Mutations of the SCN4B-encoded sodium channel β4 subunit in familial atrial fibrillation

  • Authors:
    • Ruo-Gu Li
    • Qian Wang
    • Ying-Jia Xu
    • Min Zhang
    • Xin-Kai Qu
    • Xu Liu
    • Wei-Yi Fang
    • Yi-Qing Yang
  • View Affiliations

  • Published online on: April 22, 2013     https://doi.org/10.3892/ijmm.2013.1355
  • Pages: 144-150
Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Atrial fibrillation (AF) represents the most common form of sustained cardiac arrhythmia and accounts for substantial morbidity and mortality. Mutations in the cardiac sodium channel α, β1, β2 and β3 subunit genes (SCN5A, SCN1B, SCN2B and SCN3B) have been associated with AF, which suggests that mutations in the sodium channel β4 subunit gene, SCN4B, are also involved in the pathogenesis of AF. To examine this hypothesis, the coding exons and exon-intron boundaries of SCN4B were sequenced in 170 unrelated index patients with familial AF. The available relatives of the probands carrying the identified mutations and 200 unrelated ethnically matched healthy individuals used as the controls were subsequently genotyped. The pathogenic potential of a SCN4B sequence variation was predicted using MutationTaster. As a result, 2 novel heterozygous SCN4B mutations, p.V162G and p.I166L, were identified in 2 unrelated families with AF transmitted in an autosomal dominant pattern, respectively. In each family the mutation co-segregated with AF and was absent in the 400 control chromosomes. The mutations altered the amino acids evolutionarily highly conserved across species and were both predicted to be disease-causing. To the best of our knowledge, this is the first study to demonstrate an association of SCN4B mutations with AF, suggesting SCN4B as a novel AF susceptibility gene.

Introduction

Atrial fibrillation (AF) represents the most common form of sustained cardiac arrhythmia with an estimated prevalence of 1% in the general population (1). The incidence of AF increases markedly with advancing age, ranging from less than 1% in individuals under 60 years of age to approximately 10% of those over 80 years (2). According to the Framingham Heart Study, the lifetime risk for development of AF is approximately 25% for individuals who have reached the age of 40 years (3). AF accounts for substantially increased cardiovascular morbidity and mortality. It is associated with an approximately 5-fold increase in the risk of stroke, and more than 15% of all strokes are ascribed to this disordered heart rhythm (4). The risk of AF-related thromboembolism also increases strikingly with age, rising from 1.5% at age 50–59 years to 23.5% at age 80–89 years (4). The total death rate is roughly doubled among patients with AF compared with people in normal sinus rhythm (5). AF is also responsible for compromised exercise performance, degraded quality of life, impaired cognitive function or dementia, tachycardia-induced cardiomyopathy, and left ventricular dysfunction or even congestive heart failure, conferring a large economic burden on national healthcare system worldwide (6). Despite the significant clinical importance, the molecular mechanisms involved in the pathogenesis of AF remain poorly understood.

Traditionally, AF has been regarded as a complication attributed to miscellaneous adverse cardiac or systemic conditions, including hypertension, coronary artery disease, rheumatic heart disease, valvular heart disease, pulmonary heart disease, cardiomyopathy, cardiac sur gery, diabetes mellitus type 2, obstructive sleep apnea, hyperthyroidism, and electrolyte imbalance (1). However, in 30–45% of AF patients, an underlying cause cannot be identified by routine procedures, and such AF is termed ‘idiopathic’ or ‘lone’ (1), of which at least 15% have a positive family history, a condition classified as familial AF (7). Increasing evidence has demonstrated the familial aggregation of AF and enhanced susceptibility to AF in the close relatives of patients with AF, suggesting that genetic risk factors play a pivotal role in the initiation and maintenance of AF in a subset of cases (814). Genome-wide linkage analyses with microsatellite markers mapped susceptibility loci for AF on human chromosomes 10q22, 6q14–16, 11p15.5, 5p13 and 5p15, of which AF-causative mutations in 2 genes, including KCNQ1 on chromosome 11p15.5 and NUP155 on chromosome 5p13, were identified and functionally characterized (1520). The genetic screening of candidate genes has revealed a great number of AF-associated genes, including KCNE2, KCNE3, KCNE5, KCNH2, KCNJ2, KCNA5, SCN5A, SCN1B, SCN2B, SCN3B, NPPA, GJA1, GJA5, GATA4, GATA5 and GATA6 (2144). Nevertheless, AF is of substantial genetic heterogeneity and the genetic basis for AF in an overwhelming majority of patients remains unclear.

Recent studies have highlighted the essential role of the cardiac sodium channel complex in the generation and propagation of the cardiac action potential. The complex comprises multiple protein factors, including the pore-forming α-subunit encoded by SCN5A, auxiliary β-subunits, and other accessory proteins, such as MOG1, ankyrin-G, FHF1B, Fyn and PTPH1 (45). In humans, 4 sodium channel β-subunits (β1 to β4, encoded by SCN1B to SCN4B), which are expressed in both atrial and ventricular cardiomyocytes, have been identified thus far. They share a common protein topology with an extracellular immunoglobulin-like domain, a single transmembrane spanning segment, and an intracellular C-terminal domain, and are implicated in the trafficking of sodium channels to plasma membranes, the modulation of channel gating and voltage dependence, and play a role in cell adhesion and recruitment of cytosolic proteins such as ankyrin-G (45). Mutations in SCN5A, SCN1B, SCN2B and SCN3B have been implicated in AF (2833), which prompts us to hypothesize that SCN4B is another gene contributing to AF.

