Risk stratification and targeted neuroprotection in Parkinson disease utilising the glucocerebrosidase pathway
Bibliographic record
Abstract
OBJECTIVES: Glucocerebrosidase mutations represent genetically the most significant risk factor for Parkinson disease, however their penetrance is incomplete and variable such that only a minority of glucocerebrosidase mutation carriers will develop Parkinson disease. In this thesis I aimed to investigate the basis for this incomplete penetrance, to identify indices which may be used to predict Parkinson disease conversion amongst glucocerebrosidase mutation carriers and to test a putative neuroprotective drug designed to modify the glucocerebrosidase pathway. METHODS: In chapter 2 we used meta and joint analyses to calculate the odds ratio of developing Parkinson disease with individual glucocerebrosidase mutations. In chapter 3 we prospectively assessed a cohort of glucocerebrosidase mutation carriers without Parkinson disease for prodromal signs of Parkinsonism. In chapter 4 we sought to extend the scope, scale and sustainability of this study by producing a prototype study to assess these patients remotely through the internet. In chapter 5 we investigated whether novel imaging (PET using the PK-1195 and DAT ligands), serum (alpha synuclein, tau and inflammatory markers) and urine (hypothesis generating screen) could be used to predict PD conversion. In chapter 6 we used single cell calcium imaging in a primary neuronal mouse model carrying the N370S glucocerebrosidase mutation to investigate whether deranged calcium homeostasis might be the basis for the selective vulnerability of dopaminergic neurons in glucocerebrosidase mutation carrying cells. In chapters 7 and 8 we present optimisation and preliminary data from AiM PD, a phase II, open label, non placebo controlled trial of ambroxol, a small molecular chaperone of the glucocerebrosidase enzyme. RESULTS: Chapter 2: We derived quantifiable estimates of Parkinson disease risk for 84GG, E326K N370S, L444P, D409H, RecNcil as well as important data relating to the ethnic distribution of these mutations. Chapter 3: The University of Pennslyvannia smell identification test and Montreal cognitive assessment scores of glucocerebrosidase mutation carriers were worse than those of controls. There is a clustering effect amongst glucocerebrosidase mutation carriers whereby poor scores in these assessments and the Beck’s depression index seemed to be present together in a subset of participants. Chapter 4: We show the rapsodi portal is able, using validated assessments, to detect Parkinson disease features. Preliminary data shows cognitive deficits amongst Glucocerebrosidase mutations carriers exist compared to controls. Chapter 5: PK11195 signal is increased in the substantia nigra of glucocerebrosidase mutation carriers compared to controls and this signal increase correlates with olfactory loss. Serum alpha synuclein levels in glucocerebrosidase carriers correlate with the number of severe (neuronopathic) mutations and a risk score derived from prospective assessment of prodromal Parkinson disease features. The hypothesis generating urine proteomics screen identified a number of potential markers of Parkinson disease conversion including elements of the IgG kappa light chain. Chapter 6: We found no evidence of deranged calcium homeostasis Chapter 7: The glucocerebrosidase enzyme activity assay has been optimised to be reproducibly used in cerebrospinal fluid samples in our hands. The optimal time to carry out the assay to prevent degradation of activity following freezing is within 2 weeks of collection. In vitro addition of ambroxol to control CSF at physiologically relevant concentrations caused a 50% reduction in activity levels, due presumably to anatagonistic binding to the active site of the enzyme. Chapter 8: Preliminary results show that ambroxol delivers a statistically significant increase in leucocyte glucocerebrosidase activity amongst glucocerebrosidase mutation carriers with Parkinson disease. These patients seem to have worse features of non motor Parkinson disease symptoms than idiopathic Parkinson disease cases. CONCLUSIONS: Our results collectively suggest it may be feasible to stratify risk of Parkinson disease conversion amongst glucocerebrosidase mutation carriers on the basis of genetic, clinical, imaging and biochemical indices. Moreover they suggest that ambroxol has potential as a neuroprotective agent in Parkinson disease.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".