Long QT Syndrome Genetic Testing Research Articles

The usefulness of QT interval measurement as a screening tool for cascade testing in asymptomatic patients at risk of long QT syndrome

Abstract Background Long QT syndrome (LQTS), an inherited arrhythmic syndrome, remains a public health concern with up to 3000 unexpected deaths in the US annually. A simple 12-lead ECG is the most easily accessible tool for initial screening. Purpose To describe the diagnostic utility of the standard QT correction techniques in 12-Lead ECGs, in a screening population of first-degree relatives of persons with LQTS of known genotype. Methods In this single centre study, data were included on consecutive patients undergoing cascade clinical and genetic testing for LQTS, who had a first degree relative with genotype-positive LQTS, from the years 2019 to 2022. Patient demographics, baseline ECG and genetic results were obtained. The QT interval was manually calculated between three independent readers using the tangent method and corrected using the 4 most commonly used formulae: Bazett (BQTc), Fridericia (FreQTc), Framingham (FraQTc) and Hodges (HQTc). The Mean QT was calculated by taking the average of four consecutive QT measurements in lead II or V5. The QT dispersion (QTd), was also calculated by using the formula: QTd = QT max – QT min. Results Data was available on 97 patients from 14 families. The mean age at screening was 44 years, and 51.5% were males. Two-thirds of patients were asymptomatic (n = 74, 76.3%). Fifteen patients had syncopal events. 72.2% (n = 70) of patients had a family history of arrhythmic death. After clinical screening and genotyping, 46.4% (n = 45) patients were gene positive for either KCNQ1 (75.5%) or KCNH2 (24.5%). Patients with prior syncope were more likely to be gene positive (72.7% vs 39.2%, p = 0.005). The 12-Lead ECG derived QTc result is listed in Table 1, with all correction modalities showing a higher corrected QT in the genotype-positive group (p <0.001). The diagnostic performance of BQTc was similar to that of the newer formulae (FreQTc, FraQTc and HQTc) when correcting for heart rate within the range of 60 – 100bpm as listed in Table 2. At a cut-off value of 440ms, BQTc formula had a sensitivity of 51% and a specificity of 84% for predicting genotype pathogenicity as listed in Table 3. The QT dispersion was higher in patients with KCNH2 compared to those with KCNQ1 (122msec, SD 30.5 vs 74.2 msec, SD 30.4, p value <0.001). Patients with KCNH2 were more likely to require an ICD (83.3% vs 16.7%, p <0.001). The mean Schwartz score in gene positive patient was 2.6 compared to 1.9 (p <0.003). Conclusion Formula correction of QT interval to heart rate had good overall diagnostic performance. Both FreQT and FraQT had high AUROC across different heart rates, though there was no statistically significant difference seen between correction formulae. The ECG remains a good preliminary screening tool method for identifying patients with increased risk LQTS in this population. Larger studies are needed to power for comparisons between QT correction methods.

Current real-world evidence of genetic testing diagnostic yield in a large cohort of long QT syndrome

