Volume 11, Issue 12 e2263
ORIGINAL ARTICLE
Open Access

In silico validation revealed the role of SCN5A mutations and their genotype–phenotype correlations in Brugada syndrome

Hung Manh Pham

Hung Manh Pham

Center for Gene and Protein Research, Hanoi Medical University, Hanoi, Vietnam

Vietnam National Heart Institute, Bach Mai Hospital, Hanoi, Vietnam

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Duy Phuong Dang

Duy Phuong Dang

Center for Gene and Protein Research, Hanoi Medical University, Hanoi, Vietnam

Ho Chi Minh City Heart Institute, Ho Chi Minh, Vietnam

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Thanh Dat Ta

Thanh Dat Ta

Center for Gene and Protein Research, Hanoi Medical University, Hanoi, Vietnam

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Thi Phuong Le

Thi Phuong Le

Center for Gene and Protein Research, Hanoi Medical University, Hanoi, Vietnam

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Dinh Phong Phan

Dinh Phong Phan

Center for Gene and Protein Research, Hanoi Medical University, Hanoi, Vietnam

Vietnam National Heart Institute, Bach Mai Hospital, Hanoi, Vietnam

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Hoai An Trinh

Hoai An Trinh

Hue Central Hospital, Hue, Vietnam

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Tuan Viet Tran

Tuan Viet Tran

Center for Gene and Protein Research, Hanoi Medical University, Hanoi, Vietnam

Vietnam National Heart Institute, Bach Mai Hospital, Hanoi, Vietnam

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Thi Lan Anh Luong

Thi Lan Anh Luong

Center for Gene and Protein Research, Hanoi Medical University, Hanoi, Vietnam

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Ha Minh Nguyen

Ha Minh Nguyen

Pham Ngoc Thach University of Medicine, Ho Chi Minh, Vietnam

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The-Hung Bui

The-Hung Bui

Center for Gene and Protein Research, Hanoi Medical University, Hanoi, Vietnam

Center for Molecular Medicine, Clinical Genetics Unit, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden

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Thinh Huy Tran

Thinh Huy Tran

Center for Gene and Protein Research, Hanoi Medical University, Hanoi, Vietnam

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Thanh Van Ta

Thanh Van Ta

Center for Gene and Protein Research, Hanoi Medical University, Hanoi, Vietnam

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Van-Khanh Tran

Corresponding Author

Van-Khanh Tran

Center for Gene and Protein Research, Hanoi Medical University, Hanoi, Vietnam

Correspondence

Van-Khanh Tran, Center for Gene and Protein Research, Hanoi Medical University, 1st Ton That Tung Street, Hanoi 10000, Vietnam.

Email: [email protected]

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First published: 07 August 2023
Citations: 1

Hung Manh Pham and Duy Phuong Nguyen contributed equally to this work.

[Correction added on June 25, 2024 after first online publication. The author names ‘Duy Phuong Nguyen’ and ‘Phong Hai Phan’ has been corrected to ‘Duy Phuong Dang’ and ‘Dinh Phong Phan’ respectively in this version.]

Abstract

Background

Brugada syndrome (BrS) is a rare genetic disease that causes sudden cardiac death (SCD) and arrhythmia. SCN5A pathogenic variants (about 30% of diagnosed patients) are responsible for BrS.

Aims

Lack of knowledge regarding molecular characteristics and the correlation between genotype and phenotype interfere with the risk stratification and finding the optimal treatment in Vietnam. Therefore, we identified SCN5A variants and evaluated the genotype–phenotype correlation of BrS on 117 Vietnamese probands.

Materials and Methods

The clinical characteristics and blood samples of BrS patients were collected. To determine SCN5A variants, Sanger sequencing was conducted, and subsequently, these variants were analyzed by bioinformatic tools.

Results

In this cohort, the overall rate of detected variants in SCN5A was 25.6%, which could include both pathogenic and benign variants. In genetic testing, 21 SCN5A variants were identified, including eight novels and 15 published variants. Multiple bioinformatic tools were used to predict variant effect with c.551A>G, c.1890+14G>A, c.3338C>T, c.3578G>A, and c.5484C>T as benign, while other variants were predicted as disease-causing. The family history of SCD (risk ratio [RR] = 4.324, 95% CI: 2.290–8.269, p < 0.001), syncope (RR = 3.147, 95% CI: 1.668–5.982, p = 0.0004), and ventricular tachycardia/ventricular fibrillation (RR = 3.406, 95% CI: 1.722–5.400, p = 0.0035) presented a significantly higher risk in the SCN5A (+) group, consisting of individuals carrying any variant in the SCN5A gene, compared to SCN5A (−) individuals.

