Circadian and sleep/wake-dependent variations in tau phosphorylation are driven by temperature
Bibliographic record
Abstract
STUDY OBJECTIVES: Aggregates of hyperphosphorylated tau protein are a hallmark of Alzheimer's disease (AD) and other tauopathies. Sleep disturbances are common in AD patients, and insufficient sleep may be a risk factor for AD. Recent evidence suggests that tau phosphorylation is dysregulated by sleep disturbances in mice. However, the physiological regulation of tau phosphorylation during the sleep-wake cycle is currently unknown. We thus aimed to determine whether tau phosphorylation is regulated by circadian rhythms, inherently linked to the sleep-wake cycle. METHODS: To answer these questions, we analyzed by Western blotting tau protein and associated kinases and phosphatases in the brains of awake, sleeping, and sleep-deprived B6 mice. We also recorded their temperature. RESULTS: We found that tau phosphorylation undergoes sleep-driven circadian variations as it is hyperphosphorylated during sleep but not during acute sleep deprivation. Moreover, we demonstrate that the mechanism behind these changes involves temperature, as tau phosphorylation was inversely correlated with circadian- and sleep deprivation-induced variations in body temperature, and prevented by housing the animals at a warmer temperature. Notably, similar changes in tau phosphorylation were reproduced in neuronal cells exposed to temperatures recorded during the sleep-wake cycle. Our results also suggest that inhibition of protein phosphatase 2A (PP2A) may explain the hyperphosphorylation of tau during sleep-induced hypothermia. CONCLUSION: Taken together, our results demonstrate that tau phosphorylation follows a circadian rhythm driven mostly by body temperature and sleep, and provide the physiological basis for further understanding how sleep deregulation can affect tau and ultimately AD pathology.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".