Alpha-synuclein seeding shows a wide heterogeneity in multiple system atrophy
Bibliographic record
Abstract
BACKGROUND: Multiple system atrophy (MSA) is a neurodegenerative condition characterized by variable combinations of parkinsonism, autonomic failure, cerebellar ataxia and pyramidal features. Although the distribution of synucleinopathy correlates with the predominant clinical features, the burden of pathology does not fully explain observed differences in clinical presentation and rate of disease progression. We hypothesized that the clinical heterogeneity in MSA is a consequence of variability in the seeding activity of α-synuclein both between different patients and between different brain regions. METHODS: The reliable detection of α-synuclein seeding activity derived from MSA using cell-free amplification assays remains challenging. Therefore, we conducted a systematic evaluation of 168 different reaction buffers, using an array of pH and salts, seeded with fully characterized brain homogenates from one MSA and one PD patient. We then validated the two conditions that conferred the optimal ability to discriminate between PD- and MSA-derived samples in a larger cohort of 40 neuropathologically confirmed cases, including 15 MSA. Finally, in a subset of brains, we conducted the first multi-region analysis of seeding behaviour in MSA. RESULTS: Using our novel buffer conditions, we show that the physicochemical factors that govern the in vitro amplification of α-synuclein can be tailored to generate strain-specific reaction buffers that can be used to reliably study the seeding capacity from MSA-derived α-synuclein. Using this novel approach, we were able to sub-categorize the 15 MSA brains into 3 groups: high, intermediate and low seeders. To further demonstrate heterogeneity in α-synuclein seeding in MSA, we conducted a comprehensive multi-regional evaluation of α-synuclein seeding in 13 different regions from 2 high seeders, 2 intermediate seeders and 2 low seeders. CONCLUSIONS: We have identified unexpected differences in seed-competent α-synuclein across a cohort of neuropathologically comparable MSA brains. Furthermore, our work has revealed a substantial heterogeneity in seeding activity, driven by the PBS-soluble α-synuclein, between different brain regions of a given individual that goes beyond immunohistochemical observations. Our observations pave the way for future subclassification of MSA, which exceeds conventional clinical and neuropathological phenotyping and considers the structural and biochemical heterogeneity of α-synuclein present. Finally, our methods provide an experimental framework for the development of vitally needed, rapid and sensitive diagnostic assays for 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".