Literature DB >> 32211440

Reevaluating the Mutation Classification in Genetic Studies of Bradycardia Using ACMG/AMP Variant Classification Framework.

Liting Cheng1, Xiaoyan Li1,2, Lin Zhao1, Zefeng Wang1, Junmeng Zhang1, Zhuo Liang1, Yongquan Wu1.   

Abstract

PURPOSE: Next-generation sequencing (NGS) has become more accessible, leading to an increasing number of genetic studies of familial bradycardia being reported. However, most of the variants lack full evaluation. The relationship between genetic factors and bradycardia should be summarized and reevaluated.
METHODS: We summarized genetic studies published in the PubMed database from 2008/1/1 to 2019/9/1 and used the ACMG/AMP classification framework to analyze related sequence variants.
RESULTS: We identified 88 articles, 99 sequence variants, and 34 genes after searching the PubMed database and classified ABCC9, ACTN2, CACNA1C, DES, HCN4, KCNQ1, KCNH2, LMNA, MECP2, LAMP2, NPPA, SCN5A, and TRPM4 as high-priority genes causing familial bradycardia. Most mutated genes have been reported as having multiple clinical manifestations.
CONCLUSIONS: For patients with familial CCD, 13 high-priority genes are recommended for evaluation. For genetic studies, variants should be carefully evaluated using the ACMG/AMP variant classification framework before publication.
Copyright © 2020 Liting Cheng et al.

Entities:  

Year:  2020        PMID: 32211440      PMCID: PMC7061116          DOI: 10.1155/2020/2415850

Source DB:  PubMed          Journal:  Int J Genomics        ISSN: 2314-436X            Impact factor:   2.326


1. Introduction

One of the inherited bradycardias that is currently being reported is inherited progressive cardiac conduction disease (IPCCD). Progressive cardiac conduction disease (PCCD) is an unidentified, heterogeneous, life-threatening disease that manifests as progressing fibrosis of the cardiac conduction system [1]. It is characterized by a decreased conduction rate, prolonged PR interval, and widened QRS wave, and it ultimately leads to complete atrioventricular block, syncope, and even sudden cardiac death [1]. Initially, patients present with only a widened QRS wave without a bundle branch block, and later, they develop complete atrioventricular block. Abnormalities in the conduction system may be related to changes in cardiac structure and function [2]. It is currently believed that the etiology of PCCD may be related to genetic factors, valvular disease, cardiomyopathy, and autoimmune disease [3]. PCCD caused by genetic factors was originally called progressive familial heart block (PFHB) [3], and some studies directly used PCCD or IPCCD to refer to progressive conduction system diseases related to genetic factors. It is believed that PCCD is caused by the SCN5A mutation [4], and it may also be correlated with TRPM4 [5], DSP [6], and others. Genetic studies about other kinds of familial bradycardia have been published over the past decade, such as sick sinus syndrome and heart block. However, those studies have still not been summarized, and the clinical significance of the related variants is still unknown. In 1977, Sanger et al. developed Sanger's “chain-termination” or dideoxy technique for nucleic acid sequence testing [7]. The improvement of Sanger sequencing makes DNA sequence testing for complex species available [8]. In the course of the development of next-generation sequencing (NGS), genetic testing becomes quicker, cheaper, and easier [9]. For patients who suffer from inherited cardiac disease, NGS has become a potential choice for the diagnosis, prevention, and treatment of certain diseases [9]. The relationships between inherited ion channel disease, such as long QT syndrome (LQTs) [10] and Brugada syndrome (BrS) [11], inherited cardiomyopathy, such as dilated cardiomyopathy (DCM) [12], hypertrophic cardiomyopathy (HCM) [13], and arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D) [14], and variant sequencing have been well studied. However, the role of genetic sequence variants in bradycardia is still under debate. Evaluation of sequence variants is a complex process. The integrity of both the genome and the protein being translated should be studied. In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) recommended an interpretative category of sequence variants and an algorithm for interpretation [15]. The ACMG/AMP classification framework is prominent in the evaluation of the Mendelian system. By evaluating the allele frequency, segregation, de novo, and protein expression, functional studies and other factors, sequencing variants can be scored as pathogenic or benign. The two parallel scoring systems divided mutations into 7 categories (Table 1). Sequence variants were then classified into a five-tier system: “pathogenic,” “likely pathogenic,” “uncertain significant,” “likely benign,” and “benign” (Table 2). By using this method, evaluated genomic variants can be quantified. With the development of evaluation methods for sequence variants, a growing number of databases have been developed. InterVar [16] is a tool implementing ACMG/AMP criteria that can automatically analyze sequence variants. LitVar [17] links genomic variants in PubMed and PMC, making functional studies achievable. With those databases, sequence variants can be evaluated properly.
Table 1

Pathogenic and benign criterion based on ACMG/AMP classification framework.

