Scoring Algorithm-Based Genomic Testing in Dystonia: A Prospective Validation Study

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.