Association of choroid plexus volume with white matter microstructure, glymphatic function, and peripheral systemic inflammation in Alzheimer’s disease
Bibliographic record
Abstract
There has been growing attention to the role of choroid plexus (CP) in neurodegenerative diseases. However, its relationship with various pathophysiological changes in Alzheimer's Disease (AD) remains unclear. The purpose of this study is to investigate the relationship between CP volume (CPV) and white matter microstructure, cognitive function, glymphatic function, and peripheral systemic inflammation in AD. A total of 1351 participants with cognitive impairment who had available 3 T MRI scans were included from ADNI. CPV was automatically segmented using Gaussian Mixture Model (GMM). The Mini-Mental State Examination (MMSE) was employed to assess cognitive function. PSMD and DTI-ALPS based on DTI sequence were used to reflect white matter microstructure and glymphatic system. Peripheral systemic inflammation was represented by the neutrophil-lymphocyte ratio (NLR). Group comparisons and correlations were adjusted for age, sex, education and APOE4 carrier status. Participants with AD exhibited larger CPV (p < 0.001), higher PSMD (p < 0.001) and NLR (p = 0.035), and lower DTI-ALPS (p < 0.001) compared to those with subjective cognitive decline (SCD). CP enlargement was independently associated with higher PSMD (β = 0.223, p < 0.001) and worse cognitive function both cross-sectionally (β = -0.212, p < 0.001) and longitudinally (β = -0.214, p < 0.001). Furthermore, PSMD partially mediates the impact of CP enlargement on the severity and progression of cognitive function. Partial correlation analysis revealed that CP enlargement was associated with higher NLR (r = 0.101, p = 0.001) and lower DTI-ALPS (r = -0.241, p < 0.001). These findings suggest that CPV may reflect underlying pathophysiological processes in AD and serve as a biomarker for white matter damage and cognitive impairment progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".