Rationale: Familial sick sinus syndrome (SSS) has been linked to loss-of-function mutations of the SCN5A gene, which result in decreased inward Na ؉ current, I Na . However, the functional role of I Na in cardiac pacemaking is controversial, and mechanistic links between mutations and sinus node dysfunction in SSS are unclear. Objective: To determine mechanisms by which the SCN5A mutations impair cardiac pacemaking. Methods and Results: Action potential (AP) models for rabbit sinoatrial node (SAN) cells were modified to incorporate experimentally reported I Na changes induced by 2 groups of SCN5A gene mutations (affecting the activation and inactivation of I Na , respectively). The cell models were incorporated into an anatomically detailed 2D model of the intact SAN-atrium. Effects of the mutations and vagal nerve activity on cardiac pacemaking at the single-cell and tissue levels were studied. Multielectrode extracellular potential recordings of activation pattern from intact SAN-atrium preparations were performed to test predictions of the models. At the single-cell level, the mutations slowed down pacemaking rates in peripheral, but not in central SAN cells that control the heart rhythm. However, in tissue simulations, the mutations not only slowed down pacemaking, but also compromised AP conduction across the SAN-atrium, leading to a possible SAN exit block or sinus arrest, the major features of SSS. Simulated vagal nerve activity amplified the bradycardiac effects of the mutations. Two groups of SCN5A mutations showed subtle differences in impairing the ability of the SAN to drive the surrounding atrium, primarily attributable to their differential effects on atrial excitability and conduction safety. Experimental data with tetrodotoxin and carbachol confirmed the simulation outcomes. Conclusions: Our study substantiates the causative link between SCN5A gene mutations and SSS and illustrates mechanisms by which the mutations impair the driving ability of the SAN. (Circ Res. 2010;107:126-137.)Key Words: sick sinus syndrome Ⅲ SCN5A mutation Ⅲ ion channels Ⅲ computer modeling S ick sinus syndrome (SSS) denotes a collection of cardiac arrhythmias associated with dysfunction of the sinoatrial node (SAN) that commonly lead to disorders in cardiac rhythm and conduction. 1 Such arrhythmias include intermittent sinus bradycardia, sinus arrest, sinus pause, slow SANatrium conduction, sinus exit block or alternating bradycardia and atrial tachycardia. [1][2][3][4] The symptoms of SSS vary, with patients presenting with syncope, presyncope, palpitations, or dizziness. 1,5 Many SSS patients have to be fitted with an electronic pacemaker.Mechanisms underlying the pathogenesis for sinus node dysfunction in SSS patients are unclear. SSS can occur in elderly and pediatric patients. It can also occur in healthy people without any evident structural heart disease 2,4 but with genetic defects. Recent studies have identified several gene mutations in congenital SSS patients. 2,4,6,7 Among them are the SCN5A gene mutations tha...

Background-Computer models that capture key features of the heterogeneous myofiber architecture of right and left atria and interatrial septum provide a means of investigating the mechanisms responsible for atrial arrhythmia. The data necessary to implement such models have not previously been available. The aims of this study were to characterize surface geometry and myofiber architecture throughout the atrial chambers and to investigate the effects of this structure on atrial activation. Methods and Results-Atrial surface geometry and myofiber orientations were reconstructed in 3D at 50ϫ50ϫ50-m

Rapid atrial arrhythmias such as atrial fibrillation (AF) predispose to ventricular arrhythmias, sudden cardiac death and stroke. Identifying the origin of atrial ectopic activity from the electrocardiogram (ECG) can help to diagnose the early onset of AF in a cost-effective manner. The complex and rapid atrial electrical activity during AF makes it difficult to obtain detailed information on atrial activation using the standard 12-lead ECG alone. Compared to conventional 12-lead ECG, more detailed ECG lead configurations may provide further information about spatio-temporal dynamics of the body surface potential (BSP) during atrial excitation. We apply a recently developed 3D human atrial model to simulate electrical activity during normal sinus rhythm and ectopic pacing. The atrial model is placed into a newly developed torso model which considers the presence of the lungs, liver and spinal cord. A boundary element method is used to compute the BSP resulting from atrial excitation. Elements of the torso mesh corresponding to the locations of the placement of the electrodes in the standard 12-lead and a more detailed 64-lead ECG configuration were selected. The ectopic focal activity was simulated at various origins across all the different regions of the atria. Simulated BSP maps during normal atrial excitation (i.e. sinoatrial node excitation) were compared to those observed experimentally (obtained from the 64-lead ECG system), showing a strong agreement between the evolution in time of the simulated and experimental data in the P-wave morphology of the ECG and dipole evolution. An algorithm to obtain the location of the stimulus from a 64-lead ECG system was developed. The algorithm presented had a success rate of 93%, meaning that it correctly identified the origin of atrial focus in 75/80 simulations, and involved a general approach relevant to any multi-lead ECG system. This represents a significant improvement over previously developed algorithms.