Follow-up of pre-motor symptoms of Parkinson’s disease in adult patients with Gaucher disease type 1 and analysis of their lysosomal enzyme profiles in the CSF
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide. Its classic motor symptoms may be preceded by non-motor symptoms (NMS). Population studies have identified GBA variants as risk factors for idiopathic PD. The increased risk of PD has also been suggested in other Lysosomal Storage Disorders (LSDs). OBJECTIVE: To assess the evolution of the prevalence of NMS compatible with PD in a cohort of South Brazilian adult patients with Gaucher Disease (GD) type 1, already evaluated 3 years ago (2018). Cerebrospinal Fluid (CSF) was collected to assess the levels of LSD enzymes (beta-hexosaminidases, beta-glucuronidase) and biomarker of macrophage activation (chitotriosidase, ChT), compared to controls (metachromatic leukodystrophy, MLD). Cognition was evaluated by the Montreal Cognitive Assessment (MoCA) questionnaire, daytime sleepiness by the Epworth Sleepiness Scale (ESS), depression by Beck´s Inventory, constipation by the Unified Multiple System Atrophy Rating Scale (UMSARS) scale, and REM sleep behavior disorder by the single-question screen. Hyposmia was assessed with Sniffin' Sticks (SST). RESULTS: Nineteen patients completed the follow-up (mean age of the sample was 44 years; range, 26-71). The patient with the highest number of NMS at the baseline (4 including the lowest SST score) was diagnosed with PD four years later. Apart from an improvement in the ESS score, no other statistical significance was found between the number of NMS between the first and second evaluation, nor between patients with one L444P variant (n = 5) and the rest of the cohort. CSF was collected in five patients (mean age of the sample was 40 years, range 30-53. A significant difference was found in the mean CSF activity levels of beta-hexosaminidases and beta-glucuronidase between GD1 and MLD patients. Mean ChT (CSF) was 62 nmol/h/mL in GD patients and 142 in MLD (n = 6) patients. CONCLUSIONS: The patient with the highest number of NMS in our 2018 cohort was the one that developed PD, corroborating with the importance of this longitudinal follow-up. CSF and plasma analysis might allow a better understanding of the neurodegenerative processes connecting PD and the lysosomal environment. Further analysis is needed to understand this relationship.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".