Influence of the KCNQ1 S140G Mutation on Human Ventricular Arrhythmogenesis and Pumping Performance: Simulation Study

Abstract

The KCNQ1 S140G mutation, which is involved in I_Ks current, affects atrial fibrillation. However, little is known about its effect on the mechanical behavior of the heart. Therefore, we assessed the influence of the KCNQ1 S140G mutation on ventricular electrophysiological stability and mechanical pumping performance using a multi-scale model of cardiac electromechanics. An image-based electromechanical model was used to assess the effect on electrical propagation and arrhythmogenesis of the KCNQ1 S140G mutation. In addition, it was used to compare the mechanical response under the wild-type (WT) and S140G mutation conditions. The intracellular calcium transient obtained from the electrophysiological model was applied as an input parameter to a mechanical model to implement excitation-contraction coupling. The I_Ks current equation was modified to account for expression of the KCNQ1 S140G mutation, and it included a scaling factor (ϕ) for mutant expressivity. The WT and S140G mutation conditions were compared at the single-cell and three-dimensional (3D) tissue levels. The action potential duration (APD) was reduced by 60% by the augmented I_Ks current under the S140G mutation condition, which resulted in shorter QT interval. This reduced the 3D sinus rhythm wavelength by 60% and the sustained re-entry by 56%. However, pumping efficiency of mutant ventricles was superior in sinus rhythm condition. In addition, the shortened wavelength in cardiac tissue allowed a re-entrant circuit to form and increased the probability of sustaining ventricular tachycardia and ventricular fibrillation. In contrast, under the WT condition, a normal wavelength (20.8 cm) was unlikely to initiate and sustain re-entry in the cardiac tissue. Subsequently, the S140G mutant ventricles developed a higher dominant frequency distribution range (2.0-5.3 Hz) than the WT condition (2.8-3.7 Hz). In addition, stroke volume of mutant ventricles was reduced by 65% in sustained re-entry compared to the WT condition. In conclusion, signs of the S140G mutation might be difficult to identify in sinus rhythm even though the mutant ventricles show shortened QT interval. This suggests that the KCNQ1 S140G mutation increases the risk of death by sudden cardiac arrest. In addition, the KCNQ1 S140G mutation can induce ventricular arrhythmia and lessen ventricular contractility under re-entrant conditions.

Keywords: KCNQ1 S140G mutation; dominant frequency; electromechanical simulation; pumping performance; reentry response; sinus rhythm response; ventricular arrhythmia.

