The percentage of individuals for each 20-millisecond cluster of corrected QT duration in the 2 groups of genetically affected (n = 817) and nongenetically affected individuals (n = 521). Numbers on the x-axis represent the cluster upper limit.
A 3-tier approach for genetic screening. The first step includes identification of nonprivate mutations, codons that harbor mutations occurring more than once in the long QT population (expected genotyping of up to 58% of carriers of mutations on the 5 long QT syndrome [LQTS] genes included in this study. See the “Methods” section for details). The second step is the complete screening of the coding regions of the 2 most prevalent loci (LQT1 and LQT2). This second step allows the identification of an additional 32% of carriers of mutations on the 5 LQTS genes included in this study. The final step that provides the identification of the final 10% of mutation carriers requires the screening of the open reading frame of genes SCN5A, KCNE1, and KCNE2.
Carlo Napolitano, Silvia G. Priori, Peter J. Schwartz, Raffaella Bloise, Elena Ronchetti, Janni Nastoli, Georgia Bottelli, Marina Cerrone, Sergio Leonardi. Genetic Testing in the Long QT SyndromeDevelopment and Validation of an Efficient Approach to Genotyping in Clinical Practice. JAMA. 2005;294(23):2975–2980. doi:10.1001/jama.294.23.2975
Author Affiliations: Molecular Cardiology, IRCCS Fondazione S. Maugeri Foundation (Drs Napolitano, Priori, Bloise, Ronchetti, Cerrone, and Leonardi and Mss Nastoli and Bottelli); Department of Cardiology, University of Pavia (Drs Priori and Schwartz); and IRCCS Policlinico S. Matteo (Dr Schwartz), Pavia, Italy.
Context In long QT syndrome (LQTS), disease severity and response to therapy vary according to the genetic loci. There exists a critical need to devise strategies to expedite genetic analysis.
Objective To perform genetic screening in patients with LQTS to determine the yield of genetic testing, as well as the type and the prevalence of mutations.
Design, Patients, and Setting We investigated whether the detection of a set of frequently mutated codons in the KCNQ1, KCNH2, and SCN5A genes may translate in a novel strategy for rapid efficient genetic testing of 430 consecutive patients referred to our center between June 1996 and June 2004. The entire coding regions of KCNQ1, KCNH2, SCN5A, KCNE1, and KCNE2 were screened by denaturing high-performance liquid chromatography and DNA sequencing. The frequency and the type of mutations were defined to identify a set of recurring mutations. A separate cohort of 75 consecutive probands was used as a validation group to quantify prospectively the prevalence of the recurring mutations identified in the primary LQTS population.
Main Outcome Measures Development of a novel approach to LQTS genotyping.
Results We identified 235 different mutations, 138 of which were novel, in 310 (72%) of 430 probands (49% KCNQ1, 39% KCNH2, 10% SCN5A, 1.7% KCNE1, and 0.7% KCNE2). Fifty-eight percent of probands carried nonprivate mutations in 64 codons of KCNQ1, KCNH2, and SCN5A genes. A similar occurrence of mutations at these codons (52%) was confirmed in the prospective cohort of 75 probands and in previously published LQTS cohorts.
Conclusions We have developed an approach to improve the efficiency of genetic screening for LQTS. This novel method may facilitate wider access to genotyping resulting in better risk stratification and treatment of LQTS patients.
The long QT syndrome (LQTS) is an inherited disease predisposing to cardiac arrhythmias and sudden death in young individuals. Two phenotypic variants have been described: the autosomal dominant Romano-Ward syndrome and the autosomal recessive Jervell and Lange-Nielsen syndrome.1- 4 More recently, 2 additional uncommon variants presenting with prolonged QT interval and extracardiac manifestations were reported.5,6
Six genes are known to cause Romano-Ward syndrome: 5 encoding for subunits of cardiac ion channels (KCNQ1, KCNH2, SCN5A, KCNE1, KCNE2)7 and 1 (ANK2) encoding for cardiac ankyrin, a structural protein that anchors ion channels to the cell membrane. The latter form of LQTS is extremely rare and very few carriers of mutations in the ANK2 gene have been described.8 The terms LQT1 through LQT6 describe patients affected by each genetic variant of Romano-Ward syndrome. The clinical value of genetic testing has been demonstrated by the evidence that carriers of LQTS mutations lacking QT interval prolongation, who therefore escape clinical diagnosis, have a 10% risk of major cardiac events by age 40 years when left untreated.9 Furthermore, locus-specific algorithms for risk stratification and management of patients with LQTS have been proposed and should be applied in clinical management.9- 11
We report herein results of systematic screening of one of the largest group of consecutively genotyped patients and we (1) define the yield of genetic testing in patients with Romano-Ward syndrome, (2) define the type and the prevalence of mutations, and (3) propose a novel and efficient 3-tier strategy designed to facilitate access to genotyping.
