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Record W4410444332 · doi:10.1038/s41398-025-03389-1

Associations between sleep quality, plasma neurofilament light, and cognition in older adults without dementia

2025· article· en· W4410444332 on OpenAlexfundaboutno aff
Hai-Hua Guo, Yan Fu, Liang-Yu Huang, Ze-Hu Sheng, Lan Tan, Zuo-Teng Wang

Bibliographic record

VenueTranslational Psychiatry · 2025
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNational Institutes of HealthH. Lundbeck A/SServierEisaiGenentechIXICONational Natural Science Foundation of ChinaNorthern California Institute for Research and EducationNovartis Pharmaceuticals CorporationUniversity of California, San DiegoBioClinicaU.S. Department of DefenseMeso Scale DiagnosticsAlzheimer's Disease Neuroimaging InitiativeUniversity of Southern CaliforniaBristol-Myers SquibbEli Lilly and CompanyBiogenAlzheimer's Association
KeywordsDementiaCognitionSleep (system call)MedicineSleep qualityPsychologyClinical psychologyAudiologyPsychiatryInternal medicineDisease

Abstract

fetched live from OpenAlex

The relationship between sleep quality, neurofilament light chain (NFL), and cognitive impairment, including the potential effect of plasma NFL in this association, remains unclear. Using the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, we excluded individuals with dementia or a history of sleep-related medication use at baseline, including 640 participants with complete sleep assessments and covariates. Sleep quality was assessed using the Neuropsychiatric Inventory sleep subscale, which includes ratings of frequency, severity, and their product, with higher scores indicating poorer sleep quality. Baseline and follow-up demographics, sleep indices, plasma NFL levels, and cognition scores (including Mini-Mental State Examination [MMSE], Montreal Cognitive Assessment [MoCA], Alzheimer's Disease Assessment Scale-Cognitive Subscale [ADAS13], Clinical Dementia Rating Scale-Sum of Boxes [CDRSB], Executive Function [EF], Language [LAN], and Memory [MEM]) were also collected. Multivariable linear regression examined the associations between baseline sleep quality, plasma NFL, and cognition, as well as the relationship between sleep quality and longitudinal cognitive decline, calculated using linear mixed-effects models. Mediation analysis evaluated the role of plasma NFL in the sleep-cognition association. Multiple testing significance was corrected using false discovery rate, with results presented as Q-values. Poor sleep quality scores were associated with elevated plasma NFL levels (β: 0.055 to 2.645, P < 0.05), poorer cognition (ADAS13, CDRSB, EF, LAN, MEM; β: -0.188 to 1.279, Q < 0.05), and accelerated longitudinal cognitive decline (MoCA; β: -0.005, Q < 0.05) in both models, with sensitivity analyses supporting these findings. Furthermore, plasma NFL levels partially mediated the relationship between sleep quality and both baseline cognition (ADAS13, CDRSB, LAN, MEM; P < 0.05) and longitudinal cognitive decline (MoCA; P < 0.05), with mediation proportions ranging from 9.2% to 26.7%. Poorer sleep quality was associated with cognitive impairment and accelerated cognitive decline, suggesting its potential role in Alzheimer's disease. These associations may be partially mediated by neuroaxonal injury.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

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

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 head0.037
GPT teacher head0.345
Teacher spread0.308 · 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 teacher head, 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

Citations6
Published2025
Admission routes2
Has abstractyes

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