RuleCategoryRule description
Evidence of pathogenic
Very strongPVS1Null variants which caused loss of function are known to be the mechanism of diseases.

StrongPS1Different nucleotide change caused same amino acid change with known pathogenic variants.
PS2De novo (confirmed maternity and paternity) in a patient with no family history and diseases.
PS3Functional studies supported the effect of related pathogenic variants.
PS4Variants' prevalence significantly increased in affected individuals than controls.

ModeratePM1Mutation happened in hot spot and known function domain.
PM2Absent (or extremely low) in large population studies.
PM3With recessive disease, detected in trans with pathogenic variants.
PM4Variants (in-frame deletions/insertions in a nonrepeat region or stop-loss variants) lead to changes in protein length.
PM5Different missense changes at known pathogenic amino acid residue.
PM6De novo (without confirmation of maternity and paternity).

SupportingPP1Variants known to be the causes affected multiple family members.
PP2Missense variants in a gene that have a low rate of benign missense variation are common mechanism of disease.
PP3Multiple lines of computational evidence support a deleterious effect on the gene or gene products.
PP4Phenotype specific for disease with single genetic etiology.
PP5Reputable source reports variants as pathogenic.

Evidence of benign
Stand-aloneBA1Allele frequency is >0.5% base on population database.

StrongBS1Allele frequency is greater than expected for disorder.
BS2Recessive heredity being observed in healthy adult.
BS3Functional studies show no pathogenic effect.
BS4Without segregation.

SupportingBP1Missense variant in gene where only loss of function is pathogenic.
BP2Observed in genes with overlapping function without increased disease severity or observed in cis with a pathogenic variant.
BP3Variants (in-frame deletions/insertions in a nonrepeat region or stop-loss variants) lead to changes in a repetitive region without known function.
BP4Multiple lines of computational evidence suggest no impact on gene or gene product.
BP5Variant found in a case with alternate molecular basis for disease.
BP6Report as benign.
BP7Splicing variant predict an algorithm which predict no impact to the splice consensus sequence.
Table 2

Sequence variant classification.

Pathogenic1 PVS1+≥1 (PS1‐PS4)
1 PVS1+≥2 (PM1‐PM6)
1 PVS1 + 1 (PS1‐PS4) + 1 (PM1‐PM6)
1 PVS1+≥2 (PP1‐PP5)
≥2 (PS1-PS4)
1 (PS1‐PS4)+≥3 (PM1‐PM6)
1 (PS1‐PS4) + 2 (PM1‐PM6)+≥2 (PP1‐PP5)
1 (PS1‐PS4) + 1 (PM1‐PM6)+≥4 (PP1‐PP5)

Likely pathogenic1 PVS1 + 1 (PM1‐PM6)
1 (PS1‐PS4) + 1‐2 (PM1‐PM6)
1 (PS1‐PS4)+≥2 (PP1‐PP5)
≥3 (PP1‐PP5)
2 (PM1‐PM6)+≥2 (PP1‐PP5)
1 (PM1‐PM6)+≥4 (PP1‐PP5)

Benign1 BA1
≥2 (BS1–BS4)

Likely benign1 (BS1‐BS4) + 1 (BP1‐BP7)
≥2 (BP1‐BP7)

Uncertain significantOther criteria shown above have not met OR
Criterion for benign and pathogenic is contradictory

OR: odds ratio.

At present, most of the related mutant genes reported in the literature are not analyzed according to the ACMG guidelines. In this article, we summarized and reevaluated pedigree studies of bradycardia published in PubMed from 2008/1/1 to 2019/9/1 using the ACMG/AMP variant classification framework.