To examine this hypothesis, the coding exons and splice sites of SCN4B were sequenced in patients with familial AF in contrast to ethnically matched control individuals, and the functional effect of the mutated SCN4B gene was analyzed in silico by using the online program, MutationTaster.

Materials and methods

Study subjects

A cohort of 170 unrelated index patients with familial AF identified among the Han Chinese population was recruited. The available relatives of the probands harboring the identified mutations were also enrolled in this study. A total of 200 unrelated ethnically matched healthy individuals used as the controls were enlisted. All the participants underwent evaluation by medical history, physical examination, electrocardiography and echocardiography. Peripheral venous blood specimens were prepared and clinical data including medical records, electrocardiogram and echocardiography reports were collected. The study subjects were clinically classified using a consistently applied set of definitions (7,38). In brief, AF was diagnosed by a standard 12-lead electrocardiogram demonstrating no P waves and irregular R-R intervals irrespective of clinical symptoms. Lone AF was defined as AF occurring in individuals under the age of 60 without other cardiac or systemic diseases by physical examination, electrocardiogram, transthoracic echocardiogram and extensive laboratory tests. Familial AF was defined as that present in a family with more than one first- or second-degree relative affected with AF. Relatives were classified as ‘unaffected’ if they were asymptomatic and had a normal electrocardiogram. Paroxysmal AF was defined as AF lasting more than 30 sec that terminated spontaneously. Persistent AF was defined as AF lasting more than 7 days and requiring either pharmacological therapy or electrical cardioversion for termination. AF that was refractory to cardioversion or that was allowed to continue was classified as permanent. The study protocol was reviewed and approved by the local Institutional Ethics Committee and written informed consent was obtained from all participants prior to investigation.

Genetic analysis

Genomic DNA from all participants was extracted from blood lymphocytes with the Wizard Genomic DNA Purification kit (Promega, Madison, WI, USA). Initially, the coding exons and intron/exon boundaries of the SCN4B gene were sequenced in 170 unrelated index patients with familial AF. Subsequently, genotyping for SCN4B in the available relatives of the probands carrying the identified mutations and 200 ethnically matched unrelated healthy individuals used as the controls was performed. The reference genomic DNA sequence of SCN4B was derived from GenBank (accession no. NG_011710). With the aid of online Primer3 software (http://frodo.wi.mit.edu), the primer pairs used to amplify the coding regions and splice junctions of SCN4B by polymerase chain reaction (PCR) were designed as shown in Table I. PCR was carried out using HotStar Taq DNA Polymerase (Qiagen, Hilden, Germany) on a PE 9700 Thermal Cycler (Applied Biosystems, Foster, CA, USA) with standard conditions and concentrations of reagents. Amplified products were purified with the QIAquick Gel Extraction kit (Qiagen). Both strands of each PCR product were sequenced with a BigDye® Terminator version 3.1 Cycle Sequencing kit (Applied Biosystems) under an ABI PRISM 3130XL DNA Analyzer (Applied Biosystems). The sequencing primers were those designed previously for specific region amplifications. DNA sequences were viewed and analyzed with the DNA Sequencing Analysis Software version 5.1 (Applied Biosystems). The variant was validated by resequencing of an independent PCR-generated amplicon from the same subject and met the quality control threshold with a call rate >99%. Additionally, an identified variant was searched in the single nucleotide polymorphism (SNP) database from the National Center for Biotechnology Information (NCBI, http://www.ncbi.nlm.nih.gov/SNP) to confirm the novelty.

Table I.

The intronic primers used to amplify the coding exons and exon-intron boundaries of SCN4B.

Table I.

The intronic primers used to amplify the coding exons and exon-intron boundaries of SCN4B.

ExonForward primer (5′→3′)Reverse primer (5′→3′)Size (bp)
1CTC, TCT, GCC, CGC, TAA, CTT, TCCTA, TGA, ACC, AGG, CAG, GAA, CC371
2TTG, GCA, CTG, AGG, GTG, ATA, GACAG, AAG, GGA, CCA, GAG, CGT, AG372
3GAG, GAC, CCC, GAT, TCT, TTC, TCAAA, CAC, CAA, CAC, GGT, CCA, TT387
4TGA, TAG, ATG, CCA, TGC, TCT, GCGGG, GTA, GAT, GAG, AGG, GTG, GT382
5TCT, GTA, GAA, GGC, CAG, GGA, GAGGC, AGG, ACT, CTG, GTT, TCT, TG361
Alignment of multiple SCN4B protein sequences across species

The multiple SCN4B protein sequences across various species were aligned using the online program, MUSCLE version 3.6 (http://www.ncbi.nlm.nih.gov/homologene?cmd=retrieve&dopt=multipleAlignment&list_uids=18384).

Prediction of the causative potential of a SCN4B sequence variation

The disease-causing potential of a SCN4B sequence variation was predicted using MutationTaster (http://www.mutationtaster.org), which automatically gave a probability for the variation to be either a pathogenic mutation or a benign polymorphism. Notably, the P-value is the probability of the prediction rather than the probability of error as used in t-test statistics, i.e., a value close to 1 indicates a high ‘security’ of the prediction.

