Alpha-Synuclein and the Endolysosomal System in Parkinson’s Disease: Guilty by Association
Bibliographic record
Abstract
Abnormal accumulation of the protein α- synuclein (α-syn) into proteinaceous inclusions called Lewy bodies (LB) is the neuropathological hallmark of Parkinson's disease (PD) and related disorders. Interestingly, a growing body of evidence suggests that LB are also composed of other cellular components such as cellular membrane fragments and vesicular structures, suggesting that dysfunction of the endolysosomal system might also play a role in LB formation and neuronal degeneration. Yet the link between α-syn aggregation and the endolysosomal system disruption is not fully elucidated. In this review, we discuss the potential interaction between α-syn and the endolysosomal system and its impact on PD pathogenesis. We propose that the accumulation of monomeric and aggregated α-syn disrupt vesicles trafficking, docking, and recycling, leading to the impairment of the endolysosomal system, notably the autophagy-lysosomal degradation pathway. Reciprocally, PD-linked mutations in key endosomal/lysosomal machinery genes (LRRK2, GBA, ATP13A2) also contribute to increasing α-syn aggregation and LB formation. Altogether, these observations suggest a potential synergistic role of α-syn and the endolysosomal system in PD pathogenesis and represent a viable target for the development of disease-modifying treatment for PD and related disorders.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".