Literature DB >> 32268277

Reanalysis and reclassification of rare genetic variants associated with inherited arrhythmogenic syndromes.

Oscar Campuzano1, Georgia Sarquella-Brugada2, Anna Fernandez-Falgueras3, Mónica Coll3, Anna Iglesias3, Carles Ferrer-Costa4, Sergi Cesar5, Elena Arbelo6, Ana García-Álvarez6, Paloma Jordà6, Rocío Toro7, Coloma Tiron de Llano8, Simone Grassi9, Antonio Oliva9, Josep Brugada10, Ramon Brugada11.   

Abstract

BACKGROUND: Accurate interpretation of rare genetic variants is a challenge for clinical translation. Updates in recommendations for rare variant classification require the reanalysis and reclassification. We aim to perform an exhaustive re-analysis of rare variants associated with inherited arrhythmogenic syndromes, which were classified ten years ago, to determine whether their classification aligns with current standards and research findings.
METHODS: In 2010, the rare variants identified through genetic analysis were classified following recommendations available at that time. Nowadays, the same variants have been reclassified following current American College of Medical Genetics and Genomics recommendations.
FINDINGS: Our cohort included 104 cases diagnosed with inherited arrhythmogenic syndromes and 17 post-mortem cases in which inherited arrhythmogenic syndromes was cause of death. 71.87% of variants change their classification. While 65.62% of variants were classified as likely pathogenic in 2010, after reanalysis, only 17.96% remain as likely pathogenic. In 2010, 18.75% of variants were classified as uncertain role but nowadays 60.15% of variants are classified of unknown significance.
INTERPRETATION: Reclassification occurred in more than 70% of rare variants associated with inherited arrhythmogenic syndromes. Our results support the periodical reclassification and personalized clinical translation of rare variants to improve diagnosis and adjust treatment. FUNDING: Obra Social "La Caixa Foundation" (ID 100010434, LCF/PR/GN16/50290001 and LCF/PR/GN19/50320002), Fondo Investigacion Sanitaria (FIS PI16/01203 and FIS, PI17/01690), Sociedad Española de Cardiología, and "Fundacio Privada Daniel Bravo Andreu".
Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Arrhythmias; Genetics; Pathogenicity; Sudden cardiac death

Year:  2020        PMID: 32268277      PMCID: PMC7136601          DOI: 10.1016/j.ebiom.2020.102732

Source DB:  PubMed          Journal:  EBioMedicine        ISSN: 2352-3964            Impact factor:   8.143


Evidence before this study

The American College of Medical Genetics and Genomics (ACMG) current recommendations include guidelines for obtaining an accurate assessment of rare variants. However, there is a lack of available data for each rare variant, and many remain of uncertain significance. Therefore, many of the families affected with inherited arrhythmic syndrome remain with an inconclusive genetic diagnosis, which is not helpful in clinical decision-making. Accurate interpretation of rare genetic variants is a challenge for clinical translation. Updates in recommendations for rare variant classification require the reanalysis and reclassification. An exhaustive review of the literature concerning each variant was performed through December 2019. Data was collected from: HGMD (www.hgmd.org), ClinVar (www.ncbi.nlm.nih.gov/clinvar/intro/), the National Center for Biotechnology Information SNP database (www.ncbi.nlm.nih.gov/SNP), Index Copernicus (en.indexcopernicus.com), Google Scholar (scholar.google.es), Springer Link (link.springer.com), Science Direct (www.sciencedirect.com), Excerpta Medica Database (www.elsevier.com/solutions/embase-biomedical-research), and the IEEE Xplore Digital Library (ieeexplore.ieee.org/Xplore/home.jsp). All genetic variants included in our study were compared to data from Exome Variant Server (EVS; evs.gs.washington.edu/EVS), and Genome Aggregation Database (gnomAD gnomad.broadinstitute.org/).

Added value of this study

Establishing a definite pathogenicity of rare genetic variants helps for clinical diagnosis of inherited arrhythmogenic syndromes but also helps to adopt therapeutic measures for prevention of sudden death. We have performed an accurate genetic reinterpretation of variants classified 10 years ago. Reclassification occurred in more than 70% of rare variants associated with inherited arrhythmogenic syndromes. These changes may influence clinical decisions adopted 10 years ago.

Implications of all the available evidence

Currently, classification of a genetic variant follows guidelines published in 2015 by ACMG/AMP. These recommendations are based on available data concerning the variant at the moment of classification. Data available 10 years ago is not the same as now. Therefore, reclassification and reinterpretation of a variant should be updated periodically to improve diagnosis and adjust treatment despite no concrete timeframe for this being established. In the light of our results, we propose that rare variants associated with inherited arrhythmogenic syndromes should be reanalysed within five years if already classified following ACMG recommendations, since this seems to be adequate to manage the rapid obsolescence of genetic data interpretations. In addition, our results support further urgent reanalysis of each IAS rare variant if they were not classified originally following ACMG recommendations. Alt-text: Unlabelled box

Introduction

Advances in gene sequencing technology have made genetic testing in clinical diagnosis more accessible by increasing the number of analysed genes, decreasing costs, and reducing the amount of time required for analysis [1]. For an adequate translation of genetic data to clinical practice, and in order to manage the inherited conditions, it is critical to perform an appropriate interpretation of the genetic variant [2]. Sudden death may be the first manifestation of an inherited arrhythmic syndrome (IAS), thus early identification with genetic technology may help adopt preventive measures and reduce the risk of lethal episodes in family members. Genetic analysis may also be determinant in identifying causality in sudden death deemed inconclusive after a comprehensive autopsy. For these reasons current guidelines recommend genetic analysis in diagnosed patients and relatives who may be at risk, despite remaining asymptomatic [3]. The American College of Medical Genetics and Genomics (ACMG) current recommendations include guidelines for obtaining an accurate assessment of rare variants [4]. However, there is a lack of available data for each rare variant, and many remain of uncertain significance. Therefore, many of the families affected with IAS remain with an inconclusive genetic diagnosis, which is not helpful in clinical decision-making [5]. Rare variants classified as inconclusive are disregarded, and only clinical and family history are referenced in determining risk-assessment and clinical management [4]. Clinical and functional data on rare IAS variants published in the last ten years has helped clarify their roles and improved their classification. Continuous reclassification is recommended to update their roles before clinical translation. Such re-evaluation may serve to improve psychological outcomes and risk stratification while promoting personalized management [6, 7]. Only a few reports have addressed this idea in recent years [8], [9], [10]. In the present study, we describe the reclassification of rare IAS variants reported ten years ago by our laboratory to update their roles following current guidelines.

Materials and methods

Samples

This retrospective study reanalysed rare IAS variants classified in our laboratory ten years ago (during the year 2010). Rare variants were originally classified following recommendations available in 2010 as pathogenic (P), likely pathogenic (LP), variant of unknown significance (VUS), or as likely benign (LB) [11]. Variants classified as Benign in 2010 were not reanalysed due to global frequencies higher than 1%, and already identified ten years ago as common variants. All rare variants were identified in two groups: samples from patients with a definite clinical diagnosis of IAS or post-mortem samples without a conclusive cause of death but with suspected IAS. Genetic analysis was approved by the ethics committee of Hospital Josep Trueta (Girona, Spain) following the Helsinki II declaration. Both clinical and genetic data concerning all patients were kept confidential. Written informed consent was obtained from all patients included in the study. In post-mortem cases, a family member authorized the study or judge/legal authority included molecular autopsy as part of legal process.

