Clinically relevant copy-number variants in exome sequencing data of patients with dystonia.

INTRODUCTION

Next-generation sequencing is now used on a routine basis for molecular testing but studies on copy-number variant (CNV) detection from next-generation sequencing data are underrepresented. Utilizing an existing whole-exome sequencing (WES) dataset, we sought to investigate the contribution of rare CNVs to the genetic causality of dystonia.

METHODS

The CNV read-depth analysis tool ExomeDepth was applied to the exome sequences of 953 unrelated patients with dystonia (600 with isolated dystonia and 353 with combined dystonia; 33% with additional neurological involvement). We prioritized rare CNVs that affected known disease genes and/or were known to be associated with defined microdeletion/microduplication syndromes. Pathogenicity assessment of CNVs was based on recently published standards of the American College of Medical Genetics and Genomics and the Clinical Genome Resource.

RESULTS

We identified pathogenic or likely pathogenic CNVs in 14 of 953 patients (1.5%). Of the 14 different CNVs, 12 were deletions and 2 were duplications, ranging in predicted size from 124bp to 17 Mb. Within the deletion intervals, BRPF1, CHD8, DJ1, EFTUD2, FGF14, GCH1, PANK2, SGCE, UBE3A, VPS16, WARS2, and WDR45 were determined as the most clinically relevant genes. The duplications involved chromosomal regions 6q21-q22 and 15q11-q13. CNV analysis increased the diagnostic yield in the total cohort from 18.4% to 19.8%, as compared to the assessment of single-nucleotide variants and small insertions and deletions alone.

CONCLUSIONS

WES-based CNV analysis in dystonia is feasible, increases the diagnostic yield, and should be combined with the assessment of single-nucleotide variants and small insertions and deletions.