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.

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.