Genetic analysis

Genomic DNA was extracted with Chemagic MSM I from whole blood (Chemagic human blood) or saliva (Chemagic Oragene Saliva). Concentration was determined along with purity using a NanoDrop1000 spectrophotometer (Thermo scientific). Genomic DNA was amplified by polymerase chain reaction (PCR) using intronic primers for each exon of all the genes analysed. The PCR product was purified by ExoSAP-IT (USB Corporation, Cleveland, OH, USA) and directly sequenced by dideoxy chain-termination method in an ABI Prism Big Dye® Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems, USA). Sequencing was processed in a 3130XL Genetic Analyzer (Applied Biosystems) and analysed by SeqScape Software v2.5 (Life Technologies). The genes associated with each IAS subtype were analysed following the prevailing recommendations in 2010 [11]. Genetic analysis for arrhythmogenic cardiomyopathy (ACM) included PKP2, DSP, DSC2, DSG2, DES, JUP, and TGFB3; analysis for Brugada syndrome (BrS) included SCN5A; analysis for catecholaminergic polymorphic ventricular tachycardia (CPVT) included RYR2 and CASQ2; analysis for dilated cardiomyopathy (DCM) included LMNA; analysis for hypertrophic cardiomyopathy (HCM) included MYH7, MYBPC3, TNNT2, and TNNI3; analysis for long QT Syndrome (LQTS) included KCNQ1, KCNH2, and SCN5A; and finally, analysis for sick sinus syndrome (SSS) included SCN5A and HCN4. The genes analysed in post-mortem cases were SCN5A, KCNQ1, KCNH2, KCNE1, KCNE2, KCNE3, RYR2, and CASQ2. All original sequences obtained in 2010 were comprehensively reanalysed with updated software (SeqScape v2.7, Applied Biosystems) to identify any alteration not identified at the time of report.

Data

An exhaustive review of the literature concerning each variant was performed through December 2019. Data was collected from: HGMD (www.hgmd.org), ClinVar (www.ncbi.nlm.nih.gov/clinvar/intro/), the National Center for Biotechnology Information SNP database (www.ncbi.nlm.nih.gov/SNP), Index Copernicus (en.indexcopernicus.com), Google Scholar (scholar.google.es), Springer Link (link.springer.com), Science Direct (www.sciencedirect.com), Excerpta Medica Database (www.elsevier.com/solutions/embase-biomedical-research), and the IEEE Xplore Digital Library (ieeexplore.ieee.org/Xplore/home.jsp). All genetic variants included in our study were compared to data from Exome Variant Server (EVS; evs.gs.washington.edu/EVS), and Genome Aggregation Database (gnomAD gnomad.broadinstitute.org/).

Classification

Ten years ago, variants were classified following an in-house algorithm including multiple parameters such as population frequencies, in silico predictions, and published functional data. Algorithms followed recommendations available in 2010 [11]. Part of this in-house algorithm focused on inherited arrhythmogenic disorders was published in 2015 [12]. Nowadays, all variants have been reclassified according to ACMG standards and guidelines for the interpretation of sequence variants as P, LP, VUS, LB, or benign (B) [4]. The PM2 item in the ACMG classification was considered fulfilled if Minor Allele Frequency (MAF) in relevant population databases was ≤0.1% [13]. The vast majority of reported pathogenic variants in IAS are extremely rare (<0.01%) [14]. High degree of pathogenicity (item PVS1) should only be used for rare variants in genes where loss of function is a well-established disease mechanism [15]. Genetic data were independently evaluated and classified by three clinical genetic experts. All investigators discussed and agreed on a final classification of all variants to avoid bias.

Results

Cohort

Our retrospective study included 121 cases, all Caucasian, with an even gender distribution (65 men; 53.71% and 56 women; 46.28%). Ages ranged from 19 to 51 years of age (mean age: 39.2 years). The first cohort (named “clinical group” –CL-) included 104 cases (85.95%) with a definite clinical diagnosis of IAS. Definitively, CL included 48 cases of BrS, 34 cases of ACM, 10 cases of LQTS, 7 cases of HCM, 4 cases of CPVT, and only one case diagnosed with DCM (Fig. 1). Suspicious cases with an inconclusive diagnosis were not included to avoid bias in the reclassification of genetic variants. The second cohort (named “post-mortem group” –PM-) comprised 17 post-mortem samples (14.05%) with IAS as the likely cause of death (Fig. 1). Exhaustive complete autopsies were performed in all cases, including toxicological analysis, before final judgment. Review of clinical and forensic data did not change the diagnostic decisions from ten years ago.
Fig. 1

Distribution of rare variants. White columns represent the original classification (2010). Black columns represent the classification after the reanalysis. (a) Global classification of rare variants. (b) Global classification of rare missense variants. (c) Global classification of rare radical variants. (d) Classification of rare variants in Post-Mortem group. (e) Classification of rare variants in Clinical group. (f) Classification of rare missense variants in Clinical group. (g) Classification of rare radical variants in Clinical group.

Distribution of rare variants. White columns represent the original classification (2010). Black columns represent the classification after the reanalysis. (a) Global classification of rare variants. (b) Global classification of rare missense variants. (c) Global classification of rare radical variants. (d) Classification of rare variants in Post-Mortem group. (e) Classification of rare variants in Clinical group. (f) Classification of rare missense variants in Clinical group. (g) Classification of rare radical variants in Clinical group.

Genetics

One hundred twenty-eight rare variants were localized in 17 genes: 55 in SCN5A, 17 in PKP2, 9 in KCNH2 and RyR2, 8 in DSG2, 6 in KCNQ1, 4 in MYBPC3, MYH7 and DSP, 3 in JUP, 2 in DSC2 and KCNE2, and 1 in KCNE3, DES, LMNA and TGFB3. All identified variants were exonic except one intronic variant (c.3840+1G>A_SCN5A, case 28). Of the 127 exonic variants, 96 were missense and 31 were radical (ten nonsense, fifteen deletions and six insertions). All cases carried at least one rare variant except for seven cases that carried two rare variants (case 26, LQTS; case 28, BrS; case 65, BrS; case 72, LQTS; case 79, ACM; case 107, ACM; and case 113, HCM). Original classification concluded that there were 19 P variants (14.84%), 84 LP variants (65.62%), 24 VUS variants (18.75%), and only one LB variant (0.78%) (Fig. 1) (Tables 1–3).
Table 1

Variant genetic data.

