Abstract
Congenital long QT syndrome (LQTS) is an inherited arrhythmia syndrome characterized by a prolonged QT interval in the 12-lead ECG, torsades de pointes and not negligible prevalence of sudden cardiac death. The genetic testing plays an important role in the diagnosis of LQTS. A total of 15 genes have been reported for autosomal-dominant forms of Romano–Ward-type congenital LQTS and 2 genes for autosomal-recessive forms of the Jervell and Lange–Nielsen syndrome. In this review, we summarize the recent advances in genetics of LQTS and briefly describe forward perspectives of LQTS investigation.
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Introduction
Long-QT syndrome (LQTS) is characterized by a prolonged QT interval on 12-lead electrocardiograms (ECGs) that can progress to a polymorphic ventricular tachycardia (VT) known as torsades de pointes. Clinically, torsades de pointes can produce syncope, ventricular fibrillation or even sudden cardiac death. The prevalence of congenital LQTS is reportedly 1 in 2000.1 In this review, we focus on the advances in our understanding of the genetics of LQTS.
Criteria for diagnosis
The Schwartz score2 is used to diagnose congenital LQTS (Table 1). Patients with a Schwartz score ⩾3.5 points in the absence of a secondary cause for QT prolongation are diagnosed with LQTS. Recently, in 2013, an expert consensus statement on the diagnosis and management of patients with inherited primary arrhythmia syndromes was published by the Heart Rhythm Society, the European Heart Rhythm Association and the Asia Pacific Heart Rhythm Society.3 They reported that congenital LQTS should be diagnosed when the following criteria are fulfilled:
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1)
An LQTS risk score ⩾3.5 without a secondary cause for QT prolongation.
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An unequivocally pathogenic mutation in one of the LQTS genes.
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In the presence of a corrected QT interval (QTc) ⩾500 ms on repeated 12-lead ECGs using Bazett’s formula in the absence of a secondary cause for QT prolongation.
They adjunctively mentioned that LQTS can be diagnosed when the QTc is between 480 and 499 ms on repeated 12-lead ECGs in patients with unexplained syncope, without a secondary cause for QT prolongation, and in the absence of a pathogenic mutation.
As just described, the genetic testing is included in the diagnosis criteria and has an important role in the diagnosis of LQTS.
Genetics
The three main types of LQTS and genetic testing
A total of 15 genes have been reported in autosomal dominant forms of Romano–Ward-type congenital LQTS (Table 2). Moreover, most of the genetic abnormalities identified thus far appear to prolong the duration of action potentials by decreasing the potassium current (loss-of-function mutation) or increasing the sodium or calcium current (gain-of-function mutation), resulting in clinical QT prolongation on the ECG.
Between 1995 and 1996,4, 5, 6 three major causative genes were recognized for LQTS and associated with LQTS types 1–3: KCNQ1-encoding Kv7.1 (for LQT1), KCNH2 encoding Kv11.1 (for LQT2) and SCN5A encoding Nav1.5. Napolitano et al.7 reported that they identified 235 different mutations in 310 (72%) of 430 probands (49% KCNQ1, 39% KCNH2 and 10% SCN5A). In Japan, Shimizu et al.8 reported the three major genes constituted more than 80% of total genotyped patients with LQTS. According to the Heart Rhythm Society/European Heart Rhythm Association Expert Consensus Statement on the State of Genetic Testing for the Channelopathies and Cardiomyopathies, abnormalities of the three LQTS-associated genes are detected in ~75% of clinically definite LQTS, with rates of 30%–35%, 25%–40% and 5%–10% for LQTS types LQT1, LQT2 and LQT3, respectively.9 LQTS genetic testing contributes to not only diagnosis but also gene-specific and mutation-specific risk stratification and patient management. They recommended that comprehensive or specific genetic testing for KCNQ1, KCNH2 and SCN5A be performed for any patient who fulfills the following criteria:9
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1)
where a cardiologist has established a strong suspicion for LQTS based on clinical examination,
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where a patient has asymptomatic QT prolongation in the absence of other clinical conditions that may prolong the QT interval,
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where a patient is asymptomatic, with QTc values >460 ms (prepuberty) or >480 ms (adults) on serial 12-lead ECGs and
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when an LQTS-causative mutation is identified in an index case, mutation-specific genetic testing is recommended for the family members.
