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Record W7117297734 · doi:10.1002/alz70856_104172

Sleep spindles and slow oscillations predict amyloid beta, tau pathology, and cognitive decline in persons with mild to moderate Alzheimer's Disease.”

2025· article· en· W7117297734 on OpenAlexaff
Arsenio Páez, Sam O Gillman, Shahla Bakian Dogaheh, Anna Carnes, Farida Dakterzada, Ferrán Barbé, Thien Thanh Dang‐Vu, Gerard Piñol‐Ripoll

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsConcordia UniversityInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsCognitive declineNeurodegenerationCognitionSleep spindleSleep (system call)Amyloid (mycology)Disease

Abstract

fetched live from OpenAlex

BACKGROUND: Sleep plays vital roles in brain-health and cognition, including regulating clearance of β-amyloid (Aβ) and tau proteins that hallmark Alzheimer's disease (AD). Changes in sleep physiology can predate cognitive symptoms by decades in AD, but it remains unclear which sleep characteristics predict cognitive and neurodegenerative changes after AD onset. METHODS: Using data from a prospective cohort study of mild-to-moderate AD (n = 60, 30 female, mean age 74.7) in Lleida, Spain, we analysed non-rapid eye-movement sleep spindles and slow oscillations (SO) at baseline and their associations with baseline amyloid-beta and tau, and with cognition from baseline to three-years follow-up. Participants underwent polysomnography (PSG), blood and cerebrospinal fluid draws for amyloid and tau at baseline, and neuropsychological assessment at baseline, 12, 24 and 36 months with the Mini-Mental Status Examination (MMSE), California verbal learning test (CVLT), Rey-Osterrieth Complex Figure Test (ROCF), Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog). Spindle and SO detection were performed using in-house, open-source software packages developed at Concordia University. Associations between SO and spindle and SO duration, density, power, amplitude, AD biomarkers, and cognition from baseline to 36 months were investigated with false discovery rate-adjusted generalised linear models controlling for age, sex, apnoea-hypopnea index. RESULTS: We found previously unreported associations between spindle and SO activity, biomarkers, and cognition in persons with AD. Higher spindle and SO density, duration, amplitude and power predicted significant changes in amyloid-beta 42 (β= 69.3 p = 0.001), phosphorylated (pTau-181) (β= 7.92, p = 0.001) and total-tau, and tau/Aβ42 (β= -0.52, p = 0.001), clinically and statistically significantly lower Alzheimer's Disease Assessment Scale Cognitive Subscale (better cognitive performance) (β= -9.0, p = 0.001) and higher Mini-Mental State Examination scores (better cognitive performance) (β= 15.2, p = 0.01) from baseline to 36-months, and significant changes in verbal and visual memory on the ROCF and CVLT. Spindles and SO activity also mediated the effect of pTau181/aβ42 on cognition (41-81%), while pTau181/aβ42 moderated the effect of spindles and SO on cognition. CONCLUSIONS: Our findings demonstrate that spindle and SO activity during sleep constitute predictive and non-invasive biomarkers of neurodegeneration and cognition in AD patients and novel treatment targets for delaying cognitive decline and AD progression.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0020.000

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 head0.035
GPT teacher head0.304
Teacher spread0.269 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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