2. Materials and Methods

2.1. Database Search

We searched the PubMed database by using the term “heart block” or “sick sinus syndrome” associated with “pedigree” and “‘2008/1/1'[PDAT]: ‘2019/9/1'[PDAT]” [We used the term of ((((((((((((((((((((((((Heart Block) OR Block, Heart) OR Blocks, Heart) OR Heart Blocks) OR Auriculo-Ventricular Dissociation) OR Auriculo Ventricular Dissociation) OR Auriculo-Ventricular Dissociations) OR Dissociation, Auriculo-Ventricular) OR Dissociations, Auriculo-Ventricular) OR Atrioventricular Dissociation) OR Atrioventricular Dissociations) OR Dissociation, Atrioventricular) OR Dissociations, Atrioventricular) OR A-V Dissociation) OR A V Dissociation) OR A-V Dissociations) OR Dissociation, A-V) OR Dissociations, A-V)) OR ((((((((((Hereditary bundle branch system defect) OR Heart block, progressive familial, type 1) OR Cardiac conduction defect, progressive) OR Lenegre Lev disease) OR Lenegre-Lev Disease) OR PfhbIa) OR Heart Block, Progressive Familial, Type I) OR Pfhb1a) OR Pfhbi) OR Heart block progressive, familial)) OR ((((Progressive Familial Heart Block, Type II) OR Progressive Familial Heart Block, Type Ia) OR PFHBII) OR PFHB2)) OR (((Progressive Familial Heart Block, Type Ib) OR PFHB1B) OR PFHBIB))) AND (((((((Gene) OR Cistron) OR Cistrons) OR Genetic Materials) OR Genetic Material) OR Material, Genetic) OR Materials, Genetic)) AND (“2008/01/01”[Date - Publication]: “3000”[Date - Publication])].

2.2. Study Selection

The aim of this study was to evaluate genetic studies of bradycardia, in addition to the inclusion criteria and exclusion criteria, as follows: Inclusion criterion: Article published in English or have an abstract written in English Pedigree studies with at least one family member with bradycardia (include both sick sinus syndrome and atrioventricular block) Exclusion criteria: Functional studies that demonstrate the main function of the sequence variants that are not focused on bradycardia Studies that have not demonstrated the specific mutation sites

2.3. Sequence Variants Analyze

2.3.1. Organization of Relevant Sequence Variants

After a thorough evaluation of the related articles by two researchers, we gathered basic information about relevant sequence variants. The information included the chromosome position of the sequence variant (version: GRCh38), genomic sequence, protein sequence, dbSNP, gene, clinical manifestations, and so on.

2.3.2. Clarification of Sequence Variants

The variants were named after different versions of genomics, so we used The National Center for Biotechnology Information's ClinVar database (https://www.ncbi.nlm.nih.gov/clinvar/), Online Mendelian Inheritance in Man (OMIM, https://www.omim.org), and The Human Gene Mutation Database (HGMD, http://www.hgmd.cf.ac.uk/ac/index.php) to complete detailed information on each variant.

2.3.3. Use of the ACMG/AMP Classification Framework to Evaluate

According to the ACMG/AMP classification framework, we used InterVar (http://wintervar.wglab.org) (version: hg38) to evaluate sequence variants directly. With those variants that could not be defined in InterVar, we used The Genome Aggregation Database (gnomAD, https://console.cloud.google.com/storage/browser/gnomad-public/release/2.0.2/) to evaluate the allele frequency and LitVar (https://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/LitVar/) to evaluate whether there were relevant functional studies. Under 0.001 were defined as gnomAD. Based on information gathered in the databases and the ACMG/AMP classification framework (Tables 1 and 2), we evaluated related sequence variants and proposed a clinical judgement.

3. Results and Discussion

We summarized genetic studies published in the PubMed database over 11 years (Figure 1). A total 1015 articles were enrolled after searching the database. 927 articles were excluded. Finally, 88 articles fit the profile; 99 variants and 34 genes were studied in the current article.
Figure 1

Summary of specification.

Information in InterVar was gathered to evaluate all the sequence variants, and the relevant evidence for pathogenic and benign criteria was summarized (Table 3). For mutation cannot be defined in InterVar, we used gnomAD and ClinVar to analyze frameshift mutations (Table 4) and large fragment deletions (Table 5). We also gathered information about splicing mutations (Table 6).
Table 3

Evaluate all sequence variants using InterVar database.