Conclusion

The results contribute to clarifying the impact of SCN5A variants on these phenotypes. Further follow-up studies need to be carried out to understand the functional effects of these SCN5A variants on the severity of BrS.

1 INTRODUCTION

Brugada syndrome (BrS) (OMIM: 600163) is an inherited disorder of cardiac electrical conduction, characterized by a specific ST-segment elevation in the right precordial leads (V1-V3) on the electrocardiogram (ECG), strongly associated with the high risk of ventricular arrhythmias and sudden death (Antzelevitch, 2006). Clinical presentation of BrS also involves sudden infant death syndrome and sudden unexpected nocturnal death syndrome. About 4% of all sudden death cases and at least 20% of sudden death cases with typical heart structures are associated with BrS (Kusano, 2013). The overall prevalence of BrS is globally estimated at 0.05% and found to be of different incidences in different regions. The highest prevalence of BrS is verified in Southeast Asia (3.7 per 1000 population), followed by the Middle East and South Asia, with both rates of 1.8 per 1000 population (Vutthikraivit et al., 2018). Males show a higher prevalence and more severe clinical manifestations than females (Benito et al., 2008). Mutations in SCN5A gene are associated with BrS, accounting for approximately 30% of BrS cases (Brugada et al., 2018). Variety of genes have been identified to be related to BrS, but SCN5A gene is the most dominant when occupied by >5% of positive genotyped patients (Ackerman et al., 2011). According to The European Society of Cardiology guidelines, SCN5A genetic testing is recommended in cases of Class I: the family with carriers of SCN5A mutation in BrS, Class IIa: the patients suspected with BrS based on clinical features, family history, and electrocardiographic (ECG) testing, Class IIb: the patients with ECG type 2 and type 3 of BrS (Priori et al., 2015). The genetic testing in affected family members plays a pivotal role in treatment classification which comprises at-risk (+) and precaution (−) groups.

SCN5A gene is located on chromosome 3p21 and has 28 exons that encode for the cardiac voltage-gated sodium channel (Nav1.5). Nav1.5 contains four transmembrane domains (DI-DIV) connected by inter-domain linkers. Each domain includes six transmembrane segments (S1-S6) joined by intra-extracellular loops (Rook et al., 2012). Segments S1-S4 in each domain are essential to forming a voltage-sensing domain (VSD) that is activated to generate sodium current (Chen-Izu et al., 2015). Nav1.5 induces the depolarization of atrial and ventricular action potentials, thus creating the up-stroke of the cardiac action potential (Jiang et al., 2020). To date, more than 900 SCN5A variants are associated with cardiac disorders and scattered throughout different gene regions. The variants induce the diversity of BrS phenotypes as well as causing loss-of-function or gain-of-function of sodium channel via altered voltage- and time-dependent activation/inactivation and decelerated recovery from inactivation (Savio-Galimberti et al., 2018). Therefore, identifying SCN5A variants and their functional assessment are vital in optimizing and personalizing patient treatment.

In Vietnam, data regarding the molecular characteristics of SCN5A variation are still lacking. Very few studies have determined the association between the genotype and phenotype of SCN5A variants in Vietnamese patients. Recently, computation tools have become widely used to assess the consequence of variants potentially causing disease (Thusberg et al., 2011). Thus, we conducted this study to screen for SCN5A variants and evaluated the genotype–phenotype correlation of BrS on 117 probands. The results will support risk stratification of BrS for treatment and provide detailed information to clinicians for genetic counseling.

2 MATERIALS AND METHODS

2.1 Patients collection

A total of 117 Brugada patients were included from the Vietnam National Heart Institute from January 2017 to April 2022. The patients were diagnosed with BrS according to the diagnostic criteria of the European Heart Rhythm Society. All individuals participated in the current study and signed informed consent.

Clinical characteristics of patients included age, sex, family history of sudden cardiac death (SCD) (<45 years old), clinical treatments, comorbidities, ECG measurements, sodium channel blocker challenge test, and electrophysiological study. This study was approved by the Ethics Committee of Hanoi Medical University (Hanoi Medical University Institutional Review Board, Hanoi, Vietnam, reference number: 48/HĐĐĐĐĐHYHN).

