Current controversies in determining the main mechanisms of atrial fibrillation

Combination of frequency- and time-domain characteristics of the fibrillatory waves for enhanced prediction of persistent atrial fibrillation recurrence after catheter ablation

Catheter ablation (CA) remains the cornerstone alternative to cardioversion for sinus rhythm (SR) restoration in patients with atrial fibrillation (AF). Unfortunately, despite the last methodological and technological advances, this procedure is not consistently effective in treating persistent AF. Beyond introducing new indices to characterize the fibrillatory waves (f-waves) recorded through the preoperative electrocardiogram (ECG), the aim of this study is to combine frequency- and time-domain features to improve CA outcome prediction and optimize patient selection for the procedure, given the absence of any study that jointly analyzes information from both domains. Precisely, the f-waves of 151 persistent AF patients undergoing their first CA procedure were extracted from standard V1 lead. Novel spectral and amplitude features were derived from these waves and combined through a machine learning algorithm to anticipate the intervention mid-term outcome. The power rate index (φ), which estimates the power of the harmonic content regarding the dominant frequency (DF), yielded the maximum individual discriminant ability of 64% to discern between individuals who experienced a recurrence of AF and those who sustained SR after a 9-month follow-up period. The predictive accuracy was improved up to 78.5% when this parameter φ was merged with the amplitude spectrum area in the DF bandwidth (A M S A L F ) and the normalized amplitude of the f-waves into a prediction model based on an ensemble classifier, built by random undersampling boosting of decision trees. This outcome suggests that the synthesis of both spectral and temporal features of the f-waves before CA might enrich the prognostic knowledge of this therapy for persistent AF patients.

Overview of Cardiac Arrhythmias and Treatment Strategies

Maintenance of normal cardiac rhythm requires coordinated activity of ion channels and transporters that allow well-ordered propagation of electrical impulses across the myocardium. Disruptions in this orderly process provoke cardiac arrhythmias that may be lethal in some patients. Risk of common acquired arrhythmias is increased markedly when structural heart disease caused by myocardial infarction (due to fibrotic scar formation) or left ventricular dysfunction is present. Genetic polymorphisms influence structure or excitability of the myocardial substrate, which increases vulnerability or risk of arrhythmias in patients. Similarly, genetic polymorphisms of drug-metabolizing enzymes give rise to distinct subgroups within the population that affect specific drug biotransformation reactions. Nonetheless, identification of triggers involved in initiation or maintenance of cardiac arrhythmias remains a major challenge. Herein, we provide an overview of knowledge regarding physiopathology of inherited and acquired cardiac arrhythmias along with a summary of treatments (pharmacologic or non-pharmacologic) used to limit their effect on morbidity and potential mortality. Improved understanding of molecular and cellular aspects of arrhythmogenesis and more epidemiologic studies (for a more accurate portrait of incidence and prevalence) are crucial for development of novel treatments and for management of cardiac arrhythmias and their consequences in patients, as their incidence is increasing worldwide.

Diabetes mellitus and atrial fibrillation-from pathophysiology to treatment

Type 2 diabetes mellitus (T2DM) is a leading risk factor for cardiovascular complications around the globe and one of the most common medical conditions. Atrial fibrillation (AF) is the most common supraventricular arrhythmia, with a rapidly increasing prevalence. T2DM has been closely associated with the risk of AF development, identified as an independent risk factor. Regarding cardio-vascular complications, both AF and T2DM have been linked with high mortality. The underlying pathophysiology has not been fully determined yet; however, it is multifactorial, including structural, electrical, and autonomic pathways. Novel therapies include pharmaceutical agents in sodium-glucose cotransporter-2 inhibitors, as well as antiarrhythmic strategies, such as cardioversion and ablation. Of interest, glucose-lowering therapies may affect the prevalence of AF. This review presents the current evidence regarding the connection between the two entities, the pathophysiological pathways that link them, and the therapeutic options that exist.

A possible new cardiac heterogeneity as an arrhythmogenic driver

Atrial fibrillation (AF) is the commonest cardiac arrhythmia, affecting 3 million people in the USA and 8 million in the EU (according to the European Society of Cardiology). So, why is it that even with the best medical care, around a third of the patients are treatment resistant. Extensive research of its etiology showed that AF and its mechanisms are still debatable. Some of the AF origins are ascribed to functional and ionic heterogeneities of the heart tissue and possibly to additional triggering agents. But, have all AF origins been detected? Are all accepted origins, in fact, arrhythmogenic? In order to study these questions and specifically to check our new idea of intermittency as an arrhythmogenesis agent, we chose to employ a mathematical model which was as simple as possible, but which could still be used to observe the basic network processes of AF development. At this point we were not interested in the detailed ionic propagations nor in the actual shapes of the induced action potentials (APs) during the AF outbreaks. The model was checked by its ability to exactly recapture the basic AF developmental stages known from experimental cardiac observations and from more elaborate mathematical models. We use a simple cellular automata 2D mathematical model of N × N matrices to elucidate the field processes leading to AF in a tissue riddled with randomly distributed heterogeneities of different types, under sinus node operation, simulated by an initial line of briefly stimulated cells inducing a propagating wave, and with or without an additional active ectopic action potential pulse, in turn simulated by a transitory operation of a specific cell. Arrhythmogenic contributions, of three different types of local heterogeneities in myocytes and their collaborations, in inducing AF are examined. These are: a heterogeneity created by diffuse fibrosis, a heterogeneity created by myocytes having different refractory periods, and a new heterogeneity type, created by intermittent operation of some myocytes. The developmental stages (target waves and spirals) and the different probabilities of AF occurring under each condition, are shown. This model was established as being capable of reproducing the known AF origins and their basic development stages, and in addition has shown: (1) That diffuse fibrosis on its own is not arrhythmogenic but in combination with other arrhythmogenic agents it can either enhance or limit AF. (2) In general, combinations of heterogeneities can act synergistically, and, most importantly, (3) The new type of intermittency heterogeneity proves to be extremely arrhythmogenic. Both the intermittency risk and the fibrosis role in AF generation were established. Knowledge of the character of these arrhythmogenesis agents can be of real importance in AF treatment.

Association between leucocyte telomere length and the risk of atrial fibrillation: An updated systematic review and meta-analysis

BACKGROUND AND AIMS

Advancing age is the most important risk factor of atrial fibrillation (AF). The shortening of telomere length is a biomarker of biologic aging. There is an increasing body of evidence that leucocyte telomere length (LTL) is associated with the risk of AF development. However, the results in these studies were controversial. The current systematic review and meta-analysis was conducted to examine the role of LTL in predicting the incidence of AF.

METHODS AND RESULTS

Observational studies reporting the association between LTL and the risk of AF were retrieved through 25th June, 2022 from PubMed and Embase. A total of twelve studies including 18,293 patients were included in the present analysis. Leucocyte telomere shortening was found to be an independent predictor of AF as a continuous variable in both univariate [OR:2.14; 95%CI(1.48,3.10); P < 0.0001] and multivariate analyses [OR:1.41;95%CI(1.11,1.79); P = 0.005], as well as categorical variable in multivariate analysis [OR:1.53; 95%CI(1.04,2.27); P = 0.03]. Furthermore, leucocyte telomere shortening was significantly associated with recurrent AF [OR:4.32;95%CI(2.42,7.69); P < 0.00001] but not new-onset AF [OR:1.14; 95%CI(0.90,1.45); P = 0.29]. Leucocyte telomere shortening was also associated with an increased risk of persistent AF [OR:14.73;95%CI (3.16,68.67); P = 0.0006] and paroxysmal AF [OR:2.74;95%CI(1.45,5.18); P = 0.002]. Besides, LTL was an independent predictor for progression from paroxysmal AF to persistent AF [OR:3.2;95%CI(1.66,6.18); P = 0.0005]. Differences between males [OR:1.99; 95%CI(1.29,3.06); P = 0.002] and females [OR:0.86; 95%CI (0.29,2.56);P = 0.79] were observed.

