Michael Zech1, Sylvia Boesch2, Matej Škorvánek3, Ján Necpál4, Jana Švantnerová5, Matias Wagner6, Yasemin Dincer7, Ariane Sadr-Nabavi8, Tereza Serranová9, Irena Rektorová10, Petra Havránková9, Shahzaman Ganai9, Alexandra Mosejová3, Iva Příhodová9, Jana Šarláková11, Kristína Kulcsarová3, Olga Ulmanová9, Karel Bechyně12, Miriam Ostrozovičová3, Vladimír Haň3, Joaquim Ribeiro Ventosa3, Mohammad Shariati13, Ali Shoeibi14, Sandrina Weber15, Brit Mollenhauer16, Claudia Trenkwalder16, Riccardo Berutti6, Tim M Strom17, Andres Ceballos-Baumann18, Volker Mall19, Bernhard Haslinger20, Robert Jech9, Juliane Winkelmann21. 1. Institute of Neurogenomics, Helmholtz Zentrum München, Munich, Germany; Institute of Human Genetics, Technical University of Munich, Munich, Germany. Electronic address: michael.zech@mri.tum.de. 2. Department of Neurology, Medical University Innsbruck, Innsbruck, Austria. 3. Department of Neurology, P.J. Safarik University, Kosice, Slovak Republic; Department of Neurology, University Hospital of L. Pasteur, Kosice, Slovak Republic. 4. Department of Neurology, Zvolen Hospital, Slovakia. 5. Second Department of Neurology, Faculty of Medicine, Comenius University, University Hospital Bratislava, Bratislava, Slovakia. 6. Institute of Neurogenomics, Helmholtz Zentrum München, Munich, Germany; Institute of Human Genetics, Technical University of Munich, Munich, Germany. 7. Lehrstuhl für Sozialpädiatrie, Technische Universität München, Munich, Germany; Zentrum für Humangenetik und Laboratoriumsdiagnostik (MVZ), Martinsried, Germany. 8. Department of Medical Genetics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran; Department of Neurology, Faculty of Medicine, Mashhad University of Medical Sciences, Qaem Medical Center, Mashhad, Iran; Academic Center for Education, Culture and Research (ACECR)-Khorasan Razavi, Mashhad, Iran. 9. Department of Neurology, Charles University, 1st Faculty of Medicine and General University Hospital in Prague, Prague, Czech Republic. 10. First Department of Neurology, Faculty of Medicine, St. Anne's University Hospital and CEITEC, Masaryk University, Brno, Czech Republic. 11. Department of Neurology, University Hospital Hradec Kralove, Hradec Králové, Czech Republic. 12. Department of Neurology, Hospital Písek, Písek, Czech Republic. 13. Department of Neurology, Faculty of Medicine, Mashhad University of Medical Sciences, Qaem Medical Center, Mashhad, Iran; Academic Center for Education, Culture and Research (ACECR)-Khorasan Razavi, Mashhad, Iran. 14. Department of Neurology, Faculty of Medicine, Mashhad University of Medical Sciences, Qaem Medical Center, Mashhad, Iran. 15. Institute of Neurogenomics, Helmholtz Zentrum München, Munich, Germany; Paracelsus-Elena-Klinik, Kassel, Germany. 16. Paracelsus-Elena-Klinik, Kassel, Germany; Institute of Neuropathology and Department of Neurosurgery, University Medical Center Göttingen, Göttingen, Germany. 17. Institute of Human Genetics, Technical University of Munich, Munich, Germany. 18. Schön Klinik München Schwabing, Munich, Germany. 19. Lehrstuhl für Sozialpädiatrie, Technische Universität München, Munich, Germany; Kbo-Kinderzentrum München, Munich, Germany. 20. Klinik und Poliklinik für Neurologie, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany. 21. Institute of Neurogenomics, Helmholtz Zentrum München, Munich, Germany; Institute of Human Genetics, Technical University of Munich, Munich, Germany; Lehrstuhl für Neurogenetik, Technische Universität München, Munich, Germany; Munich Cluster for Systems Neurology, SyNergy, Munich, Germany.
Abstract
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.
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.