Neuroimaging biomarkers of the Amyloid, Tau, Neurodegeneration and Vascular framework in association with sleep duration changes over time
Bibliographic record
Abstract
Abstract Background Both short and long sleep duration were previously associated with incident dementia, but underlying mechanisms of this association remains unknown. This project aims to evaluate how self‐reported sleep duration and its change over time associate with (A)myloid, (T)au, (N)eurodegeneration and (V)ascular neuroimaging markers of Alzheimer’s disease (AD). Method Within the Framingham Heart Study, two samples were studied: 271 participants (age:53.6±8.0 years; 51%M) who underwent 11C‐PiB amyloid (global, precuneus) and 18F‐Flortaucipir tau (several medial cortical limbic structures) PET imaging; and 2165 participants (age:61.3±11.1 years; 45%M) who underwent an MRI. To estimate neurodegeneration, total brain volume was extracted from MRI. Vascular MRI metrics included white matter hyperintensities (continuous, and dichotomous indicator for extensive for age), covert brain infarcts, and average free‐water. Self‐reported sleep duration was assessed both at the time of neuroimaging testing and around 15 years before, and split by categories (≤6h, 7‐8h, ≥9h). Sleep duration change over time was assessed by change between categories and by continuous delta change (split by negative and positive values for decreased or increased respectively). Logistic and linear regression models were tested between self‐reported sleep duration and neuroimaging metrics, adjusted for age and age2, sex, PET camera, APOE4 carrier status, depression, diabetes, hypertension, and prevalent cardiovascular diseases. Results No association was observed between cross‐sectional self‐reported sleep duration and neuroimaging metrics. Transitioning to longer sleep over time (≤6h to ≥9h and 7‐8h to ≥9h as compared to consistently sleeping 7‐8h) was associated with higher white matter hyperintensities burden (extensive, OR[95%CI]:3.50[0.95‐12.92], p = 0.040;ß[SE]:0.25[0.10], p = 0.015) and higher free‐water (ß[SE]:0.021[0.007], p = 0.003;ß[SE]:0.009[0.002], p = 0.0002). When looking at continuous sleep duration change, increasing sleep duration over time was also associated with higher white matter hyperintensities burden (extensive, OR[95%CI]:1.26[1.02‐1.55], p = 0.032;ß[SE]:0.10[0.04], p = 0.007) and higher free‐water (ß[SE]:0.002[0.001], p = 0.031). Self‐reported sleep duration change was not associated with PET amyloid or tau outcomes. Conclusion Vascular pathology in the brain as evidenced by higher white matter hyperintensities burden and free‐water is associated with sleep duration that is getting longer over time, thus potentially explaining its association with dementia risk. In fact, elongation of sleep duration may be an early change in the AD trajectory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".