CONCLUSIONS

Leucocyte telomere shortening predicts the risk of AF, especially recurrent AF. The predictive value is more prominent in males than in females. Shortening in LTL can predict the progression from paroxysmal to persistent AF.

A comparative study of the performance of methods for f-wave extraction

Objective.This study proposes a novel technique for atrial fibrillatory waves (f-waves) extraction and investigates the performance of the proposed method comparing with different f-wave extraction methods.Approach.We propose a novel technique combining a periodic component analysis (PiCA) and echo state network (ESN) for f-waves extraction, denoted PiCA-ESN. PiCA-ESN benefits from the advantages of using both source separation and nonlinear adaptive filtering. PiCA-ESN is evaluated by comparing with other state-of-the-art approaches, which include template subtraction technique based on principal component analysis, spatiotemporal cancellation, nonlinear adaptive filtering using an echo state neural network, and a source separation technique based on PiCA. Quality assessment is performed on a recently published reference database including a large number of simulated ECG signals in atrial fibrillation (AF). The performance of the f-wave extraction methods is evaluated in terms of signal quality metrics (SNR, ΔSNR) and robustness of f-wave features.Main results.The proposed method offers the best signal quality performance, with a ΔSNR of approximately 22 dB across all 8 sets of the reference database, as well as the most robust extraction of f-wave features, with 75% of all estimates of dominant atrial frequency well below 1 Hz.

Preoperative Prediction of Catheter Ablation Outcome in Persistent Atrial Fibrillation Patients through Spectral Organization Analysis of the Surface Fibrillatory Waves

Catheter ablation (CA) is a commonly used treatment for persistent atrial fibrillation (AF). Since its medium/long-term success rate remains limited, preoperative prediction of its outcome is gaining clinical interest to optimally select candidates for the procedure. Among predictors based on the surface electrocardiogram, the dominant frequency (DF) and harmonic exponential decay (γ) of the fibrillatory waves (f-waves) have reported promising but clinically insufficient results. Hence, the main goal of this work was to conduct a broader analysis of the f-wave harmonic spectral structure to improve CA outcome prediction through several entropy-based measures computed on different frequency bands. On a database of 151 persistent AF patients under radio-frequency CA and a follow-up of 9 months, the newly introduced parameters discriminated between patients who relapsed to AF and those who maintained SR at about 70%, which was statistically superior to the DF and approximately similar to γ. They also provided complementary information to γ through different combinations in multivariate models based on lineal discriminant analysis and report classification performance improvement of about 5%. These results suggest that the presence of larger harmonics and a proportionally smaller DF peak is associated with a decreased probability of AF recurrence after CA.

Burden of Microvascular Disease and Risk of Atrial Fibrillation in Adults with Type 2 Diabetes

BACKGROUND

Epidemiological data on the associations of microvascular disease with atrial fibrillation are scarce. We evaluated the associations of diabetes-related microvascular disease in multiple vascular beds and its burden with incident atrial fibrillation among adults with type 2 diabetes.

METHODS

A total of 7603 participants with type 2 diabetes and without atrial fibrillation were assessed for diabetic kidney disease, retinopathy, or neuropathy at baseline in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study. Incident atrial fibrillation events were adjudicated using follow-up electrocardiograms. Modified Poisson regression was used to generate risk ratios (RRs) and 95% confidence intervals (CIs) for atrial fibrillation.

RESULTS

Of the 7603 participants (mean age 62.5 years, 38.0% women, 63.4% white), 63.3% (n = 4816) had microvascular disease-defined as the presence of ≥1 of: diabetic kidney disease, retinopathy, or neuropathy at baseline. Over a median of 7 years, there were 137 atrial fibrillation events (1.8%). Participants with microvascular disease had a 1.9-fold higher risk of incident atrial fibrillation compared with those without microvascular disease (RR 1.88; 95% CI, 1.20-2.95). Compared with no microvascular disease, the RRs for atrial fibrillation were 1.62 (95% CI, 1.01-2.61) and 2.47 (95% CI, 1.46-4.16) for those with 1 and ≥2 microvascular territories affected, respectively. The RRs for atrial fibrillation by type of microvascular disease were 1.57 (95% CI, 1.09-2.26), 0.95 (95% CI, 0.53-1.70), and 1.67 (95% CI, 1.15-2.44) for neuropathy, retinopathy, and diabetic kidney disease, respectively.

CONCLUSIONS

In a large cohort of adults with type 2 diabetes, the presence of microvascular disease and its burden were independently associated with higher risk of incident atrial fibrillation.

MiR-21-3p Inhibits Adipose Browning by Targeting FGFR1 and Aggravates Atrial Fibrosis in Diabetes

A relationship between excess epicardial adipose tissue (EAT) and the risk of atrial fibrillation (AF) has been reported. Browning of EAT may be a novel approach for the prevention or treatment of AF by attenuating atrial fibrosis. Previous studies have identified microRNA-21 (miR-21) as a regulatory factor in atrial fibrosis. The present study examined the role of different subtypes of miR-21 in adipose browning and atrial fibrosis under hyperglycemic conditions. Wild type and miR-21 knockout C57BL/6 mice were used to establish a diabetic model via intraperitoneal injection of streptozotocin. A coculture model of atrial fibroblasts and adipocytes was also established. We identified miR-21-3p as a key regulator that controls adipocyte browning and participates in atrial fibrosis under hyperglycemic conditions. Moreover, fibroblast growth factor receptor (FGFR) 1, a direct target of miR-21-3p, decreased in this setting and controlled adipose browning. Gain and loss-of-function experiments identified a regulatory pathway in adipocytes involving miR-21a-3p, FGFR1, FGF21, and PPARγ that regulated adipocyte browning and participated in hyperglycemia-induced atrial fibrosis. Modulation of this signaling pathway may provide a therapeutic option for the prevention and treatment of atrial fibrosis or AF in DM.

Paradigm shifts in electrophysiological mechanisms of atrial fibrillation

Determining the sequence of activation is a major source of information for understanding the electrophysiological mechanism(s) of atrial fibrillation (AF). However, the complex morphology of the electrograms hampers their analysis, and has stimulated generations of electrophysiologists to develop a large variety of technologies for recording, pre-processing, and analysis of fibrillation electrograms. This variability of approaches is mirrored by a large variability in the interpretation of fibrillation electrograms and, thereby, opinions regarding the basic electrophysiological mechanism(s) of AF vary widely. Multiple wavelets, different types of re-entry including rotors, double layers, multiple focal activation patterns all have been advocated, and a comprehensive and commonly accepted paradigm for the fundamental mechanisms of AF is still lacking. Here, we summarize the Maastricht perspective and Cleveland perspective regarding AF mechanism(s). We also describe some of the key observations in mapping of AF reported over the past decades, and how they changed over the years, often as results of new techniques introduced in the experimental field of AF research.