Risk stratification of LQTS using the genetic information
In 600 patients with LQT1, Moss et al.10 demonstrated that those with mutations in the transmembrane region of Kv7.1, those with missense mutations and those with mutations resulting in dominant-negative ion currents had greater risk of arrhythmic events than those with other mutations. In a Japanese multicenter study, Shimizu et al.11 also reported that patients with LQT1 and transmembrane mutations are at a higher risk of cardiac events and had a greater sensitivity to sympathetic stimulation than those with C-terminal mutations. Subsequently, Barsheshet et al.12 demonstrated that patients with C-loop missense mutations in the KCNQ1 gene exhibited a high risk for life-threatening events, and that β-blocker therapy was effective for them.
Regarding LQT2, Shimizu et al.13 demonstrated in 858 patients that missense mutations in the transmembrane pore region are associated with significantly higher rates of cardiac events than are other missense mutations. Recently, Liu et al.14 also reported that a trafficking-deficient mutation in the transmembrane non-pore region of Kv11.1 causes a dominant-negative effect and a severe clinical course.
Patients with LQTS having both the pathogenic variants and a QTc>500 ms are also at high risk, in particular when they are symptomatic. In contrast, the asymptomatic genetically diagnosed LQTS patients are evaluated at lower risk. An important risk factor for these patients comes from drugs that block the IKr current and conditions that lower their plasma potassium level.3
Genome-wide association study about QT times
In 2009, two genome-wide association studies of QT intervals, the QTGEN and QTSCD, have been reported in Nature Genetics.15, 16 Common single-nucleotide polymorphisms in NOS1AP, KCNQ1, KCNH2, SCN5A, KCNJ2 and RNF207 were detected and the genes were reported as candidates for ventricular arrhythmias and sudden cardiac death. Earle et al.17 demonstrated that the single-nucleotide polymorphisms reported in NOS1AP and KCNQ1, which affect the QT interval, were also associated with an increased risk of cardiac events in patients with LQTS. Recently, they reported that single-nucleotide polymorphisms of NOS1AP increased the risk of cardiac events in patients with LQT2 and they also reported regarding the link between the KCNQ1 single-nucleotide polymorphism and the KCNH2 mutations.18 Other researchers have tried to clarify the drug–gene interactions that influence the QT interval, but numerous problems remain unresolved.19
The other genes beyond the three common LQTs
Beyond the three common LQTS gene variants, several mutations encoding ion-channel subunits, except for those associated with LQT4, LQT9, LQT11, LQT12, LQT14 and LQT15, have also been found. Notably, mutations in KCNQ1 (that is, JLN1, also associated with LQT1) and KCNE1 (that is, JLN2, also associated with LQT5) have also been found to be causal in autosomal-recessive forms of the Jervell and Lange–Nielsen syndrome attributable to a decrease in the Iks. They are accompanied by neurosensorial deafness and a markedly prolonged QT interval19 (Table 2).