2.2 Molecular genetic analysis

The genomic DNA of each participant was isolated from peripheral blood using a QIAamp Blood Kit (Qiagen) according to the manufacturer's instructions. Then, DNA concentration was measured using NanoDrop 2000 spectrophotometer (Thermo Scientific) and stored at −20°C until use.

The SCN5A coding regions were amplified by PCR using the designed primers at flanking intronic sequences described Park et al. (2012). Twenty microliters of PCR mix contains GoTaq Hot Start Master Mix 2X, 5 pmol primer, DNA template, and distilled water. PCR cycle was carried out by initial denaturation at 95°C for 5 min, followed by 37 cycles of denaturation at 95°C for 30 s, annealing at Tm of primers for 30 s, and extension at 72°C for 30 s, and final extension at 72°C for 5 min. PCR products were observed on 1.5% agarose gel by electrophoresis. Next, PCR amplicons were purified and direct sequenced on ABI 3500 genetic analyzer system (Applied Biosystems). Sequencing data were assembled to reference sequences on NCBI (NG_008934 and NM_198056) to determine the SCN5A variants by CLC Main Workbench 6.0 software.

To determine the large genomic alteration, including deletions and insertions, multiplex ligation-dependent probe amplification (MLPA) was carried out by using the SALSA MLPA probe mix P108-B2 SCN5A (MRC Holland). Results were analyzed with Coffalyser software (MRC Holland).

2.3 Predicting function of SCN5A variants

We analyzed the results on eight computational tools, including six separated predictors: Mutation Assessor (http://mutationassessor.org/r3/), Polyphen-2 (http://genetics.bwh.harvard.edu/pph2/), Mutation Taster (https://www.mutationtaster.org/), PROVEAN (http://provean.jcvi.org/index.php), FATHMM (http://fathmm.biocompute.org.uk/), SIFT (https://sift.bii.a-star.edu.sg/index.html), and two meta-scores: BayesDel addAF and MetaSVM (Adzhubei et al., 2010; Choi & Chan, 2015; Feng, 2017; Kim et al., 2017; Reva et al., 2011; Schwarz et al., 2014; Shihab et al., 2013; Sim et al., 2012). These algorithms were evaluated based on the structure and function of the targeted protein and evolutionary conservation in its sequence.

2.4 Statistical analyses

A quantitative variable is presented as mean ± standard deviation. Fisher's exact test was calculated to determine the significance of categorical variables. A risk ratio (RR) was applied to determine the correlation between phenotype and genotype of SCN5A variants. A two-tailed p < 0.05 was considered statistically significant. All tests were computed by GraphPad Prism 8 software package (San Diego, USA).

3 RESULTS

3.1 Baseline clinical manifestations

The clinical manifestations and electrocardiographic variables of the 117 participants in this study are summarized in Table 1. Of those participants, males were the majority with 97.4% (114/117) compared to females with 2.6% (3/117). Genetic testing of SCN5A gene categorized the participants into two groups: SCN5A genotype positive and SCN5A genotype negative, accounting for 25.6% and 74.4%, respectively. For the purposes of this analysis, patients with any detected variants in SCN5A were included in the genotype-positive group, including benign variants as well as pathogenic variants. The average age was 47.5 ± 12.4 years, ranging from 23 to 79 years. However, no significant difference was observed in age (p = 0.056), whereas there was a different significance related to family history with sudden death in both groups (p < 0.0001).