Index caseDiseaseGeneNucleotideProteindbSNPgnomADHGMD (disease)ClinVar2010 classification2020 classification (ACMG)
1BrSSCN5Ac.5464_5467delTCTGp.(Glu1823Hisfs*10)rs7947289241/249656 (0.0004%)CD077699 (SSS)PPP
2ACMPKP2c.1613G>Ap.(Trp538*)rs1939226724/251382 (0.001%)CM061177 (ACM)LPLPP
3BrSSCN5Ac.1717C>Tp.(Gln573*)NANACM100660 (BrS)NALPP
4BrSSCN5Ac.4477A>Tp.(Lys1493*)NANACM100735 (BrS)NALPP
5BrSSCN5Ac.2865_2866delGAp.(Glu955Aspfs*74)rs7561597374/248468 (0.001%)NANALPLP
6BrSSCN5Ac.1721delGp.(Gly574Aspfs*49)NANACD100781 (BrS)NALPLP
7ACMDSG2c.146G>Ap.(Arg49His)rs1219130061/249482 (0.0004%)CM061700 (ACM)LPVUSVUS
8LQTSKCNQ1c.421G>Ap.(Val141Met)rs199472687NACM056972 (AF)LPPLP
9BrSSCN5Ac.4562T>Ap.(Ile1521Lys)rs199473617NACM100736 (BrS)NALPVUS
10BrSSCN5Ac.4534C>Tp.(Arg1512Trp)rs13785460214/251272 (0.005%)CM994138 (BrS)VUSLPVUS
11BrSSCN5Ac.5272_5274delATCp.(Ile1758del)NANACD1810427 (PCCD)NALBVUS
12BrSSCN5Ac.707T>Gp.(Leu236Arg)NANA.NALPVUS
13ACMDSG2c.1381C>Tp.(Gln461*)rs1212557775NACM1314709 (ACM)NALPLP
14BrSSCN5Ac.4978A>Gp.(Ile1660Val)rs1994736258/251490 (0.003%)CM057204 (LQTS)VUSLPVUS
15BrSSCN5Ac.2893C>Tp.(Arg965Cys)rs19947318016/246378 (0.006%)CM024644 (BrS)VUSLPVUS
16ACMJUPc.1028G>Ap.(Ser343Asn)NANANANAVUSVUS
17BrSSCN5Ac.4352T>Cp.(Val1451Ala)NANANANALPVUS
18ACMJUPc.475G>Tp.(Val159Leu)rs78270226611/269700 (0.004%)CM1010258 (ACM)VUSVUSVUS
19BrSSCN5Ac.4493T>Cp.(Met1498Thr)rs199473263NACM057203 (LQTS)VUSLPVUS
20ACMDSPc.2956C>Tp.(Gln986*)NANACM1310184 (ACM)NALPP
21ACMPKP2c.2013delCp.Lys672Argfs*12rs7648176832/251350 (0.0007%)CD061457 (ACM)PPP
22BrSSCN5Ac.2550_2551dupGTp.Phe851Cysfs*19rs397514450NACI055774 (DCM)PPP
23BrSSCN5Ac.4856delCp.Pro1619Argfs*12NANACD100798 (BrS)NALPP
24BrSSCN5Ac.1936delp.Gln646Argfs*5rs7275051581/31374 (0.003%)CD100782 (BrS)PLPP
25BrSSCN5Ac.5174C>Tp.(Pro1725Leu)rs1994733015/251170 (0.001%)CM097849 (LQTS)VUSLPVUS
26LQTSKCNH2c.2639G>Tp.(Gly880Val)NANACM150041 (LQTS)NAPLP
KCNH2c.1838C>Tp.(Thr613Met)rs199473524NACM990761 (LQTS)PLPVUS
27ACMPKP2c.2203C>Tp.(Arg735*)rs1214344211/251356 (0.0003%)CM043061 (ACM)PPP
28BrSSCN5Ac.3840+1G>ANANANACS099837 (BrS)NAPLP
SCN5Ac.5068G>Ap.(Asp1690Asn)rs10604999001/251488 (0.0003%)CM136071 (BrS)VUSLPVUS
29BrSSCN5Ac.2669T>Cp.(Ile890Thr)NANACM130365 (BrS)NALPVUS
30BrSSCN5Ac.1705dupCp.(Arg569Profs*152)NANACI1510495 (BrS)NALPLP
31BrSSCN5Ac.1872dupAp.(Glu625Argfs*96)NANACI1510496 (BrS)NALPLP
32ACMPKP2c.1912C>Tp.(Gln638*)rs3975170121/251302 (0.0003%)CM043056 (ACM)PPP
33BrSSCN5Ac.2729C>Tp.(Ser910Leu)rs1994731751/250430 (0.0003%)CM024643 (BrS)LPLPVUS
34ACMPKP2c.604dupGp.(Val202Glyfs*14)NANACI146422 (ACM)NALPLP
35ACMDSG2c.137G>Ap.(Arg46Gln)rs1219130081/280866 (0.00003%)CM061701 (ACM)LPLPVUS
36BrSSCN5Ac.2962C>Tp.(Arg988Trp)rs7686918535/238498 (0.002%)CM137981 (BrS)VUSLPVUS
37LQTSSCN5Ac.5859_5862delTGAGp.(Ser1953Argfs*84)rs7583174661/246198 (0.0004%)NANALPLP
38BrSSCN5Ac.4213G>Ap.(Val1405Met)rs199473239NACM100715 (BrS)VUSPLP
39BrSSCN5Ac.361C>Tp.(Arg121Trp)rs199473556NACM095355 (BrS)VUSLPVUS
40BrSSCN5Ac.1100G>Ap.(Arg367His)rs28937318NACM020301 (SUNDS)LPPLP
41BrSSCN5Ac.5177C>Gp.(Pro1726Arg)NANANANALPVUS
42ACMTGFB3c.1230A>Cp.(Lys410Asn)NANANANALPVUS
43ACMDSG2c.2440T>Cp.(Cys814Arg)NANACM146425 (ACM)NALPVUS
44ACMPKP2c.275T>Ap.(Leu92*)rs7636397372/251424 (0.0007%)CM102825 (ACM)PPP
45ACMDESc.407T>Ap.(Leu136His)rs39751669515/213206 (0.007%)CM159728 (DCM)VUSVUSVUS
46ACMDSPc.6208G>Ap.(Asp2070Asn)rs413028851118/282114 (0.39%)CM198079 (BrS)LBVUSLB
47LQTSKCNQ1c.898G>Ap.(Ala300Thr)rs12007418712/249914 (0.004%)CM983511 (LQTS)VUSPLP
48BrSSCN5Ac.2548G>Ap.(Val850Met)rs9112936942/251416 (0.0007%)NANALPVUS
49BrSSCN5Ac.5380T>Ap.(Phe1794Ile)NANANANALPVUS
50BrSSCN5Ac.4018G>Ap.(Val1340Ile)rs19947360513/ 282822 (0.004%)CM100703 (BrS)VUSLPVUS
51HCMMYH7c.5779A>Tp.(Ile1927Phe)rs76730027711/251320 (0.004%)CM082963 (HCM)VUSVUSVUS
52BrSSCN5Ac.2168dupTp.(Thr724Hisfs*21)NANANANALPLP
53BrSSCN5Ac.2314G>Ap.(Asp772Asn)rs1994731575/249248 (0.002%)CM097652 (LQTS)VUSLPVUS
54BrSSCN5Ac.4219dupGp.(Ala1407Glyfs*13)NANANANALPP
55ACMDSG2c.473T>Gp.(Val158Gly)rs1911432921537/280564 (0.54%)CM070921 (ACM)LBVUSLB
56BrSSCN5Ac.1577G>Ap.(Arg526His)rs4562743814/242632 (0.005%)CM100657 (BrS)VUSLPVUS
57BrSSCN5Ac.1120T>Cp.(Trp374Arg)NANANANALPVUS
58LQTSKCNQ1c.1016T>Cp.(Phe339Ser)rs199472759NACM073160 (LQTS)LPPLP
59ACMPKP2c.1162C>Tp.(Arg388Trp)rs7662092971/251320 (0.0003%)CM097906 (ACM)LPLPVUS
60BrSSCN5Ac.4345T>Cp.(Tyr1449His)NANANANAVUSVUS
61BrSSCN5Ac.481G>Ap.(Glu161Lys)rs1994730621/240992 (0.0004%)CM023671 (BrS)LPVUSVUS
