The G51D SNCA mutation generates a slowly progressive α-synuclein strain in early-onset Parkinson’s disease
Bibliographic record
Abstract
Unique strains of α-synuclein aggregates have been postulated to underlie the spectrum of clinical and pathological presentations seen across the synucleinopathies. Whereas multiple system atrophy (MSA) is associated with a predominance of oligodendroglial α-synuclein inclusions, α-synuclein aggregates in Parkinson's disease (PD) preferentially accumulate in neurons. The G51D mutation in the SNCA gene encoding α-synuclein causes an aggressive, early-onset form of PD that exhibits clinical and neuropathological traits reminiscent of both PD and MSA. To assess the strain characteristics of G51D PD α-synuclein aggregates, we performed propagation studies in M83 transgenic mice by intracerebrally inoculating patient brain extracts. The properties of the induced α-synuclein aggregates in the brains of injected mice were examined using immunohistochemistry, a conformational stability assay, and by performing α-synuclein seed amplification assays. Unlike MSA-injected mice, which developed a progressive motor phenotype, G51D PD-inoculated animals remained free of overt neurological illness for up to 18 months post-inoculation. However, a subclinical synucleinopathy was present in G51D PD-inoculated mice, characterized by the accumulation of α-synuclein aggregates in restricted regions of the brain. The induced α-synuclein aggregates in G51D PD-injected mice exhibited distinct properties in a seed amplification assay and were much more stable than those present in mice injected with MSA extract, which mirrored the differences observed between human MSA and G51D PD brain samples. These results suggest that the G51D SNCA mutation specifies the formation of a slowly propagating α-synuclein strain that more closely resembles α-synuclein aggregates associated with PD than MSA.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".