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(Circulation. 2000;102:2796.)
© 2000 American Heart Association, Inc.

Editorials

Predicting the Long-QT Genotype From Clinical Data

From Sense to Science

Arthur A. M. Wilde, MD; Dan M. Roden, MD

From the Experimental and Molecular Cardiology Group, Academic Medical Center, University of Amsterdam, and the Interuniversity Cardiology Institute, Netherlands (A.A.M.W.), and the Division of Clinical Pharmacology and Arrhythmia Service, Departments of Medicine and Pharmacology, Vanderbilt University School of Medicine, Nashville, Tenn (D.M.R.).

Correspondence to Dr A.A.M. Wilde, Academic Medical Center, University of Amsterdam, Department of Clinical and Experimental Cardiology, M-0-052, PO Box 22700, 1100 DE Amsterdam, Netherlands. E-mail a.a.wilde{at}amc.uva.nl

Key Words: Editorials • long-QT syndrome • genes • arrhythmias

In the past 3 decades, the congenital long-QT syndrome (LQTS) has emerged as an important paradigm for understanding arrhythmogenesis. An understanding of the electrophysiological basis of arrhythmias in LQTS has now merged with new molecular genetics, solving some problems and raising new ones both in clinical management and in basic arrhythmia mechanisms (for review, see Roden and Spooner¹ ). In this scientific evolution, the international LQT registry has proved to be of paramount importance. Since 1979, data from this registry have proved to be of great value for the diagnosis, prognosis, and management of LQT patients and their relatives, and in more recent years, data from the registry represent a reliable source for attempts to correlate phenotype with genotype and vice versa.

Variability in Presentation of LQTS

We now understand that LQTS can arise as a result of mutations in multiple genes, each encoding an ion channel structural unit. Because ion channels have different time and voltage characteristics, it is tempting to speculate that the clinical presentation may be gene specific, and indeed emerging data support this idea (Table). Phenotypical differences in genetically distinct forms of LQTS may include every aspect of the clinical presentation, ie, the ECG appearance of the ST-T–wave patterns and arrhythmias, symptoms that trigger arrhythmias, QT dynamics during exercise or other triggers, efficacy of different treatment modalities, and the clinical course of affected patients (Table).

View this table: [in this window] [in a new window]   Table 1. Clinical Characteristics in Common Forms of LQTS

A gene-differentiating potential has indeed been shown for symptom-related triggers: swimming and acoustic stimuli typically trigger events in LQT1 and LQT2 patients, respectively.^{2 3 4 5} QT dynamics during exercise vary between genotypes,^{6 7} and data from the registry have suggested that the clinical course (age of onset, prognosis, etc) relies to some extent on the underlying gene defect.⁸ Finally, gene-specific ST-T patterns were described shortly after the recognition of different disease-related genes,⁹ and this concept is expanded on by the LQT registry in a study published in this issue of Circulation.¹⁰

The Present Study

In 284 gene carriers from 29 LQTS families whose genotype was known, Zhang et al¹⁰ first identified 10 "typical" ST-T patterns: 4 in LQT1, 4 in LQT2, and 2 in LQT3. The sensitivity and specificity of these patterns were subsequently tested by 4 cardiologists not involved in the initial pattern characterization study in 23 other LQT1 and LQT2 families (104 gene carriers, 13 mutations) and in 42 previously used LQT3 ECGs (2 mutations). Family-grouped ECG analysis revealed respectable mean sensitivity/specificity of 77%/81%, 79%/88%, and 54%/100% for LQT1, LQT2, and LQT3, respectively. The potential utility of these data is shown by the fact that subsequent prospective genotype identification in 127 families undergoing genetic screening (directed by the ECG findings) revealed 100% sensitivity and specificity for all 3 genotypes in the 56 of 127 families with a specific ST-T–wave pattern and a genotype that was determined.