Abstract Background Diagnostic yield in long QT syndrome (LQTS) ranges between 30-70%, depending on the studied population. LQTS can lead to an unexpected sudden cardiac death. For this reason and due to its wider current availability, genetic testing in patients with suspicion of LQTS has spread. Purpose The aim of this study is to investigate the genetic testing yield among a large cohort of heterogeneous index cases with LQTS phenotype. Methods Diagnostic yield was restrospectively evaluated in a cohort of index cases referred to our laboratory for genetic study with LQTS phenotype. Genetic study was performed with customized libraries through next generation sequencing (NGS), which included copy number variations (CNVs) analysis. Patients with LQTS phenotype studied both with "long QT panels" and with broader cardiovascular panels were included, but those with additional cardiac phenotype (cardiomyopathies, heart defects or catecholaminergic polymorphic ventricular tachycardia) were excluded. Positive genetic reports were considered when a likely pathogenic (LP) or pathogenic (P) variant could explain patient´s phenotype. Inconclusive reports were described when a variant considered risk factor (RF) or a variant of uncertain significance variant (VUS) or a hot-VUS was identified in a clinically relevant gene. Results 1183 index cases were genotyped for LQTS phenotype. Only 164 index cases (13,8%) were studied with broader panels which included between 77 and 368 genes. The rest (n=1019) were studied with LQTS panels (either with small panels which included KCNQ1, KCNH2, KCNE1, KCNE2, SCN5A, KCNJ2, CACNA1C and with up to 36 genes-QT panels). Around 27% (n=321) of the index cases had a positive result. They carried LP/P variants in the following genes: KCNQ1 (n=166, 52%), KCNH2 (n=112), SCN5A (n=25), RYR2 (n=5), CACNA1C (n=3), HCN4 (n=4), KCNJ2 (n=2), KCNE2 (n=2) and CALM2 (n=1). 53,3% of the reports were negative. However, there were some incidental findings: 2 index cases carried P variants in LDLR, 2 carried P variants in PKP2, 2 carried a P variant in MYBPC3 and 1 index case each carried a P variant in DES, TTN and DSG2. From the 231 inconclusive reports, 37 index cases carried the RF variant in KCNE1 (p.Asp85Asn), 2 carried the RF variant in SCN5A (p.Arg1193Gln) and 50 patients carried hot-VUS in KCNQ1, KCNH2, CACNA1C, SCN5a or RYR2 gene. Conclusions In our large cohort of index cases referred for genetic testing for LQTS, diagnostic yield was around 27% when considering only LP/P variants in LQTS or arrhythmic phenotype related genes. Even by including the inconclusive but potentially relevant genetic results (RF and hot VUS), the diagnostic yield in our cohort reaches 35%. This is lower than expected for LQTS cohort. It should be taken into consideration that our cohort consists of heterogeneous patients referred for LQTS genetic testing, which would probably reflects better the real world patients seen in every day practice.

CONGENITAL LONG QT SYNDROME: A SYSTEMATIC REVIEW.

SUMMARYCongenital long QT syndrome (LQTS) is a disorder of myocardial repolarization defined by a prolonged QT interval on electrocardiogram (ECG) that can cause ventricular arrhythmias and lead to sudden cardiac death. LQTS was first described in 1957 and since then its genetic etiology has been researched in many studies, but it is still not fully understood. Depending on the type of monogenic mutation, LQTS is currently divided into 17 subtypes, with LQT1, LQT2, and LQT3 being the most common forms. Based on the results of a prospective study, it is suggested that the real prevalence of congenital LQTS is around 1:2000. Clinical manifestations of congenital LQTS include LQTS-attributable syncope, aborted cardiac arrest, and sudden cardiac death. Many patients with congenital LQTS will remain asymptomatic for life. The initial diagnostic evaluation of congenital LQTS includes obtaining detailed personal and multi-generation family history, physical examination, series of 12-lead ECG recordings, and calculation of the LQTS diagnostic score, called Schwartz score. Patients are also advised to undertake 24-hour ambulatory monitoring, treadmill/cycle stress testing, and LQTS genetic testing for definitive confirmation of the diagnosis. Currently available treatment options include lifestyle modifications, medication therapy with emphasis on beta-blockers, device therapy and surgical therapy, with beta-blockers being the first-line treatment option, both in symptomatic and asymptomatic patients.

Long QT syndrome type 5-Lite: Defining the clinical phenotype associated with the potentially proarrhythmic p.Asp85Asn-KCNE1 common genetic variant