The study population includes 430 LQTS probands (97% white) with Romano Ward syndrome and 1115 family members consecutively referred to the Molecular Cardiology Laboratories of the Maugeri Foundation between June 1, 1996, and May 30, 2004, for genetic testing of Romano-Ward syndrome. We conducted LQTS testing when QT interval prolongation appeared with or without QT morphological abnormalities, borderline QT interval was associated with LQTS-related repolarization abnormalities (notches/biphasic T wave in >2 leads, or flat T wave), syncope was associated with overt or borderline QT interval prolongation, a family had a history of LQTS in sudden death family members, and documented polymorphic ventricular tachycardia (torsade de pointes) was associated with QT prolongation.
Clinical data and corrected QT (QTc, Bazett's formula) measurements were obtained by observers who were blinded to genetic status. For each individual the electrocardiograph recorded at the first contact was used for the measurement of QT duration and QTc penetrance. In probands, we also assessed the recurrence of nonprivate mutations.
A validation cohort of 75 white probands consecutively genotyped between July 2004 and January 2005 was used to test the predicted occurrence of the nonprivate mutations identified in the study population and to confirm the validity the proposed genotyping strategy.
The study was approved by the institutional review board of the Maugeri Foundation, and written informed consent was obtained in accordance with institutional review board guidelines from all individuals enrolled in the study.
Molecular analysis was performed on genomic DNA extracted from peripheral blood lymphocytes using standards methods. Coding regions of KCNQ1, KCNH2, SCN5A, KCNE1, and KCNE2 were amplified by polymerase chain reaction using exon-flanking intronic primers. Amplicons were analyzed at least at 2 temperatures based on the melting profile by denaturating high-performance liquid chromatography (WAVE, Transgenomics, Omaha, Neb). DNA sequencing (310 Automated Genetic Analyzer, Applied Biosystems, Foster City, Calif) either directly or after cloning of the polymerase chain reaction product into a plasmid vector (Topo cloning, Invitrogen, Carlsbad, Calif) was performed whenever an abnormal chromatogram was identified. A mutation was defined as a DNA change that altered the encoded protein and that was not present in any of 400 control individuals (800 chromosomes). Mutations were annotated using single-letter amino acid code and using the recommended nomenclature.12
The Kolmogorov-Smirnov test was used to assess the normal distribution of variables. Parametric tests were used to compare normally distributed variables (unpaired t test and analysis of variance with Bonferroni correction for multiple comparisons). As expected, the QTc was not normally distributed; therefore, nonparametric tests (Kruskal-Wallis and Mann-Whitney) were used to assess statistical significance. Data for continuous variables are presented as mean (SD) or median and interquartile range (IQR), as appropriate. Statistical analysis was performed using the SPSS statistical package (version 12.01, SPSS Inc, Chicago, Ill) with a 2-sided level of statistical significance <.05.
Proband is the first individual meeting the clinical diagnostic criteria for LQTS. Genetically affected are carriers of DNA mutations in LQTS-related genes. Silent carriers are genetically affected individuals with a normal QTc duration (QTc ≤440 milliseconds in men and QTc ≤460 milliseconds in women). QTc-penetrance is the percentage of genetically affected individuals with a prolonged QTc.
Among the 430 probands, 310 (72%) were identified as carriers of an LQTS-causing mutation. Genetic analysis was performed in 1115 family members of the 310 genotyped probands. Of the probands family members, 521 were genetically affected and 594 were nonaffected. Overall, we report on 831 genetically affected probands and their family members and 594 nonaffected family members.
