Regular PaperA mutation in HERG Associated with Notched T waves in Long QT Syndrome☆
Abstract
Long QT syndrome (LQT) is a genetically heterogeneous inherited disorder that causes sudden death from cardiac arrhythmia. Four loci have been mapped to chromosomes 3, 4, 7 and 11 and three specific mutated genes for LQT syndrome have been identified. LQT2 results from mutations in the human ether-a-gogo-related gene, HERG, a cardiac potassium channel, whose protein product likely underlies IKr, the rapidly activating delayed rectifier current. By SSCP analysis and direct sequencing, we determined a new missense mutation in the HERG coding sequence, a G to A transition at position 1681 resulting in the substitution of threonine for a highly conserved alanine at codon 561. This mutation, Ala561Thr, in the coding sequence of the fifth membrane-spanning domain (S5) of the HERG protein seems to convey a risk of cardiac events in affected family members. In addition to a prolonged T wave of low amplitude on the surface ECG, a distinctive biphasic T-wave pattern was found in the left precordial leads of all affected subjects with the Ala561Thr mutation regardless of age, gender and beta blocking therapy.
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Prediction of Kv11.1 potassium channel PAS-domain variants trafficking via machine learning
2023, Journal of Molecular and Cellular CardiologyCongenital long QT syndrome (LQTS) is characterized by a prolonged QT-interval on an electrocardiogram (ECG). An abnormal prolongation in the QT-interval increases the risk for fatal arrhythmias. Genetic variants in several different cardiac ion channel genes, including KCNH2, are known to cause LQTS. Here, we evaluated whether structure-based molecular dynamics (MD) simulations and machine learning (ML) could improve the identification of missense variants in LQTS-linked genes. To do this, we investigated KCNH2 missense variants in the Kv11.1 channel protein shown to have wild type (WT) like or class II (trafficking-deficient) phenotypes in vitro. We focused on KCNH2 missense variants that disrupt normal Kv11.1 channel protein trafficking, as it is the most common phenotype for LQTS-associated variants. Specifically, we used computational techniques to correlate structural and dynamic changes in the Kv11.1 channel protein PAS domain (PASD) with Kv11.1 channel protein trafficking phenotypes. These simulations unveiled several molecular features, including the numbers of hydrating waters and hydrogen bonding pairs, as well as folding free energy scores, that are predictive of trafficking. We then used statistical and machine learning (ML) (Decision tree (DT), Random forest (RF), and Support vector machine (SVM)) techniques to classify variants using these simulation-derived features. Together with bioinformatics data, such as sequence conservation and folding energies, we were able to predict with reasonable accuracy (≈75%) which KCNH2 variants do not traffic normally. We conclude that structure-based simulations of KCNH2 variants localized to the Kv11.1 channel PASD led to an improvement in classification accuracy. Therefore, this approach should be considered to complement the classification of variant of unknown significance (VUS) in the Kv11.1 channel PASD.
Diagnostic accuracy of the response to the brief tachycardia provoked by standing in children suspected for long QT syndrome
2021, Heart Rhythm O2Adult long QT syndrome (LQTS) patients have inadequate corrected QT interval (QTc) shortening and an abnormal T-wave response to the sudden heart rate acceleration provoked by standing. In adults, this knowledge can be used to aid an LQTS diagnosis and, possibly, for risk stratification. However, data on the diagnostic value of the standing test in children are currently limited.
To determine the potential value of the standing test to aid LQTS diagnostics in children.
In a prospective cohort including children (≤18 years) who had a standing test, comprehensive analyses were performed including manual and automated QT interval assessments and determination of T-wave morphology changes.
