INTRODUCTION: Previous studies showed that diagnosing congenital long QT syndrome (LQTS) is difficult due to variable penetrance and genetic heterogeneity, especially when subjects from multiple families with diverse mutations are combined. We hypothesized that a combination of clinical and ECG techniques could identify gene carriers within a single family with congenital LQTS. METHODS AND RESULTS: One hundred one genotyped members of a family with LQTS, including 26 carriers of a HERG mutation, underwent history and ECG analysis. Forty-eight family members also underwent exercise testing with QT and T wave alternans (TWA) analysis and 24-hour Holter monitoring with QT and heart rate variability analysis. A logistic regression model, which included age, gender, QTc, and QTc by age, provided the best prediction of gene carrier status, although there was substantial overlap (78%) of QTc among subjects with and without the mutation. QTc was not helpful as a discriminator in children < or = 13 years. TWA (observed infrequently) did not add significantly to the model's ability to predict abnormal genotype. CONCLUSION: Even in this homogeneous LQTS population, the phenotype was so variable that clinical and detailed ECG analyses did not permit an accurate diagnosis of gene carrier status, especially in children. Sustained microvolt TWA was a specific (100%) but insensitive (18%) marker for LQTS. Its ability to predict risk of arrhythmia in this population remains to be determined. Genetic testing serves an essential role in screening for carriers of LQTS.
INTRODUCTION: Previous studies showed that diagnosing congenital long QT syndrome (LQTS) is difficult due to variable penetrance and genetic heterogeneity, especially when subjects from multiple families with diverse mutations are combined. We hypothesized that a combination of clinical and ECG techniques could identify gene carriers within a single family with congenital LQTS. METHODS AND RESULTS: One hundred one genotyped members of a family with LQTS, including 26 carriers of a HERG mutation, underwent history and ECG analysis. Forty-eight family members also underwent exercise testing with QT and T wave alternans (TWA) analysis and 24-hour Holter monitoring with QT and heart rate variability analysis. A logistic regression model, which included age, gender, QTc, and QTc by age, provided the best prediction of gene carrier status, although there was substantial overlap (78%) of QTc among subjects with and without the mutation. QTc was not helpful as a discriminator in children < or = 13 years. TWA (observed infrequently) did not add significantly to the model's ability to predict abnormal genotype. CONCLUSION: Even in this homogeneous LQTS population, the phenotype was so variable that clinical and detailed ECG analyses did not permit an accurate diagnosis of gene carrier status, especially in children. Sustained microvolt TWA was a specific (100%) but insensitive (18%) marker for LQTS. Its ability to predict risk of arrhythmia in this population remains to be determined. Genetic testing serves an essential role in screening for carriers of LQTS.
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