Phosphorylated α-synuclein in skin Schwann cells: a new biomarker for multiple system atrophy
Bibliographic record
Abstract
Multiple system atrophy (MSA) is characterized by accumulation of phosphorylated α-synuclein (p-syn) as glial cytoplasmic inclusions in the brain and a specific biomarker for this disorder is urgently needed. We aimed at investigating if p-syn can also be detected in skin Remak non-myelinating Schwann cells (RSCs) as Schwann cell cytoplasmic inclusions (SCCi) and may represent a reliable clinical biomarker for MSA. This cross-sectional diagnostic study evaluated skin p-syn in 96 patients: 46 with probable MSA (29 with parkinsonism type MSA and 17 with cerebellar type MSA), 34 with Parkinson's disease (PD) and 16 with dementia with Lewy bodies (DLB). We also included 50 healthy control subjects. Patients were recruited from five different medical centres. P-syn aggregates in skin sections were stained by immunofluorescence, followed by analyses with confocal microscopy and immuno-electron microscopy. All analyses were performed in a blinded fashion. Overall, p-syn aggregates were found in 78% of MSA patients and 100% of patients with PD/DLB, whereas they could not be detected in controls. As for neuronal aggregates 78% of MSA patients were positive for p-syn in somatic neurons, whereas all PD/DLB patients were positive in autonomic neurons. When analysing the presence of p-syn in RSCs, 74% of MSA patients were positive, whereas no such SCCi could be observed in PD/DLB patients. Analyses by immuno-electron microscopy confirmed that SCCi were only found in cases with MSA and thus absent in those with PD/DLB. In conclusion, our findings demonstrate that (i) fibrillar p-syn in RSCs is a pathological hallmark of MSA and may be used as a specific and sensitive disease biomarker; (ii) in Lewy body synucleinopathies (PD/DLB) only neurons contain p-syn deposits; and (iii) the cell-specific deposition of p-syn in the skin thus mirrors that of the brain in many aspects and suggests that non-myelinated glial cells are also involved in the MSA pathogenesis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".