Sex Differences in Vulnerability to Tau Pathology: Impact on Cognitive Decline
Bibliographic record
Abstract
Abstract Introduction While the link between presence of amyloid and tau pathologies, neurodegeneration, and cognitive decline in aging individuals is established, it is less clear whether there are sex differences in vulnerability to these pathologies. Methods 1,464 participants (7,168 longitudinal assessments, 4.77±3.78 years of follow-up) were included from the National Alzheimer’s Coordinating Center (NACC) database. Longitudinal mixed effects and mediation models examined the sex differences across cognitive decline trajectories of amyloid (A), tau (T), and neurodegeneration (N) groups. Results A + T - males showed faster cognitive decline compared to A + T - females (p<0.005), whereas A + T + females showed steeper cognitive decline compared to A + T + males (p<0.0001). Sex also marginally moderated the mediating effect of tau on the relationship between amyloid and cognitive decline (p=0.046). Discussion Sex differences in vulnerability to tau pathology in presence of amyloid can shape cognitive decline trajectories. Highlights A + T - males showed faster cognitive decline compared to A + T - females A + T + females showed faster cognitive decline compared to A + T + males Tau status significantly mediated the relationship between amyloid status and cognitive decline Sex marginally moderated the mediating relationship between amyloid, tau, and cognitive decline The findings point to sex differences in the impact of tau pathology on cognition
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".