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Record W4206677540 · doi:10.1002/alz.055596

Sleep efficiency is associated with amyloid burden, cerebral blood flow, and cognition in healthy older adults

2021· article· en· W4206677540 on OpenAlexaboutno aff
Laura Fenton, Daniel Albrecht, Lisette Isenberg, Vahan Aslanyan, Joy Stradford, Teresa Monreal, Judy Pa

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
Fundersnot available
KeywordsSleep (system call)Cerebral blood flowEffects of sleep deprivation on cognitive performanceMontreal Cognitive AssessmentCognitionPittsburgh Sleep Quality IndexAudiologyMedicineActigraphyPsychologyCardiologyInternal medicineCognitive impairmentSleep qualityPsychiatryCircadian rhythm

Abstract

fetched live from OpenAlex

Abstract Background Prior work has identified associations between sleep quality and amyloid‐beta (Aβ). However, how sleep efficiency relates to Aβ, cerebral blood flow (CBF), and cognition are not well understood. The objective of this study was to evaluate these relationships and the modifying role of APOE4 status. Method Objective sleep efficiency, Aβ, CBF, and cognitive performance on neuropsychological assessments (MoCA, Flanker, CVLT, and Complex Figure) were examined in a sample of 52 non‐demented, older adults (age=66.5+6.82, 67% female, 27% APOE4 carriers). Sleep efficiency, defined as the percentage of time asleep within a given sleep period, was objectively measured using the GENEActiv tri‐axis accelerometer for an average of 30.25 days. Aβ was measured in vivo using positron emission tomography and the F‐18 florbetaben tracer to calculate composite SUVR scores. Global gray matter CBF was quantified using a pseudo‐continuous arterial spin labeling MRI scan. All analyses were adjusted for age, sex, and education (for cognitive measures). Result Overall, higher sleep efficiency was associated with lower Aβ burden (p=.04), higher CBF (p=.03), higher MoCA scores (p=.05) and a trend for better Complex Figure Test recall (p=.07). There was a significant moderating effect of APOE4 status on the association between sleep and Aβ, such that poorer sleep efficiency was associated with higher Aβ burden in APOE4 carriers only (p=.01). APOE4 moderation was not observed for CBF. When stratified by high and low sleep efficiency levels (median split), APOE4 carrier status predicted Aβ burden only in individuals with low sleep efficiency (p =.02). Additionally, sleep efficiency predicted performance on long delay free recall of the CVLT and Complex Figure Test (p=.01) in the low sleep efficiency group only. No association between sleep efficiency and Flanker were observed. Conclusion These results provide evidence that sleep efficiency is associated with brain health and cognition, and suggest a modifying effect of APOE4 on the relationship between sleep and amyloid. Mechanistic evidence from animal models and human studies suggests that impaired slow wave activity during NREM sleep may disrupt dynamic fluid oscillations important for amyloid clearance and brain blood flow. Future work is needed to understand the causal and temporal relationships between these processes.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.252
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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