Clinical Utility of GBA Genotyping Prior to Deep Brain Stimulation: A Narrative Review

<b>Background</b>: Variants in the <i>GBA</i> gene represent the most common genetic risk factor for Parkinson's disease and are associated with a more aggressive disease course. Deep brain stimulation is an established therapy for advanced Parkinson's disease, yet the influence of <i>GBA</i> status on postoperative outcomes remains incompletely defined. This review aims to summarize the clinical relevance of <i>GBA</i> genotyping prior to DBS and to evaluate its potential contribution to decision-making, risk stratification, and long-term management. <b>Methods</b>: A structured narrative review was conducted. The literature on sequencing methodology, variant interpretation, and postoperative outcomes in <i>GBA</i>-positive and <i>GBA</i>-negative patients was examined. Particular focus was placed on motor, cognitive, and neuropsychiatric outcomes, and on studies comparing trajectories across variant classes. <b>Results</b>: Across all study designs, patients with <i>GBA</i>-associated Parkinson's disease demonstrated robust motor improvement after DBS, with outcomes comparable to those in non-carriers. Cognitive and neuropsychiatric decline occurred more rapidly in <i>GBA</i> carriers. Recent evidence indicates that cognitive and neuropsychiatric decline is influenced more by the genetic profile than the stimulation procedure. Variant severity appears to influence postoperative trajectories. Long-read sequencing improves detection of recombinant alleles and may refine genotype-phenotype associations. Genotyping provides additional value in counseling, expectation management, and postoperative planning. <b>Conclusions</b>: DBS remains an effective motor therapy for patients with <i>GBA</i>-associated Parkinson's disease. Current findings indicate <i>GBA</i> genotyping should inform, and not limit, candidate selection. Integration of clinical, cognitive and genetic data supports more individualized management. Methodological advances in sequencing and the development of prediction models may further enhance personalized DBS planning.