Non-Invasive and Quantitative Estimation of Left Atrial Fibrosis Based on P Waves of the 12-Lead ECG-A Large-Scale Computational Study Covering Anatomical Variability

The arrhythmogenesis of atrial fibrillation is associated with the presence of fibrotic atrial tissue. Not only fibrosis but also physiological anatomical variability of the atria and the thorax reflect in altered morphology of the P wave in the 12-lead electrocardiogram (ECG). Distinguishing between the effects on the P wave induced by local atrial substrate changes and those caused by healthy anatomical variations is important to gauge the potential of the 12-lead ECG as a non-invasive and cost-effective tool for the early detection of fibrotic atrial cardiomyopathy to stratify atrial fibrillation propensity. In this work, we realized 54,000 combinations of different atria and thorax geometries from statistical shape models capturing anatomical variability in the general population. For each atrial model, 10 different volume fractions (0-45%) were defined as fibrotic. Electrophysiological simulations in sinus rhythm were conducted for each model combination and the respective 12-lead ECGs were computed. P wave features (duration, amplitude, dispersion, terminal force in V1) were extracted and compared between the healthy and the diseased model cohorts. All investigated feature values systematically in- or decreased with the left atrial volume fraction covered by fibrotic tissue, however value ranges overlapped between the healthy and the diseased cohort. Using all extracted P wave features as input values, the amount of the fibrotic left atrial volume fraction was estimated by a neural network with an absolute root mean square error of 8.78%. Our simulation results suggest that although all investigated P wave features highly vary for different anatomical properties, the combination of these features can contribute to non-invasively estimate the volume fraction of atrial fibrosis using ECG-based machine learning approaches.

Transcriptome analysis reveals key pathways that vary in patients with paroxysmal and persistent atrial fibrillation

The present study evaluated mRNA and long non-coding RNA (lncRNA) expression profiles and the pathways involved in paroxysmal atrial fibrillation (ParoAF) and persistent atrial fibrillation (PersAF). Nine left atrial appendage (LAA) tissues collected from the hearts of patients with AF (patients with ParoAF=3; and patients with PersAF=3) and healthy donors (n=3) were analyzed by RNA sequencing. Differentially expressed (DE) mRNAs and lncRNAs were identified by |Log₂ fold change|>2 and P<0.05. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes pathway enrichment, protein-protein interaction network and mRNA-lncRNA interaction network analyses of DE mRNA and mRNA at the upstream/downstream of DE lncRNA were conducted. A total of 285 and 275 DE mRNAs, 575 and 583 DE lncRNAs were detected in ParoAF and PersAF samples compared with controls, respectively. PI3K/Akt and transforming growth factor-β signaling pathways were significantly enriched in the ParoAF_Control and the calcium signaling pathway was significantly enriched in the PersAF_Control. Cis and trans analyses revealed some important interactions in DE mRNAs and lncRNA, including an interaction of GPC-AS2 with dopachrome tautomerase, and phosphodiesterase 4D and cAMP-specific with XLOC_110310 and XLOC_137634. Overall, the present study provides a molecular basis for future clinical studies on ParoAF and PersAF.

Anti-arrhythmic investigations in large animal models of atrial fibrillation

Atrial fibrillation (AF) constitutes an increasing health problem in the aging population. Animal models reflecting human phenotypes are needed to understand the mechanisms of AF, as well as to test new pharmacological interventions. In recent years, a number of large animal models, primarily pigs, goats, dog and horses have been used in AF research. These animals can to a certain extent recapitulate the human pathophysiological characteristics and serve as valuable tools in investigating new pharmacological interventions for treating AF. This review focuses on anti-arrhythmic investigations in large animals. Initially, spontaneous AF in small and large mammals is discussed. This is followed by a short presentation of frequently used methods for inducing short- and long-term AF. The major focus of the review is on anti-arrhythmic compounds either frequently used in the human clinic (ranolazine, flecainide, vernakalant and amiodarone) or being promising new AF medicine candidates (I_K,Ach , I_SK,Ca and I_K2P blockers).

Cardiac transmembrane ion channels and action potentials: cellular physiology and arrhythmogenic behavior

Cardiac arrhythmias are among the leading causes of mortality. They often arise from alterations in the electrophysiological properties of cardiac cells and their underlying ionic mechanisms. It is therefore critical to further unravel the pathophysiology of the ionic basis of human cardiac electrophysiology in health and disease. In the first part of this review, current knowledge on the differences in ion channel expression and properties of the ionic processes that determine the morphology and properties of cardiac action potentials and calcium dynamics from cardiomyocytes in different regions of the heart are described. Then the cellular mechanisms promoting arrhythmias in congenital or acquired conditions of ion channel function (electrical remodeling) are discussed. The focus is on human-relevant findings obtained with clinical, experimental, and computational studies, given that interspecies differences make the extrapolation from animal experiments to human clinical settings difficult. Deepening the understanding of the diverse pathophysiology of human cellular electrophysiology will help in developing novel and effective antiarrhythmic strategies for specific subpopulations and disease conditions.

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.

Understanding the transition from paroxysmal to persistent atrial fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhytmia, characterized by the chaotic motion of electrical wavefronts in the atria. In clinical practice, AF is classified under two primary categories: paroxysmal AF, short intermittent episodes separated by periods of normal electrical activity; and persistent AF, longer uninterrupted episodes of chaotic electrical activity. However, the precise reasons why AF in a given patient is paroxysmal or persistent is poorly understood. Recently, we have introduced the percolation-based Christensen-Manani-Peters (CMP) model of AF which naturally exhibits both paroxysmal and persistent AF, but precisely how these differences emerge in the model is unclear. In this paper, we dissect the CMP model to identify the cause of these different AF classifications. Starting from a mean-field model where we describe AF as a simple birth-death process, we add layers of complexity to the model and show that persistent AF arises from reentrant circuits which exhibit an asymmetry in their probability of activation relative to deactivation. As a result, different simulations generated at identical model parameters can exhibit fibrillatory episodes spanning several orders of magnitude from a few seconds to months. These findings demonstrate that diverse, complex fibrillatory dynamics can emerge from very simple dynamics in models of AF.

The management of atrial fibrillation in heart failure: an expert panel consensus

Heart failure (HF) and atrial fibrillation (AF) often coexist, being closely interrelated as the one increases the prevalence and incidence and worsens the prognosis of the other. Their frequent coexistence raises several challenges, including under-diagnosis of HF with preserved ejection fraction in AF and of AF in HF, characterization and diagnosis of atrial cardiomyopathy, target and impact of rate control therapy on outcomes, optimal rhythm control strategy in the era of catheter ablation, HF-related thromboembolic risk and management of anticoagulation in patients with comorbidities, such as chronic kidney disease or transient renal function worsening, coronary artery disease or acute coronary syndromes, valvular or structural heart disease interventions and cancer. In the present document, derived by an expert panel meeting, we sought to focus on the above challenging issues, outlining the existing evidence and identifying gaps in knowledge that need to be addressed.

