24S-Hydroxycholesterol Is Associated with Agitation Severity in Patients with Moderate-to-Severe Alzheimer’s Disease: Analyses from a Clinical Trial with Nabilone
Bibliographic record
Abstract
BACKGROUND: Agitation is a prevalent and difficult-to-treat symptom of Alzheimer's disease (AD). The endocannabinoid system (ECS) has been a target of interest for the treatment of agitation. However, ECS signaling may interact with AD-related changes in brain cholesterol metabolism. Elevated brain cholesterol, reflected by reduced serum 24-S-hydroxycholesterol (24S-OHC), is associated with reduced membrane fluidity, preventing ligand binding to cannabinoid receptor 1. OBJECTIVE: To assess whether 24S-OHC was associated with agitation severity and response to nabilone. METHODS: 24S-OHC was collected from AD patients enrolled in a clinical trial on nabilone at the start and end of each phase. This allowed for the cross-sectional and longitudinal investigation between 24S-OHC and agitation (Cohen Mansfield Agitation Inventory, CMAI). Post-hoc analyses included adjustments for baseline standardized Mini-Mental Status Exam (sMMSE), and analyses with CMAI subtotals consistent with the International Psychogeriatric Association (IPA) definition for agitation (physical aggression and nonaggression, and verbal aggression). RESULTS: 24S-OHC was not associated with CMAI scores cross-sectionally or longitudinally, before and after adjusting for baseline sMMSE. However, 24S-OHC was associated with greater CMAI IPA scores at baseline (F(1,36) = 4.95, p = 0.03). In the placebo phase only, lower 24S-OHC at baseline was associated with increases in CMAI IPA scores (b = -35.2, 95% CI -65.6 to -5.0, p = 0.02), and decreases in 24S-OHC were associated with increases in CMAI IPA scores (b = -20.94, 95% CI -57.9 to -4.01, p = 0.03). CONCLUSION: 24S-OHC was associated with agitation severity cross-sectionally, and longitudinally in patients with AD. However, 24S-OHC did not predict treatment response, and does not change over time with nabilone.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".