ChrPositionRefAltGeneCriterionClinical manifestAuthors
1221882785GAABCC9Likely pathogenicPCCD; SSSCelestino-Soper et al. [18]
1236731300TCACTN2Likely pathogenicAVB; AFGirolami et al. [19]
221006288ATAPOBUncertain significancePCCD; SSSCelestino-Soper et al. [18]
122567685GACACNA1CLikely pathogenicSSSZhu et al. [20]
122567694GACACNA1CLikely pathogenicSSSZhu et al. [20]
122448997CTCACNA1CLikely pathogenicPCCDGao et al. [21]
122504538GACACNA1CPathogenicAVB; Timothy syndrome 1 (TS1)Sepp et al. [49]
186447519GTCLCA2Uncertain significanceAVB; PCCDMao et al. [50]Tan et al. [51]
2219425671CADESUncertain significanceAVB; AFJurcu et al. [52]
2219418500CTDESPathogenicAVBvan Tintelen et al. [22]
1831524751AGDSG2Benign/likely benignAVBCastellana et al. [53]
1744805594GTGJC1Uncertain significanceAVBSeki et al. [54]
X101398869ACGLAUncertain significanceHCM; AVBCsanyi et al. [55]
7100676751GTGNB2Uncertain significanceSSS; AVBStallmeyer et al. [56]
1573329719CTHCN4Pathogenic/likely pathogenicSSS; LVNCMilano et al. [28]
1573343416ATHCN4Uncertain significanceSSS; AF; LVNCIshikawa et al. [31]
1573329719CTHCN4Pathogenic/likely pathogenicSSSIshikawa et al. [31]
1573323745GCHCN4Likely benignSSSSchweizer et al. [29]
1573322804CAHCN4Uncertain significanceAVBZhou et al. [57]
2044160305ATJPH2Uncertain significanceHCM; AVBVanninen et al. [58]
7150951555CAKCNH2PathogenicAVB; LQTPriest et al. [35]
2155555534ACKCNJ3Uncertain significanceSSS; AFYamada et al. [59]
112549192GAKCNQ1Pathogenic/likely pathogenicSSS; AFRighi et al. [34]
X119589315CTLAMP2PathogenicAVB; WPW; Danon diseaseMiani et al. [39]
1088446830GALDB3BenignPCCD; SSSCelestino-Soper et al. [18]
1156104224CTLMNAPathogenicAVB; VT; SCDGlocklhofer et al. [36]
1156104281AGLMNAUncertain significanceAVB; HFPetillo et al. [60]
1156106186GCLMNAUncertain significanceAVB; HFPetillo et al. [60]
1156084953GALMNAPathogenicAVB; DCMWu et al. [61]
1156104629CTLMNAPathogenicAVB; VT; SCDSaga et al. [62]
1156104755TCLMNAPathogenic/likely pathogenicAVB; muscular dystrophy; cardiomyopathyRomeike et al. [63]
1156084787CTLMNALikely benignAVB; AFSaj et al. [37]
1156108298CTLMNALikely pathogenicAVB; HCMFrancisco et al. [64]
X153297719GAMECP2Pathogenic/likely pathogenicSSSShioda et al. [38]
1147354497GAMYBPC3Uncertain significanceAVBKouakam et al. [65]
5172660006GANKX2-5Uncertain significanceAVB; AF; DCMYuan et al. [66]
5172661762CANKX2-5Uncertain significanceAVB; congenital cardiovascular diseases (CCVD)Pabst et al. [67]
5172660110GCNKX2-5Uncertain significanceAVB; ASDXie et al. [68]
111907171CTNPPAPathogenicSSS; atrial dilatation (AD)Disertori et al. [69]
X101096287GANXF5Uncertain significanceAVB; focal segmental glomerulosclerosis (FSGS)Esposito et al. [70]
201961153TAPDYNUncertain significancePCCDSu et al. [71]
201961154CGPDYNUncertain significancePCCDSu et al. [71]
7151560613AGPRKAG2Uncertain significanceHCM; AVBThevenon et al. [72]
338550326GTSCN5AUncertain significanceSSSChen et al. [73]
338603929GCSCN5AUncertain significanceAVBNikulina et al. [74]
338556532TCSCN5AUncertain significanceSSSHothi et al. [41]Asadi et al. [75]
338550734ACSCN5AUncertain significanceSSSAbe et al. [76]
338613790CTSCN5ALikely pathogenicSSSAbe et al. [76]
338566426CTSCN5APathogenicAVB; DCMWatanabe et al. [77]
338550899TASCN5AUncertain significanceSSSIshikawa et al. [31]
338581137GASCN5ALikely benignAVBHu et al. [78]
338581002CTSCN5AUncertain significanceSSS; AFL; AFMoreau et al. [79]
338633207GTSCN5AUncertain significanceAVBThongnak et al. [80]
338613787GASCN5AUncertain significancePCCD; SSSBaskar et al. [81]Celestino-Soper et al. [18]
338597787CASCN5ALikely pathogenicSSS; AFLSelly et al. [82]
338630342TASCN5APathogenic/likely pathogenicSSS; AFL; VTHolst et al. [43]
338575424CASCN5AUncertain significanceAVB; DCMGe et al. [83]
338551477ATSCN5ALikely pathogenicSSS; AVBRobyns et al. [84]
338560398GASCN5APathogenicAVBThongnak et al. [80]
338550968CASCN5AUncertain significanceSSSAbe et al. [76]
1949196760GATRPM4Uncertain significancePCCDLiu et al. [47]
1949157885GATRPM4PathogenicPCCD; SSSKruse et al. [48]
1949167950GATRPM4BenignAVB; VTBianchi et al. [46]
1949196790AGTRPM4Likely benignPCCDDaumy et al. [5]
1949202140ATTRPM4Uncertain significanceAVB; VTBianchi et al. [46]
1949171597AGTRPM4Uncertain significanceAVBStallmeyer et al. [85]
1949200395AGTRPM4PathogenicAVBStallmeyer et al. [85]
1949168301CTTRPM4PathogenicPCCDLiu et al. [47]
1949182608GATRPM4Uncertain significanceAVBSyam et al. [86]
1949188641GATRPM4Uncertain significanceAVBSyam et al. [86]
1949183108CTTRPM4Uncertain significancePCCDLiu et al. [47]
1949196597TCTRPM4Uncertain significanceAVBStallmeyer et al. [85]
2178569522GTTTNUncertain significanceSSSZhu et al. [20]
Table 4

