Cardiac electrophysiological adaptations in the equine athlete-Restitution analysis of electrocardiographic features

Muscarinic acetylcholine receptors M2 are upregulated in the atrioventricular nodal tract in horses with a high burden of second-degree atrioventricular block

Background

Second-degree atrioventricular (AV) block at rest is very common in horses. The underlying molecular mechanisms are unexplored, but commonly attributed to high vagal tone.

Aim

To assess whether AV block in horses is due to altered expression of the effectors of vagal signalling in the AV node, with specific emphasis on the muscarinic acetylcholine receptor (M2) and the G protein-gated inwardly rectifying K+ (GIRK4) channel that mediates the cardiac IK,ACh current.

Method

Eighteen horses with a low burden of second-degree AV block (median 8 block per 20 h, IQR: 32 per 20 h) were assigned to the control group, while 17 horses with a high burden of second-degree AV block (median: 408 block per 20 h, IQR: 1,436 per 20 h) were assigned to the AV block group. Radiotelemetry ECG recordings were performed to assess PR interval and incidence of second-degree AV block episodes at baseline and on pharmacological blockade of the autonomic nervous system (ANS). Wenckebach cycle length was measured by intracardiac pacing (n = 16). Furthermore, the expression levels of the M2 receptor and the GIRK4 subunit of the IKACh channel were quantified in biopsies from the right atrium, the AV node and right ventricle using immunohistochemistry and machine learning-based automated segmentation analysis (n = 9 + 9).

Results

The AV block group had a significantly longer PR interval (mean ± SD, 0.40 ± 0.05 s; p < 0.001) and a longer Wenckebach cycle length (mean ± SD, 995 ± 86 ms; p = 0.007) at baseline. After blocking the ANS, all second-degree AV block episodes were abolished, and the difference in PR interval disappered (p = 0.80). The AV block group had significantly higher expression of the M2 receptor (p = 0.02), but not the GIRK4 (p = 0.25) in the AV node compared to the control group. Both M2 and GIRK4 were highly expressed in the AV node and less expressed in the atria and the ventricles.

Conclusion

Here, we demonstrate the involvement of the m2R-IK,ACh pathway in underlying second-degree AV block in horses. The high expression level of the M2 receptor may be responsible for the high burden of second-degree AV blocks seen in some horses.

Cardiac ion channel expression in the equine model - In-silico prediction utilising RNA sequencing data from mixed tissue samples

Understanding cardiomyocyte ion channel expression is crucial to understanding normal cardiac electrophysiology and underlying mechanisms of cardiac pathologies particularly arrhythmias. Hitherto, equine cardiac ion channel expression has rarely been investigated. Therefore, we aim to predict equine cardiac ion channel gene expression. Raw RNAseq data from normal horses from 9 datasets was retrieved from ArrayExpress and European Nucleotide Archive and reanalysed. The normalised (FPKM) read counts for a gene in a mix of tissue were hypothesised to be the average of the expected expression in each tissue weighted by the proportion of the tissue in the mix. The cardiac-specific expression was predicted by estimating the mean expression in each other tissues. To evaluate the performance of the model, predicted gene expression values were compared to the human cardiac gene expression. Cardiac-specific expression could be predicted for 91 ion channels including most expressed Na+ channels, K+ channels and Ca2+ -handling proteins. These revealed interesting differences from what would be expected based on human studies. These differences included predominance of NaV 1.4 rather than NaV 1.5 channel, and RYR1, SERCA1 and CASQ1 rather than RYR2, SERCA2, CASQ2 Ca2+ -handling proteins. Differences in channel expression not only implicate potentially different regulatory mechanisms but also pathological mechanisms of arrhythmogenesis.