Figure 1

Schematic diagram of the ventricular electromechanical model. The left side of the circuit diagram is a ventricular model of electrophysiological simulation with 214,319 nodes. The electrical components of the schematic represent the current, pump, and ion exchanger from the Ten Tusscher ion model, which emulates the cell membrane for ion transport and the sarcoplasmic reticulum within cardiac cells. I_p, _k is the current due to the K⁺ pump, I_to denotes the transient outward K⁺ current, I_Na, _K is the Na⁺ −K⁺ ion exchange current, I_p, _Ca is the current of the sarcoplasmic Ca²⁺ pump, and I_Na, _Ca means the current mediated by the Na⁺ −Ca ²⁺ ion exchange pump. E_k, E_Ca, and E_Na are the equilibrium potentials of K⁺, Ca²⁺, and Na⁺ ions, respectively, whereas C_m denotes the membrane capacitance due to the phospholipid bilayer in ventricular cells. I_k1 is the inward rectifier K₁ current, I_Ks is the K⁺ current due to the slow delayed rectifier, I_Ca, _L is the L-type inward Ca²⁺ current, and I_Ca, _b denotes the background Ca²⁺ current. I_Na, _b is the background Na⁺ current, and I_Na is the fast inward Na⁺ current. I_rel is the Ca²⁺ current released from the junctional sarcoplasmic reticulum (JSR), I_leak denotes the Ca²⁺ current that leaks from the ISR, and I_up is the Ca²⁺ uptake current into the network sarcoplasmic reticulum (NSR). The mechanical components on the right are the myofilament models proposed by Rice et al. N_xB and P_xB are non-permissive and permissive confirmations of regulatory proteins, and XB_PreR is the pre-rotated state of the myosin head in relation to binding, which contributes to stiffness but does not generate force in the absence of net motion. XB_PostR denotes a strongly bound myosin head and represents the isomerization that induces strain in the extensible neck region. G_xbT is the ATP-consuming detachment transition rate, h_fT and h_bT are the forward and backward transition rates, respectively; f_aapT is the cross-bridge attachment rate of transition to the first strongly-bound state XB_PreR, and g_aapT is the reverse rate. K_np and K_pn are transition rates, K_np(TCa_Tot)^7.5 is the forward rate of the nonpermissive-to-permissive transition, in the opposite direction, and K_pn(TCa_Tot)−7.5 is the backward rate of the permissive-to-nonpermissive transition. The force due to the cross-bridge can be subdivided into an active force and passive force. The active force induces the action of the cycling cross-bridge, and the passive force induces a complete muscle response with viscoelastic elements. Mass prevents instantaneous changes in muscle-shortening velocity for quick-release protocols, whereas a linear elastic element is intended to simulate the effects of the compliant end connections that take place in real muscle preparations. The model coupled with the circulatory; C_PA, pulmonary artery compliance; R_PA, pulmonary artery resistance; C_PV, pulmonary vein compliance; R_PV, pulmonary vein resistance; C_LA, left atrium compliance; R_MI, mitral valve resistance; C_LV, left ventricular compliance; R_AO, aortic valve resistance; R_SA, systemic artery resistance; C_SA, systemic artery compliance; R_SV, systemic vein resistance; C_SV, systemic vein compliance; C_RA, right atrium compliance; R_TR, tricuspid valve resistance; C_RV, right ventricular compliance; R_PU, pulmonary valve resistance; P_RV, right ventricular pressure; V_RV, right ventricular volume; P_LV, left ventricular pressure; V_LV, left ventricular volume.

Figure 2

Single-cell simulations using various myocardial cell types under the WT and S140G mutation conditions. I_Ks currents (A–C), the corresponding AP shapes (D–F), and APDR curves (G–L) under the WT and KCNQ1 S140G mutation conditions in ventricular endocardium (Endo), mid-myocardium (M), and epicardium (Epi) cells. APD, action potential duration; DI, diastolic interval and; BCL, basic cycle length.

Figure 3

Sinus rhythm response in the 3D ventricular tissue model under the WT and S140G mutation conditions. Snapshots of the transmural distribution of membrane potential (top), strain (bottom) (A,B) and electrical activation time (EAT) and electrical deactivation time (EDT) during one cycle of sinus pacing under the WT and KCNQ1 S140G mutation condition (C). The anisotropy ratio of CV (longitudinal to transverse) is 1.5.

Figure 4

Pressure in the left ventricle and systemic artery (A) and the pressure–volume (PV) loop of the left ventricle (B) under the WT and S140G mutation conditions.

Figure 5

Membrane distribution of 3D electrical re-entry generation simulation under the WT and S140G mutation conditions. Snapshots of the transmural distribution of membrane potential over time (A), and AP shapes for re-entry generation under the WT (B), and S140G mutation (C) conditions. AP shapes were obtained at the points marked by red stars.

Figure 6

Membrane distribution of 3D electrical simulation during sustained re-entry under the WT and S140G mutation conditions. Snapshots of the transmural distribution of membrane potential over time during re-entry (A), and AP shapes during re-entry under the WT (B), and S140G (C) conditions. AP shapes were obtained at the points marked by red stars.

Figure 7

The re-entrant dynamics response under the WT and S140G mutation conditions. Dominant frequency (A) of each node in the 3D ventricle model and frequency variance (B) under the WT and S140G mutation conditions. Contour of the transmural distribution of re-entrant dynamic wave in the 3D ventricular model under the WT and S140G mutation conditions (C). Contour of the dominant frequency in each node under the WT and S140G mutation conditions (D).

Figure 8

Cardiac mechanical response of a 3D re-entrant dynamics simulation under the WT and S140G mutation conditions. Pressure in the left ventricle and aorta (A), volume of the left ventricle (B), PV loop (C), and ATP CR (consumption rate) (D) under the WT and KCNQ1 S140G mutation conditions.