Cardiomyocyte calcium handling in health and disease: Insights from in vitro and in silico studies

Calcium (Ca²⁺) plays a central role in cardiomyocyte excitation-contraction coupling. To ensure an optimal electrical impulse propagation and cardiac contraction, Ca²⁺ levels are regulated by a variety of Ca²⁺-handling proteins. In turn, Ca²⁺ modulates numerous electrophysiological processes. Accordingly, Ca²⁺-handling abnormalities can promote cardiac arrhythmias via various mechanisms, including the promotion of afterdepolarizations, ion-channel modulation and structural remodeling. In the last 30 years, significant improvements have been made in the computational modeling of cardiomyocyte Ca²⁺ handling under physiological and pathological conditions. However, numerous questions involving the Ca²⁺-dependent regulation of different macromolecular complexes, cross-talk between Ca²⁺-dependent regulatory pathways operating over a wide range of time scales, and bidirectional interactions between electrophysiology and mechanics remain to be addressed by in vitro and in silico studies. A better understanding of disease-specific Ca²⁺-dependent proarrhythmic mechanisms may facilitate the development of improved therapeutic strategies. In this review, we describe the fundamental mechanisms of cardiomyocyte Ca²⁺ handling in health and disease, and provide an overview of currently available computational models for cardiomyocyte Ca²⁺ handling. Finally, we discuss important uncertainties and open questions about cardiomyocyte Ca²⁺ handling and highlight how synergy between in vitro and in silico studies may help to answer several of these issues.

Calcium Handling Defects and Cardiac Arrhythmia Syndromes

Calcium ions (Ca²⁺) play a major role in the cardiac excitation-contraction coupling. Intracellular Ca²⁺ concentration increases during systole and falls in diastole thereby determining cardiac contraction and relaxation. Normal cardiac function also requires perfect organization of the ion currents at the cellular level to drive action potentials and to maintain action potential propagation and electrical homogeneity at the tissue level. Any imbalance in Ca²⁺ homeostasis of a cardiac myocyte can lead to electrical disturbances. This review aims to discuss cardiac physiology and pathophysiology from the elementary membrane processes that can cause the electrical instability of the ventricular myocytes through intracellular Ca²⁺ handling maladies to inherited and acquired arrhythmias. Finally, the paper will discuss the current therapeutic approaches targeting cardiac arrhythmias.

Short-Time Estimation of Fractionation in Atrial Fibrillation with Coarse-Grained Correlation Dimension for Mapping the Atrial Substrate

Atrial fibrillation (AF) is currently the most common cardiac arrhythmia, with catheter ablation (CA) of the pulmonary veins (PV) being its first line therapy. Ablation of complex fractionated atrial electrograms (CFAEs) outside the PVs has demonstrated improved long-term results, but their identification requires a reliable electrogram (EGM) fractionation estimator. This study proposes a technique aimed to assist CA procedures under real-time settings. The method has been tested on three groups of recordings: Group 1 consisted of 24 highly representative EGMs, eight of each belonging to a different AF Type. Group 2 contained the entire dataset of 119 EGMs, whereas Group 3 contained 20 pseudo-real EGMs of the special Type IV AF. Coarse-grained correlation dimension (CGCD) was computed at epochs of 1 s duration, obtaining a classification accuracy of 100% in Group 1 and 84.0–85.7% in Group 2, using 10-fold cross-validation. The receiver operating characteristics (ROC) analysis for highly fractionated EGMs, showed 100% specificity and sensitivity in Group 1 and 87.5% specificity and 93.6% sensitivity in Group 2. In addition, 100% of the pseudo-real EGMs were correctly identified as Type IV AF. This method can consistently express the fractionation level of AF EGMs and provides better performance than previous works. Its ability to compute fractionation in short-time can agilely detect sudden changes of AF Types and could be used for mapping the atrial substrate, thus assisting CA procedures under real-time settings for atrial substrate modification.

Unified mechanism of local drivers in a percolation model of atrial fibrillation

The mechanisms of atrial fibrillation (AF) are poorly understood, resulting in disappointing success rates of ablative treatment. Different mechanisms defined largely by different atrial activation patterns have been proposed and, arguably, this dispute has slowed the progress of AF research. Recent clinical evidence suggests a unifying mechanism of local drivers based on sustained reentrant circuits in the complex atrial architecture. Here, we present a percolation inspired computational model showing spontaneous emergence of AF that strongly supports, and gives a theoretical explanation for, the clinically observed diversity of activation. We show that the difference in surface activation patterns is a direct consequence of the thickness of the discrete network of heart muscle cells through which electrical signals percolate to reach the imaged surface. The model naturally follows the clinical spectrum of AF spanning sinus rhythm, paroxysmal AF, and persistent AF as the decoupling of myocardial cells results in the lattice approaching the percolation threshold. This allows the model to make the prediction that, for paroxysmal AF, reentrant circuits emerge near the endocardium, but in persistent AF they emerge deeper in the bulk of the atrial wall. If experimentally verified, this may go towards explaining the lowering ablation success rate as AF becomes more persistent.

Atrial Fibrillation in Long QT Syndrome by Genotype

BACKGROUND

Long QT syndrome (LQTS) is caused by the abnormal function of ion channels, which may also affect atrial electrophysiology and be associated with the risk of atrial fibrillation (AF). However, large-scale studies of AF risk among patients with LQTS and its relation to LQTS manifestations are lacking. We aimed to assess the risk of AF and its relationship to the LQTS genotype and the long-term prognosis in patients with LQTS.

METHODS

Genotype-positive patients with LQTS (784 LQT1, 746 LQT2, and 233 LQT3) were compared with 2043 genotype-negative family members. Information on the occurrence of AF was based on physician-reported ECG-verified events. Multivariate Cox proportional hazards regression analyses were performed for ages 0 to 60 and after 60 years (reflecting an early and late-onset of AF) to assess the risk of incident AF by genotype and the relationship of AF to the risk of cardiac events defined as syncope, documented torsades de pointes, and aborted cardiac arrest or sudden cardiac death.

RESULTS

In patients followed from birth to 60 years of age, patients with LQT3 had an increased risk of AF compared with genotype-negative family members (hazard ratio=6.62; 95% CI, 2.04-21.49; P<0.001), while neither LQT1 nor LQT2 demonstrated increased AF risk. After the age of 60 years, patients with LQT2 had significantly lower risk of AF compared with genotype-negative controls (hazard ratio=0.07; 95% CI, 0.01-0.53, P=0.011). AF was a significant predictor of cardiac events in patients with LQT3 through the age of 60 (hazard ratio=5.38; 95% CI, 1.17-24.82; P=0.031).

CONCLUSIONS

Our data demonstrate an increased risk of early age AF in patients with LQT3 and also indicate a protective effect of the LQT2 genotype in it's association with a decreased risk of AF after the age of 60.

Rotors Detected by Phase Analysis of Filtered, Epicardial Atrial Fibrillation Electrograms Colocalize With Regions of Conduction Block

BACKGROUND

Several recent studies suggest rotors detected by phase mapping may act as main drivers of persistent atrial fibrillation. However, the electrophysiological nature of detected rotors remains unclear. We performed a direct, 1:1 comparison between phase and activation time mapping in high-density, epicardial, direct-contact mapping files of human atrial fibrillation.

METHODS

Thirty-eight unipolar electrogram files of 10 s duration were recorded in patients with atrial fibrillation (n=20 patients) using a 16×16 electrode array placed on the epicardial surface of the left atrial posterior wall or the right atrial free wall. Phase maps and isochrone wave maps were constructed for all recordings. For each detected phase singularity (PS) with a lifespan of >1 cycle length, the corresponding conduction pattern was investigated in the isochrone wave maps.

