A Next-Generation Sequencing Approach to Identify Gene Mutations in Early- and Late-Onset Hypertrophic Cardiomyopathy Patients of an Italian Cohort

Int J Mol Sci. 2016 Jul 30;17(8):1239. doi: 10.3390/ijms17081239.

Abstract

Sequencing of sarcomere protein genes in patients fulfilling the clinical diagnostic criteria for hypertrophic cardiomyopathy (HCM) identifies a disease-causing mutation in 35% to 60% of cases. Age at diagnosis and family history may increase the yield of mutations screening. In order to assess whether Next-Generation Sequencing (NGS) may fulfil the molecular diagnostic needs in HCM, we included 17 HCM-related genes in a sequencing panel run on PGM IonTorrent. We selected 70 HCM patients, 35 with early (≤25 years) and 35 with late (≥65 years) diagnosis of disease onset. All samples had a 98.6% average of target regions, with coverage higher than 20× (mean coverage 620×). We identified 41 different mutations (seven of them novel) in nine genes: MYBPC3 (17/41 = 41%); MYH7 (10/41 = 24%); TNNT2, CAV3 and MYH6 (3/41 = 7.5% each); TNNI3 (2/41 = 5%); GLA, MYL2, and MYL3 (1/41=2.5% each). Mutation detection rate was 30/35 (85.7%) in early-onset and 8/35 (22.9%) in late-onset HCM patients, respectively (p < 0.0001). The overall detection rate for patients with positive family history was 84%, and 90.5% in patients with early disease onset. In our study NGS revealed higher mutations yield in patients with early onset and with a family history of HCM. Appropriate patient selection can increase the yield of genetic testing and make diagnostic testing cost-effective.

Keywords: gene variants; genetics; hypertrophic cardiomyopathy; next-generation sequencing.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Age of Onset
  • Aged
  • Biomarkers / analysis*
  • Cardiomyopathy, Hypertrophic / diagnosis*
  • Cardiomyopathy, Hypertrophic / epidemiology
  • Cardiomyopathy, Hypertrophic / genetics*
  • Cohort Studies
  • Female
  • Genetic Testing
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Italy / epidemiology
  • Male
  • Middle Aged
  • Mutation / genetics*

Substances

  • Biomarkers