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Synopsis: ST-T wave patterns can be useful for stratifying molecular genetic studies.
Source: Zhang L, et al. Circulation 2000;102:2849-2855.
In this paper, Zhang and associates representing five centers from the international long QT syndrome (LQTS) registry attempt to define whether specific ECG patterns are associated with the individual channel abnormalities described in LQTS. Patients with characterized abnormalities in the genes KvLQT1 (LQT1), HERG (LQT2) and SCN5A (LQT3) were included. The study had two phases. In phase I, resting 12-lead ECGs from 284 gene carriers among 29 LQTS families that had undergone genetic analysis were reviewed. There were 131 LQT1 patients from eight families, 93 LQT2 patients from 15 families, and 60 LQT3 patients from six families. The ECGs were reviewed by three associates and the ST-T morphology characterized. In phase II, the criteria for identifying LQTS genotype were perspectively evaluated in 104 newly identified LQT1 and LQT2 gene carriers. Since LQT3 is rare, 42 of the 60 original LQT3 ECGs were reanalyzed without knowledge of the genotype.
Four typical ST-T wave patterns were identified in LQT1 patients, four in LQT2 patients, and two in LQT3 patients. In LQT1, an infantile pattern was seen where a short ST segment merged immediately into the T wave’s upslope. A broad based T-wave pattern in LQT1 was identified by a single smooth broad based T-wave present in most leads but particularly evident in the precordial leads. Some patients with LQT1 had normal T-wave morphology with the QT interval ranging from normal to obviously prolonged. Finally, in LQT1, a late onset, normal appearing T-wave pattern was seen in which the ST segment was prolonged but the T-wave morphology appeared normal. LQT2 is characterized by bifid T waves. These were usually present in most of the 12 leads. The T-wave amplitude was usually low and various morphologies of bifid T waves were seen. In LQT3 two patterns were identified. The first pattern had late onset peaked or biphasic T waves. The T wave had a steep downslope. The QT interval was markedly prolonged. An asymmetrical pattern was also seen in long LQT3 in which the T wave was peaked and asymmetrical with a steep downslope.
All LQT1 and LQT2 families had different mutations yet the typical patterns were similar regardless of the mutation. In addition, it was observed that any or all four of the patterns for both LQT1 and LQT2 could be present in a single family.
In phase 2, 80 of 127 families exhibited patterns characteristic of LQT1, LQT2, or LQT3. In the 56 families in whom a mutation was identified, the ECG correctly predicted the site of the mutation. However, in 24 of 80 families with typical ECG patterns, no mutation was identified so the accuracy of the ECG classification cannot be assessed. Forty-seven of the 127 families had nonspecific ST-T wave patterns that did not fit any single classification. In 25 of these families, a mutation was identified. These mutations classified the family as either LQT1, LQT2, LQT3, LQT5 (MinK or KCNE1 defect), or with multiple mutations. In 22 of the families with nonspecific ECG finding, no mutation was identified.
Zhang et al conclude that ST-T wave patterns can be useful for stratifying molecular genetic studies. When a typical ECG pattern is identified, the suspected gene should be the initial target for genetic testing. This may significantly reduce the time and cost currently required for genetic testing. If therapeutic interventions based on specific genotypes are shown to be effective, then ECG screening could be helpful for therapeutic decision making.
This paper is an extension of an earlier work from the LQTS registry1 analyzing electrocardiographic patterns in patients with this syndrome. As described above, there are a number of different genes involved in LQTS and many mutations in each gene have been reported. These genes affect various ionic channels and different mutations may result in different functional properties. If the electrocardiogram could be used to predict the genetic and functional abnormality, this would simplify screening patients with known long QT syndromes in the future.
The problem clinicians have with the long QT syndrome is extreme variability of ECG findings in affected individuals. Although the gene abnormalities are transmitted with an autosomal dominant pattern, the penetrance is highly variable. In addition, the QT interval is variable and there is considerable overlap between the upper limits of the QT interval in normals and the QT interval seen in affected individuals. Some of the patterns shown in the paper by Zhang et al are quite easy to identify; however, it is disturbing that almost 40% of the patients with LQT1 had a normal appearing T wave and a QT interval that was only slightly prolonged. In addition, the bifid or notched T wave seen in LQT2 may be difficult to distinguish from U waves seen in other conditions that are not associated with malignant arrhythmias. At present, the major problem for clinicians is not to classify the responsible gene based on an electrocardiogram but to make the diagnosis of long QT syndrome. In this respect, this paper merely points out there is some relationship between the channel abnormality and the electrocardiographic manifestations. Unfortunately, it will not help clinicians evaluate patients without documented arrhythmias who present with an electrocardiogram that raises the question of a long QT syndrome or asymptomatic family members of LQTS patients.
1. Moss AJ, et al. Circulation 1995;92:2929-2934.
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