1. Introduction
In forensic medicine, an autopsy has determined the cause of only two-thirds of sudden deaths, and the remaining cases are called sudden unexplained death (SUD) [1]. The majority of SUD cases are believed to be caused by cardiovascular diseases leading to sudden cardiac death (SCD) in young people. Sudden death is usually defined as a person who appeared healthy for 24 h before the onset of symptoms that led to death [2]. SCD accounts for 15–20% of all deaths in the general population, with incidence ranging from 40 to 100 per 100,000 people annually [3]. The main causes of SCD include cardiomyopathies, channelopathies, and ischemic heart diseases. About two-thirds of SCD cases had structural abnormalities that were evident at autopsy [1,4,5]; meanwhile, no structural abnormalities of the heart were found in the remaining cases. SCD may result from complications of cardiomyopathy causing early malignant arrhythmias, leading to death before the development of the cardiomyopathy phenotype. Especially in young people, SCD is often due to cardiomyopathies such as hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), and arrhythmogenic cardiomyopathy (ACM); channelopathies including ion channel disorders such as long QT syndrome (LQTS), short QT syndrome (SQTS), Brugada syndrome (BrS), catecholaminergic polymorphic ventricular tachycardia (CPVT), progressive cardiac conduction disorder, and early repolarization syndrome; or ischemic heart diseases [6,7,8].
In atrioventricular canal disease, long QT syndrome (LQTS) is caused by a heart’s electrical system that takes too long to recharge. The disease can lead to life-threatening arrhythmias and sudden cardiac death, primarily at a young age [9]. At least 15 genes encoding different ion channels have been identified as causes of LQTS [10]. Short QT syndrome (SQTS) is considered one of the most dangerous diseases associated with sudden cardiac death, characterized by a short QT interval on the electrocardiogram. Potentially pathogenic variants have been reported in five genes (CACNA2D1, KCNH2, KCNJ2, KCNQ1, and SLC4A3); all are inherited in an autosomal dominant [2,11,12]. Brugada syndrome (BrS) is a cardiac channelopathy caused by rare mutations in the SCN5A gene, which encodes the alpha-subunit of the voltage-dependent cardiac Na+ channel protein (Nav1.5) [2,13]. SCN5A-positive BrS patients often exhibit severe conduction abnormalities [14] and have more severe arrhythmic outcomes than SCN5A-negative patients [15,16].
CPVT is a malignant arrhythmia syndrome characterized by bidirectional or polymorphic VT during physical or emotional stress, which leads to a significantly high mortality rate (30% SCD before age 40) if the patient is not detected and treated [17]. Mutations in the RYR2 gene were found in ≈60% of patients with CPVT [18] and concentrated mainly in three specific regions of the ryanodine receptor 2 (RYR2) [18,19]. Additionally, mutations in CASQ2 have been identified as causing a less common but more severe form of CPVT [20]. Mutations in RYR2 and CASQ2 result in diastolic calcium release from the SR and cause arrhythmias. Recently, two other genes, CALM1 and TRDN, involved in calcium balance, have also been identified as causing CPVT [21,22].
In addition to arrhythmias, progressive cardiac conduction disorders, early repolarization syndrome, and ischemic heart disease are also of concern and are considered causes of sudden death. Progressive cardiac conduction disorder (PCCD), characterized by delayed impulse conduction through the His–Purkinje system with right or left bundle branch block, is a heart disease leading to complete atrioventricular (AV) block, syncope, and SCD. Genetic forms of PCCD often overlap or co-occur with other heart diseases. Currently, 20 genes encoding cardiac ion channels and regulatory proteins, protein kinases, structural proteins, and transcription factors are associated with different forms of PCCD [23]. In recent years, early repolarization syndrome (ERS), which is caused by variants in eight ion channel genes (KCNJ8, ABCC9, SCN5A, SCN10A, KCND3, CACNA1C, CACNB2b, and CACNA2D1), has been considered a hereditary SCD syndrome [24,25,26,27,28,29]. In addition, cerebral small vessel disease (CSVD), a clinically and genetically heterogeneous group of disorders, is also considered a leading cause of myocardial infarction and sudden death [30]. Although most cases of CSVD are sporadic, recent reports have identified genes associated with CSVD, including NOTCH3, HTRA1, CTSA, GLA, COL4A1/A2, TREX1, and CSF1R [31].
