ClinicalGeneticGenotype-specific QT correction for heart rate and the risk of life-threatening cardiac events in adolescents with congenital long-QT syndrome
Introduction
The identification of genes associated with congenital long QT syndrome (LQTS) has had a major impact on understanding the molecular basis for ventricular arrhythmias and sudden cardiac death (SCD) in young patients without structural heart disease.1 Numerous advances have been made in the identification of risk factors for cardiac events in LQTS patients.2, 3, 4, 5, 6 However, there remains a substantial challenge to explain the widely observed genotype-phenotype variability of this genetic disorder.
A prolonged QT interval corrected for heart rate (QTc) is a major risk factor for cardiac events in LQTS patients,4, 5, 7, 8 and is usually assessed using the exponential Bazett9 and Fridericia10 correction formulas. However, heart rate–related risk of cardiac events in LQTS patients has been shown to occur in a gene-specific manner.3, 11, 12 Specifically, 82% of the lethal arrhythmic episodes in LQTS type 1 (LQT1) patients, who harbor mutations that impair the IKs current, are associated with exercise and faster heart rates, whereas in LQTS type 2 (LQT2) patients, in whom IKs current is normal, symptoms occur mostly during the night or with arousal triggers.11 This may be because the repolarizing current IKs activates during increased heart rate, and is essential for QT interval adaptation during tachycardia.13 Thus, it has been shown that faster heart rates are associated with increased arrhythmic risk in LQT1 patients,12, 14 and it is possible that the RR interval provides incremental prognostic information to mere assessment of QTc as currently calculated by QT correction formulas, particularly in LQT1 patients with fast resting heart rates.
The present study was designed to evaluate whether risk stratification for life-threatening cardiac events in LQTS patients who carry the common LQT1 and LQT2 genotypes should incorporate a genotype-specific QT correction for heart rate.
Section snippets
Study population
The study population was drawn from subjects enrolled in the International Long QT Syndrome Registry,2 for whom follow-up data were available from age 10 through 20 years. Genetic testing was performed on 3,374 members of 443 families enrolled in the registry, and identified 1,309 patients with LQT1 (727 patients from 165 proband-identified families with the KCNQ1 mutations) and LQT2 (582 patients from 176 proband-identified families with the KCNH2 mutations) genotypes. Patients with a mutation
Data collection and management
For each patient, data on personal and family history, cardiac events, and therapy were systematically recorded at each visit or medical contact. Clinical data were recorded on prospectively designed forms and included patient and family history and demographic, electrocardiogram (ECG), therapeutic, and cardiac event information. Upon enrollment in the Long QT Registry, a 12-lead ECG was obtained from each patient. From the first recorded ECG, the duration of the QT and RR intervals were
End point
The primary end point of the study was time to aborted cardiac arrest (ACA; requiring external defibrillation as part of the resuscitation) or LQTS-related SCD (death abrupt in onset without evident cause, if witnessed, or death that was not explained by any other cause if it occurred in a nonwitnessed setting), whichever occurred first, from age 10 through 20 years. We focused on life-threatening events during adolescence, which is a time period with a high event risk among the LQTS
Repolarization and heart rate measures
We analyzed the risk associated with the following 4 repolarization measures: the absolute QT interval (model 1); the QT interval corrected for heart rate using Bazett's formula (model 2: QTc = QT/RR1/2); the QT interval corrected for heart rate using Fridericia's formula (model 3: QTc[f] = QT/RR1/3); and the QT interval corrected for heart rate using the linear Framingham formula17 (model 4: QTc[fram] = 0.154(1 − RR) + QT). To evaluate the incremental prognostic contribution of heart rate to
Assessment of an improved QT correction for heart rate
Bazett9 and Fridericia10 derived their QT correction formulas by regressing log(QT) on log(RR) in a population of normal subjects, and observing that the slope was −1/2 and −1/3, respectively. These analyses result in the following log-transformed formulas: ; and . We fit a Cox model that included both log(QT) and log(RR). If Bazett's formula were optimal for risk stratification among LQT1 and LQT2 genotype carriers, the
Statistical analysis
The clinical characteristics of study patients by genotype were compared using the χ2 test and the Fisher exact test for categorical variables, and the Student t test or the Mann-Whitney U test for continuous variables.