62ACMDSG2c.166G>Ap.(Val56Met)rs121913013518/280886 (0.18%)CM070918 (ACM)LBVUSLB
63ACMPKP2c.1378G>Ap.(Asp460Asn)rs794729106NACM1213407 (ACM)NAPLP
64ACMDSPc.6361G>Cp.(Gly2121Arg)rs3682277241/251360 (0.0003%)NANALPVUS
65BrSSCN5Ac.1579G>Cp.(Gly527Arg)rs7635501648/243942 (0.003%)NAVUSLPVUS
SCN5Ac.3929C>Gp.(Pro1310Arg)NANANANALPVUS
66BrSSCN5Ac.2236G>Ap.(Glu746Lys)rs1994735825/248406 (0.002%)CM100669 (BrS)VUSLPVUS
67CPVTRYR2c.14639T>Cp.(Val4880Ala)rs1242723821NAHM030023 (CPVT)NALPVUS
68ACMPKP2c.2576delAp.(Lys859Argfs*72)NANACD146431 (ACM)NALPLP
69ACMPKP2c.1643delGp.(Gly548Valfs*15)rs794729137NACD043194 (ACM)PPP
70BrSSCN5Ac.2633G>Ap.(Arg878His)rs199473587NACM100676 (BrS)NALPVUS
71ACMPKP2c.2060T>Gp.(Leu687Arg)rs794729113NANAVUSVUSVUS
72LQTSKCNH2c.712G>Cp.(Gly238Arg)NANANANAVUSVUS
KCNQ1c.944A>Gp.(Tyr315Cys)rs74462309NACM981127 (LQTS)LPVUSLP
73BrSSCN5Ac.5859_5862delTGAGp.(Ser1953Argfs*84)rs7583174661/246198 (0.0004%)NANALPLP
74ACMPKP2c.1759G>Ap.(Val587Ile)rs146102241616/251180 (0.24%)NALBVUSLB
75BrSSCN5Ac.4981G>Ap.(Gly1661Arg)NANACM100750 (BrS)NALPVUS
76ACMDSG2c.527C>Tp.(Thr176Ile)rs5366172174/280698 (0.001%)NAVUSLPVUS
77LQTSKCNH2c.1744C>Tp.(Arg582Cys)rs121912508NACM990759 (LQTS)PPLP
78BrSSCN5Ac.5177C>Ap.(Pro1726His)NANANANALPVUS
79ACMDSC2c.835C>Tp.(Arg279Cys)rs19392270812/251360 (0.004%)CM146543 (ACM)VUSLPLP
PKP2c.1882delCp.(Gln628Argfs*28)NANACD146544 (ACM)NALPVUS
80BrSSCN5Ac.4052T>Gp.(Met1351Arg)rs199473232NACM100707 (BrS)NALPVUS
81BrSSCN5Ac.5092G>Ap.(Ala1698Thr)rs1994732953/251490 (0.001%)CM100753 (BrS)VUSVUSVUS
82SCDRYR2c.2047G>Ap.(Glu683Lys)NANANANALPVUS
83SCDRYR2c.12056T>Cp.(Met4019Thr)rs886039150NACM173280 (MI)VUSLPVUS
84SCDKCNE2c.29C>Tp.(Thr10Met)rs19947364866/282722 (0.023%)CM055291 (LQTS)VUSVUSLB
85SCDKCNH2c.2674C>Tp.(Arg892Cys)rs201627778111/277590 (0.039%)CM1413446 (SCD)VUSLPVUS
86SCDRYR2c.12919C>Tp.(Arg4307Cys)rs20009286986/248746 (0.03%)NAVUSLPVUS
87SCDKCNE1c.253G>Ap.(Asp85Asn)rs18051282637/282814 (0.9%)CM040436 (LQTS, DI)BLPLB
88BrSSCN5Ac.3911C>Tp.(Thr1304Met)rs19947360346/279030 (0.01%)CM992663 (LQTS)VUSLPVUS
89SCDSCN5Ac.1440A>Cp.(Lys480Asn)rs7529667812/249180 (0.0008%)NAVUSLPVUS
90CPVTRYR2c.14667C>Gp.(Phe4889Leu)NANANANALPVUS
91HCMMYBPC3c.2827C>Tp.(Arg943*)rs3879072673/247124 (0.001%)CM032959 (HCM)PLPP
92SCDRYR2c.8145G>Tp.(Glu2715Asp)rs20042089714/134624 (0.01%)NAVUSLPVUS
93SCDKCNH2c.865G>Ap.(Glu289Lys)rs1994728807/35014 (0.01%)CM097827 (LQTS)VUSLPVUS
94SCDKCNH2c.2860C>Tp.(Arg954Cys)rs1414018038/217960 (0.003%)CM070176 (SIDS)VUSLPVUS
95SCDSCN5Ac.3530C>Gp.(Pro1177Arg)NANANANALPVUS
96LQTSKCNQ1c.1097G>Ap.(Arg366Gln)rs1994734101/251240 (0.0003%)CM002330 (LQTS)PPLP
97SCDSCN5Ac.5054_5055delinsTTp.(Glu1685Val)NANANANALPVUS
98ACMJUPc.2069A>Gp.(Asn690Ser)rs14762850329/282402 (0.01%)CM1416877 (Autism)VUSVUSVUS
99HCMMYBPC3c.3328delAp.(Met1110Trpfs*79)NANACD1710421 (HCM)NALPP
100SCDKCNH2c.2941A>Gp.(Ser981Gly)rs7664955475/276264 (0.027%)NAVUSLPVUS
101HCMMYH7c.4377G>Cp.(Lys1459Asn)rs201307101NACM042424 (HCM)NAVUSVUS
102CPVTRYR2c.217C>Gp.(Leu73Val)rs7777539471/249224 (0.0004%)CM1413452 (SCD)NALPVUS
103LQTSKCNQ1c.1861G>Ap.(Gly621Ser)rs1994728209/177000 (0.005%)CM1413447 (SCD)VUSLPVUS
104ACMPKP2c.1130T>Cp.(Ile377Thr)rs3975169851/31416 (0.003%)NAVUSLPVUS
105SCDSCN5Ac.287T>Cp.(Leu96Pro)NANANANALPVUS
106ACMPKP2c.76G>Ap.(Asp26Asn)rs1430048081427/168710 (0.8%)CM061172 (ACM)LBLPLB
107ACMDSG2c.908C>Tp.(Ser303Phe)rs7577927142/249400 (0.0008%)CM1616318 (ACM)VUSLPVUS
DSC2c.907G>Ap.(Val303Met)rs145560678282/282824 (0.09%)CM117222 (DCM)LBLPVUS
108SCDKCNE3c.248G>Ap.(Arg83His)rs17215437859/282668 (0.3%)CM011795 (PP)LBVUSVUS
109CPVTRYR2c.12419G>Ap.(Gly4140Glu)NANANANALPVUS
110ACMPKP2c.253_256delGAGTp.(Glu85Metfs*26)rs7862043881/251410 (0.0003%)CD102829 (ACM)PPP
111BrSSCN5Ac.2924G>Cp.(Arg975Pro)NANANANALPVUS
112SCDRYR2c.7201C>Tp.(Arg2401Cys)rs13212831062/31398 (0.006%)NANALPVUS
113HCMMYBPC3c.1513_1515delAAGp.(Lys505del)rs7275042872/249264 (0.0008%)CD031519 (HCM)NAPLP
MYBPC3c.565G>Ap.(Val189Ile)rs11570052637/245140 (0.25%)CM169151 (HCM)LBLPLB
114BrSSCN5Ac.1097T>Cp.(Phe366Ser)NANANANALPVUS
115HCMMYH7c.5117T>Cp.(Leu1706Pro)rs797044602NACM042428 (Myopathy)LPVUSVUS
116HCMMYH7c.4865T>Cp.(Leu1622Pro)NANANANAVUSVUS
117SCDKCNE2c.22A>Gp.(Thr8Ala)rs22349161059/282720 (0.37%)CM003449 (LQTS, DI)LBVUSLB
118ACMDSPc.88G>Ap.(Val30Met)rs121912998358/239538 (0.14%)CM063961 (ACM)LBLPLB
119ACMPKP2c.175C>Tp.(Gln59*)NANACM1313041 (ACM)NALPP
120DCMLMNAc.1056G>Tp.(Met352Ile)NANANANAVUSVUS
121LQTSKCNH2c.982C>Gp.(Arg328Gly)rs199473505161/282246 (0.057%)NAVUSVUSVUS

