Diagnostic and prognostic value of alpha-synuclein seed amplification assay in Parkinson’s disease: a longitudinal cohort study
Bibliographic record
Abstract
Summary Background Alpha-synuclein seed amplification assay (a-syn SAA) has been proposed to be a diagnostic biomarker for Parkinson’s disease (PD). Here, we have explored the diagnostic and prognostic value of cerebrospinal fluid (CSF) a-syn SAA status and seeding kinetics in PD. Methods Baseline CSF a-syn SAA data and longitudinal clinical data were collected and analysed between 1 st January 2010 and 1 st April 2022 for the Parkinson’s Progression Markers Initiative (PPMI) and UK parkinsonism cohorts respectively. We calculated the sensitivity and specificity of a-syn SAA in PD and controls, used linear regression to analyse a-syn SAA positive vs. negative group comparisons, and used time-to-event analyses to assess the ability of a-syn SAA seeding kinetic measures to predict clinical decline in PD. Findings We studied 1,402 participants: publicly available data from the PPMI cohort, n=1275 (PD, n=1,036; controls, n=239); newly generated data from the UK parkinsonism cohort, n=127 (PD, n=66; progressive supranuclear palsy (PSP), n=52; controls n=9). Over 2-5 years of follow-up, the sensitivity of a-syn SAA in PD was 87.7% and the specificity in controls was 91.9%. A-syn SAA was positive in 8/52 (15.4%) PSP samples with distinct ‘low and slow’ kinetics. A-syn SAA negative LRRK2-PD participants (n=57) had an older mean (SD) age at symptom onset (63.0 (7.6) vs. 55.4 (9.9) years) and higher mean (SD) baseline serum neurofilament light chain levels (20.4 (13.2) vs. 13.8 (8.6) pg/ml), p<0.05, vs. a-syn SAA positive LRRK2-PD participants (n=110). The baseline seeding kinetic measure, time to threshold, predicted cognitive decline in PD, defined as MoCA ≤21 (HR 2.51, 95% CI 1.50-4.20, p=0.001). Interpretation In PD, a-syn SAA may have value as a diagnostic and prognostic biomarker in clinical practice and as a stratification tool in clinical trials. Furthermore, we have highlighted the presence of pathological heterogeneity in LRRK2-PD. Funding Medical Research Council, PSP Association.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".