Mutations in the potassium channel genes
The LQTS types associated with slowly activating delayed rectifier potassium current (IKs) dysfunction include LQT1, LQT5, LQT11, JLN1 and JLN2 (Table 2), although most are associated with LQT1. Mutations in KCNE1, which are associated with LQT5, cause defective trafficking of the IKs channel, reduce amplitude of the IKs current and influence disease pathogenesis.20 A mutation in AKAP9, which is associated with LQT11, has been shown to reduce the interaction between Kv7.1 and A-kinase anchor protein 9, reduce the cyclic AMP-induced phosphorylation of the channel, eliminate the functional response of the IKs channel to cyclic AMP and prolong the action potential in a computational model of the ventricular cardiomyocyte.21
The LQTS types associated with rapidly activating delayed rectifier potassium current (IKr) dysfunction include LQT2 and LQT6, with the former accounting for the majority of cases. Most of the mutations in KCNH2 disrupt the maturation and trafficking process before reducing the number of functional ion channels at the cell surface membrane.22 However, mutations of KCNE2 (the β-subunit of Kv11.1), which are associated with LQT6, have been reported to modulate Kv11.1 channel gating and currents, and to be proarrhythmic.23
Mutations in the sodium channel genes
The LQTS types with dysfunctional late-activating sodium channels (INa) include LQT3, LQT9, LQT10 and LQT12, although most are LQT3. Notably, numerous mutations have been characterized as leading to or predisposing to LQT3. In addition, mutations of Nav1.5 have been linked to a variety of cardiac diseases such as LQTS, Brugada syndrome, cardiac conduction defects, atrial fibrillation and dilated cardiomyopathy.24, 25 Phenotypic overlap of LQT3 with Brugada syndrome is also observed in some carriers of SCN5A mutations.26 For example, the α-subunit of Nav1.5 interacts with several regulatory proteins and the mutations of these genes cause disease related to sodium-channel dysfunction.27 SCN4B encodes the β-subunit of the sodium channel that is critical to the regulation of sarcolemmal expression and the gating of Nav1.5. An SCN4B mutation associated with LQT10 has been shown to increase the persistence of the INa with a positive shift toward inactivation.28 Caveolin-3 acts in conjunction to increase peak INa through a cyclic AMP-independent pathway; a CAV3 mutation associated with LQT9 subsequently results in QT prolongation only during β-blocker therapy.29 SNTA1 is associated with LQT12, which encodes α-1-syntrophin, and is associated with the Nav1.5 channel as part of the neuronal nitric oxide synthesis complex. A mutation in SNTA1 is associated with an increase in both the peak and the persistence of the INa due to a change in the binding of the PDZ domain.30
Mutations in other genes
A type of LQTS that is associated with a mutation in KCNJ2 is LQT7, which creates a condition known as Andersen–Tawil syndrome. This is characterized by a triad of periodic paralysis, a long QU interval associated with ventricular arrhythmias and skeletal development anomalies. In this condition, a reduction in Kir2.1 due to the KCNJ2 mutation prolongs the terminal phase of the cardiac action potential. Because of the reduced extracellular potassium levels, sodium/calcium exchanger-dependent delays after depolarization are induced, resulting in spontaneous arrhythmias.31 The common clinical characteristics of LQT7 and cathecolaminergic polymorphic VT (CPVT), such as biphasic premature ventricular contractions, make diagnosis difficult. Several factors can assist in the differential diagnosis: T-U patterns (i.e.prolonged terminal T downslope, wide T-U junction, and biphasic and enlarged U waves), relatively slow polymorphic or biphasic VT and frequent ventricular ectopic beats at rest may be useful in distinguishing LQT7 from CPVT. After KCNJ2 mutations were identified in patients with CPVT phenotype, differential diagnosis between LQT7 and CPVT by genotyping became more challenging.32
The most severe phenotypic form of LQTS is Timothy syndrome (LQT8). This is associated with point mutations in CACNA1C, which cause slowed inactivation of CaV1.2 that increase the influx of calcium, prolong the cardiac action potential and promote lethal arrhythmias. Timothy syndrome is quite rare because of the fatal phenotype and multisystem manifestations, including congenital heart disease, syndactyly, immunodeficiency, cognitive abnormalities and autism.33 Recently, mild LQT8 cases with CACNA1C mutation without phenotype of Timothy syndrome were reported.34, 35
Crotti et al.36 performed exome sequencing in infants with recurrent cardiac arrest and dramatically prolonged QTc intervals, discovering heterozygous de novo mutations in CALM1 and CALM2 encoding calmodulin (that is, LQT14 and LQT15, respectively). In addition, Makita et al.37 reported the presence of CALM1 and CALM2 mutations in LQTS probands by next-generation sequencing approaches. They revealed that these calmodulin mutations disrupted calcium-ion binding to the protein and were associated with LQTS and with overlapping features of LQTS and CPVT.
