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Scoring Algorithm‐Based Genomic Testing in Dystonia: A Prospective Validation Study
Author(s) -
Zech Michael,
Jech Robert,
Boesch Sylvia,
Škorvánek Matej,
Necpál Ján,
Švantnerová Jana,
Wagner Matias,
SadrNabavi Ariane,
Distelmaier Felix,
Krenn Martin,
Serranová Tereza,
Rektorová Irena,
Havránková Petra,
Mosejová Alexandra,
Příhodová Iva,
Šarláková Jana,
Kulcsarová Kristína,
Ulmanová Olga,
Bechyně Karel,
Ostrozovičová Miriam,
Haň Vladimír,
Ventosa Joaquim Ribeiro,
Brunet Theresa,
Berutti Riccardo,
Shariati Mohammad,
Shoeibi Ali,
Schneider Susanne A.,
Kuster Alice,
Baumann Matthias,
Weise David,
Wilbert Friederike,
Janzarik Wibke G.,
Eckenweiler Matthias,
Mall Volker,
Haslinger Bernhard,
Berweck Steffen,
Winkelmann Juliane,
Oexle Konrad
Publication year - 2021
Publication title -
movement disorders
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.352
H-Index - 198
eISSN - 1531-8257
pISSN - 0885-3185
DOI - 10.1002/mds.28614
Subject(s) - dystonia , medical diagnosis , movement disorders , comorbidity , exome sequencing , algorithm , medicine , pediatrics , physical medicine and rehabilitation , machine learning , psychiatry , computer science , pathology , mutation , biology , genetics , disease , gene
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