Zech, M. ; Jech, R.* ; Boesch, S.* ; Škorvánek, M.* ; Necpál, J.* ; Švantnerová, J.* ; Wagner, M. ; Sadr-Nabavi, A.* ; Distelmaier, F.* ; Krenn, M.* ; Serranová, T.* ; Rektorová, I.* ; Havránková, P.* ; Mosejová, A.* ; Příhodová, I.* ; Šarláková, J.* ; Kulcsarová, K.* ; Ulmanová, O.* ; Bechyně, K.* ; Ostrozovičová, M.* ; Haň, V.* ; Ventosa, J.R.* ; Brunet, T.* ; Berutti, R.* ; Shariati, M.* ; Shoeibi, A.* ; Schneider, S.A.* ; Kuster, A.* ; Baumann, M.* ; Weise, D.* ; Wilbert, F.* ; Janzarik, W.G.* ; Eckenweiler, M.* ; Mall, V.* ; Haslinger, B.* ; Berweck, S.* ; Winkelmann, J. ; Oexle, K.
Scoring algorithm-based genomic testing in dystonia: A prospective validation study.
Mov. Disord. 36, 959-1964 (2021)
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.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Typ der Hochschulschrift
Herausgeber
Korrespondenzautor
Schlagwörter
Diagnostic Yield ; Dystonia ; Exome Sequencing ; Prediction ; Rare Disease ; Scoring Algorithm
Keywords plus
ISSN (print) / ISBN
0885-3185
e-ISSN
1531-8257
ISBN
Bandtitel
Konferenztitel
Konferzenzdatum
Konferenzort
Konferenzband
Quellenangaben
Band: 36,
Heft: 8,
Seiten: 959-1964
Artikelnummer: ,
Supplement: ,
Reihe
Verlag
Wiley
Verlagsort
111 River St, Hoboken 07030-5774, Nj Usa
Hochschule
Hochschulort
Fakultät
Veröffentlichungsdatum
0000-00-00
Anmeldedatum
0000-00-00
Anmelder/Inhaber
weitere Inhaber
Anmeldeland
Priorität
Begutachtungsstatus
Peer reviewed
Förderungen
Operational Programme Integrated Infrastructure - ERDF
Slovak Grant and Development Agency
European Joint Programme on Rare Diseases
Czech Ministry of Education
Charles University, Prague, Czech Republic
Medizinische Universitat Innsbruck, Innsbruck, Austria
Helmholtz Zentrum Munchen, Munich, Germany
Technische Universitat Munchen, Munich, Germany