The extent to which the study can be applied in clinical practice has some limitations. It is important to note that the data cannot be used to diagnose LQTS, but rather to direct mutational analysis to a specific gene. In light of the occasionally very low (electrocardiographically speaking) penetrance of the disease,¹¹ it is surprising that only 10% of patients had normal QT intervals, suggesting some selection bias toward mutations with high penetrance. Furthermore, with current molecular genetic screening techniques, genotype is not established in a significant number of families: 36% in the present study (46 of 127 families) and 57% in a large European series (382 of 670 probands; S. Priori, MD, PhD, personal communication, 2000). Only 80 of 127 families (63%) had a specific ST-T–wave pattern, and even among these 80, no mutation was detected in 24. Part of the explanation may relate to the standard use of single-strand conformation polymorphism (SSCP) analysis to screen families: SSCP is known to be <100% sensitive, ie, some mutations will be missed. Judging the specificity of these ECG patterns requires some correction for this, although it is unlikely that all failures of genotyping reflect incomplete SSCP sensitivity. Thus, typical ECGs may not be so typical: specificity for LQT2 might be 100% if there are no SSCP errors or could be as low as 60% in the worst-case scenario, ie, 100% outcome with SSCP. Conversely, assuming no false-negative assignments, sensitivity remains 100% for all 3 genotypes. The value of the ECG in directing an "educated guess" of genotype (and thus directing efforts at mutational analysis) is even more limited when the ST-T–wave patterns are nonspecific, as they were in 37% of the families; here the guess was correct in 9 of 25 families (36%). Overall, on the basis of data from this prospective validation study with a rather favorable mutation detection score, the a priori chance that in a given family, ECG screening will predict the genotype is 44% (56 of 127). This requires experienced LQT ECG readers able to recognize subtle differences and ECGs from family members, an unusual occurrence for most clinicians. With an estimated prevalence of ±40% of both LQT1 and LQT2 (Table) and a 50% chance that an individual will be genotyped, the likelihood of successful LQT1 or LQT2 genotyping without knowledge of clinical data is ±20%.

Implications for Basic Mechanisms in Repolarization

For the investigator interested in the pathophysiological background of repolarization disorders, the results are fascinating. The LQT ST-T–wave pattern study demonstrates that prolonged broad-based T waves and widened bifid T waves, mostly of low amplitude, are characteristic for LQT1 and LQT2, respectively (present in 88% of both subpopulations).¹⁰ Most notable for LQT3 patients is the long isoelectric segment followed by a normal T-wave duration with a relatively sharp deflection (pattern "a," present in 82% of LQT3 patients with a typical ST-T–wave pattern).¹⁰ These ECG patterns must be telling us something important about the pathophysiology of LQT in these genetically defined subsets. The T wave is the result of repolarization gradients within the ventricles. Alterations in these gradients modify T-wave morphology, including its duration and amplitude, and it has been elegantly demonstrated that in particular, currents flowing down transmural voltage gradients present on either side of the M-cell region during the (ventricular) action potential repolarization phase are of importance.¹² Indeed, a widened T wave most likely reflects an increase in the inhomogeneities of repolarization times (action potential durations) across the ventricular wall. We are beginning to understand that even under physiological conditions, action potential durations vary across the wall of the ventricle and that this variability is determined by physiological differences in the magnitudes of ion currents (including, in some reports, I_Ks and I_Na) in different myocardial cells. Thus, the ECG effects of a mutation in an ion channel gene will be determined by the extent to which the encoded ion channel protein contributes to repolarization, compared with other normal channels in cells across the ventricular wall. The fact that most patterns in the potassium channel defects include widened T waves suggests that the defects cause increased heterogeneity of action potential durations. Conversely, the long isoelectric segment in LQT3 suggests that, at least at rest, there is no substantial heterogeneity in action potential durations in these patients, ie, that the sodium channel defect prolongs action potentials similarly in all cell types.

Recent studies of ECG patterns and action potential durations in a transmural ventricular "wedge" exposed to drugs that block I_Ks or I_Kr or that enhance inward I_Na to mimic LQT1, LQT2, and LQT3 reflect some of the clinical characteristics. Indeed, addition of catecholamines is required for an arrhythmogenic substrate in the LQT1 model,¹³ as is exercise in the clinical setting.^{5 7} Also in the LQT2 model, catecholamines are required, but the increase in QT interval, QT dispersion, and arrhythmogenic potential is transient.¹³ The LQT3 model is arrhythmogenic without the addition of catecholamines, which seems to closely mirror clinical experience, because most arrhythmic events occur at rest.^{5 7} The gene-specific ST-T–wave patterns, however, seem not to be well reproduced in the wedge. This may reflect species difference with consequent species-specific transmural ion channel distribution and/or a more homogeneous effect of drug exposure.