Note – ACM: arrhythmogenic cardiomyopathy, AF: atrial fibrillation, ACMG: American College of Medical Genetics and Genomics, B: benign, BrS: Brugada syndrome, ClinVar: clinical variation, CPVT: catecholaminergic polymorphic ventricular tachycardia, DCM: dilated cardiomyopathy, DM: disease mutation, gnomAD: genome aggregation database, HCM: hypertrophic cardiomyopathy, HGMD: human genome mutation database, LB: likely benign, LP: likely pathogenic, LQTS: long QT syndrome, LQTS-DI: long QT syndrome drug-induced, MI: myocardial infarction, NA: not available data, P: pathogenic, PCCD: progressive cardiac conduction disease, PP: periodic paralysis, SCD: sudden cardiac death, SIDS: sudden infant death syndrome, SSS: sick sinus syndrome, SUNDS: sudden unexpected death syndrome, VUS: variant of uncertain significance.

Table 3

Classification of rare variants in each gene.

2010
2020
GenesNumber variantsLBVUSLPPLBVUSLPPModification 2010 vs. 2020
DES1.1...1..NO
DSC22..2..2..YES
DSG28.35.251.YES
DSP4.13.21.1YES
JUP3.3...3..NO
KCNE11..1.1...YES
KCNE22.2..2...YES
KCNE31.1...1..NO
KCNH29.252.72.YES
KCNQ16.114.15.YES
LMNA1.1...1..NO
MYBPC34..311.12YES
MYH74.4...4..NO
PKP217.2872348YES
RYR29..9..9..YES
SCN5A5513465.38107YES
TGFB31..1..1..YES
TOTAL17128124841910772318

Note – LB: likely benign, LP: likely pathogenic, P: pathogenic, VUS: variant of uncertain significance.

Variant genetic data. Note – ACM: arrhythmogenic cardiomyopathy, AF: atrial fibrillation, ACMG: American College of Medical Genetics and Genomics, B: benign, BrS: Brugada syndrome, ClinVar: clinical variation, CPVT: catecholaminergic polymorphic ventricular tachycardia, DCM: dilated cardiomyopathy, DM: disease mutation, gnomAD: genome aggregation database, HCM: hypertrophic cardiomyopathy, HGMD: human genome mutation database, LB: likely benign, LP: likely pathogenic, LQTS: long QT syndrome, LQTS-DI: long QT syndrome drug-induced, MI: myocardial infarction, NA: not available data, P: pathogenic, PCCD: progressive cardiac conduction disease, PP: periodic paralysis, SCD: sudden cardiac death, SIDS: sudden infant death syndrome, SSS: sick sinus syndrome, SUNDS: sudden unexpected death syndrome, VUS: variant of uncertain significance. Modifications in classification of rare variant. Note – CL: clinical group, PM: post-mortem group. Classification of rare variants in each gene. Note – LB: likely benign, LP: likely pathogenic, P: pathogenic, VUS: variant of uncertain significance. Reanalysis following current ACMG guidelines conferred significant changes in 71.87% (92 of 128) of the rare variants. One variant changed from LB to VUS (0.7%), 6 rare variants changed from VUS to LB (4.6%), and one changed from VUS to LP (0.7%). Four rare variants initially classified as LP in 2010 were changed to LB (3.1%), 59 were changed to VUS (46.09%), and 10 were changed to P (7.8%). Ten rare variants classified as P in 2010 were downgraded to LP in the reclassification (7.8%). In 2010, we classified 24 rare variants as VUS (18.75%) and after reanalysis, there were 77 classified as VUS (60.15%; 17 rare variants had no modification and 60 were reclassified). Originally, the majority were LP variants (84 of 128; 65.62%), but after reanalysis, the predominant classification of the variants was VUS (77 of 128; 60.65%) in contrast to 18.75% (24 of 128), ten years ago. Just twenty-three of 128 (17.96%) were classified as LP. After reanalysis, VUS became the predominant group (77 of 128; 60.65%) in contrast to 18.75% (24 of 128) ten years ago. In 2010, only one variant (0.78%) was classified as LB while after the reanalysis, 7.8% (10 of 128) were classified LB. The percentage of P variants was similar in both classifications (19 of 128; 14.84% in 2010 and 18 of 128; 14.06% after the reanalysis) (Fig. 2).
Fig. 2

Reclassification of rare variants. White colour represents the number of rare variants classified as LB. Soft grey colour represents the number of rare variants classified as VUS. Dark grey colour represents the number of rare variants classified as LP. Black colour represents the number of rare variants classified as P. Concrete number of variants is included inside each part.

Reclassification of rare variants. White colour represents the number of rare variants classified as LB. Soft grey colour represents the number of rare variants classified as VUS. Dark grey colour represents the number of rare variants classified as LP. Black colour represents the number of rare variants classified as P. Concrete number of variants is included inside each part. A total of 128 rare variants were analysed from 121 cases of IAS (CL group). In 88 cases (82.72%), the variant classification suffered a modification according to the current ACMG recommendations: 72 of the 104 cases with an IAS diagnosis (69.23%) and 16 of the 17 (94.11%) cases from the post-mortem cohort. Originally, in the post-mortem cohort, 82.23% (14 of 17) of variants were classified as LP, while after the reanalysis the same percentage was classified as VUS (14/17; 82.82%). In the IAS cohort, 63.06% (70 of 111) of the variants were initially classified as LP. However, after the reanalysis, 56.75% (63 of 111) were classified as VUS. Differences on the classification were observed also between missense and radical variants. In the 2010 classification, 49 of the 79 missense variants (62.02%) were classified as LP, while the major classification after the reanalysis was VUS (62 of 70; 78.48%). Radical variants were predominantly classified as LP in 2010 (21 of 31; 67.74%); although after the reanalysis a 58.06% of the radical variants were classified as P. The rare variants located in five genes (DES, JUP, KCNE3, LMNA, and MYH7) did not suffer any difference in final classification (Fig. 1) (Tables 3 and 4).
Table 4

Classification of rare variants in IAS subtypes.

All
Missense
Radical
DiseaseNumber Variants201020202010202020102020
BrS49LB1...1.
VUS334333.1
LP418302116
P472027
LQTS12LB......
VUS3434..
LP382711
P6.6...
CPVT4LB......
VUS.4.4..
LP4.4...
P......
ACM36LB.6.6..
VUS10161016..
LP19512174
P791.69
DCM1LB......
VUS1111..
LP......
P......
HCM8LB.1.1..
VUS4444..
LP311.21
P12..12

Note – ACM: arrhythmogenic cardiomyopathy, BrS: Brugada syndrome, CPVT: catecholaminergic polymorphic ventricular tachycardia, DCM: dilated cardiomyopathy, HCM: hypertrophic cardiomyopathy, LB: likely benign, LQTS: long QT syndrome, LP: likely pathogenic, P: pathogenic, VUS: variant of uncertain significance.

