks of follow-up. Hence, new methods for evaluating the proarrhythmic condition of a patient before the intervention can serve as efficient predictors about the high risk of early failure of ECV, thus facilitating optimal management of AF patients. Among the wide variety of predictors that have been proposed to date, those based on estimating organization of the fibrillatory (f-) waves from the surface electrocardiogram (ECG) have reported very promising results. However, the existing methods are based on traditional entropy measures, which only assess a single time scale and often are unable to fully characterize the dynamics generated by highly complex systems, such as the heart during AF. The present work then explores whether a multi-scale entropy (MSE) analysis of the f-waves may provide early prediction of AF recurrence after ECV. In addition to the common MSE, two improved versions have also been analyzed, composite MSE (CMSE) and refined MSE (RMSE). When analyzing 70 patients under ECV, of which 31 maintained SR and 39 relapsed to AF after a four week follow-up, the three methods provided similar performance. However, RMSE reported a slightly better discriminant ability of 86%, thus improving the other multi-scale-based outcomes by 3-9% and other previously proposed predictors of ECV by 15-30%. This outcome suggests that investigation of dynamics at large time scales yields novel insights about the underlying complex processes generating f-waves, which could provide individual proarrhythmic condition estimation, thus improving preoperative predictions of ECV early failure.

A Deep Learning Approach for Featureless Robust Quality Assessment of Intermittent Atrial Fibrillation Recordings from Portable and Wearable Devices

Atrial fibrillation (AF) is the most common heart rhythm disturbance in clinical practice. It often starts with asymptomatic and very short episodes, which are extremely difficult to detect without long-term monitoring of the patient’s electrocardiogram (ECG). Although recent portable and wearable devices may become very useful in this context, they often record ECG signals strongly corrupted with noise and artifacts. This impairs automatized ulterior analyses that could only be conducted reliably through a previous stage of automatic identification of high-quality ECG intervals. So far, a variety of techniques for ECG quality assessment have been proposed, but poor performances have been reported on recordings from patients with AF. This work introduces a novel deep learning-based algorithm to robustly identify high-quality ECG segments within the challenging environment of single-lead recordings alternating sinus rhythm, AF episodes and other rhythms. The method is based on the high learning capability of a convolutional neural network, which has been trained with 2-D images obtained when turning ECG signals into wavelet scalograms. For its validation, almost 100,000 ECG segments from three different databases have been analyzed during 500 learning-testing iterations, thus involving more than 320,000 ECGs analyzed in total. The obtained results have revealed a discriminant ability to detect high-quality and discard low-quality ECG excerpts of about 93%, only misclassifying around 5% of clean AF segments as noisy ones. In addition, the method has also been able to deal with raw ECG recordings, without requiring signal preprocessing or feature extraction as previous stages. Consequently, it is particularly suitable for portable and wearable devices embedding, facilitating early detection of AF as well as other automatized diagnostic facilities by reliably providing high-quality ECG excerpts to further processing stages.

Atrial fibrillation detection using photoplethysmographic signal: the effect of the observation window

A correct and early diagnosis of cardiac arrhythmias could improve patients' quality of life. The aim of this study is to classify the cardiac rhythm (atrial fibrillation, AF, or normal sinus rhythm NSR) from the photoplethysmographic (PPG) signal and assess the effect of the observation window length. Simulated signals are generated with a PPG simulator previously proposed. The different window lengths taken into account are 20, 30, 40, 50, 100, 150, 200, 250 and 300 beats. After systolic peak detection algorithm, 10 features are computed on the inter-systolic interval series, assessing variability and irregularity of the series. Then, feature selection was performed (using the sequential forward floating search algorithm) which identified two variability parameters (Mean and rMSSD) as the best selection. Finally, the classification by linear support vector machine was performed. Using only two features, accuracy was very high for all the analyzed observation window lengths, going from 0.913±0.055 for length equal to 20 to 0.995±0.011 for length equal to 300 beats.Clinical relevance These preliminary results show that short PPG signals (20 beats) can be used to correctly detect AF.

Integrative analysis reveals essential mRNA, long non-coding RNA (lncRNA), and circular RNA (circRNA) in paroxysmal and persistent atrial fibrillation patients

OBJECTIVE

This study aimed to investigate the functions of mRNA, long non-coding RNA (lncRNA), and circular RNA (circRNA) in paroxysmal and persistent atrial fibrillation (AF) patients.

METHODS

A total of 9 left atrial appendage (LAA) tissues were collected from patients with AF (ParoAF patients = 3 and PersAF patients = 3) and donors (n=3). Genes and circRNAs were identified by per kilobase per million reads (RPKM) and number of circular reads/number of mapped reads/read length (SRPBM), respectively. Differentially expressed mRNAs (DE mRNAs), lncRNAs (DE lncRNAs), and circRNAs (DE circRNAs) were identified by | log2 (Fold Change) | ≥ 2 and p-value < 0.05. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Protein-protein, mRNA-lncRNA, and circRNA-miRNA interaction networks were constructed. In addition, logistic analysis was conducted among AF and circRNAs.

RESULTS

A total of 285 (116 up-regulated and 169 down-regulated) and 275 (110 up-regulated and 165 down-regulated) DE mRNAs, 575 (276 up-regulated and 299 down-regulated) and 583 (330 up-regulated and 253 down-regulated) DE lncRNAs, and 83 (48 up-regulated and 35 down-regulated) and 99 (58 up-regulated and 41 down-regulated) circRNAs were detected in ParoAF and PersAF, respectively, as compared with control. MAPK signal pathway as well as voltage-dependent, L type, and alpha 1C subunit calcium channel (CACNA1C) might participate in AF occurrence by preventing atrial parasympathetic remodeling. Collagen type I alpha 1 (COL1A1) and COL1A2 mostly participated in the enriched GO and KEGG terms and connected with most of the DE mRNAs. The expression of chr10: 69902697|69948883 was a protective factor against PersAF after adjusting for age (p=0.022, 95% CI: 0.003-0.634).

CONCLUSION

We found that some mRNAs, lncRNAs, circRNAs, and pathways play essential roles in AF pathogenesis and development. Moreover, one protective factor against PersAF was detected.