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

Viktoria Szabadosova1, Iveta Boronova1, Peter Ferenc1

  • 1Department of Biology, Faculty of Humanities and Natural Sciences, University of Presov, Presov, Slovakia.

Journal of Clinical Laboratory Analysis
|June 9, 2017
PubMed

Insights

Genetic analysis identified potential disease-causing variants in cardiomyopathy patients. Further research is needed to confirm their role in dilated or hypertrophic cardiomyopathy development.

Area of Science:

  • Cardiology
  • Genetics
  • Molecular Biology

Background:

  • Cardiomyopathy is a diverse group of heart muscle disorders and a leading cause of heart failure.
  • Genetic diagnosis of cardiomyopathy has advanced, but the cause remains unknown in many cases.
  • High-throughput sequencing enables efficient screening of cardiomyopathy-associated genes.

Purpose of the Study:

  • To analyze a panel of genes linked to dilated or hypertrophic cardiomyopathy.
  • To identify individuals at risk by detecting genetic variants.
  • To investigate the genetic underpinnings of cardiomyopathy in affected patients.

Main Methods:

  • Next-generation sequencing (Illumina HiSeq 2500) was employed to analyze DNA samples.
  • Whole exome sequencing was performed on 16 individuals diagnosed with cardiomyopathy.
  • Detected variants were filtered, and their functional impact was computationally predicted.

Main Results:

  • Six nonsynonymous pathogenic variants were identified: rs3744998 (EPG5), rs11551768 (MGME1), rs148374985 (MURC), rs78461695 (PLEC), rs17158558 (RET), and rs2295190 (SYNE1).
  • Two variants, rs148374985 (MURC) and rs34580776 (MYBPC3), had a minor allele frequency (MAF) < 0.01.
  • These findings highlight potential genetic contributors to cardiomyopathy.

Conclusions:

  • The detected variants may play a role in the pathogenesis of dilated or hypertrophic cardiomyopathy.
  • Further investigation is required to determine if these variants are true disease-causing mutations or susceptibility alleles.
  • Additional factors may be necessary for these variants to manifest the clinical phenotype of cardiomyopathy.
Abstract

Keywords:
bioinformatic analysiscardiomyopathiesnext-generation sequencingpanel of genespathogenic variants

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