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(Circulation. 2000;101:1237.)
© 2000 American Heart Association, Inc.

Clinical Investigation and Reports

Temporal Repolarization Lability in Hypertrophic Cardiomyopathy Caused by ß-Myosin Heavy-Chain Gene Mutations

Walter L. Atiga, MD; Lameh Fananapazir, MD; Dorothea McAreavey, MD; Hugh Calkins, MD; Ronald D. Berger, MD, PhD

From Johns Hopkins Medical Institutions, Baltimore (W.L.A., H.C., R.D.B.), and the National Institutes of Health, Bethesda (L.F., D.M.), Md.

Correspondence to Ronald D. Berger, MD, PhD, Carnegie 592, Johns Hopkins Hospital, 600 N Wolfe St, Baltimore, MD 21287. E-mail ron{at}tachy.cdisc.jhu.edu

	Abstract

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Background—Certain genetic mutations associated with hypertrophic cardiomyopathy (HCM) carry an increased risk of sudden death. QT variability identifies patients at a high risk for sudden death from ventricular arrhythmias. We tested whether patients with HCM caused by ß-myosin heavy-chain (ß-MHC) gene mutations exhibit labile ventricular repolarization using beat-to-beat QT variability analysis.

Methods and Results—We measured the QT variability index and heart rate–QT interval coherence from Holter monitor recordings in 36 patients with HCM caused by known ß-MHC gene mutations and in 26 age- and sex-matched controls. There were 7 distinct ß-MHC gene mutations in these 36 patients; 9 patients had HCM caused by the malignant Arg⁴⁰³Gln mutation and 8 patients had HCM caused by the more benign Leu⁹⁰⁸Val mutation. The QT variability index was higher in HCM patients than in controls (-1.24±0.17 versus -1.58±0.38, P<0.01), and the greatest abnormality was detected in patients with the Arg⁴⁰³Gln mutation (-0.99±0.49 versus -1.46±0.43 in controls, P<0.05). In keeping with this finding, coherence was lower for the entire HCM group than for controls (P<0.001). Coherence was also significantly lower in patients with the Arg⁴⁰³Gln mutation compared with controls (P<0.05).

Conclusions—These findings suggest that (1) patients with HCM caused by ß-MHC gene mutations exhibit labile repolarization quantified by QT variability analysis and, hence, may be more at risk for sudden death from ventricular arrhythmias, and (2) indices of QT variability may be particularly abnormal in patients with ß-MHC gene mutations that are associated with a poor prognosis.

Key Words: cardiomyopathy, hypertrophic • genetics • electrocardiography

	Introduction

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Hypertrophic cardiomyopathy (HCM) is a genetic cardiac disease with an autosomal-dominant pattern of inheritance; it is characterized by left ventricular hypertrophy in the absence of another cause for the increased cardiac mass, and it is the most common cause of sudden death in otherwise healthy young individuals.¹ The identification of patients who are at a high risk for sudden death remains an important challenge. Ventricular tachycardia is common in patients with HCM, and sudden death is thought to be caused by ventricular arrhythmias in most patients.^{1 2} Several investigators have attempted to identify HCM patients prone to sudden death from ventricular arrhythmias using ambulatory Holter monitoring,^{2 3 4} signal-averaged electrocardiography,^{1 5 6 7} tests of autonomic dysfunction and heart rate variability,⁸ QT interval prolongation and dispersion measurements,^{9 10 11} and programmed ventricular stimulation.^{5 12}

HCM, however, is not a single disease; it is caused by a variety of molecular defects associated with abnormalities of the cardiac contractile proteins that have different natural histories.^{13 14 15 16} For example, the Arg⁴⁰³Gln ß-myosin heavy-chain (ß-MHC) mutation has been associated with a high disease penetrance and incidence of sudden death, but the Val⁹⁰⁸Met and the Gly²⁵⁶Glu mutations are associated with a low disease penetrance and a benign prognosis.^{15 16} To our knowledge, no study has assessed the potential for ventricular arrhythmias in HCM patients on a mutation-specific basis. Recent evidence indicates that repolarization abnormalities may underlie ventricular arrhythmias in diverse substrates.¹⁷ We developed a method for analyzing and quantifying beat-to-beat fluctuations in ventricular repolarization in terms of QT interval variability on the surface ECG.¹⁸ In this study, we sought to test whether HCM patients with known ß-MHC gene mutations exhibit labile ventricular repolarization using beat-to-beat QT variability analysis.

