Slow wave sleep as a biomarker and therapeutic target for Alzheimer's disease
Bibliographic record
Abstract
Abstract Background Sleep disturbances are prevalent among individuals diagnosed with Alzheimer's disease (AD), typically manifested as low levels of slow‐wave sleep (SWS; N3 stage). Restoring SWS has been proposed as an intervention to slow AD progression. Trazodone, an antidepressant with sleep‐promoting properties, is frequently prescribed off‐label to improve sleep. Notably, it is well‐tolerated in elderly individuals and has been shown to specifically enhance SWS. Given its potential benefits, trazodone has been proposed as an intervention for AD. However, research on its effects beyond its antidepressant properties remains limited. This study aimed to evaluate the effects of chronic trazodone administration in a mouse model of AD, marking the first assessment of its potential as a disease‐modifying therapeutic for AD. Method We have developed a translationally‐focused administration paradigm for trazodone in C57BL/6J mice and demonstrated that acute trazodone administration dose‐dependently enhances NREM sleep and increases delta power during NREM sleep. Using this validated protocol, we administered trazodone (60mg/kg) daily to APP NL‐F mice (up to 60 days) to evaluate its effects on EEG power spectra, behaviour/cognition, and neuropathology. Two age groups were selected to represent early (9 months) and intermediate (14 months) stages of neuropathology. Result Preliminary analysis revealed that trazodone consistently enhances slow oscillation and delta power during NREM sleep over a 60‐day treatment period ( p = 0.0040, comparing baseline with 1, 4, and 8 weeks of treatment in the 9‐month‐old cohort). Importantly, preliminary neuropathological analysis reveals that 60 days of trazodone treatment leads to lower levels of Aβ pathologies, particularly in male mice. Specifically, in male APP NL‐F mice treated with trazodone from 14 to 16 months of age, the treatment was associated with significantly lower amyloid plaques in the dorsal hippocampus (46 % lower, p = 0.0174) and fibrillary plaques in the parietal cortex (18% lower, p = 0.0495). Furthermore, trazodone treatment in the male mice showed a downward trend in insoluble Aβ 42 levels (40% lower, p = 0.0555). Touchscreen cognitive testing is ongoing in 13‐ to 14‐month‐old APP NL‐F mice. Conclusion Our research suggests that trazodone should be explored as a potential disease‐modifying therapeutic for 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".