Using ClinVar to analysis frameshift mutation.

Genome ADChrdbSNPGeneVariantFunctional studyCriterion
ALG13c.383+2821_383+2822delinsTT
Chr2:219418955-219418982rs1114167332DESc.493_520del28insGCGTPathogenic
DSC2c.2688_2688delinsGAA
EXT2c.1101_1102delAG (E368Kfs18)
Chr1:156130627-156130629rs794728597LMNAc.367_369delAAGPathogenicLikely pathogenic
LMNAc.364_366AAG
LMNAc.103-105del CTG
LMNA815_818delinsCCAGAC
MYL4c.234delC
Chr5:173232761rs587784067NKX2.5c.959delCConflicting interpretations of pathogenicity
SCN5Ac.2401_2409delinsTCCUncertain significant
SCN5Ac.5355_5354delCTUncertain significant
SCN5Ac.5368 GNA
SCN5Ac.3142_3153de-l12ins11
MYH6delE933
MYL4c.234delC
Table 5

Using InterVal to analysis large fragment deletion.

Genome ADChrdbSNPGeneVariantFunctional study
DESDeletion-insertion mutation (c.1045-1063 del/G ins), deleting 7 amino acids (Met349-Arg355) and inserting 1 amino acid (Gly349)
Table 6

Analyzing splicing mutation.