	Methods

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Patient Population
Patients with HCM associated with distinct ß-MHC gene mutations who are followed at the National Institutes of Health were eligible for this study. None of the patients studied had prior sustained ventricular arrhythmias or cardiac arrest. All patients had been off any cardioactive medications for 5 half-lives at the time of data collection. Patients were excluded if they had excessive (>5%) ectopic atrial or ventricular beats, were in a rhythm other than normal sinus on Holter monitoring, had a permanent pacemaker, or had excessive noise on the electrocardiographic signal that precluded analysis of the ECG waveform. We studied 36 patients with 7 distinct ß-MHC mutations; their clinical characteristics are shown in Table 1. Six of the patients who had inherited ß-MHC gene mutations responsible for HCM in their remaining affected family members in the kindred had normal echocardiograms (impaired disease penetrance). Of these, 2 had abnormal 12-lead electrocardiograms.

View this table: [in this window] [in a new window]   Table 1. Characteristics of the Patients and Controls

Methods used to identify the genetic defects have been reported previously.^{15 16} Informed consent for genetic analysis was obtained in accordance with study protocols approved by the Review Board of the National Heart, Lung, and Blood Institute. A total of 26 age- and sex-matched normal volunteers without a history or evidence of heart disease were enrolled in the study as controls. When 2 HCM patients from different mutation subgroups were of same age and sex, the same normal control was used for comparison in both subgroups. Thus, equal numbers of data were used for each subgroup comparison between HCM patients and controls, although there were fewer total controls than HCM patients. In no case was there >1 HCM patient of the same age and sex in each mutation subgroup.

Data Collection and Analysis
All patients and controls underwent ambulatory Holter monitoring with 2 unfiltered ECG limb leads (leads I and II) using an analog tape recording system (Oxford Medical Inc). In each subject, a 256-s epoch was obtained from Holter tapes played back at 24 times real-time on an audio cassette deck (Tascam Portastudio 424, Teac Corp). These epochs were obtained from a segment of the Holter tape during which the subjects were awake and sitting still to obtain signals with the least amount of motion artifact. The ECG signals were digitized with 12-bit precision at 400 samples/s with a multichannel data acquisition system (Biopac Systems, Inc) connected to a PC and stored on removable magnetic media for off-line analysis. Temporal QT interval variability analysis of sinus rhythm data was then performed on a UNIX workstation (Sun Microsystems) using an algorithm for QT interval measurement that has been described in detail previously.¹⁸

Briefly, after baseline wander removal and R-wave detection, the algorithm finds the QT interval of each beat by determining how much the ST segment and T-wave must be stretched or compressed in time so as to best match a preselected template beat. The template is defined to include the entire T wave and the U wave (if present), because the latter phases of repolarization may exhibit lability. Evenly sampled heart rate and QT interval time series were then constructed from the sequence of RR and QT intervals.¹⁹ The heart rate mean (HRM) and variance (HRV) and QT interval mean (QTM) and variance (QTV) were computed from the respective time series for each 5-minute epoch. A normalized QT variability index (QTVI) was then derived for each epoch according to the equation:

The QTVI is thus taken as the logarithm of a quotient. The quotient quantifies the ratio between QT and heart rate variabilities; each is internally normalized by their respective mean-squares. Because a quotient is not Gaussian-distributed, the logarithm is taken to provide a normally distributed index and allow for standard statistical testing.