Other causes of SCD were related to cardiomyopathy including hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), and arrhythmogenic cardiomyopathy (ACM). HCM is the most common form that leads to left ventricular outflow tract obstruction, coronary ischemia due to the narrowing of small blood vessels, and severe arrhythmias [32], which is the main cause of sudden cardiovascular death [33]. Most of these cases are caused by pathogenic variants in the core sarcomeric genes (MYH7, MYBPC3, TNNT2, TNNI3, MYL2, MYL3, TPM1, ACTC1) [34]. To date, about 100 genes associated with cardiomyopathy have been reported [35].
An autopsy aims to determine the cause of death in the victims and predict the risks to family members. However, until now, in 40% of SUD cases, the causes could not be determined by autopsy [36]. Therefore, genetic testing has been proposed in forensic medicine to investigate sudden death through genetic analysis [37]. It is especially useful in cases of negative traditional autopsies or SUD due to underlying genetic arrhythmic heart disease. Early molecular autopsies relied on Sanger sequencing. Although this is an accurate and easy-to-use method, it is limited because it has low throughput and can only be used to analyze a subset of small genes. Recently, next-generation sequencing (NGS) technologies have allowed exome/genome examination, providing an increase in the detection of pathogenic variants and the discovery of newer genotype–phenotype associations [38,39,40]. NGS can investigate large numbers of genes and thus aid in clinical investigations and increase the likelihood of determining the cause of death.
In this study, we performed Targeted NGS sequencing in autopsy-negative SUD victims to identify genetic alterations associated with cardiomyopathy and channelopathies that may explain their causes of death.
2. Materials and Methods
2.1. Subjects
A total of 40 young SUD cases (30 men and 10 women) collected from the Department of Forensic Medicine, Hanoi Medical University, Vietnam, were investigated for molecular forensics. The victims were all <40 years old (from 1 to 40 years old, median age of 28.85) and died suddenly. Autopsy evaluations as well as toxicology screening were negative. The victims were known to be healthy 24 h before death, and none had a family history of SCD (Table 1).
2.2. Targeted Next-Generation Sequencing
To determine the cause of sudden death in the victims, we performed Targeted next-generation sequencing using a gene panel of 167 genes (Table S1) associated with cardiomyopathy and channelopathies. Genomic DNA was extracted from blood samples using the Qiagen DNA mini kit (QIAGEN, Hilden, German) following the manufacturer’s instructions. DNA concentration was determined using a Thermo Scientific NanoDrop spectrophotometer (Waltham, MA, USA). Sequencing was performed on a Nextseq 500 (Illumina, CA, USA). Variants were compared and annotated based on the GRCh38/hg19 reference genome sequence. Variants in the genes associated with cardiomyopathy and channelopathies were identified based on ACMG guidelines (The American College of Medical Genetics and Genomics) [41].
2.3. Sanger Sequencing
Sanger sequencing was performed to confirm the variants were found in these cases. PCR products were purified with the Qiagen PCR Purification kit (QIAGEN, Hilden, Germany) and sequenced on the ABI PRISM 3500 Genetic Analyzer machine (Thermo Fisher Scientific Inc., Waltham, MA, USA) in both directions using the primers that were used in the initial PCR reaction. The sequencing data were analyzed using BioEdit 7.2.5 software.
