Agitation, Oxidative Stress, and Cytokines in Alzheimer Disease: Biomarker Analyses From a Clinical Trial With Nabilone for Agitation
Bibliographic record
Abstract
The endocannabinoid system has been a target of interest for agitation in Alzheimer disease (AD) because of potential behavioral effects and its potential impact on mechanisms implicated in AD such as oxidative stress (OS) and neuroinflammation. We explored whether serum markers of OS and neuroinflammation were associated with response to the cannabinoid nabilone in agitated patients with AD (N = 38). All participants were enrolled in a 14-week, double-blind, cross-over trial comparing nabilone to placebo (6 weeks each) with a 1-week washout between phases. Samples were collected at the start and end of each phase. The cross-sectional relationship agitation (Cohen Mansfield Agitation Inventory) and OS and inflammatory markers were investigated to select markers of interest. Significant markers were then explored for their relationship with response. The OS marker, 4-hydroxynonenal (4-HNE; F 1, 35 = 6.41, P = .016), and the proinflammatory cytokine, tumor necrosis factor-α (TNF-α; F 1, 29 = 3.97, P = .06), were associated with agitation severity, and TNF-α remained significantly associated ( F 2, 25 = 3.69, P = .04) after adjustment for cognition. In the placebo phase, lower baseline 4-HNE was associated with decreases in agitation severity only (b = 0.01, P = .01), while lower baseline TNF-α was associated with decreases in agitation severity in the nabilone phase only (b = 1.14, P = .045). Changes in 4-HNE were not associated with changes in agitation severity in either phase. In the nabilone phase, lower baseline TNF-α was associated with decreases in agitation severity (b = 1.14, P = .045), and decreases in TNF-α were associated with decreases in agitation severity (b = 1.12, P = .006). These findings suggest that OS and neuroinflammation may be associated with agitation severity, while nabilone may have anti-inflammatory effects.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".