A case of long QT syndrome with triple gene abnormalities: Digenic mutations in KCNH2 and SCN5A and gene variant in KCNE1

Yoshikane, Yukako; Yoshinaga, Masao; Hamamoto, Kunihiro; Hirose, Shinichi

doi:10.1016/j.hrthm.2012.12.008

Cited by 11 publications

(7 citation statements)

References 14 publications

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“…More recently, Yoshikane and his colleagues [15] reported a family in which 2 genetic variants were harbored in the presence or absence of the KCNE1 ‐D85N polymorphism. They compared the symptoms among the family members who carried one or more of the genetic variants KCNH2 ‐N45D, SCN5A ‐A1428S, or KCNE 1‐D85N.…”

Section: Discussionmentioning

confidence: 99%

A rare KCNE1 polymorphism, D85N, as a genetic modifier of long QT syndrome

Hasegawa

Ohno

Itoh

et al. 2013

Journal of Arrhythmia

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Background The gene KCNE1 encodes the β‐subunit of cardiac voltage‐gated K+ channels and causes long QT syndrome (LQTS). LQTS is characterized by the prolongation of QT interval and lethal arrhythmias such as torsade de pointes (TdP). A KCNE1 polymorphism, D85N, has been shown to modify the phenotype of LQTS through a loss‐of‐function effect on both KCNQ1 and KCNH2 channels when co‐expressed and reconstituted in a heterologous expression system. Methods A screening for the D85N polymorphism was performed in 355 LQTS families with mutations in KCNQ1, KCNH2, or SCN5A. Among the probands who had a heterozygous status with the polymorphism, we focused on a family with a KCNH2 mutation (E58K), a N‐terminal missense mutation, and examined the clinical significance of this polymorphism. We also conducted biophysical assays to analyze the effect of the polymorphism in mammalian cells. Results In 355 probands, we found 14 probands (3.9%) who had a heterozygous compound status with the D85N polymorphism. In the family with a KCNE1‐D85N polymorphism and a KCNH2‐E58K mutation, the proband and her daughter carried both the KCNH2 mutation and the KCNE1‐D85N polymorphism. They experienced repetitive syncope and TdP. Two sons of the proband had either KCNH2‐E58K mutation or KCNE1‐D85N, but were asymptomatic. Biophysical assays of KCNE1‐D85N with KCNH2‐E58K variants produced a larger reduction in the reconstituted IKr currents compared to co‐expression with wild‐type KCNE1. Conclusions The KCNE1‐D85N polymorphism modified the clinical features of LQTS patients.

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Section: Discussionmentioning

confidence: 99%

A rare KCNE1 polymorphism, D85N, as a genetic modifier of long QT syndrome

Hasegawa

Ohno

Itoh

et al. 2013

Journal of Arrhythmia

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“…Common polymorphisms in the LEPR (Gln223Arg, rs1137101) and ADRB2 [Arg16Gly (rs1042713) and Gln27Glu (rs1042714)] genes jointly confer increased risk of obesity even though none of these polymorphisms exhibits a significant influence on their own (Pereira et al 2011). Other examples of oligogenic inheritance, involving the mutation or polymorphism of multiple unlinked genes in the same individual, include isolated gonadotropin-releasing hormone deficiency ( KAL1 , PROK2 and NELF ; Sykiotis et al 2010), hypertrophic cardiomyopathy ( MYH7 , MYBPC3 , TNNI3 and TNNT2 ; Girolami et al 2010; Lopes et al 2013), iminoglycinuria ( SLC36A2 , SLC6A20 , SLC6A18 , SLC6A19 ; Bröer et al 2008), long QT syndrome ( KCNH2 , SCN5A and KCNE1 ; Yoshikane et al 2013), chronic pancreatitis ( SPINK1 , CFTR and CTRC ; Rosendahl et al 2013), atypical haemolytic uraemic syndrome ( CFH , CD46 and CFI ; Roumenina et al 2012; Bresin et al 2013), Parkinson disease ( LRRK2 , SNCA , MAPT , GBA , BST1 , PARK16 ; Wang et al 2012), acrocallosal syndrome ( KIF7 , AHI1 , BBS2 and BBS4 ; Walsh et al 2013), autism spectrum disorders (Neale et al 2012) and a low plasma level of HDL cholesterol, a major risk factor for atherosclerosis (Cohen et al 2004; Wang et al 2008; Johansen and Hegele 2012). …”