2.4. In Silico Prediction
The influence of any novel nucleotide changes was evaluated with the following in silico prediction tools: CADD [
3. Results
In this study, 40 Vietnamese SUD victims were investigated through molecular forensics by using Targeted NGS sequencing. The detected variants were confirmed by Sanger sequencing in these cases (Figure 1 and Figure 2). The results showed that 25 (62.5%) victims harbored no variants or benign variants, and 15 (37.5%) victims had 17 variants identified on the genes associated with cardiomyopathy and channelopathies. Among them, eight of these variants were novel, five variants were pathogenic variants in the ClinVar database, and four variants were published in ClinVar but with uncertain significance (Table 2). Seven variants (41%) were detected in genes associated with cardiomyopathies including CSRP3, LAMA4, MYH6, MYBPC3, TNNI3, TNNI3K, and TNNT2. Eight variants (47%) were detected in genes related to cardiac channelopathies such as AKAP9, GSN, KCNA5, SCN5A, SCN10A, SLC4A3, and RYR2. Two other variants were detected in the HTRA1 and MYLK genes that were reported in patients with CSVD and extensive aortic, respectively. The novel variants and variants not evaluated on the ClinVar database were predicted by prediction tools. Prediction results showed that four novel variants including variants c.10498G>T, p.Asp3500Tyr (in the RYR2 gene); c.5187_5188dup, p.Arg1730llefsTer4 (in the AKAP9 gene); c.1454A>T, p.Lys485Met (in the MYH6 gene); and c.2535+1G>A (in the SLC4A3 gene), and an uncertain significance variant c.292C>G, p.Arg98Gly in the TNNI3 gene, are considered likely to cause disease (A and B in Table 3 and Table S2). In addition, variant c.683C>A, p.Pro228His in the KCNA5 gene was predicted as disease-causing by the following in silico tools: CADD (with score 24.1), Mutation taster (with score 77), Polyphen 2 (with score 1.000), and SNP&GO (with score R17). Two variants c.2275G>A, p.Glu759Lys (in the MYBPC3 gene) and c.5025A>T, p.Glu1675Asp (in the LAMA4 gene) were predicted as disease-causing by the following in silico tools: CADD (with score 26.7 and 23.6, respectively), Mutation taster (with score 56 for variant in MYBP3), PhD-SNP (with score R14 for variant in LAMA4), and Polyphen 2 (with score 1.000 and 0.998, respectively). Variants c.298C>T, p.Arg100Cys (in CSRP3), c.4840G>A, p.Glu1614Lys (in MYLK), and c.872T>C, p.Ile291Thr (in GSN) were predicted as probably damaging by the CADD and Polyphen 2 tools. However, variant c.9215G>T, p.Gly3072Val in the AKAP9 gene was assessed by prediction tools as a neutral influence variant. These variants need to be further evaluated to determine the extent of their impact.
4. Discussion
In this study, 40 Vietnamese victims who were diagnosed with SUD at ages < 40 years old were sequenced using Targeted NGS with a panel gene consisting of 167 cardiac disease-associated genes. Fifteen (37.5%) victims were identified with 17 variants in genes associated with cardiomyopathy and channelopathies (Table 2). Molecular forensics studies in young individuals with negative autopsies have identified putative pathogenic variants in genes associated with channelopathies in 11 to 26% of cases [11,42]. In 2014, Bagnall et al. [43] first performed whole exome sequencing (WES) in 28 cases of adolescent SUDs and identified three rare variants associated with LQTS and six variants related to channelopathies and cardiomyopathy. In another study, the authors performed gene panel analysis (including 69, 98, or 101 genes) on 51 SUD cases and WES on another 62 SUD cases, finding variants in 31 cases (27%) [36]. Hata et al. [44] used a panel of 70 genes to evaluate 25 SUD cases and identified five known variants and 10 novel variants predicted to be pathogenic by in silico analysis. The variants included three channelopathy-associated genes (RYR2, CACNA1C, and ANK2), three HCM- or DCM-associated genes (MYH7, LDB3, and PRKAG2), five ACM-related genes (PKP2, JUP, DSG2, DSP, and TMEM43), and two cardiac transcription factor genes (TBX5 and GATA4). The authors also identified the simultaneous presence of two heterozygous variants in 3 of 25 cases and 2 cases carrying three or more variants [44]. These data support the hypothesis that the “single gene disease” model may not apply to all cases of SUD, which can sometimes occur because of the interaction of multiple variants [45].