Conversely, the generally lower amplitude of the T wave in LQT2 patients compared with LQT1 patients is nicely simulated in experimental conditions.¹² This may reflect the greater drug-induced dispersion of transmural repolarization in the LQT2 model.¹²

Genotype-Specific Versus Mutation- Specific Phenotypes

Considerable attention to date has been focused on the differences among LQT genotypes. However, in vitro studies indicate that the functional consequences of different individual mutations in the same gene are likely to vary substantially.^{1 14} Functional potassium channels are formed by coassembly of 4 separate structural protein subunits (called -subunits), with an unknown number of function-modifying ß-subunits.¹⁵ Because each -subunit represents a distinct gene product, it is possible for mutant proteins (encoded by disease-associated alleles) to coassemble with normal proteins, ie, functional potassium channels in LQT1 or LQT2 patients may contain both wild-type and mutant protein -subunits, resulting in channels with a range of physiological properties. In fact, these heteromeric channels may be abnormal in a number of unanticipated ways; not only might they gate (open and close) abnormally,¹⁴ but they may also display abnormalities in permeation (1 HERG mutation allows sodium entry, whereas the wild-type channel of course does not)¹⁶ or trafficking.¹⁴ Thus, the clinical phenotype, including the ST-T–wave pattern, is likely to depend on the extent and type of the molecular lesion. For sodium channels, the story seems a bit simpler, because 1 sodium channel molecule is enough to make a functional channel. Nevertheless, substantial differences in in vitro function are now being described among LQT3 mutants, so subsets of clinical phenotypes are likely to emerge.

The Future

An obvious next step for the authors would have been to combine the new ECG data they have accumulated with other criteria, including the symptom-related trigger(s) and age at onset, to increase the likelihood of correct genotype prediction. Adding this information, which is almost certainly present for all families studied, could have turned what was merely a sense of what these ECGs mean into science. The study as it stands helps in directing where geneticists should look in a particular family to get to a diagnosis (if possible) faster, but the increment over currently available clinical discriminators (including cruder ECG criteria) seems small. The emerging basic and clinical data on differences in prognosis and perhaps therapy among these 3 genotypes makes this task more urgent. An expanding collaboration between molecular and clinical scientists is necessary to fully exploit the potential of the LQTS as an important paradigm for arrhythmogenesis.

Footnotes

The opinions expressed in this editorial are not necessarily those of the editors or of the American Heart Association.

References

1. Roden DM, Spooner PM. Inherited long QT syndromes: a paradigm for understanding arrhythmogenesis. J Cardiovasc Electrophysiol. 1999;10:1664–1683.[Medline] [Order article via Infotrieve]
   
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3. Wilde AAM, Jongbloed RJE, Doevendans PA, et al. Auditory stimuli as a trigger for arrhythmic events differentiate HERG-related (LQTS₂) patients from KVLQT1-related patients (LQTS₁). J Am Coll Cardiol. 1999;33:327–332.[Abstract/Free Full Text]
   
4. Moss AJ, Robinson JL, Gessman L, et al. Comparison of clinical and genetic variables of cardiac events associated with loud noise versus swimming among subjects with the long QT syndrome. Am J Cardiol. 1999;84:876–879.[Medline] [Order article via Infotrieve]
   
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8. Zareba W, Moss AJ, Schwartz PJ, et al. Influence of genotype on the clinical course of the long-QT syndrome. N Engl J Med. 1998;339:960–965.[Abstract/Free Full Text]
   
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This Article Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Wilde, A. A. M. Articles by Roden, D. M. Search for Related Content PubMed PubMed Citation Articles by Wilde, A. A. M. Articles by Roden, D. M. Related Collections Electrophysiology Clinical genetics Arrhythmias, clinical electrophysiology, drugs Electrocardiology Genetics of cardiovascular disease