Power spectra of the heart rate and QT interval time series and the cross spectrum between the 2 processes were computed from 1024-point (256-s) segments using the Blackman-Turkey method.^{20 21} The coherence function () was then computed according to the relation:

where is frequency, P_xx() is the heart rate spectrum, P_yy() is the QT interval spectrum, and P_xy() is the cross spectrum. The coherence provides a measure between 0 and 1 of the degree of linear interaction between heart rate and QT interval fluctuations as a function of the frequency of those fluctuations. A measure of mean coherence was obtained by averaging () over the frequency band from 0 to 0.2 Hz.

All HCM patients also underwent echocardiographic examination. Two-dimensional echocardiographic images were obtained in a number of cross-sectional planes using standard transducer positions to determine maximal ventricular wall thickness.

Statistical Analysis
All data are expressed as mean±SD. Comparisons between HCM patients and controls for study variables were done using the unpaired Student’s t test for normally distributed parameters and the Mann-Whitney U-test for non-normally distributed data. Statistical comparisons were not performed between HCM patients with the Arg⁸⁷⁰His and the Arg⁶⁶³His mutations and their respective controls because of the small number of patients in each of these subgroups. Statistical significance for all tests was accepted at the P<0.05 level.

	Results

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Temporal Heart Rate and QT Interval Variability
HCM Patients Versus Controls
Summary data on heart rate and QT interval means and variances that compare HCM patients with controls are shown in Figure 1 and Table 2. When all HCM patients were considered as a single group, no significant differences existed in HRM, QTM, HRV, or QTV between HCM patients and controls. However, as shown in Figure 2, the QTVI was higher in HCM patients than in controls (-1.24±0.17 versus -1.58±0.38, P<0.01). Thus, although neither the absolute QT interval variability nor the heart rate variability differed significantly from controls, normalizing QT variability by the degree of heart rate variability brought out the excess repolarization lability found in HCM patients, as quantified by the QTVI.

View larger version (30K): [in this window] [in a new window]   Figure 1. Group differences in HRM (a), QTM (b), HRV (c), and QTV (d). Central line represents distribution median, box spans from 25th to 75th percentiles, and error bars extend from 10th to 90th percentiles.

View this table: [in this window] [in a new window]   Table 2. Summary Data of the Patients and Controls

View larger version (20K): [in this window] [in a new window]   Figure 2. QTVI distributions in control subjects and all HCM patients. Box plot distributions as in Figure 1.

Mutation-Specific Findings
We examined the heart rate and QT interval means and variances and determined the QTVI for each ß-MHC group and compared them with each group’s age- and sex-matched controls (Table 2), except for the Arg⁸⁷⁰His and the Arg⁶⁶³His mutation subgroups, in which too few patients existed for valid comparisons. Substantial variation existed in QTV among the different subgroups, probably because of differences in mean patient age in these subgroups. Statistical testing between subgroups was not performed because of these age differences. The QTVI was higher for each HCM mutation subgroup tested than its respective control group. These differences in QTVI were statistically significant in those HCM patients with the Arg⁴⁰³Gln mutation (-0.99±0.49 versus -1.46±0.43, P<0.05). With the exception of a higher QTV in those with the Gly²⁵⁶Glu mutation compared with their respective controls, the HRM, QTM, HRV, and QTV were not significantly different for any of the mutation-specific groups compared with their corresponding controls.

Coherence
HCM Patients Versus Control Subjects
The mean coherence between heart rate and QT interval fluctuations for HCM patients and controls is shown in Table 2. When the HCM patients were considered as a single group, their coherence was significantly lower than that of controls (Figure 3, P<0.001), which indicates reduced coupling between heart rate and QT interval variations existed for HCM patients compared with control subjects.

View larger version (23K): [in this window] [in a new window]   Figure 3. Mean coherence distributions in control subjects and HCM patients. Box plot distributions as in Figure 1.

