LRRK2 and α-Synuclein: Distinct or Synergistic Players in Parkinson’s Disease?
Bibliographic record
Abstract
Parkinson’s disease (PD) is the most common neurodegenerative movement disorder, characterized by prominent degeneration of dopaminergic neurons in the substantia nigra and aggregation of the protein alpha-synuclein within intraneuronal inclusions known as Lewy bodies. Ninety percent of PD cases are idiopathic while the remaining 10% are associated with gene mutations that affect cellular functions ranging from kinase activity to mitochondrial quality control, hinting at a multifactorial disease process. Mutations in LRRK2 and SNCA (the gene coding for alpha-synuclein) cause monogenic forms of autosomal dominant PD, and polymorphisms in either gene are also associated with increased risk of idiopathic PD. Although Lewy bodies are a defining neuropathological feature of PD, an appreciable subset of patients with LRRK2 mutations present with a clinical phenotype indistinguishable from idiopathic PD but lack Lewy pathology at autopsy, suggesting that LRRK2-mediated PD may occur independently of alpha-synuclein aggregation. Here, we examine whether LRRK2 and alpha-synuclein, as mediators of neurodegeneration in PD, exist in common or distinct pathways. Specifically, we review evidence from preclinical models and human neuropathological studies examining interactions between the two proteins. Elucidating the degree of interplay between LRRK2 and alpha-synuclein will be necessary for treatment stratification once effective targeted disease-modifying therapies are developed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".