Two hundred ninety-six probands were heterozygous carriers of a single mutation while 14 (4.5%) were carriers of multiple genetic defects.13,14 Twelve probands were compound heterozygous of 2 (n = 11) or 3 (n = 1) mutations, while 2 probands were homozygous Romano-Ward syndrome patients.15 Among the 296 probands with a single genetic defect, mutations on the KCNQ1 gene were most prevalent in 144 (49%) of probands, followed by 115 (39%) of probands with mutations in the KCNH2, 30 (10%) in the SCN5A, 5 (1.7%) in the KCNE1, 2 (0.7%) in the KCNE2 genes. Overall, mutations on the KCNQ1 and KCNH2 genes accounted for 88% of the successfully genotyped LQTS probands. DNA of both parents of genotyped probands was available for genetic analysis in 247 cases. In this subgroup, only 29 patients (12%) did not inherit the mutation and were therefore considered sporadic cases. Since paternity analysis was not part of our study protocol, we cannot exclude that the number of true sporadic cases is even lower than the observed 12%. This number therefore represents the upper limit of the frequency of new mutations in our population.
Overall, we identified 235 different types of mutations in the probands. One hundred 138 (59%) of these mutations—56 KCNQ1, 65 KCNH2, 13 SCN5A, 2 KCNE1,2 KCNE2—were never reported previously (eTable). Missense mutations accounted for 170 (72%) of 235 of the genetic defects while the remaining 28% included 33 (14.1%) small intragenic deletions, 6 (2.7%) splice errors, 12 (5.1%) non-sense mutations, 11 (4.7%) insertions, and 3 (1.4%) duplications or insertion and deletions.
We evaluated the distribution of mutations in different regions of the proteins encoded by LQTS related genes. N-terminus, transmembrane domains, pore region, and C-terminus were defined according to genomic structure of genes and based on previously published reports.16- 18 Of the 325 mutations identified in the 310 probands, (296 in heterozygous carriers and 29 in the 14 probands with multiple mutations), 208 mutations (64%) were found in the pore region or in the transmembrane domains while 90 mutations (28%) were in the C-terminal regions, and 26 mutations (8%) in the N-terminal regions. Amino-terminal mutations were rare among KCNQ1 (n = 4) and absent among SCN5A, KCNE1, and KCNE2 while they represented 123 (18%) of 123 of mutations in KCNH2 patients.
The mean (SD) QTc among genetically affected individuals was 474 (46) milliseconds (median, 467 milliseconds; IQR, 444-495 milliseconds), the QTc among noncarrier family members was 406 (27) milliseconds (median, 409 milliseconds; IQR, 390-425 milliseconds). The QTc was significantly longer among probands 496 (46) milliseconds (median, 490 milliseconds; IQR, 462-520 milliseconds) than among genetically affected family members (461  milliseconds; median, 458 milliseconds; IQR, 436-484 milliseconds; P<.001). Interestingly, the QTc distribution in genetically affected and nonaffected family members showed a remarkable overlap (Figure 1). The QTc penetrance was defined as the percentage of those individuals presenting QTc longer than 440 milliseconds for men and QTc longer than 460 milliseconds for women. The average QTc penetrance was 60% among genetically affected family members. Patients with LQT2 and LQT3 presented higher QTc penetrance compared with those with LQT1 and LQT5; the number of patients with LQT6 was insufficient to draw conclusion (Table 1).
We tested the hypothesis that a limited number of nonprivate mutations could be present in a high percentage of patients, by assessing the proportion of probands having mutations in “repeated codons” (ie, those causing the LQTS phenotype in ≥2 cases within our cohort). Thus, we considered as repeated codons all the different amino acidic permutations found at the same position. This analysis returned 180 (58%) of 310 probands who could be successfully genotyped on 64 repeated codon (Table 1): 31 on KCNQ1 (100 probands), 25 on KCNH2 (59 probands), and 8 on SCN5A (21 probands).
