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. 2020 Sep 1;3(9):e2017357.
doi: 10.1001/jamanetworkopen.2020.17357.

Association of Sleep Electroencephalography-Based Brain Age Index With Dementia

Elissa Ye  1 , Haoqi Sun  1 , Michael J Leone  1 , Luis Paixao  1 , Robert J Thomas  2 , Alice D Lam  1 , M Brandon Westover  1
Affiliations

Association of Sleep Electroencephalography-Based Brain Age Index With Dementia

Elissa Ye et al. JAMA Netw Open. .

Abstract

Importance: Dementia is an increasing cause of disability and loss of independence in the elderly population yet remains largely underdiagnosed. A biomarker for dementia that can identify individuals with or at risk for developing dementia may help close this diagnostic gap.

Objective: To investigate the association between a sleep electroencephalography-based brain age index (BAI), the difference between chronological age and brain age estimated using the sleep electroencephalogram, and dementia.

Design, setting, and participants: In this retrospective cross-sectional study of 9834 polysomnograms, BAI was computed among individuals with previously determined dementia, mild cognitive impairment (MCI), or cognitive symptoms but no diagnosis of MCI or dementia, and among healthy individuals without dementia from August 22, 2008, to June 4, 2018. Data were analyzed from November 15, 2018, to June 24, 2020.

Exposure: Dementia, MCI, and dementia-related symptoms, such as cognitive change and memory impairment.

Main outcomes and measures: The outcome measures were the trend in BAI when moving from groups ranging from healthy, to symptomatic, to MCI, to dementia and pairwise comparisons of BAI among these groups.

Findings: A total of 5144 sleep studies were included in BAI examinations. Patients in these studies had a median (interquartile range) age of 54 (43-65) years, and 3026 (59%) were men. The patients included 88 with dementia, 44 with MCI, 1075 who were symptomatic, and 2336 without dementia. There was a monotonic increase in mean (SE) BAI from the nondementia group to the dementia group (nondementia: 0.20 [0.42]; symptomatic: 0.58 [0.41]; MCI: 1.65 [1.20]; dementia: 4.18 [1.02]; P < .001).

Conclusions and relevance: These findings suggest that a sleep-state electroencephalography-based BAI shows promise as a biomarker associated with progressive brain processes that ultimately result in dementia.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Paixao reported salary from Glenn Foundation for Medical Research during the conduct of the study. Dr Thomas reported receiving personal fees from Guidepoint Global, GLG Councils, and Jazz Pharmaceuticals outside the submitted work and owning a patent for an electrocardiography sleep spectrogram (licensed to MyCardio) and for an auto–continuous positive airway pressure algorithm (licensed to DeViliss-Drive). Dr Lam reported receiving grants from the National Institutes of Health and American Academy of Neurology Institute during the conduct of the study. Dr Westover reported serving as co-founder of Beacon Biosignals. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Brain Age Index (BAI) Across Dementia Groups
The dashed line indicates BAI = 0; MCI, mild cognitive impairment.
Figure 2.
Figure 2.. Associations of Neuropsychological Scores With Brain Age Index (BAI)
MoCA indicates Montreal Cognitive Assessment; MMSE, Mini-Mental State Examination.
Figure 3.
Figure 3.. Regression Analysis of Potential Brain Age Index (BAI) Covariates With Dementia
Squares indicate coefficients of covariates; whiskers, 95% CIs; AHI, apnea-hypopnea index; BMI, body mass index; ESS, Epworth Sleepiness Scale; and PLMI, periodic limb movement index.
Figure 4.
Figure 4.. Association of Brain Age Index (BAI) Features and Dementia
B and C, features names describe related sleep stage, frequency band, measure, statistic, and channel location of the feature in order. All correlations shown are statistically significant. REM indicates rapid eye movement; N, non–REM stage.
See this image and copyright information in PMC

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