TABLE 1. Clinical manifestations of patients in this study.
Total cases (n. %) SCN5A mutation
Positive (n. %) Negative (n. %) p-Value
n 117 30 (25.6%) 87 (74.4%)
Age 47.5 ± 12.4 43.6 ± 10.6 48.3 ± 9.8 0.056
Family history of sudden cardiac death (<45 years old) 37 20 (66.67) 17 (19.54) <0.0001
Clinical manifestations
Syncope 45 (38.46) 19 (66.33) 26 (29.89) 0.002
Nocturnal agonal respiration 11 (9.4) 4 (13.33) 7 (8.05) 0.4694
Ventricular tachycardia and ventricular fibrillation 8 (6.83) 6 (20.00) 2 (2.30) 0.0035
Cardiac arrest survivors 7 (5.98) 4 (13.33) 3 (3.45) 0.0704
Clinical treatments
None 31 (26.5) 9 (30.00) 22 (25.28) 0.6284
Pacemaker implantation 86 (73.5) 21 (70.00) 65 (74.71) 0.6362
Comorbidities
Other arrhythmias 7 (5.98) 1 (3.33) 6 (6.90) 0.6759
Atrial fibrillation 4 (3.41) 1 (3.33) 3 (3.45) 1.000
Other cardiovascular diseases 23 (19.65) 8 (26.67) 15 (17.24) 0.2915
Other internal diseases 43 (36.75) 14 (46.67) 29 (33.33) 0.1218
Type Brugada in ECG
Type 1 83 (70.95) 23 (76.67) 60 (68.96) 0.0806
Type 2 20 (17.09) 3 (10.00) 17 (19.54) 0.2754
Type 3 14 (11.96) 4 (13.33) 10 (11.49) 0.7527
Testing
Flecainide testing (+) 9 (7.69) 7 (23.33) 2 (2.30) 0.001
Electrophysiology study testing (+) 54 (46.15) 10 (33.33) 45 (51.72) 0.0934
  • * Statistical significance (p < 0.05).

Of all collected patient features, SCN5A (+) was identified with different rates in syncope, nocturnal agonal respiration, ventricular tachycardia/ventricular fibrillation (VT/VF), and cardiac arrest survivors by 66.33%, 13.33%, 20%, and 13.33%, respectively, compared to 29.89%, 8.05%, 2.3%, and 3.45% of SCN5A (˗). The prevalence of syncope and the incidence of VT/VF presented the statistical difference between SCN5A (+) and SCN5A (˗) groups with p = 0.002 and 0.0035, respectively. Neither clinical treatment methods nor comorbidities and types of BrS in ECG did show any different significance in both groups (p > 0.05). In addition, SCN5A (+) group had a higher rate of flecainide testing than the SCN5A (−) group (23.33% vs. 2.30%; p = 0.001). By contrast, a higher electrophysiology study testing was recorded in SCN5A (−) group than SCN5A (+) group, with the rate of 51.72% and 33.33% (p > 0.05), respectively.

3.2 Association analysis between phenotype and genotype of SCN5A mutation

To assess the risk of SCN5A genotype to BrS phenotype, we evaluated the RR of the clinical characteristics associated with SCN5A mutation. The results are shown in Table 2. The increased risk of 4.324 with a family history of sudden death (<45 years old) in SCN5A (+) probands (95% CI: 2.290–8.269; p < 0.0001) compared to SCN5A (−) probands. The relative risk for syncope, VT/VF, and flecainide testing were also evaluated at 3.147 (95% CI: 1.668–5.982; p = 0.0004), 3.406 (95% CI: 1.722–5.4; p = 0.0035), and 3.652 (95% CI: 1.957–5.737; p = 0.001), respectively, according to SCN5A-positive and -negative groups.

TABLE 2. Relative risks (RR) for clinical characteristics between the presence of SCN5A mutations and SCN5A negative.
Relative risk ratio 95% confidence interval p-Value
Family history of sudden death (<45 years old) 4.324 2.290–8.269 <0.0001
Syncope 3.147 1.668–5.982 0.0004
Ventricular tachycardia and ventricular fibrillation 3.406 1.722–5.400 0.0035
Flecainide testing (+) 3.652 1.957–5.737 0.001
  • * Statistical significance (p < 0.05).

3.3 Novel SCN5A variants

In our study, eight of 21 SCN5A variants were found as novel variants and were not previously recorded in the databases (ClinVar: https://www.ncbi.nlm.nih.gov/clinvar/; LOVD: https://www.lovd.nl/; dbSNP: https://www.ncbi.nlm.nih.gov/snp/). All SCN5A variants are displayed in Table 2 and Figure 1. The location on the protein sequence was followed by the UniprotKB (Q14524), as described: the N-terminus (aa 1–131), domain I (DI S1-S6, aa 132–410), inter-domain linker I-II (aa 411–717), domain II (DII S1-S6, aa 718–938), inter-domain linker II-III (IDL II-III, aa 939–1206), domain III (DIII S1-S6, aa 1207–1466), inter-domain linker III-IV (IDL III-IV, aa 1467–1529), domain IV (DII S1-S6, aa 1530–1771), and the C-terminus (aa 1772–2016). The novel variants were located mainly in the DI, accounting for 15.15%, compared to 6.06% in both N-terminal and C-terminal regions. Among SCN5A variants, a frameshift variant was determined in two patients, such as c.325_327delAAC (N109del) in exon 3. Also, genomic duplication was observed in two patients who showed a duplicate of exon 2 and 3 by MLPA. Five missense variants were identified along 28 exons of SCN5A: c.551A>G (Exon 5), c.754G>A (Exon 7), c.797T>A (Exon 7), c.980G>A (Exon 8), c.5389A>T (Exon 28), produced the amino acid change at His184Arg, Asp252Asn, Leu266His, Gly327Glu, and Ile1797Phe, respectively. A synonymous variant c.5484C>T was found in a single patient at nucleotide position 5484 with no effect on the wild-type 1828 Alanine amino acid residue (Ala1828Ala).

