Association between a computerized, Self-administered cognitive assessment and phosphorylated Tau in Alzheimer’s Disease
Bibliographic record
Abstract
Abstract Introduction Alzheimer’s Disease (AD) is the leading cause of dementia, accounting for 80% of cases globally. With an aging population, AD poses a growing concern due to its increasing mortality rate and associated healthcare costs. Early diagnosis or prediction of AD is crucial for managing and potentially slowing its progression, particularly with the advent of disease-modifying therapies. Methods This study involved a total of 60 participants: 15 with mild AD, 23 with mild cognitive impairment (MCI), and 22 healthy controls, comprising both males and females aged 50–85 years. Data collection included blood samples, the Montreal Cognitive Assessment (MoCA), and the Integrated Cognitive Assessment (ICA). Serum phosphorylated tau181 (p-tau181) levels were measured using enzyme-linked immunosorbent assay (ELISA) kits. Linear regression models were applied to predict serum biomarker levels based on the ICA index, demographic data, and APOE ε4 status. Aims and Objectives The primary aim was to examine the association between ICA scores and blood-based p-tau181 levels in individual with MCI, mild AD, and elderly healthy controls. Additionally, the study compared the correlation of ICA and MoCA with APOE ε4 status. Findings The study found that the ICA can significantly differentiate between diagnostic groups and that elevated serum p-tau181 levels are associated with cognitive decline, as measured by the ICA. Additionally, a significant correlation was observed between APOE ε4 status and cognitive decline, but not between APOE ε4 status and serum p-tau181 levels. Using a model that incorporates the ICA, demographic data, and APOE ε4 status, we were able to modestly predict serum p-tau181 levels, indicating the potential of combining cognitive assessment with biological markers for AD prediction. Discussion The findings suggest that ICA is a valuable tool in detecting cognitive decline associated with AD and correlates with increased p-tau181 levels. The significant correlation between APOE ε4 status and cognitive decline highlights its potential role in risk assessment, independent of p-tau181 levels. The study supports the use of a computerized, self-administered cognitive assessment in conjunction with blood-based biomarkers for early AD detection. Limitations include the small sample size and cross-sectional design, which restricts causal inference and longitudinal analysis. Future research should focus on larger, longitudinal studies to further validate these associations and their implications for early diagnosis and monitoring of AD progression.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".