Associations of cholinergic white matter hyperintensity volume with cognitive decline and incident dementia in older adults: a cohort study
Bibliographic record
Abstract
Abstract Background Few studies take both the volume and location of white matter hyperintensities (WMHs) into account to explore the association between WMH burden within the cholinergic pathways and cognitive impairment. We aimed to investigate associations of cholinergic WMH volume (WMHV) with global cognitive function, cognitive decline, and incident dementia in older adults, which may help us identify a potential imaging biomarker. Methods We assessed non-demented participants (n = 751, mean age 60 years) from the Taizhou Imaging Study with brain MRI at baseline and repeated measures of cognition over 5 years of follow-up. WMHV in the whole brain, the cholinergic pathways, and different tracts in the Montreal Neurologic Institute (MNI) standard space were analyzed. Linear regression, Cox regression, and partial correlation tests were performed to investigate associations between global and regional WMHV and cognitive outcomes. Results During follow-up, cholinergic WMHV was associated with an annual decline of Mini-Mental State Examination (MMSE) (β coefficient, -0.239; P = 0.004), and incident dementia (HR = 3.54; 95%CI: 2.05–6.10). Within the cholinergic pathways, WMHs in corpus callosum and corona radiata were significantly related to incident dementia. Global WMHV was also associated with global cognitive decline (β coefficient, -0.049; P = 0.002). However, greater global WMHV only slightly increased the risk of incident dementia (HR = 1.23; 95%CI: 1.11–1.35). Neither global nor cholinergic WMHV was associated with MMSE in cross-sectional analysis. Conclusions Cholinergic WMHV is associated with longitudinal cognitive decline and incident dementia in older adults, which might result from disruption of corpus callosum and corona radiata. These findings highlight the value of cholinergic WMHV as a potential indicator of cognitive deterioration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".