We validated this observation by quantifying the percentage of patients who could have been identified on the 64-condon set among previously published series of genotyped LQTS patients16,19 and in a prospective cohort of 75 LQTS probands genotyped at our institution. The screening of the set of nonprivate mutations allowed us to genotype 39 (52%) of 75 patients of our prospective cohort. In previously published studies, despite possible differences in the ethnic background of patients, the mutations included in our set would still allow for genotyping 33%19 and 39%16 of patients (Table 2).
The availability of clinical studies on a large series of genotyped patients with LQTS has highlighted major locus specific differences in the prognosis9 and in the response to therapy10,11 and has shown that carriers of LQTS mutations with a normal QTc who cannot be identified by clinical evaluation have a 10% probability of cardiac events by age 40 years if they are not appropriately treated.9 These data provide a rational for moving genetic analysis from research to diagnostic laboratories and highlight the need for defining optimal screening strategies to make genetic analysis clinically available, efficient, and potentially affordable. Data from the present study provide further support for expanded indications for genetic screening and point to a novel 3-tier approach that may be applied in clinical practice.
The clinical value of molecular screening is influenced by the percentage of successfully genotyped individuals. Our data show that 70% of Romano-Ward probands can be successfully genotyped by standard methods based on the current knowledge about the molecular substrate of LQTS. This number, obtained in a population of consecutively genotyped patients, is high enough to support the introduction of genotyping into clinical medicine. The broad experience collected by several centers that have genotyped a large number of patients with different ethnic backgrounds has made it possible to create an online repository of mutations associated with LQTS (Gene Connection for the Heart, available at http://pc4.fsm.it:81/cardmoc) so that by listing previously published mutations and their functional characterization provides a valuable tool for providing genetic counseling to patients with LQTS. Results from this study (eTable) will add another 138 novel mutations to that database.
In the present study, as in prior investigations,16 mutations were considered as causative of the phenotype whenever there was cosegregation among family members, when a mutation had been previously reported, or both. Functional characterization by expression studies of newly identified mutations was not performed. Because the majority of our patients are white, the results presented in this study should only apply to this population and the applicability of our findings to other ethnic groups will have to be investigated.
Data provided in the present study highlight the limitation of clinical diagnosis of LQTS showing that incomplete QTc penetrance severely hampers the reliability of clinical diagnosis of the disease. We have shown that by using the sex-based cutoff values for QTc, 40% of affected individuals (ie, carriers of a genetic defect) among family members cannot be identified by clinical assessment. This is concerning because, based on prior evidence, they may have as much as a 10% risk of experiencing a major cardiac event by age 40 years.9 The consequences of missing the LQTS diagnosis in a genetically affected individual with a normal QTc are relevant because such a patient will not receive β-blockers; will not be aware of the risk of transmitting LQTS to offspring; and will not be informed about avoiding environmental risk factors, such as QT prolonging drugs, strenuous physical exercise, and extreme psychological stress.
Another important finding of the present study is the demonstration that contrary to common perception, no more than 12% of the genotyped probands harbor a de novo mutation; therefore, at least 88% of probands have inherited the disease, suggesting that familial forms are more common than expected.
One of the most important factors that have prevented genetic analysis of LQTS from entering clinical practice is the assumption that the existence of so many private mutations on several genes mandates systematic screening of entire coding regions. The novel set of information reported herein show the feasibility of an effective alternative strategy that may help bring genotyping closer to routine clinical practice.
Although we identified a wide spectrum of intragenic DNA abnormalities, including missense, deletions, insertions, nonsense mutations, splice errors, and duplications, we observed that 180 (58%) of 310 probands carried mutations on 64 nonprivate codons. These codons cover 31 (3.5%) of 678 of the KCNQ1, 25 (2.2%) of 1160 of the KCNH2, and 8 (0.4%) of 2117 of the SCN5A coding regions. We hypothesized that screening of these codons is a reasonable first step in genotyping patients with LQTS, and we tested this concept in a prospective cohort of 75 probands confirming that in strict analogy with what occurred in our study population, 52% of probands carried mutations in 1 of the 64 codons that we had identified. We further validate our hypothesis in the 2 largest cohorts of genotyped patients reported in the literature.16,19 These analyses showed that, even when patients with different geographical and ethnic origin are considered, close to 40% of patients carry mutations in 1 of the most frequently mutated codons that we have identified (Table 3).