Statistical analysis

Data are expressed as the means ± SD. Continuous variables were examined for normality of distribution and the unpaired Student’s t-test was used for the comparison of numeric variables between 2 groups. Comparison of the categorical variables between 2 groups was performed using Pearson’s χ2 or Fisher’s exact tests when appropriate. A two-tailed P-value <0.05 was considered to indicate a statistically significant difference.

Results

Characteristics of the study population

A cohort of 170 unrelated patients with familial AF and a total of 200 ethnically matched unrelated healthy individuals used as the controls were registered and clinically evaluated. None of them had apparent traditional risk factors for AF. There were no significant differences between the patient and control groups in baseline characteristics including age, gender, body mass index, blood pressure, fasting blood glucose levels, serum lipid levels, left atrial dimension, left ventricular ejection fraction, heart rate at rest, as well as life style (data not shown). In the present study, 12 patients were also diagnosed with hyper-tension in accordance to the criterion that the average systolic or diastolic blood pressure (2 readings performed after 5 min of rest in the sitting position) was ≥140 or 90 mmHg, respectively, but at the time of initial diagnosis of AF, their blood pressures were normal. The baseline clinical characteristics of the 170 patients with familial AF are summarized in Table II.

Table II.

The baseline clinical characteristics of the 170 pro-bands with familial atrial fibrillation.

Table II.

The baseline clinical characteristics of the 170 pro-bands with familial atrial fibrillation.

ParameterStatistic
Age at initial diagnosis of atrial fibrillation (years)44±9
Age at present study (years)49±8
Male (n, %)112 (66)
Body mass index (kg/m2)23±3
Left ventricular ejection fraction (%)61±5
Left atrial diameter (mm)37±4
Paroxysmal atrial fibrillation (n, %)98 (58)
Persistent atrial fibrillation (n, %)51 (30)
Permanent atrial fibrillation (n, %)21 (12)
Positive family history of atrial fibrillation (n, %)170 (100)
History of cardioversion (n, %)88 (52)
Catheter-based ablation for atrial fibrillation (n, %)76 (45)
History of thromboembolic stroke (n, %)24 (14)
History of pacemaker (n, %)9 (5)
Systolic blood pressure (mmHg)128±10
Diastolic blood pressure (mmHg)80±5
Fasting blood glucose (mmol/l)6±1
Total cholesterol (mmol/l)5±1
Aspirin (n, %)37 (22)
Warfarin (n, %)78 (46)
Amiodarone (n, %)92 (54)
β-blocker (n, %)33 (19)
Calcium channel blocker (n, %)27 (16)
Digitalis (n, %)43 (25)
SCN4B mutations

Direct sequencing of the entire coding sequences and flanking intronic sequences of the SCN4B gene was performed following PCR amplification of genomic DNA from each of the 170 unrelated patients with familial AF. Two heterozygous SCN4B mutations were identified in 2 out of the 170 patients, with a mutational prevalence of approximately 1.18%. Specifically, a substitution of guanine (G) for thymine (T) in the second nucleotide of codon 162 (c.485T>G), predicting the transition of valine (V) into glycine (G) at amino acid 162 (p.V162G), was identified in the proband from family 1. A replacement of adenine (A) by cytosine (C) in the first nucleotide of codon 166 (c.496A>C), equivalent to a transversion of isoleucine (I) into leucine (L) at amino acid 166 (p.I166L), was identified in the proband from family 2. The sequence chromatograms showing the detected heterozygous SCN4B mutations in contrast to the corresponding control sequences are shown in (Fig. 1). A schematic linear topology of the SCN4B-encoded β4 subunit indicating the locations of the mutations identified in AF patients is presented in (Fig. 2). The missense mutations were not found in the 400 control alleles nor were they reported in the SNP database. A genetic scan of the families of the 2 mutation carriers showed that in each family the mutation was present in all affected living family members, but absent in the unaffected family members examined. Analysis of the pedigrees revealed that each mutation co-segregated with AF transmitted in an autosomal dominant pattern in the family with a complete penetrance. The pedigree structures of the 2 families are illustrated in (Fig. 3). The phenotypic characteristics and genotypic status of the affected family members are listed in Table III.

Table III.

The phenotypic characteristics and status of SCN4B mutations of the affected pedigree members.

Table III.

The phenotypic characteristics and status of SCN4B mutations of the affected pedigree members.

Subject information
Phenotype
Electrocardiogram
Cardiac echocardiogram
Genotype
IdentityGenderAge at time of study (years)Age at initial diagnosis of AF (years)AF (classification)Heart rate (beats/min)QRS interval (msec)QTcLAD (mm)LVEF (%)SCN4B mutations
Family 1V162G
  I-2F6232Permanent71985423862+/-
  II-1M4036Paroxysmal731064453568+/-
  II-3M3830Paroxysmal79904443260+/-
Family 2I166L
  I-1M6941Permanent681084263758+/-
  II-2F4638Persistent661004043467+/-
  III-1M2222Paroxysmal128863973064+/-

[i] AF, atrial fibrillation; F, female; M, male; QTc, corrected QT interval; LAD, left atrial dimension; LVEF, left ventricular ejection fraction; +, presence of mutation; −, absence of mutation.

