Dataset Information

Genetic testing for long-QT syndrome: distinguishing pathogenic mutations from benign variants.

ABSTRACT: Genetic testing for long-QT syndrome (LQTS) has diagnostic, prognostic, and therapeutic implications. Hundreds of causative mutations in 12 known LQTS-susceptibility genes have been identified. Genetic testing that includes the 3 most commonly mutated genes is available clinically. Distinguishing pathogenic mutations from innocuous rare variants is critical to the interpretation of test results. We sought to quantify the value of mutation type and gene/protein region in determining the probability of pathogenicity for mutations.Type, frequency, and location of mutations across KCNQ1 (LQT1), KCNH2 (LQT2), and SCN5A (LQT3) were compared between 388 unrelated "definite" (clinical diagnostic score >or=4 and/or QTc >or=480 ms) cases of LQTS and >1300 healthy controls for each gene. From these data, estimated predictive values (percent of mutations found in definite cases that would cause LQTS) were determined according to mutation type and location. Mutations were 10 times more common in cases than controls (0.58 per case versus 0.06 per control). Missense mutations were the most common, accounting for 78%, 67%, and 89% of mutations in KCNQ1, KCNH2, and SCN5A in cases and >95% in controls. Nonmissense mutations have an estimated predictive value >99% regardless of location. In contrast, location appears to be critical for characterizing missense mutations. Relative frequency of missense mutations between cases and controls ranged from approximately 1:1 in the SCN5A interdomain linker to infinity in the pore, transmembrane, and linker in KCNH2. These correspond to estimated predictive values ranging from 0% in the interdomain linker of SCN5A to 100% in the transmembrane/linker/pore regions of KCNH2. The estimated predictive value is also high in the linker, pore, transmembrane, and C terminus of KCNQ1 and the transmembrane/linker of SCN5A.Distinguishing pathogenic mutations from rare variants is of critical importance in the interpretation of genetic testing in LQTS. Mutation type, mutation location, and ethnic-specificshould be viewed as variants of uncertain significance and prompt further investigation to clarify the likelihood of disease causation. However, mutations in regions such as the transmembrane, linker, and pore of KCNQ1 and KCNH2 may be defined confidently as high-probability LQTS-causing mutations. These findings will have implications for other genetic disorders involving mutational analysis.

SUBMITTER: Kapa S

PROVIDER: S-EPMC3025752 | biostudies-literature | 2009 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genetic testing for long-QT syndrome: distinguishing pathogenic mutations from benign variants.

Kapa Suraj S Tester David J DJ Salisbury Benjamin A BA Harris-Kerr Carole C Pungliya Manish S MS Alders Marielle M Wilde Arthur A M AA Ackerman Michael J MJ

Circulation 20091019 18

<h4>Background</h4>Genetic testing for long-QT syndrome (LQTS) has diagnostic, prognostic, and therapeutic implications. Hundreds of causative mutations in 12 known LQTS-susceptibility genes have been identified. Genetic testing that includes the 3 most commonly mutated genes is available clinically. Distinguishing pathogenic mutations from innocuous rare variants is critical to the interpretation of test results. We sought to quantify the value of mutation type and gene/protein region in determ ...[more]

PMID: 19841300

Similar Datasets

Project description:BackgroundLong QT syndrome (LQTS) is an inherited arrhythmic disorder characterised by prolongation of the QT interval on ECG, presence of syncope and sudden death. The symptoms in LQTS patients are highly variable, and genotype influences the clinical course. This study aims to report the spectrum of LQTS mutations in a Swedish cohort.MethodsBetween March 2006 and October 2009, two hundred, unrelated index cases were referred to the Department of Clinical Genetics, Umeå University Hospital, Sweden, for LQTS genetic testing. We scanned five of the LQTS-susceptibility genes (KCNQ1, KCNH2, SCN5A, KCNE1, and KCNE2) for mutations by DHPLC and/or sequencing. We applied MLPA to detect large deletions or duplications in the KCNQ1, KCNH2, SCN5A, KCNE1, and KCNE2 genes. Furthermore, the gene RYR2 was screened in 36 selected LQTS genotype-negative patients to detect cases with the clinically overlapping disease catecholaminergic polymorphic ventricular tachycardia (CPVT).ResultsIn total, a disease-causing mutation was identified in 103 of the 200 (52%) index cases. Of these, altered exon copy numbers in the KCNH2 gene accounted for 2% of the mutations, whereas a RYR2 mutation accounted for 3% of the mutations. The genotype-positive cases stemmed from 64 distinct mutations, of which 28% were novel to this cohort. The majority of the distinct mutations were found in a single case (80%), whereas 20% of the mutations were observed more than once. Two founder mutations, KCNQ1 p.Y111C and KCNQ1 p.R518*, accounted for 25% of the genotype-positive index cases. Genetic cascade screening of 481 relatives to the 103 index cases with an identified mutation revealed 41% mutation carriers who were at risk of cardiac events such as syncope or sudden unexpected death.ConclusionIn this cohort of Swedish index cases with suspected LQTS, a disease-causing mutation was identified in 52% of the referred patients. Copy number variations explained 2% of the mutations and 3 of 36 selected cases (8%) harboured a mutation in the RYR2 gene. The mutation panorama is characterised by founder mutations (25%), even so, this cohort increases the amount of known LQTS-associated mutations, as approximately one-third (28%) of the detected mutations were unique.

