Circadian rhythms in older adults are associated with sleep quality, cognitive function, and ß‐amyloid burden: an accelerometry analysis of the Lifestyle Enriching Activities for Research in Neuroscience Intervention Trial ‐ LEARNit
Bibliographic record
Abstract
Abstract Background Several studies demonstrate circadian rhythm disturbances in patients with Alzheimer’s disease. However, less is known about circadian rhythms in older adults with early mild cognitive impairment. Wrist‐worn accelerometers provide continuous, objective, high resolution quantification of 24‐hour rest activity rhythms. This study examines the relationship between circadian rhythms and sleep, cognition, and ß‐amyloid (Aß) burden. Method This study examines baseline data from the “Lifestyle Enriching Activities for Research in Neuroscience Intervention Trial” (LEARNit). Sixty‐six older adults ages 55‐80 experiencing early cognitive changes wore a GENEActiv accelerometer for approximately 30 consecutive days. Accelerometer data was analyzed using the R package GGIR (version 2.8‐1), and circadian rhythm measures were extracted using the GGIR secondary package ActCR (version 0.3.0). Circadian rhythm variables include intradaily variability (fragmentation), interdaily stability (rhythm synchronization to light‐dark cycle), acrotime (peak activity time), and Midline Estimated Statistics of Rhythm or MESOR (mean activity level). Up‐MESOR and Down‐MESOR represent the timing of activity increasing above or decreasing below MESOR, respectively—lower values of each indicate a phase advance (shift towards morning), whereas higher values indicate a phase delay (shift towards evening). Sleep was assessed as mean sleep efficiency and Wake After Sleep Onset, or WASO (accumulated wakefulness after sleep onset). Cognitive tests include the Montreal Cognitive Assessment (MoCA) for global cognition and attention/processing speed (Digit Symbol Task). Aß burden was measured by positron emission tomography standard uptake value ratio for fifty‐six participants. Age‐adjusted linear regression models were used to test associations between circadian rhythms and sleep, cognition, and Aß. Result Participant characteristics are summarized in Table 1 and results are summarized in Figure 1. Intradaily variability (b = ‐0.095, p = 0.03) and interdaily stability (b = 0.34, p = 0.01) were both associated with mean sleep efficiency. Intradaily variability (b = 1.41, p<0.001) and interdaily stability (b = ‐4.45, p<0.001) were associated with WASO. Up‐MESOR was associated with MoCA total score (b = ‐0.41, p = 0.03). Up‐MESOR (b = ‐2.12, p = 0.006), Down‐MESOR (b = ‐1.99, p = 0.02), and acrotime (b = ‐4.20, p<0.001) were associated with Digit Symbol score. Down‐MESOR was significantly associated with Aß (b = ‐0.029, p = 0.02). Conclusion Circadian rhythm robustness is positively associated with better sleep quality. Participants with dynamic circadian rhythm phases demonstrated poorer cognition and higher Aß burden.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".