Depressive symptoms interact with CSF levels of p-tau in predicting cognitive performance in the early stages of Parkinson's disease
Bibliographic record
Abstract
Amyloid-β deposition and tau pathology are suggested to play a role in the emergence of depressive symptoms and cognitive decline in Parkinson's disease (PD). Additionally, studies have reported an association between presence of the APOE4 allele and poorer cognition in PD. The present study aims to investigate whether amyloid-β, tau pathology and APOE4 carrier status interact with depressive symptoms in predicting global cognition in PD. We analysed data from 348 persons with PD (PwPD) and 160 healthy controls (HCs). Linear mixed effects regression analyses were conducted to examine if CSF levels of Aβ42 and p-tau, and APOE4 carrier status did interact with depressive symptoms, as assessed by the Geriatric Depression Scale (GDS), in predicting cognition performance, as measured by Montreal Cognitive Assessment Test (MoCA) scores, over three years. Results of a first linear regression model conducted considering both PwPD and HC indicated that MoCA scores were significantly predicted by GDS, as well as by the interaction between GDS and p-tau, Group and p-tau, and between Group, p-tau and GDS. Results of the models conducted in the two groups separately indicated that, while in HC MoCA scores were predicted by age and time only, a significant interaction between GDS and CSF levels of p-tau emerged as a predictor of MoCA scores in PwPD. Specifically, post hoc analysis revealed a negative association between CSF levels of p-tau and cognitive performance that was significant only in PwPD with the highest GDS scores. Taken together, results of this study confirm that, in early stages of PD, depressive symptoms interact with CSF levels of p-tau in predicting cognitive performance. Findings highlight the importance of assessing and treating depression in PwPD as early as possible, as it might reduce the likelihood of future cognitive decline.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".