Classification of rare variants in IAS subtypes. Note – ACM: arrhythmogenic cardiomyopathy, BrS: Brugada syndrome, CPVT: catecholaminergic polymorphic ventricular tachycardia, DCM: dilated cardiomyopathy, HCM: hypertrophic cardiomyopathy, LB: likely benign, LQTS: long QT syndrome, LP: likely pathogenic, P: pathogenic, VUS: variant of uncertain significance. In 48 cases of BrS, most rare variants were originally classified as LP (41 of 49; 83.67%) but after reanalysis, most were classified as VUS (34 of 49; 69.38%). In case number 28, diagnosed with BrS, an intronic variant was originally classified as P but after reanalysis, was classified as LP. In ten cases diagnosed with LQTS, 50% (6 of 12 cases) were classified as P but almost all rare variants have been reclassified as LP (8 of 12; 66.66%). In four cases diagnosed with CPVT, all rare variants (4 of 4; 100%) were originally classified as LP but after reanalysis, the same four rare variants were classified as VUS. A total of 34 cases diagnosed with ACM were originally classified as LP (52.77%; 19 of 36), but after reanalysis, most were classified as VUS (16 of 36; 44.44%). In the one case diagnosed with DCM, the rare variant originally classified as VUS remained at the same level of pathogenicity. In seven cases diagnosed with HCM, 50% of rare variants were originally classified as VUS (4 of 8) and after reanalysis, the same percentage of VUS was maintained (Fig. 1) (Tables 1, 2 and 4).
Table 2

Modifications in classification of rare variant.

TotalTotal of ChangesPMChanges in PMCLChanges in CL
Rare Variants12892 (71,87%)1716 (94,11%)11176 (68,46%)
Cases12188 (72,72%)1716 (94,11%)10472 (69,28%)

Note – CL: clinical group, PM: post-mortem group.

Discussion

Genetic testing in patients diagnosed with IAS is highly recommended both in clinical and medico-legal settings, since death is often the first manifestation of disease [3]. However, misinterpretation of rare variant designations may lead to inaccurate genetic diagnoses and/or the adoption of unnecessary and/or inappropriate therapeutic approaches resulting in an increased morbidity and mortality. Therefore, one of the main current challenges in genetic analysis is determining the pathogenic role of rare variants. Identifying a genetic cause of IAS allows for accurate clinical diagnosis, risk stratification, adoption of personalized therapeutic measures, and early identification of relatives at risk, while also determining no genetic carriers [16]. Obtaining reliable and accountable interpretations of variant significance is as important as improving molecular diagnostic techniques, and for these reason adequate guidelines, and also a periodic update of the criteria used for interpretation and revision of the variant significances, are fundamental. In our retrospective study, we have applied current ACMG recommendations for variant classification in a cohort of patients diagnosed with IAS and post-mortem cases with suspected IAS [4]. We determined that over 70% of variants required reclassification after ten years under the updated guidelines. Specifically, after reanalysis of the variants, 69.23% of diagnosed IAS cases required a change in variant classification. In the post-mortem cohort, 94.11% required a change in variant classification. This data reinforces the need for clinical data in genetic diagnoses; a complete clinical history contributes to variant classification and helps to clarify the role of a variant in each patient. Recently, a study focused on the reclassification of VUS in IAS concluded that disease-specific phenotypes significantly increase the accuracy of classification [10]. Interestingly, we determined that many missense variants changed their classification from LP to VUS after reanalysis; this modification is mainly due to the increase of items used in ACMG recommendations. As mentioned above, increase in items implies more accuracy in classification but also stringency. In contrast, many radical variants changed from LP to P, accordingly to Harrison et al. [17] This fact suggests that variants resulting in a premature truncation of proteins and/or frameshifts should be considered highly damaging and therefore should be carefully analysed. Missense variants should be comprehensively analysed in each patient, considering all available data to perform a proper variant prioritization in a personalized clinical context [18]. Family segregation is the most robust tool to corroborate the pathogenic role of a particular variant. Unfortunately, a complete segregation for most rare variants currently associated with IAS is not available. In addition, incomplete penetrance/variable expressivity are hallmarks of IAS, so a segregation analysis of at least three generations should be recommended to obtain helpful data [19, 20]. Thus, the disease manifestation observed at the basal assessment and the clinical evolution on the follow-up, not only in the index cases but in the entire families, may also be highly useful in the understanding of the pathogenic role of the initially identified variants. Despite all the previously mentioned considerations, the frequency of rare variants in the global population is the first tool used to help to discern a potential damaging variant from other rare variants with no potential deleterious role. Nowadays, free and quick access to on-line databases focused on variant population frequencies makes this an easy routine approach. Classification of a variant as VUS or downgrading a variant status from LP to VUS does not mean that there is less pathogenic risk of IAS for any patient who carries the rare variant; ambiguous significance implies that current evidence does not back a conclusive deleterious role in IAS. Therefore, clinical translation of VUS should be performed with caution and VUS should not be discarded, at least until additional data becomes available focused on clarifying their clinical role. Current recommendations for the interpretation of rare variants [4] include more items to be considered than ten years ago [11]. This increase in items implies more accuracy in classification but also increased stringency; thus, a lack of data for some of these items leads to ambiguous classification [5]. As a consequence, a low percentage of variants classified currently as VUS confer a real of risk in IAS and most are LB [21]. To discriminate a true risk-carrying variant from a non-deleterious variant is a challenge without accurate family segregation and functional studies [7]. Expected frequencies of each IAS variant and constant update of minor allele frequencies in large global population studies should be used to help identify the genes, regions of genes, and/or types of variants strongly associated with IAS which may help to determine the roles of variants in clinical settings, particularly if they are classified as VUS [22]. At the present time, while the ACMG recommend how to classify variants, there is currently no consensus for when and how often variants should be reclassified. Therefore, reinterpretation of genetic variants occurs mainly due to a clinician's request, identification of a previously classified variant in a new patient or new data available concerning the rare variant [23]. These expectations should be explicitly delineated as part of the informed consent process before the sample is obtained and reviewed again when disclosing initial results [24]. Concerning IAS, Smith et al. reported a reclassification after one year of 3% of rare variants [25]. In 2018, a reclassification of rare variants previously considered deleterious in Brugada Syndrome was performed; only 37% were classified as P or LP following current ACMG recommendations [8]. A recent study identified a modification in 52% of rare variants classified as VUS seven years ago [10]. Therefore, the evidence supports the periodic reclassification of the rare variants in IAS despite lack of data concerning the time of re-evaluation. In our report, more than 70% of rare variants were reclassified after ten years, also supporting the necessity of re-evaluation. In the light of all this evidence, we propose that rare variants associated with IAS should be reanalysed within five years if already classified following ACMG recommendations since it seems to be adequate to manage the rapid obsolescence of genetic data interpretations. In addition, our results support further urgent reanalysis of each IAS rare variant if they were not classified originally following ACMG recommendations. The next step should be clinical translation of the re-evaluation and assessment of the implications in families because the confirmation of a variant as P, or removal of a P designation, may have a significant impact on patients and relatives. Therapeutic management can be modified but emotional and psychological impacts may have lasting effects [26]. New genetic information can lend itself to misinterpretation [5], so we recommended discussions with an expert cardiologist in genetics to explain what reclassification entails for each patient, accordingly to recent American Society of Human Genetics recommendations (ASHG) [27]. One key point is that a change in classification does not necessarily change the fact that a case has an IAS. Finally, it is important to remark that our re-information approach to families follows the ethical premise that definitive consideration for any clinical or research guideline should be improving patient medical care. We can highlight some major limitations to our study. Variant interpretation is subject to inherent intra- and inter-laboratory differences in data interpretation [28]. In the current study, three of the authors performed independent classification following ACMG recommendations and all authors came to a consensus regarding the final classification decision. All rare variants were identified after a limited analysis of genes; we cannot be sure that patients do not carry other rare variants in genes currently unassociated with IAS. Only genes currently associated with IAS were analysed. The number of cases analysed was small, so comprehensive reassessment should be performed in large cohorts of IAS samples to corroborate a periodic reclassification. Finally, lack of data for some of the rare variants, mainly concerning functional studies as well as familial segregation, impedes comprehensive interpretation of our results and definite classification. In summary, reanalysis using current ACMG recommendations showed that 71.87% of rare variants in IAS were given a new classification than originally assigned ten years ago. Many variants, however, remain of ambiguous significance. These findings emphasize the importance of cautious interpretation of variant scoring and comprehensive family segregation, supporting the periodic re-evaluation of rare variants in IAS before clinical translation. It is extremely important that in cases of significance changes after an update the geneticist promptly informs the interested patients.