Another study performed with a gene panel of 100 genes in 61 SUD cases found that 21 (34%) individuals carried variants that may have a functional effect. Ten (40%) of these variants were in genes associated with cardiomyopathy and fifteen (60%) were in genes associated with cardiac channelopathies [8]. Previous reports suggested that cardiomyopathy often has a variety of manifestations due to incomplete penetrance, so initial phenotypic changes may not be seen at autopsy or may be considered nonspecific or within the normal range. Variants associated with cardiomyopathy and structural alterations of the heart can give rise to arrhythmias—and in some cases, cause disorders through regulation of cardiac channel function [46,47,48,49]. Primary electrical disorders are thought to be caused by variants in genes encoding ion channels and cardiomyopathy [50].
Cerrone and Priori’s study also provided evidence for an association between channelopathies and hereditary cardiomyopathy with arrhythmogenic substrate-related genes thought to be involved in abnormal structures of the myocardium and primary electrical disorders [51]. In these cases, an autopsy showed that the heart had a normal structure and that the arrhythmia arose from abnormalities in the electrical function of the heart [50]. These primary electrical diseases are mainly caused by variants in the genes encoding the heart’s ion channels and receptors. Most variants that lead to ion channel dysfunction alter the electrical activity in the heart and predispose patients to fatal arrhythmias without changing the morphology of the heart tissue. Identifying genetic factors that lead to SCD is important because genetic testing can contribute to diagnosis and risk prediction.
In our study, five cases carried a known pathogenic variant in the following genes: TNNI3K (c.2302G>C, p.Glu768Gln, RCV000768402.5/Pathogenic, P3); HTRA1 (c.496C>T, p.Arg166Cys, RCV002291765.4/Pathogenic, P6); TNNT2 (c.452G>A, p.Arg151Gln, RCV000796707.6/Pathogenic, P8); SCN10A (c.2158G>A, p.Asp720Asn, VCV000532067.8/Pathogenic, P9); and SCN5A (c.515A>G, p.His184Arg, VCV000201540.5/Likely pathogenic, P12). Another four patients carried known variants in the following genes: KCNA5 (c.683C>A, p.Pro228His, VCV002202820.2, P4); MYBPC3 (c.2275G>A, p.Glu759Lys, VCV000843772.16, P5); CSRP3 (c.298C>T, p.Arg100Cys, VCV000851709.9, P10); and TNNI3 (c.292C>G, p.Arg98Gly, VCV001331910.2, P13). Based on the prediction results using prediction tools, three of these variants (KCNA5, P4; MYBPC3, P5; TNNI3, P13) were predicted to be likely to cause disease in the cases. However, the variant c.298C>T, p.Arg100Cys in the CSRP3 gene was not confirmed as the cause of the disease in case P13 (A in Table 3).
Among four cases that carried novel variants in the following genes: RYR2 (c.10498G>T, p.Asp3500Tyr, P1), AKAP9 (c.5187_5188dup, p.Arg1730llefsTer4, P2), MYH6 (c.1454A>T, p.Lys485Met, P7), and GSN (c.872T>C, p.Ile291Thr, P14), three variants (in the RYR2, AKAP9, and MYH6 genes) were evaluated as like pathogenic variants. Case P11 carried the following novel variants: c.4840G>A, p.Glu1614Lys (in the MYLK gene) and c.9215G>T, p.Gly3072Val (in the AKAP9 gene); however, variant c.4840G>A, p.Glu1614Lys in the MYLK gene was assessed as potentially damaging by CADD, version 1.7 (score: 36.0) and Polyphen version 2 (score: 0.611) software but as neutral by PhD-SNP (score: RI2) software. The variant c.9215G>T, p.Gly3072Val in the AKAP9 gene was evaluated as a neutral variant by CADD (score: 17.6), FATHMM (score: 3.76), and PhD-SNP (score: RI8) software while being evaluated as potentially harmful by Polyphen 2 (score: 0.973). Likewise, case P15 also carried the following novel variants: c.2535+1G>A (in the SLC4A3 gene) and c.5025A>T, p.Glu1675Asp (in the LAMA4 gene). The variant c.2535+1G>A in the SLC4A3 gene was evaluated as “exon-skipping” by the EX-SKIP software, “donor loss” by NetGene 2 version 2.42 and Spliceailookup software and as a damaging variant by MaxEntScan software (B in Table 3 and Table S2). The variant c.5025A>T, p.Glu1675Asp in the LAMA4 gene was assessed as a disease variant by PhD-SNP (score: RI4) and “probably damaging” by CADD (score: 23.6) and Polyphen 2 (score: 0.998), but it was assessed as a “tolerated variant” by FATHMM (score: −1.32) and “benign” by Mutation taster (score: 21) (A in Table 3). Based on the above-predicted results, the c.2535+1G>A variant in the SLC4A3 gene can be considered the cause of the disease in case P15.
