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. (c) 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society

Automated summary

The algorithm for dystonia diagnosis based on individual phenotypic aspects showed the highest diagnostic yield when the total score was 5. The sensitivity and specificity for implementing WES at the threshold of 3 points were 96% and 52% respectively.