Genome ADChrdbSNPGeneVariantFunctional study
HCN4c.1737+1G>T
Chr:1:156130615LMNAc.357-2A>G
LMNAc.357-1G>T
LMNAIVS9-3C>G
G = 0.00001Chr3:38562413rs397514447SCN5Ac.3963+2T>C
SCN5Ac.1141-2A>G
SCN5Ac.-225-820T>C
TGF beta 1c.4246-2A>G
MYH6c.2292+2T>C
We studied 88 articles, including 99 variants and 34 genes, after searching the PubMed database and identified 13 high-priority genes causing familial bradycardia, as follows: ABCC9 [18], ACTN2 [19], CACNA1C [20, 21], DES [22-27], HCN4 [28-32], KCNQ1 [33, 34], KCNH2 [35], LMNA [36, 37], MECP2 [38], LAMP2 [39], NPPA [40], SCN5A [41-45], and TRPM4 [5, 46–48] (Table 3). We use InterVar to reevaluate APOB, CLCA2 DSG2, GJC1, GLA, GNB2, JPH2, KCNJ3, LDB3, MYBPC3, NKX2-5, NXF5, PDYN, PRKAG2, and TTN, which have been published as pathogenic variants. According to the ACMG/AMP variant classification framework, those genes should be classified into uncertain significance. For the majority of related genes, the clinical manifestations were not unique. These mutations may lead to bradycardia, arrhythmia, myopathy, and nerve system disease. LMNA mutations may present as AVB and arrhythmia; DES, GJA5, TTN, LAMP2, and MECP2 mutations may present as AVB and myopathy; GNB5 mutation may present as CCD and nerve system disease; HCN4, KCNQ1, PRKAG2, and SCN5A mutations may present as CCD, myopathy, and arrhythmia. Genetic diagnosis has become an inalienable part of the diagnosis, treatment, and prevention of SCD. Cardiac ion channel disease, closely related to sudden cardiac death (SCD), has been discussed for decades. In contrast, the relationship between bradycardia and genetic factors is still unclear. Syncope and SCD caused by bradycardia are life-threatening diseases. If the relationship between genetic factors and bradycardia is eliminated, SCD could be prevented. Pedigrees of bradycardia families have been reported for decades. However, those studies are lacking. Some of the studies do not include full information about related sequence variants, and some of the studies do not list the whole family tree. In addition, the methods used to evaluate sequence variants are complex, and different centers have their own experience. It is still doubtful whether those variants are pathogenic. Therefore, ACMG/AMP promotes a guideline for thorough evaluation. By analyzing the allele frequency, segregation, de novo, protein expression, functional studies, and other factors, sequencing variants can be scored into a five-tier system: pathogenic, likely pathogenic, uncertain significant, likely benign, and benign. As accurate as the guideline may be, pathogenicity has been defined as being greater than 90% of pathogenicity [15]. According to the precise classification of pathogenicity, pedigrees of familial bradycardia can be reevaluated. InterVar [16] is a tool implementing ACMG/AMP criteria that can automatically analyze sequence variants. In this article, we used InterVar to summarize 13 high-priority genes, as follows: ABCC9, ACTN2, CACNA1C, DES, HCN4, KCNQ1, KCNH2, LMNA, MECP2, LAMP2, NPPA, SCN5A, and TRPM4 (Table 3). High-throughput sequencing (next-generation sequencing) is quite expensive. In contrast, the gene panel is cheaper and easier to analyze. We recommend that patients with a family history of bradycardia have their clinical manifestations gathered and that related pathogenic genes be highly regarded. For future reference, multicenter studies on the epidemiology of familial bradycardia should be organized. In addition, detailed information about sequence variants should be addressed in related articles and should be evaluated under the ACMG/AMP classification framework. The relationship between bradycardia and genomic variants remains unknown, and epigenetics and modifier genes should be used to investigate the relationship between genes and diseases.

4. Limitation

We summarized sequence variants published in only the PubMed database. There should be more pathogenic genes studied related to bradycardia.

5. Conclusion and Future Direction

Only 13 pathogenic genes (99 sequence variants and 34 genes being studied) were identified after using the ACMG/AMP variant classification framework to reevaluate. For future reference, pedigree studies should be fully evaluated before being published. For patients with familial CCD, 13 high-priority genes are recommended for evaluation. Compared to whole genome sequencing, this will increase the clinical utility of genetic testing.
  86 in total

1.  Sinus bradycardia, junctional rhythm, and low-rate atrial fibrillation in Short QT syndrome during 20 years of follow-up: three faces of the same genetic problem.

Authors:  Daniela Righi; Massimo S Silvetti; Fabrizio Drago
Journal:  Cardiol Young       Date:  2015-08-17       Impact factor: 1.093

Review 2.  Classification and Reporting of Potentially Proarrhythmic Common Genetic Variation in Long QT Syndrome Genetic Testing.