Long QT syndrome (LQTS) genetic test reports commonly exclude potentially proarrhythmic common variants such as p.Asp85Asn-KCNE1. The purpose of this study was to determine whether a discernible phenotype is associated with p.Asp85Asn-KCNE1 and whether relatively common KCNE1 variants underlie transient QT prolongation pedigrees with negative commercial LQTS genetic tests. Retrospective review was used to compare demographics, symptomatology, and QT parameters of individuals with p.Asp85Asn-KCNE1 in the absence of other rare/ultra-rare variants in LQTS-susceptibility genes and those who underwent comprehensive LQTS genetic testing. Compared to the Genome Aggregation Database, p.Asp85Asn-KCNE1 was more prevalent in individuals undergoing LQTS genetic testing (33/1248 [2.6%] vs 1552/126,652 [1.2%]; P= .0001). In 19 of 33 patients (58%), only p.Asp85Asn-KCNE1 was observed. These patients were predominantly female (90% vs 62%; P = .01) and were less likely to experience syncope (0% vs 34%; P = .0007), receive β-blockers (53% vs 85%; P = .001), or require an implantable cardioverter-defibrillator (5.3% vs 33%; P= .01). However, they exhibited a similar degree of QT prolongation (QTc 460 ms vs 467 ms; P = NS). Whole exome sequencing of 2 commercially genotype-negative pedigrees revealed that p.Asp85Asn-KCNE1 and p.Arg36His-KCNE1 traced with a transient QT prolongation phenotype. Functional characterization of p.Arg36His-KCNE1 demonstrated loss of function, with a 47% reduction in peak IKs current density in the heterozygous state. We provide further evidence that relatively common variants in KCNE1 may result in a mild QT phenotype designated as "LQT5-Lite" to distinguish such potentially proarrhythmic common variants (ie, functional risk alleles) from rare pathogenic variants that truly confer monogenic disease susceptibility, albeit with incomplete penetrance.

Factors influencing uptake of familial long QT syndrome genetic testing.

Ongoing challenges of clinical assessment of long QT syndrome (LQTS) highlight the importance of genetic testing in the diagnosis of asymptomatic at-risk family members. Effective access, uptake, and communication of genetic testing are critical for comprehensive cascade family screening and prevention of disease complications such as sudden cardiac death. The aim of this study was to describe factors influencing uptake of LQTS genetic testing, including those relating to access and family communication. We show those who access genetic testing are overrepresented by the socioeconomically advantaged, and that although overall family communication is good, there are some important barriers to be addressed. There were 75 participants (aged 18 years or more, with a clinical and/or genetic diagnosis of LQTS; response rate 71%) who completed a survey including a number of validated scales; demographics; and questions about access, uptake, and communication. Mean age of participants was 46 ± 16 years, 20 (27%) were males and 60 (80%) had genetic testing with a causative gene mutation in 42 (70%). Overall uptake of cascade testing within families was 60% after 4 years from proband genetic diagnosis. All participants reported at least one first-degree relative had been informed of their risk, whereas six (10%) reported at least one first-degree relative had not been informed. Those who were anxious or depressed were more likely to perceive barriers to communicating. Genetic testing is a key aspect of care in LQTS families and intervention strategies that aim to improve equity in access and facilitate effective family communication are needed.

Enhancing the Predictive Power of Mutations in the C-Terminus of the KCNQ1-Encoded Kv7.1 Voltage-Gated Potassium Channel

Despite the overrepresentation of Kv7.1 mutations among patients with a robust diagnosis of long QT syndrome (LQTS), a background rate of innocuous Kv7.1 missense variants observed in healthy controls creates ambiguity in the interpretation of LQTS genetic test results. A recent study showed that the probability of pathogenicity for rare missense mutations depends in part on the topological location of the variant in Kv7.1's various structure-function domains. Since the Kv7.1's C-terminus accounts for nearly 50% of the overall protein and nearly 50% of the overall background rate of rare variants falls within the C-terminus, further enhancement in mutation calling may provide guidance in distinguishing pathogenic long QT syndrome type 1 (LQT1)-causing mutations from rare non-disease-causing variants in the Kv7.1's C-terminus. Therefore, we have used conservation analysis and a large case-control study to generate topology-based estimative predictive values to aid in interpretation, identifying three regions of high conservation within the Kv7.1's C-terminus which have a high probability of LQT1 pathogenicity.