Mutation-Specific Findings
When mutation-specific differences were considered, mean coherence was lower in nearly all HCM mutation subgroups (except for those with the Arg⁶⁶³His mutation) than each group’s respective age- and sex-matched controls. This difference was statistically significant (P<0.05) in those with the Arg⁴⁰³Gln mutation. HCM patients with the Arg⁴⁰³Gln mutation also had the lowest mean coherence of any HCM subgroup (Table 2).

	Discussion

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Major Findings
We found that patients with HCM demonstrated higher normalized beat-to-beat QT interval variability than controls, suggesting that these patients have a greater amount of temporal repolarization lability. In addition, mean coherence was significantly lower in HCM patients than in controls, indicating that fluctuations in QT interval occurred with a reduced coupling to heart rate for HCM patients. When individual HCM mutations were considered, each mutation subgroup had a higher QTVI than its respective controls. These group-specific differences from controls were statistically significant in HCM patients with the Arg⁴⁰³Gln mutation. Similarly, coherence between heart rate and QT interval was lower than that in the respective controls in 6 of the 7 HCM mutation subgroups; this again reached statistical significance in the Arg⁴⁰³Gln mutation subgroup.

Genotype-Phenotype Correlations in Hypertrophic Cardiomyopathy
A prominent feature of familial HCM is its genetic diversi-ty,^{13 14 15 16 22 23 24 25 26 27 28 29 30 31} which leads to markedly variable phenotypic and clinical presentations.³² HCM demonstrates nonallelic (intergenic) heterogeneity in that 7 genes have been shown to cause it, including those coding for ß-MHC,^{23 24} -tropomyosin,^{25 26} cardiac troponin T^{25 26} and troponin I,³⁰ cardiac myosin binding protein-C,²⁸ and essential and regulatory light chains of myosin.²⁹ The genotypic heterogeneity of HCM is accompanied by phenotypic diversity; the natural course of HCM in certain families is more malignant than in others, and disease severity varies even among individuals of a particular kindred.

HCM is associated with an increased risk for sudden death. Recently, it was recognized that certain ß-MHC gene mutations are associated with a particularly high risk for sudden death.^{13 14 15 16} For example, in several families, the Arg⁴⁰³Gln mutation has been associated with almost complete disease penetrance and a survival rate of only 50% at the age of 30 years.¹⁵ However, both the Leu⁹⁰⁸Val and the Gly²⁵⁶Glu mutations are associated with a low disease penetrance and risk of sudden death.^{15 31}

Given the genotypic and phenotypic heterogeneity of HCM, it is not surprising that prior studies using broadly applied noninvasive measures for the risk stratification of HCM patients have shown conflicting results and have had limited sensitivity and specificity. In the present study, we used a noninvasive measure of beat-to-beat QT interval variability in HCM patients on a mutation-specific basis to determine whether differences in temporal ventricular repolarization lability exist compared with controls.

Significance of Repolarization Lability
We previously showed that patients with ischemic and nonischemic dilated cardiomyopathy demonstrate higher beat-to-beat QT interval variability and reduced coherence between heart rate and QT interval than controls.¹⁸ We subsequently showed in patients with ischemic and nonischemic heart disease referred for electrophysiologic testing that the QTVI identified patients with sudden death and predicted arrhythmia-free survival.³³ The present study provides evidence that repolarization abnormalities may play an important role in the genesis of malignant arrhythmias in patients with familial HCM, particularly those with a mutation associated with a high incidence of sudden death.

Other investigators have examined the role of abnormal repolarization in patients with HCM.^{9 10 11 34} Dritsas et al⁹ demonstrated the presence of a prolonged QT interval and increased corrected QT dispersion in 24 patients with HCM. As part of a study of corrected QT interval in children with several types of cardiomyopathies, Martin et al¹⁰ reported on 25 patients with HCM and found that a prolonged corrected QT interval was common but that it was a poor predictor of ventricular arrhythmia and cardiac arrest in children with HCM. In a retrospective study, Buja et al¹¹ examined QT interval and QT dispersion in 26 HCM patients, half of whom had prior ventricular arrhythmias (8 of which were nonsustained) and compared these measurements with those from 13 normal subjects. The authors found that QT dispersion was significantly increased in patients with HCM, especially in those who had ventricular arrhythmias.

