Movement disorders clinical practice · 2026
Age at Onset Predicts Motor and Non-motor Severity in Cervical Dystonia.
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Rafee Shameer, Williams Laura, O'Riordan Sean, Hutchinson Michael, Fearon Conor
Аннотация
BACKGROUND: Cervical dystonia (CD) is the most common focal dystonia and shows significant heterogeneity in both motor and non-motor symptoms. Although motor symptoms typically prompt clinical presentation, non-motor features are the principal determinants of quality of life. Previous efforts to classify CD have focused on selected motor and non-motor clinical characteristics, suggesting distinct subtypes with potential prognostic implications.
OBJECTIVE: We employed cluster analysis to identify phenotypic subgroups within a large CD population with detailed motor and non-motor assessments.
METHODS: Adult patients with idiopathic isolated CD were included. Data were collected across five domains using validated instruments: motor severity (TWSTRS2-Severity), quality of life (CDIP-58 total and EQ-5D-5L utility index), disability (TWSTRS2-Disability), pain (TWSTRS2-Pain), and psychiatric symptoms (HADS-Total). Hierarchical cluster analysis using Ward's linkage method was performed to identify phenotypic subgroups.
RESULTS: 201 CD patients (67% female) were included for analysis. Median age was 62 years. Hierarchical cluster analysis identified two distinct phenotypic subgroups (Clusters A and B). Cluster A patients (n = 78) demonstrated significantly earlier disease onset (35 vs 48 years) and greater symptom burden across all variables (p < 0.001) when compared with Cluster B (n = 123). The largest between-cluster differences were observed for CDIP-58, HADS-Total, and TWSTRS2-Pain. Motor severity showed a smaller effect size, suggesting non-motor features more strongly distinguish these phenotypes.
CONCLUSION: Hierarchical cluster analysis identified two distinct CD phenotypes: an earlier onset high-burden subgroup and later onset low-burden subgroup. These clusters were primarily distinguished by non-motor features (quality of life, mood, pain, and disability). Our findings highlight age at onset as a key determinant of CD phenotype.
OBJECTIVE: We employed cluster analysis to identify phenotypic subgroups within a large CD population with detailed motor and non-motor assessments.
METHODS: Adult patients with idiopathic isolated CD were included. Data were collected across five domains using validated instruments: motor severity (TWSTRS2-Severity), quality of life (CDIP-58 total and EQ-5D-5L utility index), disability (TWSTRS2-Disability), pain (TWSTRS2-Pain), and psychiatric symptoms (HADS-Total). Hierarchical cluster analysis using Ward's linkage method was performed to identify phenotypic subgroups.
RESULTS: 201 CD patients (67% female) were included for analysis. Median age was 62 years. Hierarchical cluster analysis identified two distinct phenotypic subgroups (Clusters A and B). Cluster A patients (n = 78) demonstrated significantly earlier disease onset (35 vs 48 years) and greater symptom burden across all variables (p < 0.001) when compared with Cluster B (n = 123). The largest between-cluster differences were observed for CDIP-58, HADS-Total, and TWSTRS2-Pain. Motor severity showed a smaller effect size, suggesting non-motor features more strongly distinguish these phenotypes.
CONCLUSION: Hierarchical cluster analysis identified two distinct CD phenotypes: an earlier onset high-burden subgroup and later onset low-burden subgroup. These clusters were primarily distinguished by non-motor features (quality of life, mood, pain, and disability). Our findings highlight age at onset as a key determinant of CD phenotype.