OBJECTIVES: Genetic testing, a gold standard for long QT syndrome (LQTS) diagnosis, is time-consuming and costly when all the 15 candidate genes are screened. Since genotype-specific ECG patterns are present in most LQT1-3 mutation carriers, we tested the utility of ECG-guided genotyping in a large cohort of Chinese LQTS patients. METHODS AND RESULTS: We enrolled 230 patients (26 ± 17 years, 66% female) with a clinical diagnosis of LQTS. Genotypes were predicted as LQT1-3 based on the presence of ECG patterns typical for each genotype in 200 patients (85 LQT1, 110 LQT2 and 5 LQT3). Family-based genotype prediction was also conducted if gene-specific ECG patterns were found in other affected family members. Mutational screening identified 104 mutations (44% novel), i.e. 46 KCNQ1, 54 KCNH2 and 4 SCN5A mutations. The overall predictive accuracy of ECG-guided genotyping was 79% (157/200) and 79% (67/85), 78% (86/110) and 80% (4/5) for LQT1, LQT2 and LQT3, respectively. The predictive accuracy was 98% (42/43) when family-based ECG assessment was performed. CONCLUSIONS: From this large-scale genotyping study, we found that LQT2 is the most common genotype among the Chinese. Family-based ECG-guided genotyping is highly accurate. ECG-guided genotyping is time- and cost-effective. We therefore recommend it as an optimal approach for the genetic diagnosis of LQTS.
OBJECTIVES: Genetic testing, a gold standard for long QT syndrome (LQTS) diagnosis, is time-consuming and costly when all the 15 candidate genes are screened. Since genotype-specific ECG patterns are present in most LQT1-3 mutation carriers, we tested the utility of ECG-guided genotyping in a large cohort of Chinese LQTS patients. METHODS AND RESULTS: We enrolled 230 patients (26 ± 17 years, 66% female) with a clinical diagnosis of LQTS. Genotypes were predicted as LQT1-3 based on the presence of ECG patterns typical for each genotype in 200 patients (85 LQT1, 110 LQT2 and 5 LQT3). Family-based genotype prediction was also conducted if gene-specific ECG patterns were found in other affected family members. Mutational screening identified 104 mutations (44% novel), i.e. 46 KCNQ1, 54 KCNH2 and 4SCN5A mutations. The overall predictive accuracy of ECG-guided genotyping was 79% (157/200) and 79% (67/85), 78% (86/110) and 80% (4/5) for LQT1, LQT2 and LQT3, respectively. The predictive accuracy was 98% (42/43) when family-based ECG assessment was performed. CONCLUSIONS: From this large-scale genotyping study, we found that LQT2 is the most common genotype among the Chinese. Family-based ECG-guided genotyping is highly accurate. ECG-guided genotyping is time- and cost-effective. We therefore recommend it as an optimal approach for the genetic diagnosis of LQTS.
Authors: Ankavipar Saprungruang; Apichai Khongphatthanayothin; John Mauleekoonphairoj; Pharawee Wandee; Supaluck Kanjanauthai; Zahurul A Bhuiyan; Arthur A M Wilde; Yong Poovorawan Journal: Indian Pacing Electrophysiol J Date: 2018-07-20