Cox proportional hazards regression models were used to assess the independent contribution of each of the 4 repolarization measures, with and without further adjustment for the RR interval, to the development of ACA or SCD during follow-up in LQT1 and LQT2 patients. Prespecified
Results
Baseline clinical and ECG characteristics and cardiac events during follow-up in carriers of the LQT1 and LQT2 genotypes are shown in Table 1. Gender distribution and the frequency of a family history of a LQTS-related SCD were similar in the 2 genotype groups. Baseline heart rates and the corrected QT intervals were similar among LQT1 and LQT2 patients, whereas the absolute QT interval was significantly longer among LQT2 patients as compared with LQT1 patients. The baseline RR and QT intervals
Association between repolarization measures and outcome before further adjustment for the RR interval
Multivariate analysis showed that the exponential Bazett formula was the only correction method that independently predicted the risk of life-threatening events among LQT1 patients, whereas among LQT2 patients all analyzed QT correction formulas showed a similar association with outcome (Table 2). Thus, among LQT1 patients, 100-ms increments in QTc(b) were associated with a significant 2.8-fold increase in the risk of life-threatening cardiac events, whereas among LQT2 patients 100-ms
Association between repolarization measures and outcome after further adjustment for the RR interval
When the RR interval was included as an additional covariate in each of the 4 models, the effects of heart rate were shown to be significantly different between LQT1 and LQT2 patients (Table 2).
In LQT1 patients, each of the 4 repolarization measures was demonstrated to be a more powerful (>3-fold risk increase) and significant predictor of outcome in the models that included the RR interval compared with the respective models that did not include heart rate as a covariate. Multivariate analysis
Genotype-specific QT correction for heart rate
The ratio of the estimated coefficients on log(RR) and log(QT) in the Cox models were different for LQT1 versus LQT2 patients (Table 3). In LQT1 patients, the ratio of the estimated coefficients was about 0.8, significantly different from the ratio implied by the correction of either Bazett (0.5) or Fridericia (0.33), neither of which sufficiently corrects for RR. In LQT2 patients, the ratio of the estimated coefficients on log(RR) and log(QT) was about 0.2 (Table 3). This was not statistically
Discussion
Several important clinical implications emerge from the current study of LQTS patients: (1) resting heart rate is an independent predictor of life-threatening cardiac events in LQT1 but not LQT2 patients, with a statistically significant difference in heart rate–related risk between genotypes; (2) current formulas that correct the QT interval duration for heart rate have important limitations for risk assessment in LQT1 patients; and (3) risk stratification for life-threatening cardiac events
Study limitations
In the present study, we evaluated risk factors for LQTS-related life-threatening cardiac events during adolescence, a time period that has been shown to be associated with the highest event rate in patients with this genetic disorder7 and when heart rates are usually faster than 60 beats/min. However, the phenotypic expression of LQTS has been shown to be age dependent.7, 8 Thus, it is possible that the risk associated with heart rate may be different in older LQTS patients. Further studies
Conclusion
Investigations of clinical aspects and basic causal mechanisms of LQTS have provided novel and important insights into the fundamental nature of the electrical activity of the human heart and into the relationship between disturbances in ion flow and cardiac disease. Our findings suggest that an understanding of the genotype-phenotype relationship in this genetic disorder can lead to improved criteria for risk stratification for life-threatening arrhythmic events in affected patients.
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Cited by (0)
This work was supported in part by research grants HL-33843 and HL-51618 to the University of Rochester Medical Center from the National Institutes of Health, Bethesda, Maryland. Dr. Moss reports receiving a research grant from GeneDx; Dr. Kaufman received research grants from CardioDx and St. Jude Medical. Dr. Ackerman has a consulting relationship and license agreement/royalty arrangement with PGxHealth and received consultant fees from Medtronic, Biotronik, Boston Scientific, and St Jude Medical. This research was carried out while Dr. Alon Barsheshet was a Mirowski-Moss Career Development Awardee at the University of Rochester Medical Center, Rochester, New York.