Tester et al. [52] also showed that at least one-third of SUD cases in young people were found to be due to variants in the receptor gene, of which variants in cardiac ryanodine (RYR2) account for nearly 14% of cases. AKAP9 variants were associated with types of cardiovascular including LQTS type 11 [53,54,55,56], Brugada syndrome [57,58], sudden death of unknown cause [59,60,61,62], severe ventricular arrhythmias [63,64], and cardiomyopathy [65]. Huynh and colleagues confirmed that AKAP9 variants are associated with fatal arrhythmias and sudden cardiac death [9]. Of interest, some patients may carry the AKAP9 variant and other genes associated with channelopathies, suggesting the complexity of multifactorial and polygenic inheritance in these patients [54,61]. The variant in the SLC4A3 anion exchanger gene is considered a cause of SQTS in the patients [66]. In Christiansen’s study, about a quarter of patients with SQTS carried potentially pathogenic variants in SLC4A3, representing the most common variants and emphasizing the importance of the inclusion of SLC4A3 in the genetic screening of patients with SQTS or onset sudden cardiac death [67].
In addition, stroke is the main cause of death in young people. However, the actual genetic cause of stroke is still unknown. Cerebral small vessel disease (CSVD), often causing stroke, is characterized by young adult onset [68] and is considered to be caused by variants in the high temperature-demanding serine peptidase A1 (HTRA1) gene [69]. The HTRA1 gene encodes a serine enzyme that mediates cell signaling and protein degradation and plays an important role in vascular integrity [70]. Autosomal dominant genetic variants on HTRA1 have been reported in families with CSVD in Italy, Spain, Greece, and China [61,71,72,73]. Heterozygous HTRA1 variants may be responsible for impaired HTRA1 protease activity or form stabilizers leading to the phenotype in patients [74].
In this study, using Targeted NGS sequencing and prediction tools, we identified variations in related genes in 15 SUD cases out of a total of 40 studied cases. Of these 15 cases, the cause of sudden death in 12 cases was identified, and three cases (P10, P11, and P14) required further evaluation to determine the exact cause of sudden death. Forensic molecular autopsy has recently proven valuable in SUD cases and is increasingly used to explain these cases.
There are some limitations in our study. For the first limitation, we used a gene panel with 167 genes related to cardiomyopathy and channelopathies which was reported previously, leading to the possibility of not detecting the variants in other related genes. The second limitation of our study is that we did not conduct studies to evaluate the influence of variants, so we have not yet reached accurate conclusions about the cause of SUD in some cases.
5. Conclusions
In our study, 40 SUD cases were investigated with Targeted NGS sequencing, and 17 variants in genes associated with cardiomyopathy and channelopathies in 15 cases were identified. By predicting the pathogenicity of the variants found using prediction software, the cause of death was determined in 12 cases. The obtained results showed that next-generation sequencing is a tool that can be used in molecular forensics to determine the cause of disease in SUD cases.
Conceptual framework design, T.N.T.; writing—original draft preparation, N.T.K.L.; writing—review and editing, T.N.T., N.T.K.L., H.L.S., T.T.V., D.D.V., L.T.T., N.T.X. and N.H.H.; data curation and investigation, T.N.T., H.N.T. and N.V.T.; methodology and software, N.T.K.L. and N.V.T. All authors have read and agreed to the published version of the manuscript.
This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Hanoi Medical University (Approval No. 913/GCN-HDDDNCYSH-DHYHN).
This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Hanoi Medical University (Approval No. 913/GCN-HDDDNCYSH-DHYHN). Written informed consent was obtained from the patient’s parents for the publication of any potentially identifiable images or data included in this article.
Data is contained within the article or
We would like to thank the patients and their families who participated in this study.