RESULTS

When using sinusoidal recomposition and Hilbert Transform, 138 PSs were detected. One hundred and four out of 138 PSs were detected within 1 electrode distance (1.5 mm) from a line of conduction block between nonrotating wavefronts detected by activation mapping. Far fewer rotating wavefronts were detected when rotating activity was identified based on wave mapping (18 out of 8219 detected waves). Fourteen out of these 18 cases were detected as PSs in phase mapping. Phase analysis of filtered electrograms produced by simulated wavefronts separated by conduction block also identified PSs on the line of conduction block.

CONCLUSIONS

PSs identified by phase analysis of filtered epicardial electrograms colocalize with conduction block lines identified by activation mapping. Detection of PSs using phase analysis has a low specificity for identifying rotating wavefronts during human atrial fibrillation using activation mapping.

Reference database and performance evaluation of methods for extraction of atrial fibrillatory waves in the ECG

OBJECTIVE

This study proposes a reference database, composed of a large number of simulated ECG signals in atrial fibrillation (AF), for investigating the performance of methods for extraction of atrial fibrillatory waves (f-waves).

APPROACH

The simulated signals are produced using a recently published and validated model of 12-lead ECGs in AF. The database is composed of eight signal sets together accounting for a wide range of characteristics known to represent major challenges in f-wave extraction, including high heart rates, high morphological QRST variability, and the presence of ventricular premature beats. Each set contains 30 5 min signals with different f-wave amplitudes. The database is used for the purpose of investigating the statistical association between different indices, designed for use with either real or simulated signals.

MAIN RESULTS

Using the database, available at the PhysioNet repository of physiological signals, the performance indices unnormalized ventricular residue (uVR), designed for real signals, and the root mean square error, designed for simulated signals, were found to exhibit the strongest association, leading to the recommendation that uVR should be used when characterizing performance in real signals.

SIGNIFICANCE

The proposed database facilitates comparison of the performance of different f-wave extraction methods and makes it possible to express performance in terms of the error between simulated and extracted f-wave signals.

Relationship between Atrial Tissue Remodeling and ECG Features in Atrial Fibrillation

The difference in the atrial organizational structure between patients with atrial fibrillation (AF) and those with sinus rhythm was investigated. In order to analyze the rationality in explaining the electrocardiogram (ECG) characteristics of AF with statistics data or tissue remodeling model, and the logical relationship between the hypothesis of pulmonary veins (PV) muscle sleeves and that of multi wavelets in mechanism of AF, we examined the expression of collagen volume fraction of type I (CVF-I) with picrosirius red staining, connexin 40 (Cx40) by immunohistochemistry, and intercalated disc (ID) using transmission electron microscope in atrial tissue. The results showed that there was significant difference in the expression of CVF-I (t=3.827, P<0.01), Cx40 (t=4.21, P<0.01), and groups of the ID that keeping the electrical transmission and atrial electrical coupling synchronization (t=15.116, P<0.001), but no significant difference was found in total IDs (t=0.611, P=0.543) between patients with AF and those with sinus rhythm. The quantitative differences in the tissue remodeling could not explain the ECG characteristics of AF. The number of normal IDs and abnormal distribution are the structural basis to trigger and maintain atrial electrical remodeling, and induce and maintain AF. Such histological reconstruction supports the hypothesis of multi wavelets and can also explain ECG features.

The stationary wavelet transform as an efficient reductor of powerline interference for atrial bipolar electrograms in cardiac electrophysiology

OBJECTIVE

The most relevant source of signal contamination in the cardiac electrophysiology (EP) laboratory is the ubiquitous powerline interference (PLI). To reduce this perturbation, algorithms including common fixed-bandwidth and adaptive-notch filters have been proposed. Although such methods have proven to add artificial fractionation to intra-atrial electrograms (EGMs), they are still frequently used. However, such morphological alteration can conceal the accurate interpretation of EGMs, specially to evaluate the mechanisms supporting atrial fibrillation (AF), which is the most common cardiac arrhythmia. Given the clinical relevance of AF, a novel algorithm aimed at reducing PLI on highly contaminated bipolar EGMs and, simultaneously, preserving their morphology is proposed.

APPROACH

The method is based on the wavelet shrinkage and has been validated through customized indices on a set of synthesized EGMs to accurately quantify the achieved level of PLI reduction and signal morphology alteration. Visual validation of the algorithm's performance has also been included for some real EGM excerpts.

MAIN RESULTS

The method has outperformed common filtering-based and wavelet-based strategies in the analyzed scenario. Moreover, it possesses advantages such as insensitivity to amplitude and frequency variations in the PLI, and the capability of joint removal of several interferences.

SIGNIFICANCE

The use of this algorithm in routine cardiac EP studies may enable improved and truthful evaluation of AF mechanisms.

Biomarkers Associated with Atrial Fibrosis and Remodeling

Atrial fibrillation is the most common rhythm disturbance encountered in clinical practice. Although often considered as solely arrhythmic in nature, current evidence has established that atrial myopathy constitutes both the substrate and the outcome of atrial fibrillation, thus initiating a vicious, self-perpetuating cycle. This myopathy is triggered by stress-induced (including pressure/volume overload, inflammation, oxidative stress) responses of atrial tissue, which in the long term become maladaptive, and combine elements of both structural, especially fibrosis, and electrical remodeling, with contemporary approaches yielding potentially useful biomarkers of these processes. Biomarker value becomes greater given the fact that they can both predict atrial fibrillation occurrence and treatment outcome. This mini-review will focus on the biomarkers of atrial remodeling (both electrical and structural) and fibrosis that have been validated in human studies, including biochemical, histological and imaging approaches.

Modeling cardiac complexity: Advancements in myocardial models and analytical techniques for physiological investigation and therapeutic development in vitro

Cardiomyopathies, heart failure, and arrhythmias or conduction blockages impact millions of patients worldwide and are associated with marked increases in sudden cardiac death, decline in the quality of life, and the induction of secondary pathologies. These pathologies stem from dysfunction in the contractile or conductive properties of the cardiomyocyte, which as a result is a focus of fundamental investigation, drug discovery and therapeutic development, and tissue engineering. All of these foci require in vitro myocardial models and experimental techniques to probe the physiological functions of the cardiomyocyte. In this review, we provide a detailed exploration of different cell models, disease modeling strategies, and tissue constructs used from basic to translational research. Furthermore, we highlight recent advancements in imaging, electrophysiology, metabolic measurements, and mechanical and contractile characterization modalities that are advancing our understanding of cardiomyocyte physiology. With this review, we aim to both provide a biological framework for engineers contributing to the field and demonstrate the technical basis and limitations underlying physiological measurement modalities for biologists attempting to take advantage of these state-of-the-art techniques.

The Association Between Diabetes Mellitus and Atrial Fibrillation: Clinical and Mechanistic Insights

A number of clinical studies have reported that diabetes mellitus (DM) is an independent risk factor for Atrial fibrillation (AF). After adjustment for other known risk factors including age, sex, and cardiovascular risk factors, DM remains a significant if modest risk factor for development of AF. The mechanisms underlying the increased susceptibility to AF in DM are incompletely understood, but are thought to involve electrical, structural, and autonomic remodeling in the atria. Electrical remodeling in DM may involve alterations in gap junction function that affect atrial conduction velocity due to changes in expression or localization of connexins. Electrical remodeling can also occur due to changes in atrial action potential morphology in association with changes in ionic currents, such as sodium or potassium currents, that can affect conduction velocity or susceptibility to triggered activity. Structural remodeling in DM results in atrial fibrosis, which can alter conduction patterns and susceptibility to re-entry in the atria. In addition, increases in atrial adipose tissue, especially in Type II DM, can lead to disruptions in atrial conduction velocity or conduction patterns that may affect arrhythmogenesis. Whether the insulin resistance in type II DM activates unique intracellular signaling pathways independent of obesity requires further investigation. In addition, the relationship between incident AF and glycemic control requires further study.