Authors:  John R Giudicessi; Dan M Roden; Arthur A M Wilde; Michael J Ackerman
Journal:  Circulation       Date:  2018-02-06       Impact factor: 29.690

3.  A newly identified missense mutation in CLCA2 is associated with autosomal dominant cardiac conduction block.

Authors:  Zhuo Mao; Yi Wang; Hao Peng; Fang He; Li Zhu; He Huang; Xianghong Huang; Xiaowei Lu; Xiaojun Tan
Journal:  Gene       Date:  2019-07-18       Impact factor: 3.688

4.  Sick sinus syndrome with HCN4 mutations shows early onset and frequent association with atrial fibrillation and left ventricular noncompaction.

Authors:  Taisuke Ishikawa; Seiko Ohno; Takashi Murakami; Kentaro Yoshida; Hiroyuki Mishima; Tetsuya Fukuoka; Hiroki Kimoto; Risa Sakamoto; Takafumi Ohkusa; Takeshi Aiba; Akihiko Nogami; Naokata Sumitomo; Wataru Shimizu; Koh-Ichiro Yoshiura; Hitoshi Horigome; Minoru Horie; Naomasa Makita
Journal:  Heart Rhythm       Date:  2017-01-17       Impact factor: 6.343

5.  Preprodynorphin gene mutation causes progressive cardiac conduction disease: A whole-exome analysis of a pedigree.

Authors:  Jian-Yao Su; Rong-Feng Zhang; Ying-Xue Dong; Ming-Hui Yang; Xiao-Meng Yin; Lian-Jun Gao; Hui-Hua Li; Yun-Long Xia; Yan-Zong Yang
Journal:  Life Sci       Date:  2019-01-03       Impact factor: 5.037

6.  Identification of a new lamin A/C mutation in a Chinese family affected with atrioventricular block as the prominent phenotype.

Authors:  Xiaoyan Wu; Qing K Wang; Le Gui; Mugen Liu; Xianqin Zhang; Runming Jin; Wei Li; Lu Yan; Rong Du; Qiufen Wang; Jianfang Zhu; Junguo Yang
Journal:  J Huazhong Univ Sci Technolog Med Sci       Date:  2010-02-14

Review 7.  Inhibition of late sodium current by mexiletine: a novel pharmotherapeutical approach in timothy syndrome.

Authors:  Yuanfeng Gao; Xiaolin Xue; Dayi Hu; Wenling Liu; Yue Yuan; Hongmei Sun; Lei Li; Katherine W Timothy; Li Zhang; Cuilan Li; Gan-Xin Yan
Journal:  Circ Arrhythm Electrophysiol       Date:  2013-04-11

8.  Targeted resequencing identifies TRPM4 as a major gene predisposing to progressive familial heart block type I.

Authors:  Xavier Daumy; Mohamed-Yassine Amarouch; Pierre Lindenbaum; Stéphanie Bonnaud; Eric Charpentier; Beatrice Bianchi; Sabine Nafzger; Estelle Baron; Swanny Fouchard; Aurélie Thollet; Florence Kyndt; Julien Barc; Solena Le Scouarnec; Naomasa Makita; Hervé Le Marec; Christian Dina; Jean-Baptiste Gourraud; Vincent Probst; Hugues Abriel; Richard Redon; Jean-Jacques Schott
Journal:  Int J Cardiol       Date:  2016-01-11       Impact factor: 4.164

9.  A novel desmin (DES) indel mutation causes severe atypical cardiomyopathy in combination with atrioventricular block and skeletal myopathy.

Authors:  Ilona Schirmer; Mareike Dieding; Bärbel Klauke; Andreas Brodehl; Anna Gaertner-Rommel; Volker Walhorn; Jan Gummert; Uwe Schulz; Lech Paluszkiewicz; Dario Anselmetti; Hendrik Milting
Journal:  Mol Genet Genomic Med       Date:  2017-12-23       Impact factor: 2.183

10.  Heterozygous junctophilin-2 (JPH2) p.(Thr161Lys) is a monogenic cause for HCM with heart failure.

Authors:  Sari U M Vanninen; Krista Leivo; Eija H Seppälä; Katriina Aalto-Setälä; Olli Pitkänen; Piia Suursalmi; Antti-Pekka Annala; Ismo Anttila; Tero-Pekka Alastalo; Samuel Myllykangas; Tiina M Heliö; Juha W Koskenvuo
Journal:  PLoS One       Date:  2018-09-20       Impact factor: 3.240

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