Details are in the caption following the image
Schematic representation of SCN5A mutations on cardiac voltage-gated sodium channel (Nav1.5).

3.4 Known SCN5A variants

Aside from novel variants, 13 known SCN5A variants were recorded in this study. Of these, 11 missense variants have been verified in the dbSNP, containing c.1100G>A (R367H) in exon 9 (rs28937318), c.1712G>C (S571T) in exon 12 (rs199473126), c.1975C>T (R659W) in exon 13 (rs730880205), c.2236G>A (E746K) in exon 14 (rs199473582), c.2678G>A (R893H) in exon 16 (rs199473172), c.2893C>T (R965C) in exon 17 (rs199473180), c.3338C>T (A1113V) in exon 18 (rs199473194), c.3578G>A (R1193Q) in exon 20 (rs41261344), c.4171G>A (G1391R) in exon 24 (rs780405533), c.4534C>T (R1511W) in exon 26 (rs137854602), and c.5693G>A (R1898H) in exon 28 (rs370694515). Two patients carried c.1890+14G>A (rs145427253) at the splice site region of intron 12 and a TCT deletion at the position 4850 to 5852 (c.4850_4852delTCT) (rs749697698), which caused frameshift on protein sequence (I1617del) was found in exon 27.

3.5 In silico analysis of SCN5A variants

To determine the impact of SCN5A variants in BrS, multiple bioinformatics tools were utilized; if the results of ≥4 tools were in agreement on pathogenicity, a variant was considered damaging. The results are revealed in Table 3. Of a total of 21 variants, 15 were predicted as disease-causing by at least four algorithms. Significantly, the variants c.797T>A, c.980G>A, c.1100G>A, c.2678G>A, c.2893C>T, and c.4534C>T were indicated as potentially pathogenic variants by all algorithms. Conversely, five variants were identified as benign, including c.551A>G, c.1890+14G>A, c.3338C>T, c.3578G>A, and c.5484C>T.

TABLE 3. SCN5A variants found in the studied group.
Nucleotide Protein Location Variant type dbSNP ID Cases References
Ex2-Ex3 Dup Exon 2–3 Frameshift - 2 In this study
c.325_327delAAC N109del Exon 3, N-terminal Frameshift - 2 In this study
c.551A>G H184R Exon 5, DI/S2-S3 Missense - 2 In this study
c.754G>A D252N Exon 7, DI/S4-S5 Missense - 1 In this study
c.797T>A L266H Exon 7, DI/S5 Missense - 1 In this study
c.980G>A G327E Exon 8, DI/S5-S6 Missense - 1 In this study
c.1100G>A R367H Exon 9, DI/S5-S6 Missense rs28937318 1 Kapplinger et al. (2010)
c.1890+14G>A Intron 12 Splice site rs145427253 2 Duzkale et al. (2013)
c.1712G>C S571T Exon 12, DI-DII Missense rs199473126 1 Kapplinger et al. (2009)
c.1975C>T R659W Exon 13, DI-DII Missense rs730880205 4 Shen et al. (2022)
c.2236G>A E746K Exon 14, DII/S1-S2 Missense rs199473582 1 Kapplinger et al. (2010)
c.2678G>A R893H Exon 16, DII/S5-S6 Missense rs199473172 2 Yamagata et al. (2017)
c.2893C>T R965C Exon 17, DII-DIII Missense rs199473180 4 Chimparlee et al. (2021)
c.3338C>T A1113V Exon 18, DII-DIII Missense rs199473194 1 Kapplinger et al. (2010)
c.3578G>A R1193Q Exon 20, DII-DIII Missense rs41261344 1 Abe et al. (2018)
c.4171G>A G1391R Exon 24, DIII/S5-S6 Missense rs780405533 1 Szperl et al. (2018)
c.4534C>T R1511W Exon 26, DIII-DIV Missense rs137854602 1 Meregalli et al. (2009)
c.4850_4852delTCT F1617del Exon 27, DIV/S3-S4 Frameshift rs749697698 2 Chen et al. (2005)
c.5389A>T I1797F Exon 28, C-terminal Missense - 1 In this study
c.5484C>T A1828A Exon 28, C-terminal Synonymous - 1 In this study
c.5693G>A R1898H Exon 28, C-terminal Missense rs370694515 1 te Riele et al. (2017)