Sex differences in stroke: Challenges and opportunities

Biologic sex influences many variables that are important to brain health in general, and to stroke or cerebral ischemia in particular, such as general health status, cerebrovascular anatomy and function, unique risk factors such as pregnancy and preeclampsia, symptomatology, and therapeutic response. A more complete understanding of the scale and depth of sexual dimorphism in the brain and the role of more general sex-based factors is crucial to reducing the burden of stroke in women and men. This focused review highlights recent findings in stroke, including sex differences in epidemiology, risk factor reduction, comparative use of stroke therapeutics in both sexes, the importance of frailty in women, and the biologic basis for sex differences in stroke. Such findings show tremendous promise for the future of personalized medicine in stroke prevention and treatment.

A novel wavelet-based filtering strategy to remove powerline interference from electrocardiograms with atrial fibrillation

OBJECTIVE

The electrocardiogram (ECG) is currently the most widely used recording to diagnose cardiac disorders, including the most common supraventricular arrhythmia, such as atrial fibrillation (AF). However, different types of electrical disturbances, in which power-line interference (PLI) is a major problem, can mask and distort the original ECG morphology. This is a significant issue in the context of AF, because accurate characterization of fibrillatory waves (f-waves) is unavoidably required to improve current knowledge about its mechanisms. This work introduces a new algorithm able to reduce high levels of PLI and preserve, simultaneously, the original ECG morphology.

APPROACH

The method is based on stationary wavelet transform shrinking and makes use of a new thresholding function designed to work successfully in a wide variety of scenarios. In fact, it has been validated in a general context with 48 ECG recordings obtained from pathological and non-pathological conditions, as well as in the particular context of AF, where 380 synthesized and 20 long-term real ECG recordings were analyzed.

MAIN RESULTS

In both situations, the algorithm has reported a notably better performance than common methods designed for the same purpose. Moreover, its effectiveness has proven to be optimal for dealing with ECG recordings affected by AF, since f-waves remained almost intact after removing very high levels of noise.

SIGNIFICANCE

The proposed algorithm may facilitate a reliable characterization of the f-waves, preventing them from not being masked by the PLI nor distorted by an unsuitable filtering applied to ECG recordings with AF.

A Computational Framework to Benchmark Basket Catheter Guided Ablation in Atrial Fibrillation

Catheter ablation is a curative therapeutic approach for atrial fibrillation (AF). Ablation of rotational sources based on basket catheter measurements has been proposed as a promising approach in patients with persistent AF to complement pulmonary vein isolation. However, clinically reported success rates are equivocal calling for a mechanistic investigation under controlled conditions. We present a computational framework to benchmark ablation strategies considering the whole cycle from excitation propagation to electrogram acquisition and processing to virtual therapy. Fibrillation was induced in a patient-specific 3D volumetric model of the left atrium, which was homogeneously remodeled to sustain reentry. The resulting extracellular potential field was sampled using models of grid catheters as well as realistically deformed basket catheters considering the specific atrial anatomy. The virtual electrograms were processed to compute phase singularity density maps to target rotor tips with up to three circular ablations. Stable rotors were successfully induced in different regions of the homogeneously remodeled atrium showing that rotors are not constrained to unique anatomical structures or locations. Density maps of rotor tip trajectories correctly identified and located the rotors (deviation < 10 mm) based on catheter recordings only for sufficient resolution (inter-electrode distance ≤3 mm) and proximity to the wall (≤10 mm). Targeting rotor sites with ablation did not stop reentries in the homogeneously remodeled atria independent from lesion size (1-7 mm radius), from linearly connecting lesions with anatomical obstacles, and from the number of rotors targeted sequentially (≤3). Our results show that phase maps derived from intracardiac electrograms can be a powerful tool to map atrial activation patterns, yet they can also be misleading due to inaccurate localization of the rotor tip depending on electrode resolution and distance to the wall. This should be considered to avoid ablating regions that are in fact free of rotor sources of AF. In our experience, ablation of rotor sites was not successful to stop fibrillation. Our comprehensive simulation framework provides the means to holistically benchmark ablation strategies in silico under consideration of all steps involved in electrogram-based therapy and, in future, could be used to study more heterogeneously remodeled disease states as well.

Mapping of atrial fibrillation: strategies to understand an enigmatic arrhythmia

The three-dimensional (3D) mapping of cardiac arrhythmias has evolved in recent years to an important and extremely useful tool, providing important insights into arrhythmia mechanisms and thus improving ablation success rates, especially in complex arrhythmias. In atrial fibrillation (AF), the most common but also one of the most complex cardiac arrhythmias, progress in mapping technology has been focusing on several aspects according to the type of AF.In paroxysmal AF, important progress in the exact anatomic reconstruction of the main ablation target, i.e., the pulmonary veins (PV), has been achieved. Perhaps even more importantly, new insights into conduction patterns, such as deceleration at the PV ostia, spiral conduction more distally into the PV, and PV cross-talk have been detected and enable faster and more sustainable PV isolation.In persistent AF, the basic understanding of ongoing AF is perhaps the electrophysiological challenge of the 21st century. Since AF is instable in its course, mapping tools that assess statistically returning patterns or deal with so-called AF "rotors" or "drivers" have been developed, offering unique insights into possible AF mechanisms. Refined high-density bi-atrial voltage maps make it possible to further characterize the arrhythmogenic substrate and scar zones, while new and innovative mapping algorithms enable automated, fast, and reliable annotation of up to thousands of electrograms.This improved understanding of AF mechanisms has led to the development of promising new ablation strategies, some of which are already in use in clinical routine.

Oxidative stress and atrial fibrillation: an update

Atrial remodelling involves electrophysiological and structural abnormalities that promote the development and perpetuation of atrial fibrillation. Experimental and clinical data indicate that oxidative stress is implicated in the pathophysiology of atrial remodelling. The mechanistic links between atrial remodelling and oxidative stress are complex with several underlying diseases and conditions may affect these pathways. Therefore, the development of antioxidant interventions in this setting remains difficult. Besides classical antioxidant compounds, several agents with pleiotropic effects, including anti-inflammatory and antioxidant, have been tested in experimental and clinical settings with variable results. Strategies applying conventional antioxidants in specific situations such as postoperative atrial fibrillation show beneficial effects, especially the two-step regimen of antioxidants combination. Of note, there are limited data on the development of strategies that target specific sources of reactive oxygen species implicated in atrial remodelling. Lifestyle, diet, and risk factors modification is a complementary promising approach. This updated review provides a concise and critical overview of all available data regarding oxidative stress and its modulation in atrial fibrillation. Future directions on this exciting field are also discussed.