All authors declare that they have no conflicts of interest.
Footnotes
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Enlarge this image.Figure 1. Sanger sequencing results confirming the novel variants in victims. Red letters are the positions of the altered amino acids.
Characteristics of sudden unexplained cardiac death cases.
| ID | Sex/Age | Event at SUD | Medical History | Autopsy Findings | |
|---|---|---|---|---|---|
| Height (cm) | Health | ||||
| P1 | F/14 | Sleep at night | 160 | Normal | Negative |
| P2 | M/29 | Sleep at night | 178 | Normal | Negative |
| P3 | M/25 | Driving/daytime | 158 | Normal | Negative |
| P4 | M/19 | Sleep at night | 175 | Normal | Negative |
| P5 | M/28 | Sleep at night | 174 | Normal | Negative |
| P6 | M/40 | Eating at night | 152 | Normal | Negative |
| P7 | M/39 | Sleep at daytime | 170 | Normal | Negative |
| P8 | M/22 | Rest at daytime | 162 | Normal | Negative |
| P9 | M/29 | Sleep at night | 168 | Normal | Negative |
| P10 | F/33 | Sleep at night | 158 | Normal | Negative |
| P11 | F/25 | Rest at daytime | 156 | Normal | Negative |
| P12 | M/35 | Sleep at night | 170 | Normal | Negative |
| P13 | M/39 | Sleep at night | 165 | Normal | Negative |
| P14 | M/24 | Working/daytime | 180 | Normal | Negative |
| P15 | M/23 | Sleep at night | 168 | Normal | Negative |
| P16 | M/27 | Working/daytime | 160 | Normal | Negative |
| P17 | M/30 | Working/daytime | 172 | Normal | Negative |
| P18 | F/1 | Rest at daytime | 76 | Normal | Negative |
| P19 | M/30 | Sleep at night | 169 | Normal | Negative |
| P20 | M/40 | Sleep at night | 172 | Normal | Negative |
| P21 | F/32 | Rest at daytime | 159 | Normal | Negative |
| P22 | M/27 | Working/daytime | 160 | Normal | Negative |
| P23 | M/34 | Sleep at night | 167 | Normal | Negative |
| P24 | M/40 | Sleep at night | 162 | Normal | Negative |
| P25 | M/38 | Sleep at night | 170 | Normal | Negative |
| P26 | M/40 | Rest at daytime | 162 | Normal | Negative |
| P27 | M/35 | Sleep at daytime | 164 | Normal | Negative |
| P28 | F/2 | Rest at daytime | 80 | Normal | Negative |
| P29 | M/33 | Rest at daytime | 162 | Normal | Negative |
| P30 | M/27 | Sleep at night | 173 | Normal | Negative |
| P31 | M/35 | Sleep at night | 170 | Normal | Negative |
| P32 | M/32 | Sleep at night | 162 | Normal | Negative |
| P33 | M/33 | Sleep at night | 167 | Normal | Negative |
| P34 | M/39 | Playing a sport | 166 | Normal | Negative |
| P35 | M/24 | Sleep at night | 179 | Normal | Negative |
| P36 | M/19 | Working/daytime | 169 | Normal | Negative |
| P37 | F/29 | Rest at daytime | 155 | Normal | Negative |
| P38 | F/20 | Sleep at night | 158 | Normal | Negative |
| P39 | M/23 | Sleep at night | 168 | Normal | Negative |
| P40 | F/40 | Sleep at night | 159 | Normal | Negative |
Variants found in SUD victims.
