Genetic Profile and Symptom Pattern Explain Variability of Deep Brain Stimulation Effect in Dystonia - Mahboubeh Ahmadipour; Luigi M. Romito; Antonio E. Elia; Nico Golfré Andreasi; Roberto Eleopra; Alberto Mazzoni; Fabiana Colucci (Annals of Clinical and Translational Neurology)
ABSTRACT Objective Bilateral globus pallidus pars interna deep brain stimulation (GPi‐DBS) is a recognized and effective treatment option for drug‐resistant dystonia patients. However, the clinical GPi‐DBS outcomes vary significantly. Herein, we explored the pre‐implant factors affecting GPi‐DBS effectiveness. Methods Genetic profiles, symptom distribution, age at onset, disease duration, and severity of a cohort of 31 GPi‐DBS dystonia patients were collected. Dystonia motor severity was evaluated before and after GPi‐DBS using the Burke–Fahn–Marsden Dystonia‐Rating‐Scale (BFMDRS‐M). We assessed the interplay of the aforementioned factors in determining the BFMDRS‐M improvement through a multilinear regression analysis. Results BFMDRS‐M score showed a significant improvement (47.8%) since the first year, remaining stable at 5 years (54.3%). Lower limb (0.20), upper limb (0.16) and trunk (0.24) symptoms showed a significantly larger improvement compared to cranial symptoms (0.07, p < 0.05). Consequently, patients with more pronounced lower limb motor symptoms displayed a greater GPi‐DBS effect (p < 0.01). However, pre‐treatment localization of motor symptoms accounted only for 31% of the Inter‐Patient Variability (IPV) in post‐GPi‐DBS improvement. Amelioration varied also across genetic profiles, with the largest improvement reported for DYT‐TOR1A patients (n = 9, 64.2% in the first year), predicting 36% of IPV. Interestingly, combining motor and genetic profiles predicted 73% of the IPV. Including the clinical profile of the patient (age at onset, disease severity and duration) increased prediction accuracy to 81%. Interpretation Our results suggest that motor and genetic profiles contribute independently to the efficacy of the GPi‐DBS treatment. These results may support a personalized prediction of DBS outcomes in dystonia patients.