We included 47 LQTS children and 86 control children. At baseline, the QTc that identified LQTS children with a 90% sensitivity was 435 ms, which yielded a 65% specificity. A QTc ≥ 490 ms after standing only slightly increased sensitivity (91%, 95% confidence interval [CI]: 80%–98%) and slightly decreased specificity (58%, 95% CI: 47%–70%). Sensitivity increased slightly more when T-wave abnormalities were present (94%, 95% CI: 82%–99%; specificity 53%, 95% CI: 42%–65%). When a baseline QTc ≥ 440 ms was accompanied by a QTc ≥ 490 ms and T-wave abnormalities after standing, sensitivity further increased (96%, 95% CI: 85%–99%) at the expense of a further specificity decrease (41%, 95% CI: 30%–52%). Beat-to-beat analysis showed that 30 seconds after standing, LQTS children had a greater increase in heart rate compared to controls, which was more evidently present in LQTS boys and LQTS type 1 children.
In children, the standing test has limited additive diagnostic value for LQTS over a baseline electrocardiogram, while T-wave abnormalities after standing also have limited additional value. The standing test for LQTS should only be used with caution in children.
Beyond the length and look of repolarization: Defining the non-QTc electrocardiographic profiles of patients with congenital long QT syndrome
2018, Heart RhythmLittle is known about the spectrum and prevalence of ECG features beyond the length and morphology of repolarization in patients with congenital long QT syndrome (LQTS).
The purpose of this study was to characterize the full ECG phenotype of LQTS patients and evaluate differences by age and LQTS genotype.
Retrospective review of 943 patients with LQTS (57% female; median age 25 years; interquartile range 9–34 years) was performed. Comprehensive analysis of their initial evaluation ECG was performed using definitions outlined in professional guidelines.
Bradycardia was common (n = 320 [34%]), regardless of beta-blocker use. Left-axis deviation (n = 33 [3.5%]) and bundle branch block (n = 5 [0.5%]) were uncommon. T-wave inversion (TWI) involving leads V1 and V3 was more common in LQTS type 2 compared to LQTS type 1 or type 3 (odds ratio [OR] for V1: 2.67, 95% confidence interval [CI] 1.8–3.9; OR for V3: 1.76, 95% CI 1.2–2.6), whereas TWI in leads III and aVF was most common in LQTS type 3 (OR for III: 2.38, 95% CI 1.4–4.2; OR for aVF: 3.14, 95% CI 1.6–6.4). Notched T waves were most apparent at younger ages (48% in patients age 4–10 compared to 12% in patients age >40: P <.0001).
Beyond the QT interval and bradycardia, ECG abnormalities are uncommon in LQTS patients, and patients almost never have concomitant bundle branch block. Notably, 19% of LQTS patients overall and 27% of LQTS type 2 patients exhibit anterior TWI that would satisfy a diagnostic criterion for arrhythmogenic right ventricular cardiomyopathy, thus creating the potential for diagnostic miscues.
Comparison of automated interval measurements by widely used algorithms in digital electrocardiographs
2018, American Heart JournalCitation Excerpt :It can be estimated from the significantly different cycle lengths in men and in women that rate adjustment by any of the standard formulae would result in longer QT values for women than for men in this population. The effect of a 50% admixture of long QT subjects in the total population, half LQT1 and half LQT2, on mean QT values in men and women is uncertain and requires further study.14,15 As seen in Figure 2, other differences between groups within each algorithm include trends toward shorter PR intervals, shorter QRS durations, and significantly longer QT intervals in the LQT subjects, with longer QT in LQT2 than in LQT1 groups.
Automated measurements of electrocardiographic (ECG) intervals by current-generation digital electrocardiographs are critical to computer-based ECG diagnostic statements, to serial comparison of ECGs, and to epidemiological studies of ECG findings in populations. A previous study demonstrated generally small but often significant systematic differences among 4 algorithms widely used for automated ECG in the United States and that measurement differences could be related to the degree of abnormality of the underlying tracing. Since that publication, some algorithms have been adjusted, whereas other large manufacturers of automated ECGs have asked to participate in an extension of this comparison.