According to a commonly used criterion to diagnose long QT syndrome (46), the corrected QT interval was defined as normal range (≤440 msec) or prolonged (>440 msec). Using this definition, all 3 AF patients from family 1 had long QT (Table III). The mother of the proband experienced recurrent syncopal episodes that began when she was 26 years old. Since that time, she had experienced >20 syncopal episodes, the majority of which were preceded by emotional or physical stress. The electrocardiogram revealed a markedly prolonged QT interval (corrected QT interval was 542 msec), and the echocardiogram documented a structurally normal heart. Therefore, she was diagnosed with long QT syndrome.

Multiple alignments of SCN4B protein sequences

A cross-species alignment of SCN4B protein sequences displayed that the altered amino acids were evolutionarily highly conserved, as presented in (Fig. 4), suggesting that the amino acids are functionally important.

Causative potential of SCN4B sequence variations

The SCN4B sequence variations of c.485T>G and c.496A>C were both automatically predicted to be disease-causing mutations by MutationTaster, with P-values of 0.745474 for c.485T>G and 0.996496 for c.496A>C. No SNPs in the altered regions were found in the MutationTaster database.

Discussion

In the present study, 2 novel heterozygous SCN4B mutations, p.V162G and p.I166L, were identified in 2 families with AF, respectively. In each family, the missense mutation was present in all the affected family members examined but was absent in the unaffected family members available. These 2 mutations were not detected in the 400 normal chromosomes from an ethnically-matched control population. A cross-species alignment of multiple SCN4B protein sequences exhibited that the altered amino acids were evolutionarily highly conserved. Functional analysis in silico demonstrated that the mutations were both disease-causing. Therefore, it is highly likely that mutated SCN4B gene contributes to the pathogenesis of AF in these families.

The SCN4B gene maps on human chromosome 11q23.3, and is composed of 5 exons, encoding a type 1 membrane protein of 228 amino acids, which forms an auxiliary β4 subunit of voltage-gated sodium channel (47). Quantitative analysis of the tissue distribution of the sodium channel β4 subunit showed that β4 was expressed primarily in excitable tissues, including neuronal, muscular and cardiac tissues from mice, rats and humans (47,48). Similar to the β1–β3 subunits, β4 contains an N-terminal cleaved signal sequence, an extracellular V-type immunoglobulin-like fold, a single transmembrane α helix, and a short intracellular C-terminal tail that may participate in protein-protein interactions. In the immunoglobulin-like fold of the predicted mature β4 protein, there are 3 cysteines, of which the cysteines at positions 23 and 101 are completely conserved across all other β subunits, as well as other V-type immunoglobulin-like folds, and have been proposed to form an intramolecular disulfide bond that stabilizes the structure of the extracellular domain. The β4 subunit is covalently associated with sodium channel α subunit via a disulfide bond to constitute a functional ion channel complexity and functions to increase the expression of sodium channel at the cell surface and modulate its gating kinetics and voltage dependence, which suggests an important role of the β4 subunit in cardiac electrophysiology (45,47).

The findings that the mutated SCN4B gene predisposes to AF may be partially attributed to dysfunctional sodium channels. Sodium channels play a pivotal role not only in the initiation of the action potential but also in the maintenance of the action potential dome, and the loss of sodium channel function can result in shortened refractoriness and slowed conduction, which creates an important electrophysiological substrate for reentry in favor of AF (49,50). Additionally, the gain of sodium channel function may give rise to enhanced cellular excitability, increased spontaneous action potential depolarization and reduced threshold for action potential firing, forming an arrhythmogenic matrix prone to AF (5153). The SCN4B mutations, p.V162G and p.I166L identified in this study, were both located in the transmembrane domain, and thus may be expected to exert a critical effect on the conduction of sodium ions across the membrane and voltage-dependent gating of sodium channel. Therefore, it can by hypothesized that SCN4B is an integral structural component of the cardiac sodium channel complex required for the sodium channel to function adequately, and the mutations, p.V162G and p.I166L, may alter sodium current density and the voltage dependence of sodium channel activation or inactivation. However, the detailed electrophysiological mechanisms by which the mutated SCN4B gene confers susceptibility to AF remain to be elucidated.

Of note, all 3 AF patients from family 1, who harbored the SCN4B mutation p.V162G, had a prolonged QT interval, and the mother of the proband had been diagnosed as having long QT syndrome. Since 10–15% of patients with long QT syndrome have a normal QT interval (54), it could not be ruled out that other family members carrying a SCN4B mutation had long QT syndrome. Consistent our results, Medeiros-Domingo et al (55) performed a genetic analysis of SCN4B in 263 patients with congenital long QT syndrome and found the heterozygous missense mutation, p.L179F, with a mutational prevalence of approximately 0.38%. This mutation was not observed in 800 reference alleles and led to an increase in late sodium current. Tan et al (56) genotyped SCN4B in 292 cases with sudden infant death syndrome and discovered the heterozygous mutation, p.S206L, with a mutational prevalence of approximately 0.34%. Functional analysis revealed that this mutation accentuated the late sodium current and increased the ventricular action potential duration. These findings indicate that AF may share a common genetic origin with long QT syndrome as well as sudden infant death. Considering that congenital long QT syndrome is potentially lethal secondary to malignant ventricular arrhythmias and that the mutated SCN4B gene has been linked to sudden infant death, the present study is of significant clinical importance.

In conclusion, to our knowledge, this is the first study presenting SCN4B as a novel AF-susceptibility gene and suggests a common genetic basis for AF and congenital long QT syndrome, as well as sudden infant death. The findings provide significant insight into the molecular mechanisms underlying arrhythmias and provide potential therapeutic strategies for the early prophylaxis and personalized therapy of arrhythmias.