Genetics of Long QT Syndrome

Long QT syndrome (LQTS) is a potentially life-threatening cardiac arrhythmia characterized by delayed myocardial repolarization that produces QT prolongation and increased risk for torsades des pointes (TdP)-triggered syncope, seizures, and sudden cardiac death (SCD) in an otherwise healthy young individual with a structurally normal heart. Currently, there are three major LQTS genes (KCNQ1, KCNH2, and SCN5A) that account for approximately 75% of the disorder. For the major LQTS genotypes, genotype-phenotype correlations have yielded gene-specific arrhythmogenic triggers, electrocardiogram (ECG) patterns, response to therapies, and intragenic and increasingly mutation-specific risk stratification. The 10 minor LQTS-susceptibility genes collectively account for less than 5% of LQTS cases. In addition, three atypical LQTS or multisystem syndromic disorders that have been associated with QT prolongation have been described, including ankyrin-B syndrome, Anderson-Tawil syndrome (ATS), and Timothy syndrome (TS). Genetic testing for LQTS is recommended in patients with either a strong clinical index of suspicion or persistent QT prolongation despite their asymptomatic state. However, genetic test results must be interpreted carefully.

To Be or Not to Be

Congenital long-QT syndrome (LQTS) is a rare heritable disorder that is associated with a high risk of syncope and sudden cardiac death. Since 1996, LQTS has been categorized based on mutations to genes that encode cardiac ion channel subunits or proteins that modulate ionic currents in the heart. The most common LQTS gene mutations involve KCNQ1 (LQT1), KCNH2 (LQT2), and SCN5A (LQT3). Multiple other rare gene mutations have been identified and postulated to cause LQTS (LQT4–LQT13). However, in some cases, the identified mutations are part of a more complex clinical disorder (ie, LQT7 and LQT8) and may not be part of the LQTS in the classical sense. In other cases, such as LQT9, there are limited data supporting a causative link between a mutation and LQTS. Article see p 452 The CAV3 gene encodes an integral membrane protein called caveolin 3. Caveolins play an important role in signal transduction and vesicular transport within cells. Mutations to CAV3 have been found to cause diseases of both skeletal and cardiac muscle. Furthermore, mutations to CAV3 were recently identified as rare, potentially disease-causing mutations in a series of patients referred for LQTS genetic testing.1 In 2006, Vatta et al1 reported finding 1 of 4 novel CAV3 mutations (T78M, A85T, F97C, and S141R) in 6 (0.7%) of 904 unrelated patients. Cellular electrophysiological characterization of 2 of these mutations (F97C and S141R) revealed that the mutations resulted in as much as a 4-fold increase in the late sodium current (INaL). Based on the recognition that …

Epilepsy Misdiagnosed as Long QT Syndrome: It Can Go Both Ways

Cardiogenic seizures are common and could be the sentinel event heralding the presence of congenital long QT syndrome (LQTS). Distinguishing a cardiogenic seizure from a neurogenic one is of the utmost importance. Herein, we present the case of a 12-year-old boy with recurrent episodes of syncope and seizures. Despite absence of QT prolongation on electrocardiogram, absence of documented arrhythmias, a negative LQTS genetic test, and recurrent episodes while on nadolol beta-blocker therapy, he was diagnosed with LQTS and implanted with an implantable cardioverter defibrillator (ICD). When syncope and seizure occurred with normal sinus rhythm documented on the ICD, he was referred to neurology, and an electroencephalogram was positive for numerous bursts of bilaterally synchronous generalized discharges. He was started on antiepileptic treatment after which his seizures resolved. His LQTS diagnosis was removed, beta-blocker therapy discontinued, and his ICD was explanted. He has been seizure-free for over 2 years.

Results of Genetic Testing in 855 Consecutive Unrelated Patients Referred for Long QT Syndrome in a Clinical Laboratory