4 DISCUSSION

BrS is a rare inherited cardiac disorder and is generally related to sudden death during sleeping in South East Asia. Most BrS patients are diagnosed without clarifying clinical manifestations, leading to the challenge of early diagnosis. SCN5A gene encodes for the cardiac voltage-gated sodium channel (Nav1.5) and is responsible for the incidence of BrS. The SCN5A variants are estimated in up to 30% of the patients. Loss-of-function mutations on SCN5A have been investigated to cause dilated cardiomyopathy and lower expression levels of SCN5A or produce defective Nav1.5 proteins (Wilde & Amin, 2018). Therefore, genetic screening of SCN5A is necessary for the clinical diagnosis of BrS patients, identification of non-genetic carriers, and selection of promising strategies to prevent genetic carriers in the offspring.

BrS is well known to be more distributed and severe in males than in females. The vast frequency of affected males in this study was marked at 97.43%, in agreement with prevalence in Asia (Milman et al., 2019). Several hypotheses have been postulated to clarify the gender discrepancy. Variable sex receptors containing estrogen, progesterone, and testosterone are discovered in the cardiac myocytes; thus, the alteration of sex hormone concentration can cause fluctuation in the performance and expression of myocardial ion channels (Lizotte et al., 2009).

In our study, the prevalence of SCN5A variants was determined at 25.6%, higher than Taiwanese and Hispanic populations, which accounted for 8% and 16%, respectively (García-Castro et al., 2010; Juang et al., 2015). Syncope and SCD are common clinical characteristics in BrS-related SCN5A variants. We found that syncope and a risk family history of SCD were presented in 38.46% and 31.62% of our BrS patients, respectively. The syncope symptom of those who carried SCN5A variants (66.33%) has a significantly higher risk than those of non-carriers (RR = 3.147, [95% CI: 1.668–5.982], p = 0.004). A similar rate was obtained in a meta-analysis, which was evaluated at 35.9% in the occurrence of syncope related to SCN5A (+) (RR = 1.12, [95% CI: 0.87–1.45], p = 0.37) (Raharjo et al., 2018). Moreover, our data contrast with the result of Yamagata et al. (2017), who did not observe a statistical difference in the family history of SCD (p = 0.5); however, a significantly higher rate of cardiac events was recorded between SCN5A (+) and SCN5A (−) groups (HR = 1.1, 95% CI: 1.1–3.8, p = 0.02) (Yamagata et al., 2017). In addition, BrS could be related to the major arrhythmic events (MAEs), comprising VT and VF (RR = 3.406, [95% CI: 1.722–5.4], p = 0.0035). Sommariva et al. (2013) indicated that the patients harboring SCN5A variants had an increased risk of MAEs than none of those (p = 0.024) (Sommariva et al., 2013). Nishii et al. (2010) determined the existence of SCN5A variants related to early and frequent recurrence of VF in symptomatic BrS patients, not in the first onset of VF (21.7% vs. 20.0%, p = 0.373) (Nishii et al., 2010). The variable correlation of BrS clinical phenotype may be produced by inter-individual genetic differences, regulating excitation-contraction physiology and affecting arrhythmia susceptibility among distinct ethnicities (Splawski et al., 2002; Suh & Vijg, 2005).