Fundamentals of arrhythmogenic mechanisms and treatment strategies for equine atrial fibrillation

Atrial fibrillation (AF) is the most common pathological arrhythmia in horses. Although it is not usually a life-threatening condition on its own, it can cause poor performance and make the horse unsafe to ride. It is a complex multifactorial disease influenced by both genetic and environmental factors including exercise training, comorbidities or ageing. The interactions between all these factors in horses are still not completely understood and the pathophysiology of AF remains poorly defined. Exciting progress has been recently made in equine cardiac electrophysiology in terms of diagnosis and documentation methods such as cardiac mapping, implantable electrocardiogram (ECG) recording devices or computer-based ECG analysis that will hopefully improve our understanding of this disease. The available pharmaceutical and electrophysiological treatments have good efficacy and lead to a good prognosis for AF, but recurrence is a frequent issue that veterinarians have to face. This review aims to summarise our current understanding of equine cardiac electrophysiology and pathophysiology of equine AF while providing an overview of the mechanism of action for currently available treatments for equine AF.

ECG Restitution Analysis and Machine Learning to Detect Paroxysmal Atrial Fibrillation: Insight from the Equine Athlete as a Model for Human Athletes

Atrial fibrillation is the most frequent arrhythmia in both equine and human athletes. Currently, this condition is diagnosed via electrocardiogram (ECG) monitoring which lacks sensitivity in about half of cases when it presents in paroxysmal form. We investigated whether the arrhythmogenic substrate present between the episodes of paroxysmal atrial fibrillation (PAF) can be detected using restitution analysis of normal sinus-rhythm ECGs. In this work, ECG recordings were obtained during routine clinical work from control and horses with PAF. The extracted QT, TQ, and RR intervals were used for ECG restitution analysis. The restitution data were trained and tested using k-nearest neighbor (k-NN) algorithm with various values of neighbors k to derive a discrimination tool. A combination of QT, RR, and TQ intervals was used to analyze the relationship between these intervals and their effects on PAF. A simple majority vote on individual record (one beat) classifications was used to determine the final classification. The k-NN classifiers using two-interval measures were able to predict the diagnosis of PAF with area under the receiving operating characteristic curve close to 0.8 (RR, TQ with k ≥ 9) and 0.9 (RR, QT with k ≥ 21 or TQ, QT with k ≥ 25). By simultaneously using all three intervals for each beat and a majority vote, mean area under the curves of 0.9 were obtained for all tested k-values (3-41). We concluded that 3D ECG restitution analysis can potentially be used as a metric of an automated method for screening of PAF.

Animal Models of Atrial Fibrillation

Atrial fibrillation (AF) is the most common sustained arrhythmia encountered in humans and is a significant source of morbidity and mortality. Despite its prevalence, our mechanistic understanding is incomplete, the therapeutic options have limited efficacy, and are often fraught with risks. A better biological understanding of AF is needed to spearhead novel therapeutic avenues. Although "natural" AF is nearly nonexistent in most species, animal models have contributed significantly to our understanding of AF and some therapeutic options. However, the impediments of animal models are also apparent and stem largely from the differences in basic physiology as well as the complexities underlying human AF; these preclude the creation of a "perfect" animal model and have obviated the translation of animal findings. Herein, we review the vast array of AF models available, spanning the mouse heart (weighing 1/1000th of a human heart) to the horse heart (10× heavier than the human heart). We attempt to highlight the features of each model that bring value to our understanding of AF but also the shortcomings and pitfalls. Finally, we borrowed the concept of a SWOT analysis from the business community (which stands for strengths, weaknesses, opportunities, and threats) and applied this introspective type of analysis to animal models for AF. We identify unmet needs and stress that is in the context of rapidly advancing technologies, these present opportunities for the future use of animal models.

The application of Lempel-Ziv and Titchener complexity analysis for equine telemetric electrocardiographic recordings

The analysis of equine electrocardiographic (ECG) recordings is complicated by the absence of agreed abnormality classification criteria. We explore the applicability of several complexity analysis methods for characterization of non-linear aspects of electrocardiographic recordings. We here show that complexity estimates provided by Lempel-Ziv ’76, Titchener’s T-complexity and Lempel-Ziv ’78 analysis of ECG recordings of healthy Thoroughbred horses are highly dependent on the duration of analysed ECG fragments and the heart rate. The results provide a methodological basis and a feasible reference point for the complexity analysis of equine telemetric ECG recordings that might be applied to automate detection of equine arrhythmias in equine clinical practice.