Our aim was to examine the diagnostic yield of genetic testing in 855 consecutive unrelated cases referred for Long QT syndrome (LQTS). Eight hundred fifty five consecutive patients with a mean age at testing of 27.5±18.6 years, were referred for LQTS genetic testing and had accompanying clinical information. KCNQ1, KCNH2, SCN5A, ANK2, KCNE1, KCNE2, CACNA1C, KCNJ2, CAV3, and SCN4B were analyzed using Next-Generation sequencing in all patients, and 395 patients were also tested for an additional two genes, AKAP9 and SNTA1. We retrospectively analyzed the diagnostic yield of this genetic test and factors that predicted the likelihood of a disease causing mutation using ANOVA, χ2, t-test, and receiver operator curves. At least one mutation was identified in 30.3% of the patients (n=259), and 18 patients (2.1%) had two mutations. Patients with two mutations had a longer QTc interval (p<0.01) than patients with one mutation. A longer QTc duration and family history of LQTS were each associated with a higher yield of positive results on genetic testing (p<0.01 for each). Using a QTc cutoff of 476 msec or greater, the genetic testing had a sensitivity of 72% and a specificity of 49%. Mutations within the transmembrane domain of KCNQ1 were associated with a greater risk of cardiac arrest and syncope relative to mutations in other domains of the gene. Mutations in SCN5A were associated with a higher frequency of cardiac arrest (52.6%). Sequencing-based genetic testing has a sensitivity of 72% and has clinical utility.

Founder mutations characterise the mutation panorama in 200 Swedish index cases referred for Long QT syndrome genetic testing

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.

Letter by Kaufman Regarding Article, “Closer Look at Genetic Testing in Long-QT Syndrome: Will DNA Diagnostics Ever Be Enough?”

HomeCirculationVol. 121, No. 23Letter by Kaufman Regarding Article, “Closer Look at Genetic Testing in Long-QT Syndrome: Will DNA Diagnostics Ever Be Enough?” Free AccessLetterPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessLetterPDF/EPUBLetter by Kaufman Regarding Article, “Closer Look at Genetic Testing in Long-QT Syndrome: Will DNA Diagnostics Ever Be Enough?” Elizabeth S. Kaufman, MD Elizabeth S. KaufmanElizabeth S. Kaufman Heart and Vascular Research Center, MetroHealth Campus of Case Western Reserve University, Cleveland, Ohio Search for more papers by this author Originally published15 Jun 2010https://doi.org/10.1161/CIRCULATIONAHA.109.921593Circulation. 2010;121:e439To the Editor:In his editorial, “Closer Look at Genetic Testing in Long-QT Syndrome: Will DNA Diagnostics Ever Be Enough?,”1 Dr MacRae categorizes genotyping as having no additional benefit in patients who meet clinical criteria for long-QT syndrome. I would like to point out that if the family mutation is unknown, genotyping such patients can be very useful. Knowledge of the long-QT syndrome subtype can help the clinician stratify risk and identify the therapy most likely to be protective. The different genetic subtypes of long-QT syndrome (ie, LQT1, LQT2, and LQT3) have different clinical outcomes and respond differently to various treatments.2,3 The informed clinician can judge when β-blocker medication is adequate and when an implantable cardioverter-defibrillator is required to prevent sudden cardiac death.A second point that deserves emphasis is that genetic testing in borderline phenotype individuals with a known family mutation can be of great value. A negative test identifies those who do not require further testing and treatment, whereas a positive test leads to appropriate follow-up of vulnerable individuals.DisclosuresNone. References 1 MacRae CA. Closer look at genetic testing in long-QT syndrome: will DNA diagnostics ever be enough? Circulation. 2009; 120: 1745–1748.LinkGoogle Scholar2 Priori SG, Schwartz PJ, Napolitano C, Bloise R, Ronchetti E, Grillo M, Vicentini A, Spazzolini C, Nastoli J, Bottelli G, Folli R, Cappelletti D. Risk stratification in the long-QT syndrome. N Engl J Med. 2003; 348: 1866–1874.CrossrefMedlineGoogle Scholar3 Priori SG, Napolitano C, Schwartz PJ, Grillo M, Bloise R, Ronchetti E, Moncalvo C, Tulipani C, Veia A, Bottelli G, Nastoli J. Association of long QT syndrome loci and cardiac events among patients treated with beta-blockers. JAMA. 2004; 292: 1341–1344.CrossrefMedlineGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetails June 15, 2010Vol 121, Issue 23 Advertisement Article InformationMetrics https://doi.org/10.1161/CIRCULATIONAHA.109.921593PMID: 20547937 Originally publishedJune 15, 2010 PDF download Advertisement SubjectsGenetics