Section: Oligogenic Inheritance and Its Implications For Disease Penementioning

confidence: 99%

Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease

et al. 2013

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Some individuals with a particular disease-causing mutation or genotype fail to express most if not all features of the disease in question, a phenomenon that is known as ‘reduced (or incomplete) penetrance’. Reduced penetrance is not uncommon; indeed, there are many known examples of ‘disease-causing mutations’ that fail to cause disease in at least a proportion of the individuals who carry them. Reduced penetrance may therefore explain not only why genetic diseases are occasionally transmitted through unaffected parents, but also why healthy individuals can harbour quite large numbers of potentially disadvantageous variants in their genomes without suffering any obvious ill effects. Reduced penetrance can be a function of the specific mutation(s) involved or of allele dosage. It may also result from differential allelic expression, copy number variation or the modulating influence of additional genetic variants in cis or in trans. The penetrance of some pathogenic genotypes is known to be age- and/or sex-dependent. Variable penetrance may also reflect the action of unlinked modifier genes, epigenetic changes or environmental factors. At least in some cases, complete penetrance appears to require the presence of one or more genetic variants at other loci. In this review, we summarize the evidence for reduced penetrance being a widespread phenomenon in human genetics and explore some of the molecular mechanisms that may help to explain this enigmatic characteristic of human inherited disease.

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“…Although this mutation is found in o1% of the general population, it has been described as an LQTS modulator 31,32 and associated with a QT prolongation. 33 Similarly, KCNE2 p.(Thr8Ala) was found in 0.5% of the general population but was also described as a VUS.…”

Section: Mutation Analysismentioning

confidence: 99%

Genetic analysis, in silico prediction, and family segregation in long QT syndrome

et al. 2014

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The heritable cardiovascular disorder long QT syndrome (LQTS), characterized by prolongation of the QT interval on electrocardiogram, carries a high risk of sudden cardiac death. We sought to add new data to the existing knowledge of genetic mutations contributing to LQTS to both expand our understanding of its genetic basis and assess the value of genetic testing in clinical decision-making. Direct sequencing of the five major contributing genes, KCNQ1, KCNH2, SCN5A, KCNE1, and KCNE2, was performed in a cohort of 115 non-related LQTS patients. Pathogenicity of the variants was analyzed using family segregation, allele frequency from public databases, conservation analysis, and Condel and Provean in silico predictors. Phenotype-genotype correlations were analyzed statistically. Sequencing identified 36 previously described and 18 novel mutations. In 51.3% of the index cases, mutations were found, mostly in KCNQ1, KCNH2, and SCN5A; 5.2% of cases had multiple mutations. Pathogenicity analysis revealed 39 mutations as likely pathogenic, 12 as VUS, and 3 as non-pathogenic. Clinical analysis revealed that 75.6% of patients with QTcZ500 ms were genetically confirmed. Our results support the use of genetic testing of KCNQ1, KCNH2, and SCN5A as part of the diagnosis of LQTS and to help identify relatives at risk of SCD. Further, the genetic tools appear more valuable as disease severity increases. However, the identification of genetic variations in the clinical investigation of single patients using bioinformatic tools can produce erroneous conclusions regarding pathogenicity. Therefore segregation studies are key to determining causality.

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A case of long QT syndrome with triple gene abnormalities: Digenic mutations in KCNH2 and SCN5A and gene variant in KCNE1

Cited by 11 publications

References 14 publications

A rare KCNE1 polymorphism, D85N, as a genetic modifier of long QT syndrome

A rare KCNE1 polymorphism, D85N, as a genetic modifier of long QT syndrome

Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease

Genetic analysis, in silico prediction, and family segregation in long QT syndrome

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