Acknowledgements

We would like to thank the participants for their devotion to the study. This study was supported by grants from the National Natural Science Fund of China (81070153, 81270161 and 30570768), the Natural Science Fund of Shanghai, China (10ZR1428000), the Personnel Development Foundation of Shanghai, China (2010019) and the Key Program of Basic Research of Shanghai, China (10JC1414000, 10JC1414001 and 10JC1414002).

References

1. 

Fuster V, Rydén LE, Cannom DS, Crijns HJ, Curtis AB, Ellenbogen KA, Halperin JL, Kay GN, Le Huezey JY, Lowe JE, Olsson SB, Prystowsky EN, Tamargo JL, Wann LS, Smith SC Jr, Priori SG, Estes NA III, Ezekowitz MD, Jackman WM, January CT, Lowe JE, Page RL, Slotwiner DJ, Stevenson WG, Tracy CM, Jacobs AK, Anderson JL, Albert N, Buller CE, Creager MA, Ettinger SM, Guyton RA, Halperin JL, Hochman JS, Kushner FG, Ohman EM, Stevenson WG, Tarkington LG and Yancy CW; American College of Cardiology Foundation/American Heart Association Task Force: 2011 ACCF/AHA/HRS focused updates incorporated into the ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. Circulation. 123:e269–e367. 2011.

2. 

Go AS, Hylek EM, Phillips KA, Chang Y, Henault LE, Selby JV and Singer DE: Prevalence of diagnosed atrial fibrillation in adults: national implications for rhythm management and stroke prevention: the AnTicoagulation and Risk Factors in Atrial Fibrillation (ATRIA) Study. JAMA. 285:2370–2375. 2001. View Article : Google Scholar : PubMed/NCBI

3. 

Lloyd-Jones DM, Wang TJ, Leip EP, Larson MG, Levy D, Vasan RS, D’Agostino RB, Massaro JM, Beiser A, Wolf PA and Benjamin EJ: Lifetime risk for development of atrial fibrillation: the Framingham Heart Study. Circulation. 110:1042–1046. 2004. View Article : Google Scholar : PubMed/NCBI

4. 

Wolf PA, Abbott RD and Kannel WB: Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. Stroke. 22:983–988. 1991. View Article : Google Scholar : PubMed/NCBI

5. 

Benjamin EJ, Wolf PA, D’Agostino RB, Silbershatz H, Kannel WB and Levy D: Impact of atrial fibrillation on the risk of death: the Framingham Heart Study. Circulation. 98:946–952. 1998. View Article : Google Scholar : PubMed/NCBI

6. 

Magnani JW, Rienstra M, Lin H, Sinner MF, Lubitz SA, McManus DD, Dupuis J, Ellinor PT and Benjamin EJ: Atrial fibrillation: current knowledge and future directions in epidemiology and genomics. Circulation. 124:1982–1993. 2011. View Article : Google Scholar : PubMed/NCBI

7. 

Darbar D, Herron KJ, Ballew JD, Jahangir A, Gersh BJ, Shen WK, Hammill SC, Packer DL and Olson TM: Familial atrial fibrillation is a genetically heterogeneous disorder. J Am Coll Cardiol. 41:2185–2192. 2003. View Article : Google Scholar : PubMed/NCBI

8. 

Ellinor PT, Yoerger DM, Ruskin JN and MacRae CA: Familial aggregation in lone atrial fibrillation. Hum Genet. 118:179–184. 2005. View Article : Google Scholar : PubMed/NCBI

9. 

Arnar DO, Thorvaldsson S, Manolio TA, Thorgeirsson G, Kristjansson K, Hakonarson H and Stefansson K: Familial aggregation of atrial fibrillation in Iceland. Eur Heart J. 27:708–712. 2006. View Article : Google Scholar : PubMed/NCBI

10. 

Junttila MJ, Raatikainen MJ, Perkiömäki JS, Hong K, Brugada R and Huikuri HV: Familial clustering of lone atrial fibrillation in patients with saddleback-type ST-segment elevation in right precordial leads. Eur Heart J. 28:463–468. 2007. View Article : Google Scholar : PubMed/NCBI

11. 

Christophersen IE, Ravn LS, Budtz-Joergensen E, Skytthe A, Haunsoe S, Svendsen JH and Christensen K: Familial aggregation of atrial fibrillation: a study in Danish twins. Circ Arrhythm Electrophysiol. 2:378–383. 2009. View Article : Google Scholar : PubMed/NCBI

12. 

Yang YQ, Zhang XL, Wang XH, Tan HW, Shi HF, Fang WY and Liu X: Familial aggregation of lone atrial fibrillation in the Chinese population. Intern Med. 49:2385–2391. 2010. View Article : Google Scholar : PubMed/NCBI

13. 

Lubitz SA, Yin X, Fontes JD, Magnani JW, Rienstra M, Pai M, Villalon ML, Vasan RS, Pencina MJ, Levy D, Larson MG, Ellinor PT and Benjamin EJ: Association between familial atrial fibrillation and risk of new-onset atrial fibrillation. JAMA. 304:2263–2269. 2010. View Article : Google Scholar : PubMed/NCBI

14. 