Mutations at KCNQ1 and an unknown locus cause long QT syndrome in a large Australian family: Implications for genetic testing

A large Australian family affected with long QT syndrome (LQTS) was studied. The medical characteristics of the 16 clinically affected members were consistent with LQT1. A previously identified mutation in KCNQ1 was found in 12 affected individuals and 1 unaffected infant but absent in 4 affected family members. A haplotype consisting of specific alleles for microsatellites flanking in KCNQ1 was associated with the mutation. This was absent from the four affected individuals without the mutation, who had three different haplotypes in this region, indicating that LQTS is unlikely to be segregating with KCNQ1 in these anomalous family members. A genome scan revealed 12 regions where all four of these individuals shared alleles. One region on chromosome 21 contained the KCNE1, KCNE2, KCNJ6, and KCNJ15 genes. A common variant of KCNE1 was segregating in the family but did not explain the anomalous cases. A candidate region on chromosome 7 contained the AKAP9 and KCND2 genes. A previously reported mutation in the N-terminal Yotiao region of AKAP9 was absent from the family. No evidence was found implicating any other known or suspected LQTS gene. This family shows that there remain unidentified genetic causes of LQTS which are clinically significant and highlights the difficulties associated with genetic testing in LQTS, since we cannot rule out risk in individuals who are negative for the known mutation in KCNQ1 without knowing the second disease locus.

Utility of Treadmill Testing in Identification and Genotype Prediction in Long-QT Syndrome

The clinical diagnosis of long-QT syndrome (LQTS) remains challenging when ECG abnormalities are borderline or intermittent. Despite issues with access, cost, and heterogeneity of LQTS mutations, genetic testing remains the diagnostic gold standard for diagnosis of LQTS. We sought to develop a provocative testing strategy to unmask the LQTS phenotype and relate this to the results of genetic testing. From 1995 to 2008, 159 consecutive patients with suspected LQTS underwent provocative testing that consisted of a modified Bruce protocol treadmill exercise test, with ECGs recorded supine at rest, immediately on standing, and at 1-minute intervals during exercise, at peak exercise, and at 1-minute intervals during the recovery phase. Similar testing was carried out on a stationary bike in a gradual and burst exercise fashion. LQTS was confirmed with genotyping in all 95 affected LQTS patients and excluded with negative family screening in 64 control subjects. Patients were studied before and after initiation of beta-blockers. Of 159 patients, 50 had an LQT1 mutation and 45 had an LQT2 mutation. In the LQTS group, 44.3% of patients had a normal-to-borderline resting QTc interval. LQTS patients exhibited a greater prolongation in QTc with postural change than unaffected patients (LQT1: 40 ms [IQR, 42]; LQT2: 35 ms [IQR, 46]; and LQTS-negative: 21 ms [IQR, 37]; P=0.029). During exercise, LQT1 patients had marked QTc prolongation compared with LQT2 and LQTS-negative patients (LQT1: 65 ms [60], LQT2: 3 ms [46], LQTS negative: 5 ms [41]; P<0.0001). QT hysteresis was more pronounced in patients with LQT2 mutations compared with LQT1 and LQT-negative patients (LQT2: 40 ms [10], LQT1: 15 ms [40]; LQTS-negative: 20 ms [20]; P<0.001). beta-Blockade normalized the QTc changes seen with standing and QT hysteresis. The presence and genotype of LQTS can be predicted by a combination of postural and exercise changes in the QT/RR relationship. beta-Blockade normalized these changes. Routine exercise testing is useful in predicting and directing genetic testing in LQTS.

Genetic Testing for Long-QT Syndrome: Distinguishing Pathogenic Mutations From Benign Variants

Genetic Testing for Long-QT Syndrome: Distinguishing Pathogenic Mutations From Benign Variants

Genetic Testing for Long-QT Syndrome

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-specific should 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.

