Impaired 24-h activity patterns are associated with an increased risk of Alzheimer's disease, Parkinson's disease, and cognitive decline

Abstract

Background: Sleep-wake regulating circuits are affected during prodromal stages in the pathological progression of both Alzheimer's disease (AD) and Parkinson's disease (PD), and this disturbance can be measured passively using wearable devices. Our objective was to determine whether accelerometer-based measures of 24-h activity are associated with subsequent development of AD, PD, and cognitive decline.

Methods: This study obtained UK Biobank data from 82,829 individuals with wrist-worn accelerometer data aged 40 to 79 years with a mean (± SD) follow-up of 6.8 (± 0.9) years. Outcomes were accelerometer-derived measures of 24-h activity (derived by cosinor, nonparametric, and functional principal component methods), incident AD and PD diagnosis (obtained through hospitalization or primary care records), and prospective longitudinal cognitive testing.

Results: One hundred eighty-seven individuals progressed to AD and 265 to PD. Interdaily stability (a measure of regularity, hazard ratio [HR] per SD increase 1.25, 95% confidence interval [CI] 1.05-1.48), diurnal amplitude (HR 0.79, CI 0.65-0.96), mesor (mean activity; HR 0.77, CI 0.59-0.998), and activity during most active 10 h (HR 0.75, CI 0.61-0.94), were associated with risk of AD. Diurnal amplitude (HR 0.28, CI 0.23-0.34), mesor (HR 0.13, CI 0.10-0.16), activity during least active 5 h (HR 0.24, CI 0.08-0.69), and activity during most active 10 h (HR 0.20, CI 0.16-0.25) were associated with risk of PD. Several measures were additionally predictive of longitudinal cognitive test performance.

Conclusions: In this community-based longitudinal study, accelerometer-derived metrics were associated with elevated risk of AD, PD, and accelerated cognitive decline. These findings suggest 24-h rhythm integrity, as measured by affordable, non-invasive wearable devices, may serve as a scalable early marker of neurodegenerative disease.

Keywords: Alzheimer’s disease; Cognitive aging; Parkinson’s disease; Rest-activity rhythms.

Fig. 1

Quantitative metrics of 24-h activity patterns. Left, cosinor variables are calculated by fitting a cosine function to the accelerometer data. Mesor (midline-estimating statistic of rhythm) is the mean activity level of the cosine wave. Amplitude is defined as the distance between the mean activity level and the peak of the cosine wave. Right, nonparametric variables do not require fitting a shape to the accelerometer data. Interdaily stability is defined as the regularity of the 24-h rhythm across days, whereas intradaily variability represents the fragmentation of activity within the average 24-h day. L5 (least active 5 h) represents the mean activity level during what is typically time in bed, and M10 (most active 10 h) represents mean activity level during the day

Fig. 2

Conversion to Alzheimer’s and Parkinson’s disease by 24-h rhythm quartiles. Survival curves with 95% confidence intervals for A Alzheimer’s disease and B Parkinson’s disease based on quartiles for each of the 24-h rhythm metrics. The y-axes represent the percent of individuals converting to Alzheimer’s or Parkinson’s disease out of the full study sample. Abbreviations: IV, intradaily variability; IS, interdaily stability, L5, least active 5 h; M10, most active 10 h

Fig. 3

Adjusted hazard ratios for Alzheimer’s and Parkinson’s disease by 24-h rhythms. Forest plots showing standardized hazard ratios (HR) per standard deviation increase and 95% confidence intervals (CI) for developing A Alzheimer’s disease and B Parkinson’s disease, from Cox regression models including age at actigraphy collection, sex, college education, baseline general health, baseline body mass index, and baseline Townsend deprivation index. Abbreviations: IV, intradaily variability; IS, interdaily stability, L5, least active 5 h; M10, most active 10 h

Fig. 4

Average 24-h activity curves and functional principal components analysis for Parkinson’s disease. A Average activity curves in individuals who progressed to Parkinson’s disease (red) or matched individuals who did not progress to Parkinson’s disease (blue). Each plotted point represents a 30-s epoch of average activity. Daytime activity levels are visibly lower in individuals who progressed to Parkinson’s disease. B Four components were derived from 24-h data from individuals who progressed to Parkinson’s disease and matched controls. The solid line represents the same average activity curve in each of the four plots, plotted against clock time. Each of the four components is visualized by showing the average weight of positive fPCA scores (dashed) or negative scores (dotted) added to the average activity pattern. C For the first component, the right violin plot shows weights (scores) for every individual, with a black bar representing the group mean