Computational Modeling of Electrophysiology and Pharmacotherapy of Atrial Fibrillation: Recent Advances and Future Challenges

The pathophysiology of atrial fibrillation (AF) is broad, with components related to the unique and diverse cellular electrophysiology of atrial myocytes, structural complexity, and heterogeneity of atrial tissue, and pronounced disease-associated remodeling of both cells and tissue. A major challenge for rational design of AF therapy, particularly pharmacotherapy, is integrating these multiscale characteristics to identify approaches that are both efficacious and independent of ventricular contraindications. Computational modeling has long been touted as a basis for achieving such integration in a rapid, economical, and scalable manner. However, computational pipelines for AF-specific drug screening are in their infancy, and while the field is progressing quite rapidly, major challenges remain before computational approaches can fill the role of workhorse in rational design of AF pharmacotherapies. In this review, we briefly detail the unique aspects of AF pathophysiology that determine requirements for compounds targeting AF rhythm control, with emphasis on delimiting mechanisms that promote AF triggers from those providing substrate or supporting reentry. We then describe modeling approaches that have been used to assess the outcomes of drugs acting on established AF targets, as well as on novel promising targets including the ultra-rapidly activating delayed rectifier potassium current, the acetylcholine-activated potassium current and the small conductance calcium-activated potassium channel. Finally, we describe how heterogeneity and variability are being incorporated into AF-specific models, and how these approaches are yielding novel insights into the basic physiology of disease, as well as aiding identification of the important molecular players in the complex AF etiology.

MicroRNAs in Atrial Fibrillation: from Expression Signatures to Functional Implications

Atrial fibrillation (AF) is the most common sustained arrhythmia and is associated with pronounced morbidity and mortality. Its prevalence, expected to further increase for the forthcoming years, and associated frequent hospitalizations turn AF into a major health problem. Structural and electrical atrial remodelling underlie the substrate for AF, but the exact mechanisms driving this remodelling remain incompletely understood. Recent studies have shown that microRNAs (miRNA), short non-coding RNAs that regulate gene expression, may be involved in the pathophysiology of AF. MiRNAs have been implicated in AF-induced ion channel remodelling and fibrosis. MiRNAs could therefore provide insight into AF pathophysiology or become novel targets for therapy with miRNA mimics or anti-miRNAs. Moreover, circulating miRNAs have been suggested as a new class of diagnostic and prognostic biomarkers of AF. However, the origin and function of miRNAs in tissue and plasma frequently remain unknown and studies investigating the role of miRNAs in AF vary in design and focus and even present contradicting results. Here, we provide a systematic review of the available clinical and functional studies investigating the tissue and plasma miRNAs in AF and will thereafter discuss the potential of miRNAs as biomarkers or novel therapeutic targets in AF.

Statins and new-onset atrial fibrillation in a cohort of patients with hypertension. Analysis of electronic health records, 2006-2015

Hypertension is the most prevalent risk factor for new-onset atrial fibrillation (AF). But few studies have addressed the effect of statins on the incidence of this arrhythmia in patients with hypertension. This study aimed to evaluate the effect of statins on new-onset of this arrhythmia in a hypertensive population, accounting for AF risk. Data from the Information System for the Development of Research in Primary Care was used to recruit a retrospective cohort of ≥55-year-old hypertensive individuals with no ischemic vascular disease, in 2006-2007, followed up through 2015. The effect of initiating statin treatment on new-onset atrial fibrillation was assessed with Cox proportional hazards models adjusted by the propensity score of receiving statin treatment, in the overall study population and stratified by AF risk. Of 100 276 included participants, 9814 initiated statin treatment. The AF incidence per 1000 person-years (95% confidence interval) was 12.5 (12.3-12.8). Statin use associated with a significant (9%) reduction in AF incidence. Differences in absolute AF incidence were higher in the highest AF risk subgroup, and the estimated number needed to treat to avoid one case was 720. The relative effect was poor, similar across groups, and non-significant, as was the association of statins with adverse effects. We found a limited protective effect of statins over new-onset AF in this hypertensive population with no ischemic vascular disease. If there is no further indication, hypertensive patients would not benefit from statin use solely for AF primary prevention.

Waveform Integrity in Atrial Fibrillation: The Forgotten Issue of Cardiac Electrophysiology

Atrial fibrillation (AF) is the most common arrhythmia in clinical practice with an increasing prevalence of about 15% in the elderly. Despite other alternatives, catheter ablation is currently considered as the first-line therapy for the treatment of AF. This strategy relies on cardiac electrophysiology systems, which use intracardiac electrograms (EGM) as the basis to determine the cardiac structures contributing to sustain the arrhythmia. However, the noise-free acquisition of these recordings is impossible and they are often contaminated by different perturbations. Although suppression of nuisance signals without affecting the original EGM pattern is essential for any other later analysis, not much attention has been paid to this issue, being frequently considered as trivial. The present work introduces the first thorough study on the significant fallout that regular filtering, aimed at reducing acquisition noise, provokes on EGM pattern morphology. This approach has been compared with more refined denoising strategies. Performance has been assessed both in time and frequency by well established parameters for EGM characterization. The study comprised synthesized and real EGMs with unipolar and bipolar recordings. Results reported that regular filtering altered substantially atrial waveform morphology and was unable to remove moderate amounts of noise, thus turning time and spectral characterization of the EGM notably inaccurate. Methods based on Wavelet transform provided the highest ability to preserve EGM morphology with improvements between 20 and beyond 40%, to minimize dominant atrial frequency estimation error with up to 25% reduction, as well as to reduce huge levels of noise with up to 10 dB better reduction. Consequently, these algorithms are recommended as a replacement of regular filtering to avoid significant alterations in the EGMs. This could lead to more accurate and truthful analyses of atrial activity dynamics aimed at understanding and locating the sources of AF.

Calcium-mediated cellular triggered activity in atrial fibrillation

Although atrial fibrillation (AF) is the most commonly encountered cardiac arrhythmia, the basic mechanisms underlying this disorder remain incompletely understood. During the past decade or so, it has become clear that alterations in intracellular Ca²⁺ handling may play a role in the pathogenesis of AF. Studies in small and large animal models, as well as atrial samples from patients with different forms of AF, have implicated ryanodine receptor type 2 (RyR2) dysfunction and enhanced spontaneous Ca²⁺ release events from the sarcoplasmic reticulum (SR) as a potential cause of proarrhythmic cellular ectopic (triggered) activity in AF. The molecular mechanisms leading to RyR2 dysfunction and SR Ca²⁺ leak depend on the clinical stage of AF or specific animal model studied. This review focuses on the mechanisms and role of calcium-mediated cellular triggered activity in AF, and addresses some of the current controversies in the field.

[Remodeling of the aging heart : Sinus node dysfunction and atrial fibrillation]

The incidence of both sinus node dysfunction (SND) and atrial fibrillation (AF) increases with age. SND and AF frequently coexist. Likewise, they are often associated with cardiovascular diseases. Both arrhythmias share similar pathomechanisms such as structural and functional remodeling, i. e., degenerative fibrosis and altered Ca²⁺ handling, respectively. A growing body of evidence suggests an important role for the CamKII (Ca²⁺/calmodulin-dependent protein kinase II) in structural as well as in functional remodeling. In the sinus node, remodeling leads to degenerative fibrosis and as a consequence to sinus node arrest or to reentry (brady/tachycardia). In the atrium, remodeling sets the conditions for reentry and its triggering mechanisms, especially the conditions for triggered activity on the basis of delayed afterdepolarizations (DAD). Thus, SND and AF seem to be different phenotypes of related pathophysiological mechanisms. On the other hand, it remains controversial as to whether SND causes AF or vice versa.