Closer Look at Genetic Testing in Long-QT Syndrome

Increasingly affordable sequencing has led to an explosion of DNA diagnostics and has fueled the hope for a genetic revolution in medicine. The popular vision is of definitive prediction of lifetime risk for a broad range of conditions from the primary analysis of each individual’s genomic sequence.1,2 The resultant panel of sequence variants will define the specific traits to which an individual is susceptible, triggering the institution of preventive measures or targeted therapies. Efficacy and safety will be largely assured for each of the chosen interventions. However, with the potential exception of pharmacogenetic studies in which the molecular targets are known, robust genotype-phenotype correlations are remarkably sparse and, in most instances, simply inadequate for rigorous risk prediction.3 Although genetics has transformed our understanding of the biology of disease, on closer examination it is not immediately evident when the “genomic revolution” will be realized as currently conceived for many cardiovascular conditions.3,4 Articles see pp 1752 and 1761 Nothing tests the tools of clinical risk prediction quite like sudden death.5 The difficulties encountered in the clinical application of genetic data, even in inherited conditions such as the long-QT syndrome (LQTS), in which the transmitted risk of sudden death is several hundred-fold greater than that in the general population, highlight some of the hurdles that must be overcome if DNA diagnosis is ever to transform cardiovascular medicine. Genetic testing for LQTS has been commercially available for several years, but a critical analysis of the clinical utility of test results reveals a rather mixed picture (see the Table).4 View this table: Table. Utility of LQTS Genetic Testing Genetic testing is commonly performed in those with a family history of LQTS and a known mutation, yet often the rationale is debatable. Individuals meeting the clinical criteria for LQTS in such families have …

Spectrum and prevalence of mutations from the first 2,500 consecutive unrelated patients referred for the FAMILION ® long QT syndrome genetic test

Long QT syndrome (LQTS) is a potentially lethal, highly treatable cardiac channelopathy for which genetic testing has matured from discovery to translation and now clinical implementation. Here we examine the spectrum and prevalence of mutations found in the first 2,500 unrelated cases referred for the FAMILION LQTS clinical genetic test. Retrospective analysis of the first 2,500 cases (1,515 female patients, average age at testing 23 +/- 17 years, range 0 to 90 years) scanned for mutations in 5 of the LQTS-susceptibility genes: KCNQ1 (LQT1), KCNH2 (LQT2), SCN5A (LQT3), KCNE1 (LQT5), and KCNE2 (LQT6). Overall, 903 referral cases (36%) hosted a possible LQTS-causing mutation that was absent in >2,600 reference alleles; 821 (91%) of the mutation-positive cases had single genotypes, whereas the remaining 82 patients (9%) had >1 mutation in > or =1 gene, including 52 cases that were compound heterozygous with mutations in >1 gene. Of the 562 distinct mutations, 394 (70%) were missense, 428 (76%) were seen once, and 336 (60%) are novel, including 92 of 199 in KCNQ1, 159 of 226 in KCNH2, and 70 of 110 in SCN5A. This cohort increases the publicly available compendium of putative LQTS-associated mutations by >50%, and approximately one-third of the most recently detected mutations continue to be novel. Although control population data suggest that the great majority of these mutations are pathogenic, expert interpretation of genetic test results will remain critical for effective clinical use of LQTS genetic test results.

Abstract 4400: Comprehensive Open Reading Frame Mutational Analysis of the RYR2- Encoded Ryanodine Receptor/Calcium Channel in Patients Diagnosed Previously with Either Catecholaminergic Polymorphic Ventricular Tachycardia or Genotype Negative, Exercise-Induced Long QT Syndrome

