Association of alpha-synuclein co-pathology with beta-amyloid and phosphorylated tau levels in Alzheimer’s disease
Bibliographic record
Abstract
Misfolded α-synuclein (α-syn) aggregates can be present in the cerebrospinal fluid (CSF) of individuals with Alzheimer’s disease (AD), even in the absence of clinical signs of synucleinopathy. This co-pathology may influence AD progression at the molecular level. Detection of α-synuclein aggregates using seed amplification assay (SAA) enables stratification of AD patients beyond classical biomarkers included in the AT(N) framework. The AT(N) framework allows biological classification of AD based on its core pathological processes: β-amyloid aggregation (A), tau accumulation and hyperphosphorylation (T), and non-specific neurodegeneration (N). This study aimed to explore whether α-syn co-pathology, detected by SAA, is associated with altered concentrations and longitudinal trajectories of CSF β-amyloid 42 (Aβ42) and phosphorylated tau 181 (p-tau181) in the biomarker-defined AD group. Data from A+T+ participants (N = 609) in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were analysed, using Roche Elecsys electrochemiluminescence immunoassay (ECLIA) and SAA results. Substantial discrepancies between clinical diagnosis and AT profiles were observed. Twenty-nine percent of A+T+ participants were α-synpositive (S+), indicating a high prevalence of α-syn co-pathology in biologically defined AD. Cross-sectional comparisons revealed that S+ individuals had lower baseline Aβ42 concentrations compared to α-synnegative (S−) participants. Linear mixed-effects models (LMEMs) showed a significantly steeper decline in Aβ42 over time in the S+ group, supporting the hypothesis that misfolded α-syn aggregation accelerates amyloid aggregation. However, p-tau181 levels increased more slowly in S+ than in S− individuals, contrary to expectations. These associations remained significant after adjustment for age, sex, diagnosis, and APOE-ε4 genotype. These findings suggest that α-syn co-pathology may affect AD progression through its interaction with Aβ42 and support its integration into biomarker-based classification frameworks.
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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 | 0.001 |
| 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".