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Erschienen in:
01.08.2016 | Original Research Article
Semiconductor Whole Exome Sequencing for the Identification of Genetic Variants in Colombian Patients Clinically Diagnosed with Long QT Syndrome
Erschienen in: Molecular Diagnosis & Therapy | Ausgabe 4/2016
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Background and Objective
Inherited long QT syndrome (LQTS) is a cardiac channelopathy characterized by a prolongation of QT interval and the risk of syncope, cardiac arrest, and sudden cardiac death. Genetic diagnosis of LQTS is critical in medical practice as results can guide adequate management of patients and distinguish phenocopies such as catecholaminergic polymorphic ventricular tachycardia (CPVT). However, extensive screening of large genomic regions is required in order to reliably identify genetic causes. Semiconductor whole exome sequencing (WES) is a promising approach for the identification of variants in the coding regions of most human genes.
Methods
DNA samples from 21 Colombian patients clinically diagnosed with LQTS were enriched for coding regions using multiplex polymerase chain reaction (PCR) and subjected to WES using a semiconductor sequencer.
Results
Semiconductor WES showed mean coverage of 93.6 % for all coding regions relevant to LQTS at >10× depth with high intra- and inter-assay depth heterogeneity. Fifteen variants were detected in 12 patients in genes associated with LQTS. Three variants were identified in three patients in genes associated with CPVT. Co-segregation analysis was performed when possible. All variants were analyzed with two pathogenicity prediction algorithms. The overall prevalence of LQTS and CPVT variants in our cohort was 71.4 %. All LQTS variants previously identified through commercial genetic testing were identified.
Conclusion
Standardized WES assays can be easily implemented, often at a lower cost than sequencing panels. Our results show that WES can identify LQTS-causing mutations and permits differential diagnosis of related conditions in a real-world clinical setting. However, high heterogeneity in sequencing depth and low coverage in the most relevant genes is expected to be associated with reduced analytical sensitivity.