Fox CS, Parise H, D’Agostino RB Sr, Lloyd-Jones DM, Vasan RS, Wang TJ, Levy D, Wolf PA and Benjamin EJ: Parental atrial fibrillation as a risk factor for atrial fibrillation in offspring. JAMA. 291:2851–2855. 2004. View Article : Google Scholar : PubMed/NCBI

15. 

Brugada R, Tapscott T, Czernuszewicz GZ, Marian AJ, Iglesias A, Mont L, Brugada J, Girona J, Domingo A, Bachinski LL and Roberts R: Identification of a genetic locus for familial atrial fibrillation. N Engl J Med. 336:905–911. 1997. View Article : Google Scholar : PubMed/NCBI

16. 

Ellinor PT, Shin JT, Moore RK, Yoerger DM and MacRae CA: Locus for atrial fibrillation maps to chromosome 6q14–16. Circulation. 107:2880–2883. 2003.PubMed/NCBI

17. 

Chen YH, Xu SJ, Bendahhou S, Wang XL, Wang Y, Xu WY, Jin HW, Sun H, Su XY, Zhuang QN, Yang YQ, Li YB, Liu Y, Xu HJ, Li XF, Ma N, Mou CP, Chen Z, Barhanin J and Huang W: KCNQ1 gain-of-function mutation in familial atrial fibrillation. Science. 299:251–254. 2003. View Article : Google Scholar : PubMed/NCBI

18. 

Oberti C, Wang L, Li L, Dong J, Rao S, Du W and Wang Q: Genome-wide linkage scan identifies a novel genetic locus on chromosome 5p13 for neonatal atrial fibrillation associated with sudden death and variable cardiomyopathy. Circulation. 110:3753–3759. 2004. View Article : Google Scholar

19. 

Darbar D, Hardy A, Haines JL and Roden DM: Prolonged signal-averaged P-wave duration as an intermediate phenotype for familial atrial fibrillation. J Am Coll Cardiol. 51:1083–1089. 2008. View Article : Google Scholar : PubMed/NCBI

20. 

Zhang X, Chen S, Yoo S, Chakrabarti S, Zhang T, Ke T, Oberti C, Yong SL, Fang F, Li L, de la Fuente R, Wang L, Chen Q and Wang QK: Mutation in nuclear pore component NUP155 leads to atrial fibrillation and early sudden cardiac death. Cell. 135:1017–1027. 2008. View Article : Google Scholar : PubMed/NCBI

21. 

Yang Y, Xia M, Jin Q, Bendahhou S, Shi J and Chen Y, Liang B, Lin J, Liu Y, Liu B, Zhou Q, Zhang D, Wang R, Ma N, Su X, Niu K, Pei Y, Xu W, Chen Z, Wan H, Cui J, Barhanin J and Chen Y: Identification of a KCNE2 gain-of-function mutation in patients with familial atrial fibrillation. Am J Hum Genet. 75:899–905. 2004. View Article : Google Scholar : PubMed/NCBI

22. 

Lundby A, Ravn LS, Svendsen JH, Hauns S, Olesen SP and Schmitt N: KCNE3 mutation V17M identified in a patient with lone atrial fibrillation. Cell Physiol Biochem. 21:47–54. 2008. View Article : Google Scholar : PubMed/NCBI

23. 

Ravn LS, Aizawa Y, Pollevick GD, Hofman-Bang J, Cordeiro JM, Dixen U, Jensen G, Wu Y, Burashnikov E, Haunso S, Guerchicoff A, Hu D, Svendsen JH, Christiansen M and Antzelevitch C: Gain of function in IKs secondary to a mutation in KCNE5 associated with atrial fibrillation. Heart Rhythm. 5:427–435. 2008. View Article : Google Scholar : PubMed/NCBI

24. 

Hong K, Bjerregaard P, Gussak I and Brugada R: Short QT syndrome and atrial fibrillation caused by mutation in KCNH2. J Cardiovasc Electrophysiol. 16:394–396. 2005. View Article : Google Scholar : PubMed/NCBI

25. 

Xia M, Jin Q, Bendahhou S, He Y, Larroque MM and Chen Y, Zhou Q, Yang Y, Liu Y, Liu B, Zhu Q, Zhou Y, Lin J, Liang B, Li L, Dong X, Pan Z, Wang R, Wan H, Qiu W, Xu W, Eurlings P, Barhanin J and Chen Y: A Kir2.1 gain-of-function mutation underlies familial atrial fibrillation. Biochem Biophys Res Commun. 332:1012–1019. 2005. View Article : Google Scholar : PubMed/NCBI

26. 

Olson TM, Alekseev AE, Liu XK, Park S, Zingman LV, Bienengraeber M, Sattiraju S, Ballew JD, Jahangir A and Terzic A: Kv1.5 channelopathy due to KCNA5 loss-of-function mutation causes human atrial fibrillation. Hum Mol Genet. 15:2185–2191. 2006. View Article : Google Scholar : PubMed/NCBI

27. 

Yang Y, Li J, Lin X, Yang Y, Hong K, Wang L, Liu J, Li L, Yan D, Liang D, Xiao J, Jin H, Wu J, Zhang Y and Chen YH: Novel KCNA5 loss-of-function mutations responsible for atrial fibrillation. J Hum Genet. 54:277–283. 2009. View Article : Google Scholar : PubMed/NCBI

28. 

Olson TM, Michels VV, Ballew JD, Reyna SP, Karst ML, Herron KJ, Horton SC, Rodeheffer RJ and Anderson JL: Sodium channel mutations and susceptibility to heart failure and atrial fibrillation. JAMA. 293:447–454. 2005. View Article : Google Scholar : PubMed/NCBI

29. 