Declaration of Competing Interest

The authors have no conflicts of interest to declare.
  28 in total

1.  HRS/EHRA expert consensus statement on the state of genetic testing for the channelopathies and cardiomyopathies: this document was developed as a partnership between the Heart Rhythm Society (HRS) and the European Heart Rhythm Association (EHRA).

Authors:  Michael J Ackerman; Silvia G Priori; Stephan Willems; Charles Berul; Ramon Brugada; Hugh Calkins; A John Camm; Patrick T Ellinor; Michael Gollob; Robert Hamilton; Ray E Hershberger; Daniel P Judge; Hervè Le Marec; William J McKenna; Eric Schulze-Bahr; Chris Semsarian; Jeffrey A Towbin; Hugh Watkins; Arthur Wilde; Christian Wolpert; Douglas P Zipes
Journal:  Europace       Date:  2011-08       Impact factor: 5.214

Review 2.  Settling the score: variant prioritization and Mendelian disease.

Authors:  Karen Eilbeck; Aaron Quinlan; Mark Yandell
Journal:  Nat Rev Genet       Date:  2017-08-14       Impact factor: 53.242

3.  Recommendations for interpreting the loss of function PVS1 ACMG/AMP variant criterion.

Authors:  Ahmad N Abou Tayoun; Tina Pesaran; Marina T DiStefano; Andrea Oza; Heidi L Rehm; Leslie G Biesecker; Steven M Harrison
Journal:  Hum Mutat       Date:  2018-09-07       Impact factor: 4.878

4.  Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium.

Authors:  Laura M Amendola; Gail P Jarvik; Michael C Leo; Heather M McLaughlin; Yassmine Akkari; Michelle D Amaral; Jonathan S Berg; Sawona Biswas; Kevin M Bowling; Laura K Conlin; Greg M Cooper; Michael O Dorschner; Matthew C Dulik; Arezou A Ghazani; Rajarshi Ghosh; Robert C Green; Ragan Hart; Carrie Horton; Jennifer J Johnston; Matthew S Lebo; Aleksandar Milosavljevic; Jeffrey Ou; Christine M Pak; Ronak Y Patel; Sumit Punj; Carolyn Sue Richards; Joseph Salama; Natasha T Strande; Yaping Yang; Sharon E Plon; Leslie G Biesecker; Heidi L Rehm
Journal:  Am J Hum Genet       Date:  2016-05-12       Impact factor: 11.025

5.  Physician interpretation of variants of uncertain significance.

Authors:  Sarah K Macklin; Jessica L Jackson; Paldeep S Atwal; Stephanie L Hines
Journal:  Fam Cancer       Date:  2019-01       Impact factor: 2.375

6.  ACMG recommendations for standards for interpretation and reporting of sequence variations: Revisions 2007.

Authors:  C Sue Richards; Sherri Bale; Daniel B Bellissimo; Soma Das; Wayne W Grody; Madhuri R Hegde; Elaine Lyon; Brian E Ward
Journal:  Genet Med       Date:  2008-04       Impact factor: 8.822

7.  Patient re-contact after revision of genomic test results: points to consider-a statement of the American College of Medical Genetics and Genomics (ACMG).

Authors:  Karen L David; Robert G Best; Leslie Manace Brenman; Lynn Bush; Joshua L Deignan; David Flannery; Jodi D Hoffman; Ingrid Holm; David T Miller; James O'Leary; Reed E Pyeritz
Journal:  Genet Med       Date:  2018-12-22       Impact factor: 8.822

8.  Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.

Authors:  Sue Richards; Nazneen Aziz; Sherri Bale; David Bick; Soma Das; Julie Gastier-Foster; Wayne W Grody; Madhuri Hegde; Elaine Lyon; Elaine Spector; Karl Voelkerding; Heidi L Rehm
Journal:  Genet Med       Date:  2015-03-05       Impact factor: 8.822

9.  Analysis of protein-coding genetic variation in 60,706 humans.

Authors:  Monkol Lek; Konrad J Karczewski; Eric V Minikel; Kaitlin E Samocha; Eric Banks; Timothy Fennell; Anne H O'Donnell-Luria; James S Ware; Andrew J Hill; Beryl B Cummings; Taru Tukiainen; Daniel P Birnbaum; Jack A Kosmicki; Laramie E Duncan; Karol Estrada; Fengmei Zhao; James Zou; Emma Pierce-Hoffman; Joanne Berghout; David N Cooper; Nicole Deflaux; Mark DePristo; Ron Do; Jason Flannick; Menachem Fromer; Laura Gauthier; Jackie Goldstein; Namrata Gupta; Daniel Howrigan; Adam Kiezun; Mitja I Kurki; Ami Levy Moonshine; Pradeep Natarajan; Lorena Orozco; Gina M Peloso; Ryan Poplin; Manuel A Rivas; Valentin Ruano-Rubio; Samuel A Rose; Douglas M Ruderfer; Khalid Shakir; Peter D Stenson; Christine Stevens; Brett P Thomas; Grace Tiao; Maria T Tusie-Luna; Ben Weisburd; Hong-Hee Won; Dongmei Yu; David M Altshuler; Diego Ardissino; Michael Boehnke; John Danesh; Stacey Donnelly; Roberto Elosua; Jose C Florez; Stacey B Gabriel; Gad Getz; Stephen J Glatt; Christina M Hultman; Sekar Kathiresan; Markku Laakso; Steven McCarroll; Mark I McCarthy; Dermot McGovern; Ruth McPherson; Benjamin M Neale; Aarno Palotie; Shaun M Purcell; Danish Saleheen; Jeremiah M Scharf; Pamela Sklar; Patrick F Sullivan; Jaakko Tuomilehto; Ming T Tsuang; Hugh C Watkins; James G Wilson; Mark J Daly; Daniel G MacArthur
Journal:  Nature       Date:  2016-08-18       Impact factor: 49.962

10.  Classification of Genes: Standardized Clinical Validity Assessment of Gene-Disease Associations Aids Diagnostic Exome Analysis and Reclassifications.

Authors:  Erica D Smith; Kelly Radtke; Mari Rossi; Deepali N Shinde; Sourat Darabi; Dima El-Khechen; Zöe Powis; Katherine Helbig; Kendra Waller; Dorothy K Grange; Sha Tang; Kelly D Farwell Hagman
Journal:  Hum Mutat       Date:  2017-02-13       Impact factor: 4.878

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  15 in total

1.  Rare Variants Associated with Arrhythmogenic Cardiomyopathy: Reclassification Five Years Later.

Authors:  Marta Vallverdú-Prats; Mireia Alcalde; Georgia Sarquella-Brugada; Sergi Cesar; Elena Arbelo; Anna Fernandez-Falgueras; Mónica Coll; Alexandra Pérez-Serra; Marta Puigmulé; Anna Iglesias; Victoria Fiol; Carles Ferrer-Costa; Bernat Del Olmo; Ferran Picó; Laura Lopez; Paloma Jordà; Ana García-Álvarez; Coloma Tirón de Llano; Rocío Toro; Simone Grassi; Antonio Oliva; Josep Brugada; Ramon Brugada; Oscar Campuzano
Journal:  J Pers Med       Date:  2021-02-26

2.  Overlap phenotypes of the left ventricular noncompaction and hypertrophic cardiomyopathy with complex arrhythmias and heart failure induced by the novel truncated DSC2 mutation.

