124 The Use of Next Generation Sequencing to Determine Genotype-Phenotype Correlations in Dilated Cardiomyopathy. (3rd June 2016)

• Record Type: Journal Article
• Authors: Wicks, Eleanor; Proven, Andrew; Syrris, Petros; Elliott, Perry
• Is Part Of: Heart. Volume 102(2016)Supplement 6
• Page Start: A87
• Page End: A88
• Publication Date: 2016-06-03
• Subjects: dilated cardiomyopathy -- next generation sequencing -- genetics; Heart -- Diseases -- Treatment -- Periodicals; Cardiology -- Periodicals; 616.12
• DOI: 10.1136/heartjnl-2016-309890.124
• Languages: English
• ISSNs: 1355-6037

Abstract

Abstract : Background: Dilated cardiomyopathy (DCM) is the leading cause of non-ischaemic heart failure. It causes approximately 10, 000 deaths in Europe per year. Studies suggest that up to 50% of patients with DCM have a genetic predisposition and that mutations within one of 40 genes coding for structural and functional cardiac proteins accounts for up to 40% of familial disease. The relevance of genotype to clinical phenotype, treatment and prognosis is poorly understood. This study aimed to clinically and genetically characterise probands with familial DCM using next-generation sequencing technology (NGS) to determine specific genotype-phenotype correlations in DCM. Methods: 72 probands with DCM were consecutively recruited into this study within our centre. All received pre-test genetic counselling and provided written informed consent. All patients were clinically characterised using a standard phenotyping protocol. Genomic data isolated from peripheral blood lymphocytes using standardised protocols, was collected and screened for all major genes involved in cardiomyopathies and selected candidate genes using NGS. Eighty-six genes with 1528 exons representing 500kb of coding sequence, were studied using target enrichment methods (Agilent SureSelect System) followed by sequencing on the Illumina HiSeq 2000 platform. Clinical parameters were correlated with genotype findings. Results: Variant calling from 72 probands (male 54%, age 41 years (mean 40.7, range 14 to 68 years) generated 1415 exonic and splice-site calls. After filtering, 420 distinct candidate variants were reported, 253 of which were published pathogenic mutations, 112 of which were frameshift insertion/deletion or splice-site variants predicted to cause loss of function (thus likely to be pathogenic). A further 55 novel variants were considered potentially pathogenic on the basis of preliminary in silico analysis. Each proband, on average, carried 3 published pathogenic variants which included known mutations associated with DCM and other forms of cardiomyopathy. Up to two further variants predicted to be pathogenic were identified per DCM proband illustrating genetic heterogeneity. However, there was no simple correlation between a specific mutation or the number of mutations and the clinical phenotype. Moreover, there was no evidence of a 'poly-hit' theory of multiple mutations contributing to a worsened phenotype nor of specific variant demonstrating causality of phenotype suggesting that genotype-phenotype correlations in DCM are complex and may be influenced by both genetic and epigenetic factors. Conclusion: This study demonstrates the exciting potential for utilisation of next generation sequencing in routine clinical practice. However it highlights the genetic heterogeneity and high frequency of novel variants with uncertain effects on gene function in DCM. This presents considerable challenges for clinical interpretation. Large-scale phenotyping is therefore required to fully understand genotype-phenotype relations in DCM.