Investigating the ionic mechanisms behind the pathogenesis of Atrial Fibrillation in Hypertrophic Cardiomyopathy (HCM) using an electromechanically coupled human atrial computational model

Atrial fibrillation (AF) is a frequent comorbidity in patients with hypertrophic cardiomyopathy (HCM), a condition primarily defined by ventricular hypertrophy but also associated with a significant arrhythmic burden. AF can occur even in the absence of extensive atrial structural remodeling, suggesting that certain sarcomeric mutations may directly influence atrial electrophysiology and calcium handling, thereby creating a vulnerable substrate for arrhythmogenesis. This work aims to investigate whether these mutations induce functional alterations at the cellular level, such as changes in action potential duration, resting membrane potential, and calcium handling dynamics, which could collectively lead to proarrhythmic behavior. Events like early or delayed afterdepolarizations, and triggered activity will be analyzed as possible contributors to increased AF susceptibility. To explore these mechanisms, single-cell simulations are carried out using a human electromechanical atrial model (MBS2023), which incorporates bidirectional mechano-electrical coupling and accounts for both feedforward and feedback interactions between electrical activity, calcium handling, and mechanical stretch. Simulation protocols include the introduction of sarcomeric mutations commonly associated with HCM both in isolation and in combination with atrial or ventricular-like HCM remodeling. Results indicate that while mutations alone primarily induce hypercontractility with minimal electrophysiological abnormalities, the presence of electrical remodeling can markedly alter the substrate. These findings demonstrate that the proarrhythmic phenotype in HCM is highly dependent on both the specific sarcomeric mutation and the remodeling context. The study provides a mechanistic link between genetic variants, ionic remodeling, and AF susceptibility, emphasizing the need for patient-specific assessments to predict arrhythmic risk and guiding potential therapeutic strategies.