Authors:  Yubi Lin; Jiana Huang; Zhiling Zhu; Zuoquan Zhang; Jianzhong Xian; Zhe Yang; Tingfeng Qin; Linxi Chen; Jingmin Huang; Yin Huang; Qiaoyun Wu; Zhenyu Hu; Xiufang Lin; Geyang Xu
Journal:  Orphanet J Rare Dis       Date:  2021-11-24       Impact factor: 4.123

3.  Discerning the Ambiguous Role of Missense TTN Variants in Inherited Arrhythmogenic Syndromes.

Authors:  Estefanía Martínez-Barrios; Georgia Sarquella-Brugada; Alexandra Pérez-Serra; Anna Fernández-Falgueras; Sergi Cesar; Mónica Coll; Marta Puigmulé; Anna Iglesias; Mireia Alcalde; Marta Vallverdú-Prats; Carles Ferrer-Costa; Bernat Del Olmo; Ferran Picó; Laura López; Victoria Fiol; José Cruzalegui; Clara Hernández; Elena Arbelo; Simone Grassi; Antonio Oliva; Rocío Toro; Josep Brugada; Ramon Brugada; Oscar Campuzano
Journal:  J Pers Med       Date:  2022-02-08

4.  Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes.

Authors:  Julia K Goodrich; Moriel Singer-Berk; Rachel Son; Abigail Sveden; Jordan Wood; Eleina England; Joanne B Cole; Ben Weisburd; Nick Watts; Lizz Caulkins; Peter Dornbos; Ryan Koesterer; Zachary Zappala; Haichen Zhang; Kristin A Maloney; Andy Dahl; Carlos A Aguilar-Salinas; Gil Atzmon; Francisco Barajas-Olmos; Nir Barzilai; John Blangero; Eric Boerwinkle; Lori L Bonnycastle; Erwin Bottinger; Donald W Bowden; Federico Centeno-Cruz; John C Chambers; Nathalie Chami; Edmund Chan; Juliana Chan; Ching-Yu Cheng; Yoon Shin Cho; Cecilia Contreras-Cubas; Emilio Córdova; Adolfo Correa; Ralph A DeFronzo; Ravindranath Duggirala; Josée Dupuis; Ma Eugenia Garay-Sevilla; Humberto García-Ortiz; Christian Gieger; Benjamin Glaser; Clicerio González-Villalpando; Ma Elena Gonzalez; Niels Grarup; Leif Groop; Myron Gross; Christopher Haiman; Sohee Han; Craig L Hanis; Torben Hansen; Nancy L Heard-Costa; Brian E Henderson; Juan Manuel Malacara Hernandez; Mi Yeong Hwang; Sergio Islas-Andrade; Marit E Jørgensen; Hyun Min Kang; Bong-Jo Kim; Young Jin Kim; Heikki A Koistinen; Jaspal Singh Kooner; Johanna Kuusisto; Soo-Heon Kwak; Markku Laakso; Leslie Lange; Jong-Young Lee; Juyoung Lee; Donna M Lehman; Allan Linneberg; Jianjun Liu; Ruth J F Loos; Valeriya Lyssenko; Ronald C W Ma; Angélica Martínez-Hernández; James B Meigs; Thomas Meitinger; Elvia Mendoza-Caamal; Karen L Mohlke; Andrew D Morris; Alanna C Morrison; Maggie C Y Ng; Peter M Nilsson; Christopher J O'Donnell; Lorena Orozco; Colin N A Palmer; Kyong Soo Park; Wendy S Post; Oluf Pedersen; Michael Preuss; Bruce M Psaty; Alexander P Reiner; Cristina Revilla-Monsalve; Stephen S Rich; Jerome I Rotter; Danish Saleheen; Claudia Schurmann; Xueling Sim; Rob Sladek; Kerrin S Small; Wing Yee So; Timothy D Spector; Konstantin Strauch; Tim M Strom; E Shyong Tai; Claudia H T Tam; Yik Ying Teo; Farook Thameem; Brian Tomlinson; Russell P Tracy; Tiinamaija Tuomi; Jaakko Tuomilehto; Teresa Tusié-Luna; Rob M van Dam; Ramachandran S Vasan; James G Wilson; Daniel R Witte; Tien-Yin Wong; Noël P Burtt; Noah Zaitlen; Mark I McCarthy; Michael Boehnke; Toni I Pollin; Jason Flannick; Josep M Mercader; Anne O'Donnell-Luria; Samantha Baxter; Jose C Florez; Daniel G MacArthur; Miriam S Udler
Journal:  Nat Commun       Date:  2021-06-09       Impact factor: 17.694

Review 5.  Genetic Variants as Sudden-Death Risk Markers in Inherited Arrhythmogenic Syndromes: Personalized Genetic Interpretation.

Authors:  Oscar Campuzano; Georgia Sarquella-Brugada; Elena Arbelo; Sergi Cesar; Paloma Jordà; Alexandra Pérez-Serra; Rocío Toro; Josep Brugada; Ramon Brugada
Journal:  J Clin Med       Date:  2020-06-15       Impact factor: 4.241

6.  Too much sugar leaves a sour taste: A cardiac disease caused by excess glycogen deposit.

Authors:  Back Sternick Eduardo
Journal:  EBioMedicine       Date:  2020-04-24       Impact factor: 8.143

Review 7.  Update on Genetic Basis of Brugada Syndrome: Monogenic, Polygenic or Oligogenic?

Authors:  Oscar Campuzano; Georgia Sarquella-Brugada; Sergi Cesar; Elena Arbelo; Josep Brugada; Ramon Brugada
Journal:  Int J Mol Sci       Date:  2020-09-28       Impact factor: 5.923

8.  Sudden Death without a Clear Cause after Comprehensive Investigation: An Example of Forensic Approach to Atypical/Uncertain Findings.

Authors:  Simone Grassi; Mònica Coll Vidal; Oscar Campuzano; Vincenzo Arena; Alessandro Alfonsetti; Sabina Strano Rossi; Francesca Scarnicci; Anna Iglesias; Ramon Brugada; Antonio Oliva
Journal:  Diagnostics (Basel)       Date:  2021-05-17

Review 9.  Clinical Genetics of Inherited Arrhythmogenic Disease in the Pediatric Population.

Authors:  Estefanía Martínez-Barrios; Sergi Cesar; José Cruzalegui; Clara Hernandez; Elena Arbelo; Victoria Fiol; Josep Brugada; Ramon Brugada; Oscar Campuzano; Georgia Sarquella-Brugada
Journal:  Biomedicines       Date:  2022-01-05

10.  Genetic variants associated with inherited cardiovascular disorders among 13,131 asymptomatic older adults of European descent.

Authors:  Ingrid Winship; Eric Schadt; John J McNeil; Paul Lacaze; Robert Sebra; Moeen Riaz; Jodie Ingles; Jane Tiller; Bryony A Thompson; Paul A James; Diane Fatkin; Christopher Semsarian; Christopher M Reid; Andrew M Tonkin
Journal:  NPJ Genom Med       Date:  2021-06-16       Impact factor: 8.617

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