Abstract

Early afterdepolarizations (EADs) are abnormal oscillations during the plateau phase of the cardiac action potential and have been linked to cardiac arrhythmias. At the cellular level, EADs can be caused by reactivation of the L-type calcium (Ca2+) channels, spontaneous Ca2+ releases from the sarcoplasmic reticulum, or both. In tissue, these EADs can trigger action potentials in neighboring cells, which may propagate as a nonlinear wave. In this scenario, EADs are attributed to cellular/subcellular/channel properties. In this study, we show a novel mechanism of EADs due to heterogeneous distribution of excitable and non-excitable cells in tissue, using a physiologically detailed computational model and mathematical analysis. In tissue, excitability of cells depends on the cell type and physiological and pathological conditions. Non-excitable cells create a non-excitable gap in tissue, which has been thought to be a cause of slow waves and reflected waves. Here, we show that the non-excitable gap also can be responsible for EAD generation. However, EADs occur only when the non-excitable gap size is optimal. If the gap size is too small, no EADs occur. If the gap size is too large, the action potential wave cannot propagate through the gap region. We also demonstrate that EADs caused by the non-excitable gap can initiate reentry in tissue, which has been linked to ventricular tachycardia and fibrillation. Thus, the non-excitable gap can lead to both focal and reentrant arrhythmias. EADs shown in this study are spatial phenomena and require tissue heterogeneity. Our study sheds light on the role of tissue heterogeneity on focal and reentrant arrhythmias.

Highlights

  • Sudden cardiac death is one of the major causes of death in the world [1]

  • When cells are well connected via gap junctions without a non-excitable gap, the action potential wave propagates smoothly without Early afterdepolarizations (EADs) in the cable (Figure 2A)

  • The gap size is critical for the formation of EADs

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Summary

Methods

We used a physiologically detailed model of the rabbit ventricular action potential model used in our previous studies [19, 36,37,38]. We solve this equation using the operator splitting method [39]. We use the Euler method with the variable time step of 0.01∼0.1 ms to compute the single cell action potential. We used double precision in our simulations and checked the results using smaller time steps.

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