Lysosomal Pathogenesis of Parkinson's Disease: Insights From LRRK2 and GBA1 Rodent Models
Bibliographic record
Abstract
The discovery of mutations in LRRK2 and GBA1 that are linked to Parkinson’s disease provided further evidence that autophagy and lysosome pathways are likely implicated in the pathogenic process. Their protein products are important regulators of lysosome function. LRRK2 has kinase-dependent effects on lysosome activity, autophagic efficacy and lysosomal Ca 2+ signaling. Glucocerebrosidase (encoded by GBA1 ) is a hydrolytic enzyme contained in the lysosomes and contributes to the degradation of alpha-synuclein. PD-related mutations in LRRK2 and GBA1 slow the degradation of alpha-synuclein, thus directly implicating the dysfunction of the process in the neuropathology of Parkinson’s disease. The development of genetic rodent models of LRRK2 and GBA1 provided hopes of obtaining reliable preclinical models in which to study pathogenic processes and perform drug validation studies. Here, I will review the extensive characterization of these models, their impact on understanding lysosome alterations in the course of Parkinson’s disease and what novel insights have been obtained. In addition, I will discuss how these models fare with respect to the features of a “gold standard” animal models and what could be attempted in future studies to exploit LRRK2 and GBA1 rodent models in the fight against Parkinson’s 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".