Associations between blood-based biomarkers of Alzheimer’s disease with cognition in motoric cognitive risk syndrome: A pilot study using plasma Aβ42 and total tau
Bibliographic record
Abstract
Background: Motoric cognitive risk (MCR) syndrome is a conceptual construct that combines slow gait speed with subjective cognitive complaints and has been shown to be associated with an increased risk of developing dementia. However, the relationships between the pathology of Alzheimer's disease (AD) and MCR syndrome remain uncertain. Therefore, the purpose of this study was to determine the levels of plasma AD biomarkers (Aβ42 and total tau) and their relationships with cognition in individuals with MCR. Materials and methods: This was a cross-sectional pilot study that enrolled 25 individuals with normal cognition (NC), 27 with MCR, and 16 with AD. Plasma Aβ42 and total tau (t-tau) levels were measured using immunomagnetic reduction (IMR) assays. A comprehensive neuropsychological assessment was also performed. Results: The levels of plasma t-tau proteins did not differ significantly between the MCR and AD groups, but that of plasma t-tau was significantly increased in the MCR and AD groups, compared to the NC group. Visuospatial performance was significantly lower in the MCR group than in the NC group. The levels of plasma t-tau correlated significantly with the Montreal Cognitive Assessment (MoCA) and Boston naming test scores in the MCR group. Conclusion: In this pilot study, we found significantly increased plasma t-tau proteins in the MCR and AD groups, compared with the NC group. The plasma t-tau levels were also significantly correlated with the cognitive function of older adults with MCR. These results implied that MCR and AD may share similar pathology. However, these findings need further confirmation in longitudinal studies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".