Seven widely used automated algorithms for computer-based interpretation participated in this blinded study of 800 digitized ECGs provided by the Cardiac Safety Research Consortium. All tracings were different from the study of 4 algorithms reported in 2014, and the selected population was heavily weighted toward groups with known effects on the QT interval: included were 200 normal subjects, 200 normal subjects receiving moxifloxacin as part of an active control arm of thorough QT studies, 200 subjects with genetically proved long QT syndrome type 1 (LQT1), and 200 subjects with genetically proved long QT syndrome Type 2 (LQT2).
For the entire population of 800 subjects, pairwise differences between algorithms for each mean interval value were clinically small, even where statistically significant, ranging from 0.2 to 3.6 milliseconds for the PR interval, 0.1 to 8.1 milliseconds for QRS duration, and 0.1 to 9.3 milliseconds for QT interval. The mean value of all paired differences among algorithms was higher in the long QT groups than in normals for both QRS duration and QT intervals. Differences in mean QRS duration ranged from 0.2 to 13.3 milliseconds in the LQT1 subjects and from 0.2 to 11.0 milliseconds in the LQT2 subjects. Differences in measured QT duration (not corrected for heart rate) ranged from 0.2 to 10.5 milliseconds in the LQT1 subjects and from 0.9 to 12.8 milliseconds in the LQT2 subjects.
Among current-generation computer-based electrocardiographs, clinically small but statistically significant differences exist between ECG interval measurements by individual algorithms. Measurement differences between algorithms for QRS duration and for QT interval are larger in long QT interval subjects than in normal subjects. Comparisons of population study norms should be aware of small systematic differences in interval measurements due to different algorithm methodologies, within-individual interval measurement comparisons should use comparable methods, and further attempts to harmonize interval measurement methodologies are warranted.
Value of the “Standing Test” in the Diagnosis and Evaluation of Beta-blocker Therapy Response in Long QT Syndrome
2017, Revista Espanola de CardiologiaLos pacientes con síndrome de QT largo (SQTL) tienen una adaptación anormal del QT a los cambios bruscos de la frecuencia cardiaca producidos con la bipedestación. Este trabajo estudia la utilidad del test de bipedestación en una cohorte de pacientes con SQTL y evalúa si el fenómeno de «mala adaptación» del QT se normaliza con el tratamiento con bloqueadores beta.
Se realizó un electrocardiograma basal y otro inmediatamente tras la bipedestación a 36 pacientes con SQTL (6 [17%] con QTL1, 20 [56%] con QTL2, 3 [8%] con QTL7 y 7 [19%] con genotipo no identificado) y 41 controles. Se midió el intervalo QT corregido (QTc) basal (QTcdecúbito) y tras la bipedestación (QTcbipedestación) y el incremento del QTc (ΔQTc = QTcbipedestación – QTcdecúbito). Se repitió el test en 26 de los pacientes bajo tratamiento con bloqueadores beta.
El QTcbipedestación y el ΔQTc fueron mayores en el grupo de SQTL que en el grupo control (QTcbipedestación, 528 ± 46 frente a 420 ± 15 ms; p < 0,0001; ΔQTc, 78 ± 40 frente a 8 ± 13 ms; p < 0,0001). No hubo diferencias significativas entre los pacientes con QTL1 y QTL2. Los pacientes con SQTL presentaron patrones típicos del segmento ST-onda T tras la bipedestación. Las curvas receiver operating characteristic del QTcbipedestación y ΔQTc mostraron un incremento significativo del valor diagnóstico comparadas con la del QTcdecúbito (área bajo la curva de ambos, 0,99 frente a 0,85; p < 0,001). El tratamiento con bloqueadores beta atenuó la respuesta a la bipedestación de los pacientes con SQTL (en tratamiento, QTcbipedestación, 440 ± 32 ms [p < 0,0001] y ΔQTc, 14 ± 16 ms [p < 0,0001]).
