Elevated Tau PET Signal Depends on Abnormal Amyloid Levels and Correlates with Cognitive Impairment in Elderly Persons without Dementia
Bibliographic record
Abstract
BACKGROUND: The recent developed PET ligands for amyloid-β (Aβ) and tau allow these two neuropathological hallmarks of Alzheimer's disease (AD) to be mapped and quantified in vivo and to be examined in relation to cognition. OBJECTIVE: To assess the associations among Aβ, tau, and cognition in non-demented subjects. METHODS: Three hundred eighty-nine elderly participants without dementia from the Alzheimer's Disease Neuroimaging Initiative underwent tau and amyloid PET scans. Cross-sectional comparisons and longitudinal analyses were used to evaluate the relationship between Aβ and tau accumulation. The correlations between biomarkers of both pathologies and performance in memory and executive function were measured. RESULTS: Increased amyloid-PET retention was associated with greater tau-PET retention in widespread cortices. We observed a significant tau increase in the temporal composite regions of interest over 24 months in Aβ+ but not Aβ- subjects. Finally, tau-PET retention but not amyloid-PET retention significantly explained the variance in memory and executive function. Higher level of tau was associated with greater longitudinal memory decline. CONCLUSION: These findings suggested PET-detectable Aβ plaque pathology may be a necessary antecedent for tau-PET signal elevation. Greater tau-PET retention may demonstrate poorer cognition and predict prospective memory decline in non-demented subjects.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".