Darbar D, Kannankeril PJ, Donahue BS, Kucera G, Stubblefield T, Haines JL, George AL Jr and Roden DM: Cardiac sodium channel (SCN5A) variants associated with atrial fibrillation. Circulation. 117:1927–1935. 2008. View Article : Google Scholar : PubMed/NCBI

30. 

Watanabe H, Darbar D, Kaiser DW, Jiramongkolchai K, Chopra S, Donahue BS, Kannankeril PJ and Roden DM: Mutations in sodium channel beta1- and beta2-subunits associated with atrial fibrillation. Circ Arrhythm Electrophysiol. 2:268–275. 2009. View Article : Google Scholar : PubMed/NCBI

31. 

Olesen MS, Holst AG, Svendsen JH, Haunsø S and Tfelt-Hansen J: SCN1Bb R214Q found in 3 patients: 1 with Brugada syndrome and 2 with lone atrial fibrillation. Heart Rhythm. 9:770–773. 2012. View Article : Google Scholar : PubMed/NCBI

32. 

Wang P, Yang Q, Wu X, Yang Y, Shi L, Wang C, Wu G, Xia Y, Yang B, Zhang R, Xu C, Cheng X, Li S, Zhao Y, Fu F, Liao Y, Fang F, Chen Q, Tu X and Wang QK: Functional dominant-negative mutation of sodium channel subunit gene SCN3B associated with atrial fibrillation in a Chinese GeneID population. Biochem Biophys Res Commun. 398:98–104. 2010. View Article : Google Scholar : PubMed/NCBI

33. 

Olesen MS, Jespersen T, Nielsen JB, Liang B, Møller DV, Hedley P, Christiansen M, Varró A, Olesen SP, Haunsø S, Schmitt N and Svendsen JH: Mutations in sodium channel β-subunit SCN3B are associated with early-onset lone atrial fibrillation. Cardiovasc Res. 89:786–793. 2011.

34. 

Hodgson-Zingman DM, Karst ML, Zingman LV, Heublein DM, Darbar D, Herron KJ, Ballew JD, de Andrade M, Burnett JC Jr and Olson TM: Atrial natriuretic peptide frameshift mutation in familial atrial fibrillation. N Engl J Med. 359:158–165. 2008. View Article : Google Scholar : PubMed/NCBI

35. 

Thibodeau IL, Xu J, Li Q, Liu G, Lam K, Veinot JP, Birnie DH, Jones DL, Krahn AD, Lemery R, Nicholson BJ and Gollob MH: Paradigm of genetic mosaicism and lone atrial fibrillation: physiological characterization of a connexin 43-deletion mutant identified from atrial tissue. Circulation. 122:236–244. 2010. View Article : Google Scholar

36. 

Gollob MH, Jones DL, Krahn AD, Danis L, Gong XQ, Shao Q, Liu X, Veinot JP, Tang AS, Stewart AF, Tesson F, Klein GJ, Yee R, Skanes AC, Guiraudon GM, Ebihara L and Bai D: Somatic mutations in the connexin 40 gene (GJA5) in atrial fibrillation. N Engl J Med. 354:2677–2688. 2006. View Article : Google Scholar : PubMed/NCBI

37. 

Yang YQ, Zhang XL, Wang XH, Tan HW, Shi HF, Jiang WF, Fang WY and Liu X: Connexin40 nonsense mutation in familial atrial fibrillation. Int J Mol Med. 26:605–610. 2010.PubMed/NCBI

38. 

Jiang JQ, Shen FF, Fang WY, Liu X and Yang YQ: Novel GATA4 mutations in lone atrial fibrillation. Int J Mol Med. 28:1025–1032. 2011.PubMed/NCBI

39. 

Yang YQ, Wang MY, Zhang XL, Tan HW, Shi HF, Jiang WF, Wang XH, Fang WY and Liu X: GATA4 loss-of-function mutations in familial atrial fibrillation. Clin Chim Acta. 412:1825–1830. 2011. View Article : Google Scholar : PubMed/NCBI

40. 

Wang J, Sun YM and Yang YQ: Mutation spectrum of the GATA4 gene in patients with idiopathic atrial fibrillation. Mol Biol Rep. 39:8127–8135. 2012. View Article : Google Scholar : PubMed/NCBI

41. 

Yang YQ, Wang J, Wang XH, Wang Q, Tan HW, Zhang M, Shen FF, Jiang JQ, Fang WY and Liu X: Mutational spectrum of the GATA5 gene associated with familial atrial fibrillation. Int J Cardiol. 157:305–307. 2012. View Article : Google Scholar : PubMed/NCBI

42. 

Yang YQ, Wang XH, Tan HW, Jiang WF, Fang WY and Liu X: Prevalence and spectrum of GATA6 mutations associated with familial atrial fibrillation. Int J Cardiol. 155:494–496. 2012. View Article : Google Scholar : PubMed/NCBI

43. 

Yang YQ, Li L, Wang J, Zhang XL, Li RG, Xu YJ, Tan HW, Wang XH, Jiang JQ, Fang WY and Liu X: GATA6 loss-of-function mutation in atrial fibrillation. Eur J Med Genet. 55:520–526. 2012. View Article : Google Scholar : PubMed/NCBI

44. 

