Brain Amyloid Contribution to Cognitive Dysfunction in Early-Stage Parkinson’s Disease: The PPMI Dataset
Bibliographic record
Abstract
BACKGROUND: The pathological processes underlying cognitive impairment in Parkinson's disease (PD) are heterogeneous and the contribution of cerebral amyloid deposits is poorly defined, particularly in the early stages of the disease. OBJECTIVE: To investigate regional [18F]florbetaben binding to amyloid-β (Aβ) and its contribution to cognitive dysfunction in early stage PD. METHODS: A multicenter cohort of 48 PD patients from the Parkinson's Progression Marker Initiative (PPMI) underwent [18F]florbetaben positron emission tomography (PET) scanning. Clinical features, including demographic characteristics, motor severity, cerebrospinal fluid (CSF), and cognitive testing were systematically assessed according to the PPMI study protocol. For the purpose of this study, we analyzed various neuropsychological tests assessing all cognitive functions. RESULTS: There were 10/48 (21%) amyloid positive PD patients (PDAβ+). Increased [18F]florbetaben uptake in widespread cortical and subcortical regions was associated with poorer performance on global cognition, as assessed by Montreal Cognitive Assessment (MoCA), and impaired performance on Symbol Digit Modality test (SDMT). Further, we found that PDAβ+ patients had higher CSF total-tau/Aβ1 - 42 (p = 0.001) and phosphorylated-tau/Aβ1 - 42 in (p = 0.002) compared to amyloid-negative PD. CONCLUSION: These findings suggest that multiple disease processes are associated with PD cognitive impairment and amyloid deposits may be observed already in early stages. However, prevalence of amyloid positivity is in the range of literature age-matched control population. Increased cortical and subcortical amyloid is associated with poor performance in attentive-executive domains while cognitive deficits at MoCA and SDMT may identify amyloid-related dysfunction in early PD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".