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Introduction: Given the unique natural history of GBA-related Parkinson's disease (GBA-PD) and the potential for novel treatments in this population, genetic testing prioritization for the identification of GBA-PD patients is crucial for prognostication, individualizing treatment, and stratification for clinical trials. Assessing the predictive value of certain clinical traits for the GBA-variant carrier status will help target genetic testing in clinical settings where cost and access limit its availability. Methods: In-depth clinical characterization through standardized rating scales for motor and non-motor symptoms and self-reported binomial information of a cohort of subjects with PD (n = 100) from our center and from the larger cohort of the Parkinson's Progression Marker Initiative (PPMI) was utilized to evaluate the predictive values of clinical traits for GBA variant carrier status. The model was cross-validated across the two cohorts. Results: Leveraging non-motor symptoms of PD, we established successful discrimination of GBA variants in the PPMI cohort and study cohort (AUC 0.897 and 0.738, respectively). The PPMI cohort model successfully generalized to the study cohort data using both MDS-UPDRS scores and binomial data (AUC 0.740 and 0.734, respectively) while the study cohort model did not. Conclusions: We assessed the predictive value of non-motor symptoms of PD for identifying GBA carrier status in the general PD population. These data can be used to determine a simple, clinically oriented model using either the MDS-UPDRS or subjective symptom reporting from patients. Our results can inform patient counseling about the expected carrier risk and test prioritization for the expected identification of GBA variants.
RESUMO
BACKGROUND: Genetic mutations in beta-glucocerebrosidase (GBA) represent the major genetic risk factor for Parkinson's disease (PD). GBA participates in both the endo-lysosomal pathway and the immune response, two important mechanisms involved in the pathogenesis of PD. However, modifiers of GBA penetrance have not yet been fully elucidated. METHODS: We characterized the transcriptomic profiles of circulating monocytes in a population of patients with PD and healthy controls (CTRL) with and without GBA variants (n = 23 PD/GBA, 13 CTRL/GBA, 56 PD, 66 CTRL) and whole blood (n = 616 PD, 362 CTRL, 127 PD/GBA, 165 CTRL/GBA). Differential expression analysis, pathway enrichment analysis, and outlier detection were performed. Ultrastructural characterization of isolated CD14+ monocytes in the four groups was also performed through electron microscopy. RESULTS: We observed hundreds of differentially expressed genes and dysregulated pathways when comparing manifesting and non-manifesting GBA mutation carriers. Specifically, when compared to idiopathic PD, PD/GBA showed dysregulation in genes involved in alpha-synuclein degradation, aging and amyloid processing. Gene-based outlier analysis confirmed the involvement of lysosomal, membrane trafficking, and mitochondrial processing in manifesting compared to non-manifesting GBA-carriers, as also observed at the ultrastructural levels. Transcriptomic results were only partially replicated in an independent cohort of whole blood samples, suggesting cell-type specific changes. CONCLUSIONS: Overall, our transcriptomic analysis of primary monocytes identified gene targets and biological processes that can help in understanding the pathogenic mechanisms associated with GBA mutations in the context of PD.