Evolution and Predictive Role of Plasma Alzheimer’s Disease-related Pathological Biomarkers in Parkinson’s Disease
Bibliographic record
Abstract
Plasma Alzheimer's disease-related pathological biomarkers' role in Parkinson's disease (PD) remains unknown. We aimed to determine whether plasma Alzheimer's disease-related biomarkers can predict PD progression. A total of 184 PD patients and 86 healthy controls were included and followed up for 5 years. Plasma phosphorylated tau181 (p-tau181), Aβ40, and Aβ42 were measured at baseline and the 1- and 2-year follow-ups using the Quanterix-single-molecule array. Global cognitive function and motor symptoms were assessed using the Montreal Cognitive Assessment and Unified Parkinson's Disease Rating Scale part III. Genetic analyses were conducted to identify APOE and MAPT genotypes. Plasma p-tau181 levels were higher in PD than healthy controls. APOE-ε4 carriers had lower plasma Aβ42 levels and Aβ42/Aβ40 ratio. The linear mixed-effects models showed that Montreal Cognitive Assessment scores were associated with plasma p-tau181/Aβ42 ratio (β -1.719 [-3.398 to -0.040], p = .045). Higher baseline plasma p-tau181 correlated with faster cognitive decline and motor symptoms deterioration in total patients (β -0.170 [-0.322 to -0.018], p = .029; β 0.329 [0.032 to 0.626], p = .030) and APOE-ε4 carriers (β -0.318 [-0.602 to -0.034], p = .030; β 0.632 [0.017 to 1.246], p = .046), but not in the noncarriers. Higher baseline plasma Aβ40 correlated with faster cognitive decline in total patients (β -0.007 [-0.015 to -0.0001], p = .047) and faster motor symptoms deterioration in total patients (β 0.026 [0.010 to 0.041], p = .001) and APOE-ε4 carriers (β 0.044 [-0.026 to 0.049], p = .020), but not in the noncarriers. The plasma p-tau181/Aβ2 ratio monitors the cognitive status of PD. Higher baseline plasma p-tau181 and Aβ40 predict faster cognitive decline and motor symptoms deterioration in PD, especially in APOE-ε4 carriers.
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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 | 0.002 |
| 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 | 0.001 | 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".