Plasma Levels of α-Synuclein, Aβ-40 and T-tau as Biomarkers to Predict Cognitive Impairment in Parkinson’s Disease
Bibliographic record
Abstract
OBJECTIVE: In this study, we assessed plasma biomarkers to identify cognitive impairment in Parkinson's disease (PD) patients by applying ultra-sensitive immunomagnetic reduction-based immunoassay (IMR). METHODS: The study enrolled 60 PD patients and 28 age- and sex-matched normal controls. Complete cognitive function assessments were performed on participants using the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating. PD patients with an MMSE score of ≦26 were defined as having cognitive impairment. Meanwhile, a 99mTc-TRODAT-1 scan was performed and plasma levels of Aβ-40, Aβ-42, T-tau, and α-synuclein were evaluated using IMR, subsequent correlation analyses were then performed. RESULTS: = 0.002) are significantly correlated with MMSE scores. The TRODAT scan results, including visual inspection and quantification, revealed significant correlations between Aβ-40 and PD. Multiple regression analysis showed that the plasma levels of Aβ-40 (OR = 0.921, 95% CI = 0.879-0.962), α-synuclein (OR = 3.016, 95% CI = 1.703-5.339), and T-tau (OR = 1.069, 95% CI = 1.026-1.115) were independently associated with PD patients with cognitive impairment. The cutoff values for predicting cognitive deficits in PD patients were 45.101 pg/ml of Aβ-40, (Area under curve (AUC) = 0.791), 0.389 pg/ml of α-synuclein, (AUC = 0.790), and 30.555 pg/ml of T-tau (AUC = 0.726). CONCLUSION: Plasma levels of α-synuclein, Aβ-40, and T-tau are potential biomarkers to detect cognitive impairment in PD patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".