Project description:Intrauterine fetal death or stillbirth occurs in approximately 1 out of every 160 pregnancies and accounts for 50% of all perinatal deaths. Postmortem evaluation fails to elucidate an underlying cause in many cases. Long QT syndrome (LQTS) may contribute to this problem.To determine the spectrum and prevalence of mutations in the 3 most common LQTS susceptible genes (KCNQ1, KCNH2, and SCN5A) for a cohort of unexplained cases.In this case series, retrospective postmortem genetic testing was conducted on a convenience sample of 91 unexplained intrauterine fetal deaths (mean [SD] estimated gestational age at fetal death, 26.3 [8.7] weeks) that were collected from 2006-2012 by the Mayo Clinic, Rochester, Minnesota, or the Fondazione IRCCS Policlinico San Matteo, Pavia, Italy. More than 1300 ostensibly healthy individuals served as controls. In addition, publicly available exome databases were assessed for the general population frequency of identified genetic variants.Comprehensive mutational analyses of KCNQ1 (KV7.1, LQTS type 1), KCNH2 (HERG/KV11.1, LQTS type 2), and SCN5A (NaV1.5, LQTS type 3) were performed using denaturing high-performance liquid chromatography and direct DNA sequencing on genomic DNA extracted from decedent tissue. Functional analyses of novel mutations were performed using heterologous expression and patch-clamp recording.The 3 putative LQTS susceptibility missense mutations (KCNQ1, p.A283T; KCNQ1, p.R397W; and KCNH2 [1b], p.R25W), with a heterozygous frequency of less than 0.05% in more than 10 000 publicly available exomes and absent in more than 1000 ethnically similar control patients, were discovered in 3 intrauterine fetal deaths (3.3% [95% CI, 0.68%-9.3%]). Both KV7.1-A283T (16-week male) and KV7.1-R397W (16-week female) mutations were associated with marked KV7.1 loss-of-function consistent with in utero LQTS type 1, whereas the HERG1b-R25W mutation (33.2-week male) exhibited a loss of function consistent with in utero LQTS type 2. In addition, 5 intrauterine fetal deaths hosted SCN5A rare nonsynonymous genetic variants (p.T220I, p.R1193Q, involving 2 cases, and p.P2006A, involving 2 cases) that conferred in vitro electrophysiological characteristics consistent with potentially proarrhythmic phenotypes.In this molecular genetic evaluation of 91 cases of intrauterine fetal death, missense mutations associated with LQTS susceptibility were discovered in 3 cases (3.3%) and overall, genetic variants leading to dysfunctional LQTS-associated ion channels in vitro were discovered in 8 cases (8.8%). These preliminary findings may provide insights into mechanisms of some cases of stillbirth.

Project description:Background Diagnosis of congenital long-QT syndrome (LQTS) is complicated by phenotypic ambiguity, with a frequent normal-to-borderline resting QT interval. A 3-step algorithm based on exercise response of the corrected QT interval (QTc) was previously developed to diagnose patients with LQTS and predict subtype. This study evaluated the 3-step algorithm in a population that is more representative of the general population with LQTS with milder phenotypes and establishes sex-specific cutoffs beyond the resting QTc. Methods and Results We identified 208 LQTS likely pathogenic or pathogenic KCNQ1 or KCNH2 variant carriers in the Canadian NLQTS (National Long-QT Syndrome) Registry and 215 unaffected controls from the HiRO (Hearts in Rhythm Organization) Registry. Exercise treadmill tests were analyzed across the 5 stages of the Bruce protocol. The predictive value of exercise ECG characteristics was analyzed using receiver operating characteristic curve analysis to identify optimal cutoff values. A total of 78% of male carriers and 74% of female carriers had a resting QTc value in the normal-to-borderline range. The 4-minute recovery QTc demonstrated the best predictive value for carrier status in both sexes, with better LQTS ascertainment in female patients (area under the curve, 0.90 versus 0.82), with greater sensitivity and specificity. The optimal cutoff value for the 4-minute recovery period was 440 milliseconds for male patients and 450 milliseconds for female patients. The 1-minute recovery QTc had the best predictive value in female patients for differentiating LQTS1 versus LQTS2 (area under the curve, 0.82), and the peak exercise QTc had a marginally better predictive value in male patients for subtype with (area under the curve, 0.71). The optimal cutoff value for the 1-minute recovery period was 435 milliseconds for male patients and 455 milliseconds for femal patients. Conclusions The 3-step QT exercise algorithm is a valid tool for the diagnosis of LQTS in a general population with more frequent ambiguity in phenotype. The algorithm is a simple and reliable method for the identification and prediction of the 2 major genotypes of LQTS.

Dataset Information

Genetic testing for long-QT syndrome: distinguishing pathogenic mutations from benign variants.

Publications

Genetic testing for long-QT syndrome: distinguishing pathogenic mutations from benign variants.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets