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Related Experiment Video

Updated: Mar 21, 2026

Multi-Modal Home Sleep Monitoring in Older Adults
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Machine Learning-Based Sleep Electroencephalographic Brain Age Index and Dementia Risk: An Individual Participant

Haoqi Sun1, Sasha Milton2, Yi Fang2

  • 1Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts.

JAMA Network Open
|March 19, 2026
PubMed
Summary
This summary is machine-generated.

A higher electroencephalography (EEG) brain age index (BAI) in sleep is linked to an increased risk of developing dementia. This finding suggests BAI could be a valuable noninvasive marker for early dementia detection in community settings.

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Area of Science:

  • Neuroscience
  • Gerontology
  • Biomedical Engineering

Background:

  • Sleep electroencephalography (EEG) microstructures are crucial for cognition and change with age.
  • Interpreting complex sleep EEG data conventionally is challenging.
  • The machine learning-based EEG brain age index (BAI) quantifies the difference between brain age derived from sleep EEG and chronological age.

Purpose of the Study:

  • To investigate the association between the sleep EEG-based brain age index (BAI) and the risk of incident dementia in community-dwelling populations.

Main Methods:

  • An individual participant data (IPD) meta-analysis pooled data from five longitudinal cohorts.
  • Sleep EEG data from overnight, home-based polysomnography were analyzed using interpretable machine learning to compute BAI.
  • Fine-Gray models and random-effects meta-analysis were employed to assess the association between BAI and incident dementia, considering death as a competing risk.

Main Results:

  • The meta-analysis included 7105 participants across five cohorts (MESA, ARIC, FHS-OS, MrOS, SOF).
  • Each 10-year increase in BAI was associated with a 39% higher risk of incident dementia (HR, 1.39; P < .001).
  • This association remained significant after adjusting for covariates, comorbidities, apnea-hypopnea index, and apolipoprotein E ε4 status.

Conclusions:

  • A higher sleep EEG-based BAI is significantly associated with an increased risk of incident dementia.
  • The findings underscore the potential of BAI as a noninvasive digital marker for early dementia detection in community settings.