Serine/Threonine Phosphatases in Atrial Fibrillation

Serine/threonine protein phosphatases control dephosphorylation of numerous cardiac proteins, including a variety of ion channels and calcium-handling proteins, thereby providing precise post-translational regulation of cardiac electrophysiology and function. Accordingly, dysfunction of this regulation can contribute to the initiation, maintenance and progression of cardiac arrhythmias. Atrial fibrillation (AF) is the most common heart rhythm disorder and is characterized by electrical, autonomic, calcium-handling, contractile, and structural remodeling, which include, among other things, changes in the phosphorylation status of a wide range of proteins. Here, we review AF-associated alterations in the phosphorylation of atrial ion channels, calcium-handling and contractile proteins, and their role in AF-pathophysiology. We highlight the mechanisms controlling the phosphorylation of these proteins and focus on the role of altered dephosphorylation via local type-1, type-2A and type-2B phosphatases (PP1, PP2A, and PP2B, also known as calcineurin, respectively). Finally, we discuss the challenges for phosphatase research, potential therapeutic significance of altered phosphatase-mediated protein dephosphorylation in AF, as well as future directions.

Potassium currents in the heart: functional roles in repolarization, arrhythmia and therapeutics

This is the second of the two White Papers from the fourth UC Davis Cardiovascular Symposium Systems Approach to Understanding Cardiac Excitation-Contraction Coupling and Arrhythmias (3-4 March 2016), a biennial event that brings together leading experts in different fields of cardiovascular research. The theme of the 2016 symposium was 'K⁺ channels and regulation', and the objectives of the conference were severalfold: (1) to identify current knowledge gaps; (2) to understand what may go wrong in the diseased heart and why; (3) to identify possible novel therapeutic targets; and (4) to further the development of systems biology approaches to decipher the molecular mechanisms and treatment of cardiac arrhythmias. The sessions of the Symposium focusing on the functional roles of the cardiac K⁺ channel in health and disease, as well as K⁺ channels as therapeutic targets, were contributed by Ye Chen-Izu, Gideon Koren, James Weiss, David Paterson, David Christini, Dobromir Dobrev, Jordi Heijman, Thomas O'Hara, Crystal Ripplinger, Zhilin Qu, Jamie Vandenberg, Colleen Clancy, Isabelle Deschenes, Leighton Izu, Tamas Banyasz, Andras Varro, Heike Wulff, Eleonora Grandi, Michael Sanguinetti, Donald Bers, Jeanne Nerbonne and Nipavan Chiamvimonvat as speakers and panel discussants. This article summarizes state-of-the-art knowledge and controversies on the functional roles of cardiac K⁺ channels in normal and diseased heart. We endeavour to integrate current knowledge at multiple scales, from the single cell to the whole organ levels, and from both experimental and computational studies.

Triggered activity in atrial myocytes is influenced by Na+/Ca2+ exchanger activity in genetically altered mice

AIMS

In atrial fibrillation, increased function of the Na⁺/Ca²⁺-exchanger (NCX) is one among several electrical remodeling mechanisms.

METHODS/RESULTS

Using the patch-clamp- and Ca²⁺ imaging-methods, we investigated atrial myocytes from NCX-homozygous-overexpressor (OE)- and heterozygous-knockout (KO)-mice and their corresponding wildtypes (WT_OE; WT_KO). NCX mediated Ca²⁺ extrusion capacity was reduced in KO and increased in OE. There was no evidence for structural or molecular remodeling. During a proarrhythmic pacing-protocol, the number of low amplitude delayed afterdepolarizations (DADs) was unaltered in OE vs. WT_OE and KO vs. WT_KO. However, DADs triggered full spontaneous action potentials (sAP) significantly more often in OE vs. WT_OE (ratio sAP/DAD: OE:0.18±0.05; WT_OE:0.02±0.02; p<0.001). Using the same protocol, a DAD triggered an sAP by tendency less often in KO vs. WT_KO (p=0.06) and significantly less often under a more aggressive proarrhythmic protocol (ratio sAP/DAD: KO:0.01±0.003; WT KO: 0.12±0.05; p=0.007). The DAD amplitude was increased in OE vs. WT_OE and decreased in KO vs. WT_KO. There were no differences in SR-Ca²⁺-load, the number of spontaneous Ca²⁺-release-events or IKACh/IK1.

CONCLUSIONS

Atrial myocytes with increased NCX expression exhibited increased vulnerability towards sAPs while atriomyocytes with reduced NCX expression were protected. The underlying mechanism consists of a modification of the DAD-amplitude by the level of NCX-activity. Thus, although the number of spontaneous Ca²⁺-releases and therefore DADs is unaltered, the higher DAD-amplitude in OE made a transgression of the voltage-threshold of an sAP more likely. These findings indicate that the level of NCX activity could influence triggered activity in atrial myocytes independent of possible remodeling processes.

Mechanisms of arrhythmogenesis related to calcium-driven alternans in a model of human atrial fibrillation

The occurrence of atrial fibrillation (AF) is associated with progressive changes in the calcium handling system of atrial myocytes. Calcium cycling instability has been implicated as an underlying mechanism of electrical alternans observed in patients who experience AF. However, the extent to which calcium-induced alternation of electrical activity in the atria contributes to arrhythmogenesis is unknown. In this study, we investigated the effects of calcium-driven alternans (CDA) on arrhythmia susceptibility in a biophysically detailed, 3D computer model of the human atria representing electrical and structural remodeling secondary to chronic AF. We found that elevated propensity to CDA rendered the atria vulnerable to ectopy-induced arrhythmia. It also increased the complexity and persistence of arrhythmias induced by fast pacing, with unstable scroll waves meandering and frequently breaking up to produce multiple wavelets. Our results suggest that calcium-induced electrical instability may increase arrhythmia vulnerability and promote increasing disorganization of arrhythmias in the chronic AF-remodeled atria, thus playing an important role in the progression of the disease.

Lone Atrial Fibrillation Is Associated With Impaired Left Ventricular Energetics That Persists Despite Successful Catheter Ablation

Supplemental Digital Content is available in the text.

Lone atrial fibrillation (AF) may reflect a subclinical cardiomyopathy that persists after sinus rhythm (SR) restoration, providing a substrate for AF recurrence. To test this hypothesis, we investigated the effect of restoring SR by catheter ablation on left ventricular (LV) function and energetics in patients with AF but no significant comorbidities.

Anti-arrhythmic strategies for atrial fibrillation: The role of computational modeling in discovery, development, and optimization

Atrial fibrillation (AF), the most common cardiac arrhythmia, is associated with increased risk of cerebrovascular stroke, and with several other pathologies, including heart failure. Current therapies for AF are targeted at reducing risk of stroke (anticoagulation) and tachycardia-induced cardiomyopathy (rate or rhythm control). Rate control, typically achieved by atrioventricular nodal blocking drugs, is often insufficient to alleviate symptoms. Rhythm control approaches include antiarrhythmic drugs, electrical cardioversion, and ablation strategies. Here, we offer several examples of how computational modeling can provide a quantitative framework for integrating multiscale data to: (a) gain insight into multiscale mechanisms of AF; (b) identify and test pharmacological and electrical therapy and interventions; and (c) support clinical decisions. We review how modeling approaches have evolved and contributed to the research pipeline and preclinical development and discuss future directions and challenges in the field.