Future perspectives
Numerous ion-channel mutations have been reported and various approaches have been used to confirm the associated functional change, including expression models (using human embryonic kidney cells, Chinese hamster ovary cells or Xenopus oocytes), experimental mouse models, computational approaches, neonatal mouse cardiomyocytes and induced pluripotent stem cells.38, 39 The assessment of gene expression with induced pluripotent stem cells is useful when confirming drug efficacy, in particular in cases with complex genotypes.40, 41
Furthermore, gene analysis techniques have advanced remarkably. As previously mentioned, we can obtain significant amount of data using next-generation sequencing approaches, exome analysis42 and genome-wide association studies. Next-generation sequencing technology allows a comprehensive genetic analysis of LQTS such as a copy number variation.43 Whole-exome sequencing is efficient to elucidate the underlying genetic mechanism of diseases. However, an investigator often faces difficulties to identify the possible disease causative variant among hundreds of variants per patient DNA sample and it takes up a lot of energy. We have to identify potential candidate genes by considering genotype–phenotype association, the relationship between genotype and disease development of each family member, publicly available internet-based gene-prioritization tools, in silico variant annotation prediction and functional studies.44, 45
In addition, we can use the large bioinformatics data registries of genome browsers, such as HapMap (http://hapmap.ncbi.nlm.nih.gov/), NCBI (http://www.ncbi.nlm.nih.gov/), UCSC (https://genome.ucsc.edu/), 1000 genome data (http://www.1000genomes.org/) and recently publicly available database, the ExAC browser, which contains exome sequencing data on up to 60 000 individuals (http://exac.broadinstitute.org/).
A recent epochal report demonstrated that rapid whole-genome sequencing could be performed with a speed-optimized bioinformatics platform in LQTS patients that could provide comprehensive diagnostic information at 10 days of life. Their approach was certified by the Clinical Laboratory Improvement Amendments.46 The goal of identifying the genetic basis of the disease is to individualize and optimize treatment strategies. Finally, it is important to identify and profile the relatives of LQTS probands to identify their risk. In a review article reported by Semsarian et al.47, in sudden cardiac death cases where no cause of death is identified at post mortem, genetic testing of post-mortem blood in a specialized multidisciplinary clinic setting may identify a cause of death in up to 30%. The ultimate goal is to prevent future adverse clinical outcomes and sudden cardiac death (SCD) events in surviving relatives.
Porta et al.48 reported that patients with higher sympathetic control of the QT interval and reduced vagal control of the heart rate were at lower risk of complications than other patients with LQT1 carrying the same mutation. Myerburg49 has also stated that gene expression was modulated by physiological fluctuations, drug and electrolytes, and environmental factors, and that we must consider the role of epistasis with other modifying gene variants.
Thus, both genomic and non-genomic factors are important when diagnosing congenital ion-channel diseases and the need to advance genetic analysis is therefore apparent.
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Acknowledgements
Dr W Shimizu was supported in part by a research grant for cardiovascular disease (H24-033 and H26-040) from the Ministry of Health, Labour and Welfare, Japan, and a Nippon Medical School Grant-in-Aid for Medical Research. Dr Y Nakano was supported by JSPS KAKENHI Grant Number 26461130.
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Nakano, Y., Shimizu, W. Genetics of long-QT syndrome. J Hum Genet 61, 51–55 (2016). https://doi.org/10.1038/jhg.2015.74
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DOI: https://doi.org/10.1038/jhg.2015.74
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