Li J, Liu WD, Yang ZL and Yang YQ: Novel GATA6 loss-of-function mutation responsible for familial atrial fibrillation. Int J Mol Med. 30:783–790. 2012.PubMed/NCBI

45. 

Meadows LS and Isom LL: Sodium channels as macromolecular complexes: implications for inherited arrhythmia syndromes. Cardiovasc Res. 67:448–458. 2005. View Article : Google Scholar : PubMed/NCBI

46. 

Schwartz PJ, Moss AJ, Vincent GM and Crampton RS: Diagnostic criteria for the long QT syndrome: an update. Circulation. 88:782–784. 1993. View Article : Google Scholar : PubMed/NCBI

47. 

Yu FH, Westenbroek RE, Silos-Santiago I, McCormick KA, Lawson D, Ge P, Ferriera H, Lilly J, DiStefano PS, Catterall WA, Scheuer T and Curtis R: Sodium channel beta4, a new disulfide-linked auxiliary subunit with similarity to beta2. J Neurosci. 23:7577–7585. 2003.PubMed/NCBI

48. 

Maier SK, Westenbroek RE, McCormick KA, Curtis R, Scheuer T and Catterall WA: Distinct subcellular localization of different sodium channel alpha and beta subunits in single ventricular myocytes from mouse heart. Circulation. 109:1421–1427. 2004. View Article : Google Scholar

49. 

Terrenoire C, Simhaee D and Kass RS: Role of sodium channels in propagation in heart muscle: how subtle genetic alterations result in major arrhythmic disorders. J Cardiovasc Electrophysiol. 18:900–905. 2007. View Article : Google Scholar : PubMed/NCBI

50. 

Nattel S: New ideas about atrial fibrillation 50 years on. Nature. 415:219–226. 2002.PubMed/NCBI

51. 

Makiyama T, Akao M, Shizuta S, Doi T, Nishiyama K, Oka Y, Ohno S, Nishio Y, Tsuji K, Itoh H, Kimura T, Kita T and Horie M: A novel SCN5A gain-of-function mutation M1875T associated with familial atrial fibrillation. J Am Coll Cardiol. 52:1326–1334. 2008. View Article : Google Scholar : PubMed/NCBI

52. 

Li Q, Huang H, Liu G, Lam K, Rutberg J, Green MS, Birnie DH, Lemery R, Chahine M and Gollob MH: Gain-of-function mutation of Nav1.5 in atrial fibrillation enhances cellular excitability and lowers the threshold for action potential firing. Biochem Biophys Res Commun. 380:132–137. 2009. View Article : Google Scholar : PubMed/NCBI

53. 

Blana A, Kaese S, Fortmüller L, Laakmann S, Damke D, van Bragt K, Eckstein J, Piccini I, Kirchhefer U, Nattel S, Breithardt G, Carmeliet P, Carmeliet E, Schotten U, Verheule S, Kirchhof P and Fabritz L: Knock-in gain-of-function sodium channel mutation prolongs atrial action potentials and alters atrial vulnerability. Heart Rhythm. 7:1862–1869. 2010. View Article : Google Scholar : PubMed/NCBI

54. 

Moric-Janiszewska E, Markiewicz-Łoskot G, Loskot M, Weglarz L, Hollek A and Szydlowski L: Challenges of diagnosis of long-QT syndrome in children. Pacing Clin Electrophysiol. 30:1168–1170. 2007. View Article : Google Scholar : PubMed/NCBI

55. 

Medeiros-Domingo A, Kaku T, Tester DJ, Iturralde-Torres P, Itty A, Ye B, Valdivia C, Ueda K, Canizales-Quinteros S, Tusié-Luna MT, Makielski JC and Ackerman MJ: SCN4B-encoded sodium channel beta4 subunit in congenital long-QT syndrome. Circulation. 116:134–142. 2007. View Article : Google Scholar : PubMed/NCBI

56. 

Tan BH, Pundi KN, Van Norstrand DW, Valdivia CR, Tester DJ, Medeiros-Domingo A, Makielski JC and Ackerman MJ: Sudden infant death syndrome-associated mutations in the sodium channel beta subunits. Heart Rhythm. 7:771–778. 2010. View Article : Google Scholar : PubMed/NCBI

Related Articles

Journal Cover

July 2013
Volume 32 Issue 1

Print ISSN: 1107-3756
Online ISSN:1791-244X

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
APA
Li, R., Wang, Q., Xu, Y., Zhang, M., Qu, X., Liu, X. ... Yang, Y. (2013). Mutations of the SCN4B-encoded sodium channel β4 subunit in familial atrial fibrillation. International Journal of Molecular Medicine, 32, 144-150. https://doi.org/10.3892/ijmm.2013.1355
MLA
Li, R., Wang, Q., Xu, Y., Zhang, M., Qu, X., Liu, X., Fang, W., Yang, Y."Mutations of the SCN4B-encoded sodium channel β4 subunit in familial atrial fibrillation". International Journal of Molecular Medicine 32.1 (2013): 144-150.
Chicago
Li, R., Wang, Q., Xu, Y., Zhang, M., Qu, X., Liu, X., Fang, W., Yang, Y."Mutations of the SCN4B-encoded sodium channel β4 subunit in familial atrial fibrillation". International Journal of Molecular Medicine 32, no. 1 (2013): 144-150. https://doi.org/10.3892/ijmm.2013.1355