La evaluación del intervalo QTc tras la bipedestación proporciona un alto rendimiento diagnóstico y podría ser de gran utilidad en la monitorización del tratamiento con bloqueadores beta en los pacientes con SQTL.
Patients with congenital long QT syndrome (LQTS) have an abnormal QT adaptation to sudden changes in heart rate provoked by standing. The present study sought to evaluate the standing test in a cohort of LQTS patients and to assess if this QT maladaptation phenomenon is ameliorated by beta-blocker therapy.
Electrographic assessments were performed at baseline and immediately after standing in 36 LQTS patients (6 LQT1 [17%], 20 LQT2 [56%], 3 LQT7 [8%], 7 unidentified-genotype patients [19%]) and 41 controls. The corrected QT interval (QTc) was measured at baseline (QTcsupine) and immediately after standing (QTcstanding); the QTc change from baseline (ΔQTc) was calculated as QTcstanding – QTcsupine. The test was repeated in 26 patients receiving beta-blocker therapy.
Both QTcstanding and ΔQTc were significantly higher in the LQTS group than in controls (QTcstanding, 528 ± 46 ms vs 420 ± 15 ms, P < .0001; ΔQTc, 78 ± 40 ms vs 8 ± 13 ms, P < .0001). No significant differences were noted between LQT1 and LQT2 patients. Typical ST-T wave patterns appeared after standing in LQTS patients. Receiver operating characteristic curves of QTcstanding and ΔQTc showed a significant increase in diagnostic value compared with the QTcsupine (area under the curve for both, 0.99 vs 0.85; P < .001). Beta-blockers attenuated the response to standing in LQTS patients (QTcstanding, 440 ± 32 ms, P < .0001; ΔQTc, 14 ± 16 ms, P < .0001).
Evaluation of the QTc after the simple maneuver of standing shows a high diagnostic performance and could be important for monitoring the effects of beta-blocker therapy in LQTS patients.
Full English text available from: www.revespcardiol.org/en
Clinical profile and mutation spectrum of long QT syndrome in Saudi Arabia: The impact of consanguinity
2017, Heart RhythmCongenital long QT syndrome (LQTS) is an inherited, potentially fatal arrhythmogenic disorder. At least 16 genes have been implicated in LQTS; the yield of genetic analysis of 3 genes (KCNQ1, KCNH2, and SCN5A) is about 70%, with KCNQ1 mutations accounting for ∼50% of positive cases. LQTS is mostly inherited in an autosomal dominant pattern. Systemic analysis of LQTS has not been previously conducted in a population with a high degree of consanguinity.
To describe the clinical and molecular profiles of LQTS in the highly consanguineous Saudi population.
Fifty-six Saudi families with LQTS were consecutively recruited and evaluated. Sequencing of KCNQ1, KCNH2, and SCN5A genes was conducted on all probands, followed by screening of family relatives.
Genetic analysis was positive in 32 (57.2%) families, with mutations in KCNQ1 identified in 28 families (50%). Surprisingly, 17 (53.1%) probands were segregating homozygous mutations. Family screening identified 123 individuals with mutations; 89 (72.4%) were heterozygous, 23 (18.7%) were homozygous, and 11 (8.9%) were compound heterozygous. Compared to heterozygous, the phenotype was more severe in homozygous individuals, with cardiac symptoms in 78.3% (vs 12.4%), family history of sudden death in 64.7% (vs 44.4%), and prolonged QT interval in 100% (vs 43.8%). Congenital deafness was found in 11 (47.8%) homozygous probands.
Our study provides insight into the clinical and molecular profiles of LQTS in a consanguineous population. It underscores the importance of preemptive management in homozygous patients with LQTS and the value of clinical and molecular screening of at-risk relatives.
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Please address all correspondence to: Pascale Guicheney, INSERM UR153, Hôpital Pitié-Salpétrière, Institut de Myologie, 47 boulevard de l'Hôpital, 75013 Paris, France.