0725 Self-reported sleep quality and sleep architecture are associated with plasma neurofilament light in older adults without dementia
Bibliographic record
Abstract
Abstract Introduction Sleep disruption is common in older adults with multiple chronic conditions and can occur before the clinical onset of Alzheimer’s disease (AD). Sleep disruption plays an important role in AD pathology and has been associated with neuro-imaging evidence of AD, and cerebrospinal fluid elevations of amyloid, tau, and neurodegeneration (ATN) biomarkers. Plasma ATN biomarkers are increasingly used in AD research. We examined the associations of self-reported sleep quality and electroencephalogram (EEG) sleep architecture with plasma ATN biomarkers in sedentary older adults without dementia. Methods We used baseline data from an ongoing randomized controlled trial that examines the effect of physical activity on sleep and cognition in community-dwelling sedentary older adults without dementia (Montreal Cognitive Assessment [MoCA]>17, n=102). Participants reported demographics, completed the Pittsburgh Sleep Quality Index (PSQI) questionnaire, and provided blood samples to measure plasma ATN biomarkers [amyloid-beta (Aβ)42/42, total-tau (T-tau), and neurofilament light (NFL)]. Two-night home-based sleep EEG measures (Sleep Profiler) were collected from 56 of the 102 participants. Multiple regression models were conducted to test the associations between sleep measures and plasma ATN biomarkers. Results Participants were aged 69.9 ± 6.0 years, 80% were women, and they had 3.1±1.7 chronic conditions. Most had intact cognitive function (68.6% MoCA≥ 26) and 28.6% of the sample had mild cognitive impairment (17< MoCA< 25). In models adjusted for age, sex, race, education, and number of comorbidities, higher PSQI scores (β=0.84, 95% confident interval (CI)= [0.12,1.62]), longer non-rapid eye movement (NREM) N3 duration (β=4.43, 95% CI= [0.48,8.18]), and higher REM latency (β=0.04, 95% CI= [0.02, 0.05]) were associated with higher NFL. Longer REM sleep duration (β=-11.13, 95% CI= [-20.55, -1.71]) was associated with lower NFL. There were no other significant associations of sleep measures with other ATN biomarkers. Conclusion Self-reported sleep quality and sleep architecture were associated with plasma NFL among older adults with intact cognition and mild cognitive impairment. Plasma NFL may be a sensitive and promising biomarker that links sleep disruption and AD-related outcomes in older adults without dementia. Future research with a larger sample is needed to further test this association. Support (if any) National Institute of Nursing Research R00NR016484
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".