Baseline Neurodegeneration Influences the Longitudinal Effects of Tau on Cognition
Bibliographic record
Abstract
BACKGROUND: Cerebrospinal fluid t-tau (CSF t-tau) is a measure of neurodegeneration in Alzheimer's disease (AD) and has been increasingly demonstrated to be a non-specific biomarker within the AD continuum. OBJECTIVE: We sought to test whether t-tau influences the longitudinal effects of amyloid-β (Aβ) and phospho-tau (p-tau) on memory and executive function (EF) in mild cognitive impairment (MCI). METHODS: 319 MCI individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with baseline and 2-year CSF Aβ, p-tau, t-tau, and neuropsychological assessments were studied. Mediation and moderation analyses evaluated the role of t-tau in the effects of Aβ and p-tau on memory and EF over 2 years. RESULTS: We found that high baseline p-tau but not Aβ was associated with higher t-tau and lower memory scores at 2 years follow-up. The association between p-tau and memory impairment was partially mediated by t-tau, whereby higher p-tau was indirectly associated with lower memory via higher t-tau. t-tau also moderated the association between p-tau and memory. When t-tau level was relatively lower, higher p-tau was associated with lower memory scores at 2 years. When t-tau level was higher, the memory scores were low regardless of the p-tau level. CONCLUSION: Tau-induced neurodegeneration is one key pathway by which AD pathology (p-tau) affects memory impairment. Furthermore, in individuals with lower levels of tau-induced neurodegeneration, higher levels of p-tau were required for memory impairment. Our findings suggest that t-tau plays a significant role in how early AD pathology affects cognitive outcomes.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".