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J Clin Lab Anal. 2018 Feb;32(2). doi: 10.1002/jcla.22254. Epub 2017 Jun 8.

Analysis of selected genes associated with cardiomyopathy by next-generation sequencing.

Author information

1
Department of Biology, Faculty of Humanities and Natural Sciences, University of Presov, Presov, Slovakia.
2
Cardiocentre, Faculty Hospital of J.A. Reiman, Presov, Slovakia.
3
Center of Languages and Cultures of National Minorities, University of Presov, Presov, Slovakia.

Abstract

BACKGROUND:

As the leading cause of congestive heart failure, cardiomyopathy represents a heterogenous group of heart muscle disorders. Despite considerable progress being made in the genetic diagnosis of cardiomyopathy by detection of the mutations in the most prevalent cardiomyopathy genes, the cause remains unsolved in many patients. High-throughput mutation screening in the disease genes for cardiomyopathy is now possible because of using target enrichment followed by next-generation sequencing. The aim of the study was to analyze a panel of genes associated with dilated or hypertrophic cardiomyopathy based on previously published results in order to identify the subjects at risk.

METHODS:

The method of next-generation sequencing by IlluminaHiSeq 2500 platform was used to detect sequence variants in 16 individuals diagnosed with dilated or hypertrophic cardiomyopathy. Detected variants were filtered and the functional impact of amino acid changes was predicted by computational programs.

RESULTS:

DNA samples of the 16 patients were analyzed by whole exome sequencing. We identified six nonsynonymous variants that were shown to be pathogenic in all used prediction softwares: rs3744998 (EPG5), rs11551768 (MGME1), rs148374985 (MURC), rs78461695 (PLEC), rs17158558 (RET) and rs2295190 (SYNE1). Two of the analyzed sequence variants had minor allele frequency (MAF)<0.01: rs148374985 (MURC), rs34580776 (MYBPC3).

CONCLUSION:

Our data support the potential role of the detected variants in pathogenesis of dilated or hypertrophic cardiomyopathy; however, the possibility that these variants might not be true disease-causing variants but are susceptibility alleles that require additional mutations or injury to cause the clinical phenotype of disease must be considered.

KEYWORDS:

bioinformatic analysis; cardiomyopathies; next-generation sequencing; panel of genes; pathogenic variants

PMID:
28594148
DOI:
10.1002/jcla.22254
[Indexed for MEDLINE]

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