UCLA

Arrhythmias and sudden cardiac death (SCD) represent a leading cause of mortality in the US and worldwide. Currently, the most effective therapy for preventing SCD is the implantable cardioverter-defibrillator (ICD). ICDs however can only terminate arrhythmias after they have already occurred and have numerous severe side effects and poor cost-effectiveness. Therefore, the ideal anti-arrhythmic strategy is the prevention of arrhythmia initiation, or arrhythmogenesis, in the first place. Unfortunately, multiple clinical trials have demonstrated that many of the currently available anti-arrhythmic drugs are not generally effective in the prevention of ventricular arrhythmias, and in some cases may even be pro-arrhythmic unintuitively causing increased mortality. Thus, improved anti-arrhythmic strategies are needed which require improved mechanistic understanding of the arrhythmogenesis process.

Computational modeling is a powerful research tool, complementary to experimental and clinical studies, to study the underlying mechanisms of arrhythmias. In this dissertation, we use computer modeling and patch clamp experiments to investigate the spontaneous initiation of triggered and reentrant ventricular arrhythmias as related to delayed afterdepolarizations (DADs) and long QT syndrome (LQTS). We first describe a dynamical threshold for DAD-mediated triggered activity which is lower than the sodium channel threshold and manifests under conditions of hypokalemia and slow spontaneous calcium release. Next, we investigate the critical factors that determine DAD-mediated triggered activity formation in cardiac tissue. Thirdly, we study whether sub-threshold DADs can act as an arrhythmogenic trigger and find that DADs can generate both triggers and a reentry substrate simultaneously. And finally, we detail a novel common mechanism of arrhythmia initiation across different genotypes of LQTS called “R-from-T”, which blurs the usual notions between arrhythmia trigger and substrate beyond the traditional paradigm. The mechanistic insights gained from these studies help inform the development of new arrhythmia prevention strategies.