In the current study, 21 different SCN5A variants were successfully identified. Interestingly, one genomic duplication (Ex2-Ex3 dup) (2/117) was detected in our patients. To date, very few publications have shown the large rearrangement in SCN5A. Eastaugh et al. (2011) first described a major deletion in SCN5A. The c.999-424_1338 + 81del causes loss of exon 9 and 10 of SCN5A, resulting in haploinsufficiency (Eastaugh et al., 2011). The deletions of SCN5A were expressed in the other regions such as promoter, exons, and even the whole SCN5A gene (Hertz et al., 2015; Jenewein et al., 2017; Trujillo-Quintero et al., 2019). It is a fact that genomic instability always leads to the complete loss of function of the affected gene; therefore, these variants are more likely to induce the BrS phenotype. Several studies have been performed to identify the genomic imbalance in SCN5A, but the frequency rearrangement was 0% (García-Molina et al., 2013; Koopmann et al., 2007). These findings suggest that MLPA technique should be included when conducting genetic screening for BrS, even though the rearrangement rate is infrequent.

The novel variant c.325_327delAAC (N109del) was located on the N-terminal of Nav1.5 protein. N-terminal is a conserved region and plays a crucial role in regulating the cardiac sodium channel. The alteration of N-terminal can cause the increase or decrease of function on the channel, involving a quality control mechanism (Clatot et al., 2012). Following this mechanism, cells carried mutants use endoplasmic reticulum-associated degradation (ERAD) as a protective role to degrade proteins that fail to acquire their native conformation by the ubiquitin–proteasome system (Brodsky & Scott, 2007). The majority of our novel missense variants were discovered scattered from S2 to S6 segments of DI, consisting of c.551A>G (H184R), c.754G>A (D252N), c.797T>A (L266H), and c.980G>A (G327E). Most of these variants were predicted as pathogenic variants, except c.551A>G (H184R) as benign (Figure 1; Table 4). The S1-S4 components of each domain are considered as the voltage sensor domain (VSD), which plays a central function in controlling the activity of the channel, while S5-S6 segments assemble to form the pore domain and are responsible for the ion selectivity of Nav1.5 (Chen-Izu et al., 2015). Thus, minor structure modifications can initiate the dysregulation functioning of the channel. Additionally, two novel variants, c.5389A>T (I1797F) and c.5484C>T (A1828A), were found on the C-terminal of Nav1.5 and predicted as disease-causing and benign, respectively. The substitutions in the C-terminal domain have been explored to modulate channel inactivation (Glaaser et al., 2006). Although the synonymous c.5484C>T (A1828A) variant did not change the amino acid sequence, it may disrupt mRNA transcription, translation, and splicing (Goymer, 2007; Stergachis et al., 2013).

TABLE 4. Predicting pathogenesis of SCN5A variants by in silico analysis tools.
Nucleotide change Variant In silico analysis tools
Mutation assessor Poly-phen2 Mutation taster PROVEAN FATHMM SIFT BayesDel addAF MetaSVM Total
Ex2-Ex3 Dup - - - - - - - - -
c.325_327del N109del - - DC DC - - - - DC
c.551A>G H184R BN BN BN BN DC BN DC DC BN
c.754G>A D252N BN DC DC DC DC BN DC DC DC
c.797T>A L266H DC DC DC DC DC DC DC DC DC
c.980G>A G327E DC DC DC DC DC DC DC DC DC
c.1100G>A R367H DC DC DC DC DC DC DC DC DC
c.1890+14G>A - - BN - - - - - BN
c.1712G>C S571T BN DC DC BN DC BN DC DC DC
c.1975C>T R659W BN DC DC DC DC DC DC DC DC
c.2236G>A E746K BN BN DC BN DC BN DC DC DC
c.2678G>A R893H DC DC DC DC DC DC DC DC DC
c.2893C>T R965C DC DC DC DC DC DC DC DC DC
c.3338C>T A1113V BN BN BN BN DC BN BN BN BN
c.3578G>A R1193Q BN BN BN BN DC BN BN BN BN
c.4171G>A G1391R BN DC BN DC DC DC DC DC DC
c.4534C>T R1511W DC DC DC DC DC DC DC DC DC
c.4850_4852del F1617del - DC DC DC - - - - DC
c.5389A>T I1797F BN DC DC DC DC DC DC DC DC
c.5484C>T A1828A BN - DC BN - BN - - BN
c.5693G>A R1898H BN DC DC DC DC BN DC DC DC
  • Abbreviations: BN, benign; DC, disease-causing; -, not available.

