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      Genetic complexity in hypertrophic cardiomyopathy revealed by high-throughput sequencing

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          Abstract

          Background

          Clinical interpretation of the large number of rare variants identified by high throughput sequencing (HTS) technologies is challenging. The aim of this study was to explore the clinical implications of a HTS strategy for patients with hypertrophic cardiomyopathy (HCM) using a targeted HTS methodology and workflow developed for patients with a range of inherited cardiovascular diseases. By comparing the sequencing results with published findings and with sequence data from a large-scale exome sequencing screen of UK individuals, we sought to quantify the strength of the evidence supporting causality for detected candidate variants.

          Methods and results

          223 unrelated patients with HCM (46±15 years at diagnosis, 74% males) were studied. In order to analyse coding, intronic and regulatory regions of 41 cardiovascular genes, we used solution-based sequence capture followed by massive parallel resequencing on Illumina GAIIx. Average read-depth in the 2.1 Mb target region was 120. Rare (frequency<0.5%) non-synonymous, loss-of-function and splice-site variants were defined as candidates. Excluding titin, we identified 152 distinct candidate variants in sarcomeric or associated genes (89 novel) in 143 patients (64%). Four sarcomeric genes ( MYH7, MYBPC3, TNNI3, TNNT2) showed an excess of rare single non-synonymous single-nucleotide polymorphisms (nsSNPs) in cases compared to controls. The estimated probability that a nsSNP in these genes is pathogenic varied between 57% and near certainty depending on the location. We detected an additional 94 candidate variants (73 novel) in desmosomal, and ion-channel genes in 96 patients (43%).

          Conclusions

          This study provides the first large-scale quantitative analysis of the prevalence of sarcomere protein gene variants in patients with HCM using HTS technology. Inclusion of other genes implicated in inherited cardiac disease identifies a large number of non-synonymous rare variants of unknown clinical significance.

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          Most cited references 56

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          Hypertrophic cardiomyopathy: distribution of disease genes, spectrum of mutations, and implications for a molecular diagnosis strategy.

          Hypertrophic cardiomyopathy is an autosomal-dominant disorder in which 10 genes and numerous mutations have been reported. The aim of the present study was to perform a systematic screening of these genes in a large population, to evaluate the distribution of the disease genes, and to determine the best molecular strategy in clinical practice. The entire coding sequences of 9 genes (MYH7, MYBPC3, TNNI3, TNNT2, MYL2, MYL3, TPM1, ACTC, andTNNC1) were analyzed in 197 unrelated index cases with familial or sporadic hypertrophic cardiomyopathy. Disease-causing mutations were identified in 124 index patients ( approximately 63%), and 97 different mutations, including 60 novel ones, were identified. The cardiac myosin-binding protein C (MYBPC3) and beta-myosin heavy chain (MYH7) genes accounted for 82% of families with identified mutations (42% and 40%, respectively). Distribution of the genes varied according to the prognosis (P=0.036). Moreover, a mutation was found in 15 of 25 index cases with "sporadic" hypertrophic cardiomyopathy (60%). Finally, 6 families had patients with more than one mutation, and phenotype analyses suggested a gene dose effect in these compound-heterozygous, double-heterozygous, or homozygous patients. These results might have implications for genetic diagnosis strategy and, subsequently, for genetic counseling. First, on the basis of this experience, the screening of already known mutations is not helpful. The analysis should start by testing MYBPC3 and MYH7 and then focus on TNNI3, TNNT2, and MYL2. Second, in particularly severe phenotypes, several mutations should be searched. Finally, sporadic cases can be successfully screened.
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            dbSNP: a database of single nucleotide polymorphisms.

            In response to a need for a general catalog of genome variation to address the large-scale sampling designs required by association studies, gene mapping and evolutionary biology, the National Cancer for Biotechnology Information (NCBI) has established the dbSNP database. Submissions to dbSNP will be integrated with other sources of information at NCBI such as GenBank, PubMed, LocusLink and the Human Genome Project data. The complete contents of dbSNP are available to the public at website: http://www.ncbi.nlm.nih.gov/SNP. Submitted SNPs can also be downloaded via anonymous FTP at ftp://ncbi.nlm.nih.gov/snp/
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              A rare variant in MYH6 is associated with high risk of sick sinus syndrome.

              Through complementary application of SNP genotyping, whole-genome sequencing and imputation in 38,384 Icelanders, we have discovered a previously unidentified sick sinus syndrome susceptibility gene, MYH6, encoding the alpha heavy chain subunit of cardiac myosin. A missense variant in this gene, c.2161C>T, results in the conceptual amino acid substitution p.Arg721Trp, has an allelic frequency of 0.38% in Icelanders and associates with sick sinus syndrome with an odds ratio = 12.53 and P = 1.5 × 10⁻²⁹. We show that the lifetime risk of being diagnosed with sick sinus syndrome is around 6% for non-carriers of c.2161C>T but is approximately 50% for carriers of the c.2161C>T variant.
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                Author and article information

                Journal
                J Med Genet
                J. Med. Genet
                jmedgenet
                jmg
                Journal of Medical Genetics
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                0022-2593
                1468-6244
                April 2013
                8 February 2013
                : 50
                : 4
                : 228-239
                Affiliations
                [1 ]UCL Institute of Cardiovascular Science , London, UK
                [2 ]Department of Molecular Haematology and Cancer Biology, UCL Genomics , UCL Institute of Child Health , London, UK
                [3 ]UCL Genetics Institute , London, UK
                [4 ]www.uk10.k.org
                Author notes
                [Correspondence to ] Prof. Perry Elliott, The Heart Hospital, 16-18 Westmoreland Street, London W1G 8PH, UK; perry.elliott@ 123456ucl.ac.uk

                LRL and AZ contributed equally to this paper and are join first authors

                Article
                jmedgenet-2012-101270
                10.1136/jmedgenet-2012-101270
                3607113
                23396983
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/3.0/ and http://creativecommons.org/licenses/by-nc/3.0/legalcode

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                1506
                Genotype-Phenotype Correlations
                Original article
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                Genetics

                hypertrophic cardiomyopathy, genetics, high-throughput sequencing

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