CNV Detection from Targeted Next-Generation Panel Sequencing Data Increases the Diagnostic Yield in Patients with Neuromuscular Diseases

Background/Purpose: Gene dosage abnormalities account for a significant proportion of pathogenic mutations in rare genetic disease related genes tested in DNA diagnostic laboratories.

Methods: We developed a bioinformatics method to detect exonic CNVs using read depth data derived from targeted NGS panels.

Results: Within routine diagnostics, we analyzed a total of 434 patients indicated to have neuromuscular diseases for SNVs and CNVs. In 35 (10.2%) of these patients, we found pathogenic single nucleotide variants (class 4, 5) which are causative for the disease. Further analysis with our CNV pipeline increased this diagnostic yield to 52 (15.2%). Furthermore, eight CNVs were detected in genes with a recessive mode of inheritance where previously no heterozygous pathogenic SNV was found.

Conclusion: NGS data are a suitable data source for the simultaneous detection of SNVs and CNVs for clinical diagnosis. We were able to increase the diagnostic yield with the analysis of our CNV pipeline.