Together with novel variants, 13 known variants also were identified. The c.1100G>A (R367H, rs28937318) variant has been evaluated to cause loss-of-function in Nav1.5 channel and is also associated with atrial standstill and early repolarization in idiopathic ventricular fibrillation (Kapplinger et al., 2010; Takehara et al., 2004; Watanabe et al., 2011). The c.1890+14G>A variant was found in the intronic region and was predicted benign on the ClinVar database (rs145427253) (Duzkale et al., 2013). Other variants were determined to occur at 28.57% (6/21) on the internal domain linker, such as DI-II (c.1712G>C (S571T), c.1975C>T (R659W)), DII-III (c.2893C>T (R965C), c.3338C>T (A1113V), c.3578G>A (R1193Q)), and DIII-IV (c.4534C>T (R1511W)) (Abe et al., 2018; Chimparlee et al., 2021; Kapplinger et al., 2009, 2010; Meregalli et al., 2009; Shen et al., 2022). Of these variants, c.3338C>T (A1113V) and c.3578G>A (R1193Q) were predicted as benign, and damage was evaluated in the other. The mutation rate on the linker domains on Nav1.5 was relatively high, accounting for 35% in the study of Kapplinger et al. (2009) Several studies have reported the affection of SCN5A variants on internal domain linkers. They indicated that these linkers play a valuable function in pathogenesis (Smits et al., 2005; Wehrens et al., 2003; Yamamura et al., 2010). Variant c.2236G>A (E746K) (DII/ S1-S2) was a hot spot for BrS and related to the reduced activation process on Nav1.5 channel (Huang et al., 2017; Zaytseva et al., 2022). An alteration c.2678G>A caused the change of amino acids from Arg to His at position 893, also detected on DII. This variant induced loss-of-function, showing a significant decrease in the current density peak than the wild-type through patch clamp (Ishikawa et al., 2021). The c.4171G>A (G1391R) variant was first reported by Szperl et al. (2018) in the Polish population. Genotype and phenotype analysis showed that the carriers with G1391R variant presented a higher risk of cardiac events in females than in males (Szperl et al., 2018). The minor deletion c.4850_4852delTCT (F1617del) variant was found to be associated with LQT3 syndrome, which induced the change of fast inactivation by decreasing gating charges (Chen et al., 2005). According to te Riele et al. (2017), the missense variant c.5693G>A (R1898H) led to a decrease at 36% in peak sodium current (p = 0.002), also in the abundance of Nav1.5 (p = 0.005) on fluorescence microscopy and N-Cadherin (p = 0.026) clusters at the intercalated disk (te Riele et al., 2017).

Our study's genotype–phenotype correlation and the functional prediction of all variants were only approached by statistical analysis and bioinformatic tools. Further, follow-up studies should be performed to provide insight into the role of SCN5A variants in the severity of BrS and promptly specify the most appropriate treatment for each patient.

5 CONCLUSION

Our study initially evaluated the genotype–phenotype correlation of SCN5A variants with patients of BrS in Vietnam. The presence of SCN5A variants shows a significantly higher risk in the family history of sudden death, syncope, and arrhythmia. Aside from published SCN5A variants, seven additional variants were predicted to cause functional alteration in cardiac voltage-gated sodium channel (Nav1.5). Follow-up studies should be conducted to clarify the impact of SCN5A variants on the clinical characteristics of BrS.

AUTHOR CONTRIBUTIONS

Van-Khanh Tran, Hung Manh Pham, Thinh Huy Tran, Thanh Van Ta, and The-Hung Bui: Conceived and designed the study and analysis. Thi Phuong Le, Dinh Phong Phan, Hoai An Trinh, Thanh Van Ta, and Ha Minh Nguyen: Contributed to data collection and carried out the experiments, performed analysis, and finalized the results. Hung Manh Pham, Duy Phuong Dang, Thanh Dat Ta, and Van-Khanh Tran: Contributed to the drafting of the manuscript. All authors have read and approved the final version for publication.

ACKNOWLEDGMENTS

We sincerely thank the patients and their parents for giving us consent and allowing us to publish the data.

    FUNDING INFORMATION

    This study was supported by the Ministry of Health of Vietnam, grant number 2723/QĐ-BYT.

    CONFLICT OF INTEREST STATEMENT

    The authors declare that there is no conflict of interest regarding the publication of this article.

    ETHICS STATEMENT

    This study was approved by the Ethics Committee of Hanoi Medical University (Hanoi Medical University Institutional Review Board, Hanoi, Vietnam, reference number: 48/HĐĐĐĐĐHYHN).

    CONSENT

    Written informed consent was obtained from the patient for publication.

    DATA AVAILABILITY STATEMENT

    The data are available from the corresponding author upon request.

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