Pathogenic mutations in the RYR2 -encoded cardiac ryanodine receptor cause type 1 catecholaminergic polymorphic ventricular tachycardia (CPVT1), a cardiac channelopathy with increased propensity for lethal ventricular dysrhythmias. Most RYR2 mutational analyses target three canonical domains encoded by &lt; 40% of the translated exons. The extent of mutations localizing outside of these domains remains unknown as RYR2 has not been examined comprehensively in most patient cohorts. Mutational analysis of all 105 RYR2 exons was performed using PCR, DHPLC, and DNA sequencing on 108 unrelated patients (57% females, 96% white, age at diagnosis 18 ± 13 years, mean QTc 424 ± 26 ms) with either an explicit referral diagnosis of CPVT (N = 60) or an initial diagnosis of exercise-induced long QT syndrome (LQTS) but with QTc &lt; 480 ms and a subsequent negative LQTS genetic test (N = 48). Two hundred healthy individuals from the Human Genetic Cell Repository were examined to assess allelic frequency for all non-synonymous variants detected. Thirty-eight (15 novel) possible CPVT1-associated mutations absent in 400 reference alleles, were detected in 44 unrelated patients (41%). Three cases (7%) had &gt;1 RYR2 mutation. Besides the 25 exons known previously to contain causative mutations, eight new mutation-containing exons were identified: 10, 12, 13, 21, 26, 40, 42, and 48. Nearly two-thirds of the CPVT1-positive patients had mutations that localized to one of only 7 exons: 8, 14, 47, 90, 93, 100, and 101. In addition, 5 (2 novel) common non-synonymous single nucleotide polymorphisms were identified. This study represents one of the largest cohorts of patients for which RYR2 was examined in its entirety. Possible CPVT1 mutations in RYR2 were identified in approximately 41% of both CPVT referrals and LQTS gene-negative patients with exercise-induced syncope and QTc &lt;480 ms. Including the eight new exons hosting mutations in this study, 33 of the 105 translated exons are now known to host possible mutations. Considering that two-thirds of CPVT1-positive cases would be discovered by selective analysis of &lt;10 exons, a tiered targeting strategy for mutation discovery may afford a more cost-effective approach to CPVT genetic testing.

Abstract 2966: Should a Minimum Corrected QT Interval (QTc) be a Prerequisite for Long QT Syndrome Genetic Testing?

Background: Long QT Syndrome (LQTS) genetic testing has been available clinically since August 2004. In cases of bona fide LQTS, the yield of genetic testing is approximately 75%. Recently (HRS 2007), Priori and colleagues have suggested that referral for LQTS genetic testing should be based on the screening QTc citing a yield of &lt; 2% for cases referred to their research program with a QTc &lt; 440 ms. Here, we analyze the effect of QTc on the yield in two of the largest assembled cohorts of unrelated patients (pts) referred for LQTS genetic testing. Methods: From August 1997 to July 2006, 1125 unrelated pts (717 females, average age at diagnosis 23.5 yrs, average QTc 473 ms) were referred to either the Mayo Clinic Windland Smith Rice Sudden Death Genomics Laboratory (N = 541) for research-based LQTS genetic testing or to PGxHealth (N = 574) for the FAMILION ® LQTS genetic test. Comprehensive open reading frame and splice site analysis (60 exons) for LQTS-causing mutations involving KCNQ1 (LQT1), KCNH2 (LQT2), SCN5A (LQT3), KCNE1 (LQT5), and KCNE2 (LQT6) was conducted by either dHPLC/DNA sequencing (Mayo), or by direct DNA sequencing (FAMILION). Results: The probability of a positive genetic test increased dramatically with increasing QTc, ranging from 5% for the 38 pts referred for genetic testing despite a QTc &lt; 400 ms to 60% for the 168 pts with a QTc &gt; 500 ms (p &lt; 0.00001). Akin to the Priori cohort, the yield of the genetic test was similar among the subset of pts with a QTc &lt; 470 ms (64% Priori, 61% Mayo cohort, and 53% FAMILION, p = NS). However, the yield for those pts with a QTc between 440 and 470 ms was much greater in the Mayo (49%) and FAMILION (36%) cohorts compared to the Priori cohort (14%, p &lt; 0.0005). In contrast to the 2% yield observed in Italy, 22% of pts with QTc &lt; 440 ms referred to Mayo Clinic and 14.5% of the FAMILION referrals had a positive genetic test (p &lt; 0.001). Conclusions: Whereas only 2% of patients with a QTc &lt; 440 ms had a positive genetic test in Italy, the yield was ten times greater among those referred to Mayo Clinic despite the same QTc cut-off. The cumulative index of suspicion for LQTS rather than a pre-specified QTc cut-off should guide clinical decision making as to the appropriate utilization of the genetic test.