The role of copy-number variants (CNV) as a cause of hypertrophic cardiomyopathy (HCM) is poorly studied. The aim of this study was to use high-throughput sequence (HTS) data combined with a read-dept Show more
The role of copy-number variants (CNV) as a cause of hypertrophic cardiomyopathy (HCM) is poorly studied. The aim of this study was to use high-throughput sequence (HTS) data combined with a read-depth strategy, to screen for CNV in cardiomyopathy-associated genes in a large consecutive cohort of HCM patients. Five-hundred-and-five unrelated HCM patients were genotyped using a HTS approach for 41 cardiovascular genes. We used a previously validated read-depth strategy (ExomeDepth) to call CNVs from the short-read sequence data. Detected CNVs in 19 cardiomyopathy-associated genes were then validated by comparative genomic hybridization array. Twelve CNVs were identified. Four CNVs in 4 patients (0.8% of the cohort) were validated: one large deletion in MYBPC3, one large deletion in PDLIM3, one duplication of the entire TNNT2 gene and one large duplication in LMNA. Our data suggest that the proportion of HCM cases with pathogenic CNVs is small (<1%). For the small subset of patients with clearly interpretable CNVs, our findings have direct clinical implications. Short read sequence data can be used for CNV calling, but the high false positive rate requires a validation step. The two-step strategy described here is effective at identifying novel genetic causes of HCM and similar techniques should be applied whenever possible. Show less
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 Show more
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. 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%). 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. Show less