Total Tau Protein Mediates the Association of Ischemic Cerebrovascular Disease with Cognitive Decline
Bibliographic record
Abstract
Background: Patients with transient ischemic attack (TIA) or ischemic stroke demonstrate an increased risk of cognitive dysfunction. Accumulating evidence indicates that ischemic cerebrovascular disease (ICVD) may interact with the amyloid/tau/neurodegeneration (AT[N]) biomarkers to promote dementia. However, the precise pathological mechanisms remain to be fully characterized. Objective: To elucidate the interrelationships among ICVD, ATN biomarkers in cerebrospinal fluid (CSF), and cognition. Methods: A total of 2524 participants were recruited from the CABLE study. ICVD referred to TIA/ischemic stroke. Cognitive performance was assessed by China Modified Mini-Mental State Examination (CM-MMSE) and Montreal Cognitive Assessment-b (MoCA-b). Multivariate linear regression analyses were performed to evaluate the associations of ICVD with CSF ATN biomarkers and cognition. Causal mediation analyses were used to identify whether the association was mediated by ATN biomarkers. Results: ICVD was associated with higher total-tau (t-tau) (p = 2.828×10-2) and poorer cognition (CM-MMSE: p = 1.539×10-5, MoCA-b: p = 4.552×10-6). Additionally, no discernible correlation surfaced between ICVD and amyloid-β (Aβ) 42 (p = 6.910×10-1) or phosphorylated tau (p-tau) (p = 4.324×10-1). The influence of ICVD on cognitive function was partially mediated by CSF t-tau (CM-MMSE: proportion: 2.74%, MoCA-b: proportion: 2.51%). Subgroup analyses revealed the influences of t-tau were especially evident in male (CM-MMSE: proportion: 5.45%, MoCA-b: proportion: 5.38%) and mid-life group (CM-MMSE: proportion: 9.83%, MoCA-b: proportion: 5.31%). Conclusions: These results delineated t-tau as a potential mediator for the influence of ICVD on cognition. Targeting brain ischemia and alleviating neuronal injury induced by ischemia may be a promising approach for preventing cognitive decline.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".