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Scoring Algorithm-Based Genomic Testing in Dystonia: A Prospective Validation Study
M. Zech, R. Jech, S. Boesch, M. Škorvánek, J. Necpál, J. Švantnerová, M. Wagner, A. Sadr-Nabavi, F. Distelmaier, M. Krenn, T. Serranová, I. Rektorová, P. Havránková, A. Mosejová, I. Příhodová, J. Šarláková, K. Kulcsarová, O. Ulmanová, K. Bechyně,...
Language English Country United States
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
33949708
DOI
10.1002/mds.28614
Knihovny.cz E-resources
- MeSH
- Algorithms MeSH
- Dystonic Disorders * genetics MeSH
- Dystonia * diagnosis genetics MeSH
- Genetic Testing MeSH
- Humans MeSH
- Parkinson Disease * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
BACKGROUND: Despite the established value of genomic testing strategies, practice guidelines for their use do not exist in many indications. OBJECTIVES: We sought to validate a recently introduced scoring algorithm for dystonia, predicting the diagnostic utility of whole-exome sequencing (WES) based on individual phenotypic aspects (age-at-onset, body distribution, presenting comorbidity). METHODS: We prospectively enrolled a set of 209 dystonia-affected families and obtained summary scores (0-5 points) according to the algorithm. Singleton (N = 146), duo (N = 11), and trio (N = 52) WES data were generated to identify genetic diagnoses. RESULTS: Diagnostic yield was highest (51%) among individuals with a summary score of 5, corresponding to a manifestation of early-onset segmental or generalized dystonia with coexisting non-movement disorder-related neurological symptoms. Sensitivity and specificity at the previously suggested threshold for implementation of WES (3 points) was 96% and 52%, with area under the curve of 0.81. CONCLUSIONS: The algorithm is a useful predictive tool and could be integrated into dystonia routine diagnostic protocols. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society.
Academic Center for Education Culture and Research Khorasan Razavi Mashhad Iran
Department of Neurology Ludwig Maximilians University Munich Germany
Department of Neurology Medical University Innsbruck Innsbruck Austria
Department of Neurology Medical University of Vienna Vienna Austria
Department of Neurology P J Safarik University Kosice Slovak Republic
Department of Neurology University Hospital Hradec Kralove Czech Republic
Department of Neurology University Hospital of L Pasteur Kosice Slovak Republic
Department of Neurology Zvolen Hospital Zvolen Slovakia
Department of Pediatrics Medical University Innsbruck Innsbruck Austria
Hospital Písek Písek Czech Republic
Institute of Human Genetics Technical University of Munich Munich Germany
Institute of Neurogenomics Helmholtz Zentrum München Munich Germany
kbo Kinderzentrum München Munich Germany
Klinik für Neurologie Asklepios Fachklinikum Stadtroda Stadtroda Germany
Lehrstuhl für Neurogenetik Technische Universität München Munich Germany
Lehrstuhl für Sozialpädiatrie Technische Universität München Munich Germany
References provided by Crossref.org
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