Characterization of a novel KCNQ1 mutation for type 1 long QT syndrome and assessment of the therapeutic potential of a novel IKs activator using patient-specific induced pluripotent stem cell-derived cardiomyocytes.

INTRODUCTION: Type 1 long QT syndrome (LQT1) is a common type of cardiac channelopathy associated with loss-of-function mutations of KCNQ1. Currently there is a lack of drugs that target the defected slowly activating delayed rectifier potassium channel (IKs). With LQT1 patient-specific human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (hiPSC-CMs), we tested the effects of a selective IKs activator ML277 on reversing the disease phenotypes. METHODS: A LQT1 family with a novel heterozygous exon 7 deletion in the KCNQ1 gene was identified. Dermal fibroblasts from the proband and her healthy father were reprogrammed to hiPSCs and subsequently differentiated into hiPSC-CMs. RESULTS: Compared with the control, LQT1 patient hiPSC-CMs showed reduced levels of wild type KCNQ1 mRNA accompanied by multiple exon skipping mRNAs and a ~50% reduction of the full length Kv7.1 protein. Patient hiPSC-CMs showed reduced IKs current (tail current density at 30 mV: 0.33±0.02 vs. 0.92±0.21, P<0.05) and prolonged action potential duration (APD) (APD 50 and APD90: 603.9±39.2 vs. 319.3±13.8 ms, P<0.005; and 671.0±41.1 vs. 372.9±14.2 ms, P<0.005). ML277, a small molecule recently identified to selectively activate KV7.1, reversed the decreased IKs and partially restored APDs in patient hiPSC-CMs. CONCLUSIONS: From a LQT1 patient carrying a novel heterozygous exon7 deletion mutation of KCNQ1, we generated hiPSC-CMs that faithfully recapitulated the LQT1 phenotypes that are likely associated with haploinsufficiency and trafficking defect of KCNQ1/Kv7.1. The small molecule ML277 restored IKs function in hiPSC-CMs and could have therapeutic value for LQT1 patients.

In silico cardiac risk assessment in patients with long QT syndrome: type 1: clinical predictability of cardiac models.

OBJECTIVES: The study was designed to assess the ability of computer-simulated electrocardiography parameters to predict clinical outcomes and to risk-stratify patients with long QT syndrome type 1 (LQT1). BACKGROUND: Although attempts have been made to correlate mutation-specific ion channel dysfunction with patient phenotype in long QT syndrome, these have been largely unsuccessful. Systems-level computational models can be used to predict consequences of complex changes in channel function to the overall heart rhythm. METHODS: A total of 633 LQT1-genotyped subjects with 34 mutations from multinational long QT syndrome registries were studied. Cellular electrophysiology function was determined for the mutations and introduced in a 1-dimensional transmural electrocardiography computer model. The mutation effect on transmural repolarization was determined for each mutation and related to the risk for cardiac events (syncope, aborted cardiac arrest, and sudden cardiac death) among patients. RESULTS: Multivariate analysis showed that mutation-specific transmural repolarization prolongation (TRP) was associated with an increased risk for cardiac events (35% per 10-ms increment [p < 0.0001]; ≥upper quartile hazard ratio: 2.80 [p < 0.0001]) and life-threatening events (aborted cardiac arrest/sudden cardiac death: 27% per 10-ms increment [p = 0.03]; ≥upper quartile hazard ratio: 2.24 [p = 0.002]) independently of patients' individual QT interval corrected for heart rate (QTc). Subgroup analysis showed that among patients with mild to moderate QTc duration (<500 ms), the risk associated with TRP was maintained (36% per 10 ms [p < 0.0001]), whereas the patient's individual QTc was not associated with a significant risk increase after adjustment for TRP. CONCLUSIONS: These findings suggest that simulated repolarization can be used to predict clinical outcomes and to improve risk stratification in patients with LQT1, with a more pronounced effect among patients with a lower-range QTc, in whom a patient's individual QTc may provide less incremental prognostic information.

Combined assessment of sex- and mutation-specific information for risk stratification in type 1 long QT syndrome.

BACKGROUND: Men and women with type 1 long QT syndrome (LQT1) exhibit time-dependent differences in the risk for cardiac events. OBJECTIVE: We hypothesized that sex-specific risk for LQT1 is related to the location and function of the disease-causing mutation in the KCNQ1 gene. METHODS: The risk for life-threatening cardiac events (comprising aborted cardiac arrest [ACA] or sudden cardiac death [SCD]) from birth through age 40 years was assessed among 1051 individuals with LQT1 (450 men and 601 women) by the location and function of the LQT1-causing mutation (prespecified as mutations in the intracellular domains linking the membrane-spanning segments [ie, S2-S3 and S4-S5 cytoplasmic loops] involved in adrenergic channel regulation vs other mutations). RESULTS: Multivariate analysis showed that during childhood (age group: 0-13 years) men had >2-fold (P < .003) increased risk for ACA/SCD than did women, whereas after the onset of adolescence the risk for ACA/SCD was similar between men and women (hazard ratio = 0.89 [P = .64]). The presence of cytoplasmic-loop mutations was associated with a 2.7-fold (P < .001) increased risk for ACA/SCD among women, but it did not affect the risk among men (hazard ratio 1.37; P = .26). Time-dependent syncope was associated with a more pronounced risk-increase among men than among women (hazard ratio 4.73 [P < .001] and 2.43 [P = .02], respectively), whereas a prolonged corrected QT interval (≥ 500 ms) was associated with a higher risk among women than among men. CONCLUSION: Our findings suggest that the combined assessment of clinical and mutation location/functional data can be used to identify sex-specific risk factors for life-threatening events for patients with LQT1.

A quantitative assessment of T-wave morphology in LQT1, LQT2, and healthy individuals based on Holter recording technology.

BACKGROUND: The clinical course and the precipitating risk factors in the congenital long QT syndrome (LQTS) are genotype specific. OBJECTIVES: The goal of this study was to develop a computer algorithm allowing for electrocardiogram (ECG)-based identification and differentiation of LQT1 and LQT2 carriers. METHODS: Twelve-lead ECG Holter monitor recordings were acquired in 49 LQT1 carriers, 25 LQT2 carriers, and 38 healthy subjects as controls. The cardiac beats were clustered based on heart-rate bin method. Scalar and vectorial repolarization parameters were compared for similar heart rates among study groups. The Q to Tpeak (QTpeak), the Tpeak to Tend interval, T-wave magnitude and T-loop morphology were automatically quantified using custom-made algorithms. RESULTS: QTpeak from lead II and the right slope of the T-wave were the most discriminant parameters for differentiating the 3 groups using prespecified heart rate bin (75.0 to 77.5 beats/min). The predictive model utilizing these scalar parameters was validated using the entire spectrum of heart rates. Both scalar and vectorcardiographic models provided very effective identification of tested subjects in heart rates between 60 and 100 beats/min, whereas they had limited performance during tachycardia and slightly better discrimination in bradycardia. In the 60 to 100 beats/min heart rate range, the best 2-variable model identified correctly 89% of healthy subjects, 84% of LQT1 carriers, and 92% of LQT2 carriers. A model including 3 parameters based purely on scalar ECG parameters could correctly identify 90% of the population (89% of healthy subjects, 90% of LQT1 carriers, and 92% of LQT2 carriers). CONCLUSION: Automatic algorithm quantifying T-wave morphology discriminates LQT1 and LQT2 carriers and healthy subjects with high accuracy. Such computerized ECG methodology could assist physicians evaluating subjects suspected for LQTS.