| ID | Gene | cDNA/Protein | dbSNP/MAF/ClinVar/ExAC | Zygosity |
|---|---|---|---|---|
| P1 | RYR2 | c.51C>G | novel | het |
| P2 | AKAP9 | c.5187_5188dup | novel | het |
| P3 | TNNI3K | c.2302G>C | rs202238194/0.00000 | het |
| P4 | KCNA5 | c.683C>A | VCV002202820.2 | het |
| P5 | MYBPC3 | c.2275G>A | rs750810342/0.00002487 | het |
| P6 | HTRA1 | c.496C>T | rs2097494390/VCV001325819.5 | het |
| P7 | MYH6 | c.1454A>T | novel | het |
| P8 | TNNT2 | c.452G>A | rs730881101/0.00000 | het |
| P9 | SCN10A | c.2158G>A | rs781354273/0.00006/VCV000532067.8 | het |
| P10 | CSRP3 | c.298C>T | rs201214593/0.00004/VCV000851709.9 | het |
| P11 | MYLK | c.4840G>A | novel | het |
| AKAP9 | c.9215G>T | novel | het | |
| P12 | SCN5A | c.515A>G | rs794728898/0.000102/VCV000201540.5 | het |
| P13 | TNNI3 | c.292C>G | rs730881068/0.00005/VCV001331910.2 | het |
| P14 | GSN | c.872T>C | novel | het |
| P15 | SLC4A3 | c.2535+1G>A | novel | het |
| LAMA4 | c.5025A>T | novel | het |
(A) Predictions from in silico software for variants. (B) Predictions from in silico software for the splice variant SLC4A3: c.2535+1G>A.
| (A) | |||||||
|---|---|---|---|---|---|---|---|
| Gene/Variants | ClinVar | CADD | FATHMM | Mutation Taster | PhD-SNP | Polyphen 2 | SNP&GO |
| RYR2 | Novel | 25.5 | −4.21 | 160 | Neutral RI8 | 1.000 | Disease RI1 |
| KCNA5 | Uncertain significance | 24.1 | −0.21 | 77 | Neutral RI5 | 1.000 | Disease RI7 |
| MYBPC3 | Uncertain significance | 26.7 | −0.20 | 56 | Neutral RI5 | 1.000 | - |
| MYH6 | Novel | 28.9 | −2.60 | - | Disease RI6 | 1.000 | Disease RI9 |
| CSRP3 | Uncertain significance | 28.5 | −0.28 | 89 | - | 0.110 | Disease RI2 |
| MYLK | Novel | 36.0 | - | - | Neutral RI2 | 0.611 | - |
| AKAP9 | Novel | 17.6 | 3.76 | - | Neutral RI8 | 0.973 | - |
| TNNI3 | Uncertain significance | 26.3 | −3.49 | 125 | Neutral RI1 | 1.000 | Disease RI10 |
| GSN | Novel | 29.1 | −0.34 | Benign | Neutral RI7 | 1.000 | - |
| LAMA4 | Novel | 23.6 | −1.32 | 21 | Disease RI4 | 0.998 | Neutral RI7 |
| (B) | |||||||
| In Silico Prediction Tools | Wildtype | Mutant | Prediction | ||||
| EX-SKIP | −218.867 | Exon-skipping | |||||
| Fruitfly | NA | NA | - | ||||
| MaxEntScan | 1.51 | −6.67 | Damage variant | ||||
| NetGene2 | 0.60 | 0.00 | Donor loss | ||||
| Spliceailookup | 0.98 | 0.00 | Donor loss | ||||
Supplementary Materials
The following supporting information can be downloaded at
References
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; Nguyen Van Tung 6
; Le Tat Thanh 2 ; Nguyen Thi Xuan 2 ; Nguyen, Huy Hoang 6
1 Department of Forensic Medicine, Hanoi Medical University, 1 Ton That Tung Str., Dongda, Hanoi 100000, Vietnam;
2 Institute of Genome Research, Vietnam Academy of Science and Technology, 18-Hoang Quoc Viet Str., Caugiay, Hanoi 100000, Vietnam;
3 Department of Pathology, National Cancer Hospital, 43 Quan Su Str., Hoan Kiem, Hanoi 100000, Vietnam;
4 Cardiovascular Intensive Care Unit, Heart Institute, 108 Military Central Hospital, 1B Tran Hung Dao Str., Hai Ba Trung, Hanoi 100000, Vietnam;
5 Faculty of Biotechnology, Graduate University of Science and Technology, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet Str., Caugiay, Hanoi 100000, Vietnam;
6 Institute of Genome Research, Vietnam Academy of Science and Technology, 18-Hoang Quoc Viet Str., Caugiay, Hanoi 100000, Vietnam;