Although these studies provided evidence for abnormal spatial ventricular repolarization in HCM patients, they did not assess temporal repolarization abnormalities. Recently, Momiyami et al³⁴ demonstrated that the presence of T-wave alternans during exercise identified those HCM patients considered to be at high risk for ventricular arrhythmias, thus providing evidence that unstable repolarization may be a marker of high risk in these patients. However, none of the above studies took into account genotypic and phenotypic heterogeneity among HCM patients.

Our study specifically addressed the issue of genotypic and phenotypic variability and the importance of these factors on the mechanisms of malignant ventricular arrhythmias and sudden death. It is interesting to note that QT interval variability was highest and that coherence between heart rate and QT interval was lowest for patients with the mutation associated with the highest risk for sudden death, the Arg⁴⁰³Gln ß-MHC mutation. Prior studies have demonstrated that ventricular tachycardia is rarely induced in these patients during electrophysiological studies, but that a high prevalence of myocardial ischemia exists in these patients, which is often accompanied by symptoms of impaired consciousness.^{15 16} This suggests that the mechanism underlying malignant ventricular arrhythmias in HCM patients with the Arg⁴⁰³Gln mutation may be related to myocardial ischemia. Conceivably, ischemic mechanisms may also underlie the temporal repolarization abnormalities we observed in this patient subgroup.

Clinical Implications
The results of our study suggest that repolarization lability may play an important role in the mechanism of ventricular arrhythmias in patients with HCM, particularly in those with a known ß-MHC mutation associated with a poor prognosis, such as the Arg⁴⁰³Gln mutation. Our findings that those patients with the most malignant mutation had the highest normalized QT variability and the lowest coherence between heart rate and QT interval also suggest that this noninvasive measurement may be useful as a tool for risk stratification, although this hypothesis needs to be tested prospectively.

Limitations
Although we attempted to include similar numbers of HCM patients in each ß-MHC mutation subgroup, some kindreds were much larger than others, allowing more members to meet entry criteria for the study. Thus, comparisons between the various mutations could not be performed, which limited our analyses to comparisons with each subgroup’s respective age- and sex-matched controls. Additional kindreds of each mutation must be found before comparisons between mutation-specific groups can be performed. Also, an important factor that must be considered is that several patients were from kindreds in which many members had sudden death, which led to selection bias for survivors less prone to die suddenly. However, the fact that a significant difference existed between those with the Arg⁴⁰³Gln mutation and controls indicates the ability of the QTVI to identify temporal ventricular repolarization abnormalities, even in patients with mild disease.

Finally, we note that QT variability was assessed in each patient on the basis of a single 256-s ECG epoch, so our measurements may be subject to sampling errors. However, we previously showed that QT variability is highly reproducible over 24 hours in diverse patient groups.³⁵ Furthermore, it is unlikely that group differences between HCM patients and controls can be explained on the basis of sampling errors.

	Acknowledgments

 
Dr Berger is a recipient of a FIRST Award (R29-HL-54584) from the National Heart, Lung, and Blood Institute and is a Solo Cup Clinician Scientist. This work was supported by grant P50-HL-52307 from the National Heart, Lung, and Blood Institute. The authors thank Dorothy Tripodi for her expert technical assistance in the data collection.

	Footnotes

 
Dr Berger is a consultant for and holds equity in Robin Medical, Inc, which is developing QT variability instrumentation. The terms of this arrangement are being managed by Johns Hopkins University in accordance with its conflict of interest policies.

Received March 10, 1999; revision received September 23, 1999; accepted October 7, 1999.

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