Associations of plasma von Willebrand Factor levels with cognitive decline and neurodegeneration in older adults without dementia
Bibliographic record
Abstract
Background Previous studies have suggested that von Willebrand Factor (VWF) may be implicated in the pathogenesis of Alzheimer’s disease (AD). However, the association between plasma VWF levels and cognitive decline and neurodegeneration in older adults without dementia remains unclear. Methods We investigated the cross-sectional and longitudinal associations between plasma von Willebrand Factor (VWF) levels and cognitive decline, as measured by the Mini-Mental State Examination (MMSE) and the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB), as well as the volumes of six brain regions: the hippocampus, entorhinal cortex, middle temporal gyrus, fusiform gyrus, ventricles, and whole brain. Linear mixed-effects models were used to assess the association between plasma VWF levels and longitudinal changes in cognitive function and neuroimaging markers over time. Results The study cohort consisted of 340 older adults without dementia at baseline. We observed that lower plasma VWF levels were associated with a faster rate of cognitive decline (MMSE: coefficient = 0.204, 95% CIs = [0.030, 0.378], p-value = 0.021; CDR-SB: coefficient = −0.268, 95% CIs = [−0.374, −0.163], p-value <0.001). Additionally, lower plasma VWF levels were linked to a more rapid reduction in the volumes of the hippocampus (coefficient = 0.016, 95% CIs = [0.004, 0.027], p-value = 0.009), entorhinal cortex (coefficient = 0.031, 95% CIs = [0.014, 0.048], p-value <0.001), and fusiform gyrus (coefficient = 0.047, 95% CIs = [0.008, 0.085], p-value = 0.017), as well as a faster enlargement of the ventricles (coefficient = −0.380, 95% CIs = [−0.558, −0.203], p-value <0.001). However, no significant relationships were observed between plasma VWF levels and changes in the volumes of the middle temporal gyrus or the whole brain (all p-values > 0.05). Conclusion Our findings may contribute to the growing body of knowledge on the vascular contributions to cognitive function and may help identify potential biomarkers for the early detection and intervention of AD.
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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 | 0.001 | 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".