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Clinically relevant copy-number variants in exome sequencing data of patients with dystonia
M. Zech, S. Boesch, M. Škorvánek, J. Necpál, J. Švantnerová, M. Wagner, Y. Dincer, A. Sadr-Nabavi, T. Serranová, I. Rektorová, P. Havránková, S. Ganai, A. Mosejová, I. Příhodová, J. Šarláková, K. Kulcsarová, O. Ulmanová, K. Bechyně, M....
Jazyk angličtina Země Velká Británie
Typ dokumentu časopisecké články, práce podpořená grantem
- MeSH
- dospělí MeSH
- dystonické poruchy diagnóza genetika MeSH
- dystonie diagnóza genetika MeSH
- kohortové studie MeSH
- lidé MeSH
- sekvenování exomu * MeSH
- variabilita počtu kopií segmentů DNA * genetika MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
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.
Academic Center for Education Culture and Research Khorasan Razavi Mashhad Iran
Department of Neurology Hospital Písek Písek Czech Republic
Department of Neurology Medical University Innsbruck Innsbruck Austria
Department of Neurology P J Safarik University Kosice Slovak Republic
Department of Neurology University Hospital Hradec Kralove Hradec Králové Czech Republic
Department of Neurology University Hospital of L Pasteur Kosice Slovak Republic
Department of Neurology Zvolen Hospital Slovakia
Institute of Human Genetics Technical University of Munich Munich Germany
Institute of Neurogenomics Helmholtz Zentrum München Munich Germany
Kbo Kinderzentrum München Munich Germany
Lehrstuhl für Neurogenetik Technische Universität München Munich Germany
Lehrstuhl für Sozialpädiatrie Technische Universität München Munich Germany
Munich Cluster for Systems Neurology SyNergy Munich Germany
Paracelsus Elena Klinik Kassel Germany
Schön Klinik München Schwabing Munich Germany
Zentrum für Humangenetik und Laboratoriumsdiagnostik Martinsried Germany
Citace poskytuje Crossref.org
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- $a Zech, Michael $u 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
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- $a 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.
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