We therefore propose that the screening of the 64 codons (Table 2) should be the first step of a multilevel strategy for LQTS genetic analysis (Figure 2). Based on the evidence that in our study 88% of successfully genotyped patients carry mutations in the KCNQ1 and KCNH2 genes, it would seem logical that DNA of patients who test negative for the search for mutations in the 64 codons should be analyzed by assessing the coding regions of KCNQ1 and KCNH2 genes. Only patients who test negative to the first 2 steps, would then move to the last level of this 3-tier approach for LQTS genotyping and their DNA would be screened for mutations on SCN5A, KCNE1, and KCNE2 genes (Figure 2). At this stage, further evaluation of T-wave morphology20 or triggers for cardiac events10 could provide hints for further optimization of the genotyping process.
It is clear that the more complete the screening process the higher the accuracy of the results of genetic analysis. Considering that multiple mutations may coexist in patients with LQTS (4.5% of probands in this study), the ideal screening should include the evaluation of the entire coding region of each disease-related gene in every patient. However, this comprehensive approach may be neither practical nor cost-effective. The 3-tier approach proposed herein may provide an alternative whenever the screening of all genes is not feasible. The choice of the technique used to identify the set of recurrent mutations among the many available will influence the cost of the test. Based on current costs, we estimate that a single tube multiplex polymerase chain reaction amplification and subsequent allele specific oligonucleotide hybridization could provide an entry-level screening at a cost that is less than 1 of 20 of commercially available LQTS genotyping by denaturing high-performance liquid chromatography. A more elaborated approach may allow the development of a chip for the detection of recurrent LQTS mutations that could be used for the screening of a large unselected population, such as the one suitable for preprescription genotyping to withdraw the use of QT prolonging agents in genetically affected LQTS individuals.21
We report the results of systematic genetic screening of 430 probands affected by Romano Ward syndrome with the objectives of defining the yield of genetic analysis in the disease and the relative prevalence of mutations in the LQTS genetic loci. We identified a core of 64 critical codons that harbor mutations in approximately 50% of LQTS probands and therefore propose a novel 3-tier approach to LQTS genotyping that may reduce time and costs required for genetic screening. The novel strategy for LQTS genotyping may facilitate the access to genetic testing to a broader group of individuals, such as patients receiving drugs that block IKr, a delayed-rectifier potassium current, and prolong QT interval; family members of individuals with idiopathic ventricular fibrillation; and depending on results of further investigation, members of the general population to define the prevalence of known genetic variants of LQTS.
Corresponding Author: Silvia G. Priori, MD, PhD, Molecular Cardiology, Maugeri Foundation, University of Pavia, Via Ferrata 8, 27100 Pavia, Italy (firstname.lastname@example.org).
Author Contributions: Drs Napolitano and Priori had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Napolitano, Priori.
Acquisition of data: Napolitano, Bloise, Ronchetti, Nastoli, Bottelli, Cerrone, Leonardi.
Analysis and interpretation of data: Napolitano, Priori, Schwartz, Ronchetti, Nastoli, Bottelli, Leonardi.
Drafting of the manuscript: Napolitano, Priori, Ronchetti, Nastoli, Bottelli, Cerrone, Leonardi.
Critical revision of the manuscript for important intellectual content: Napolitano, Priori, Schwartz, Bloise, Cerrone.
Statistical analysis: Napolitano, Priori, Bloise, Ronchetti, Nastoli, Bottelli, Leonardi.
Obtained funding: Priori.
Administrative, technical, or material support: Priori, Schwartz.
Study supervision: Priori, Bloise.
Financial Disclosures: Dr Priori has a patent pending for the proposed screening algorithm. Otherwise, none were reported.
Funding/Support: This work was supported by grants GP0227Y01 and GGP04066 Telethon, 2003/180 Ricerca Finalizzata, RBNE01XMP4_006 and RBLA035A4X_002FIRB, 2001067817_003 COFIN, HL68880 National Institutes of Health.
Role of the Sponsors: The funding organizations did not participate in the design and conduct of the study, and in the collection, analysis, and interpretation of the data, or in the preparation, review, or approval of the manuscript.
Additional Information: The eTable of novel mutations is available here.