A biological age biomarker based on circadian rest‐activity rhythms and risk of dementia

Background Circadian function is altered with aging, leading to changes in the ∼24‐h rhythms of behavior and physiology. Based on circadian rest‐activity rhythms (CRAR), we previously constructed a biological age biomarker to characterize the aging profile of circadian function—circadian age (CircAge)—in older adults (>65 years) and showed its association with risk of Alzheimer’s dementia. Here, we constructed CircAge in middle‐to‐older‐aged adults and tested whether it predicts all‐cause dementia. Method Participants from the UK Biobank with valid actigraphy data were studied (n = ∼97,000; 42‐78 years old). We developed a machine‐learning‐based regression model with 23 CRAR features derived from actigraphy (using cosinor, nonparametric, uniform‐phase‐empirical‐mode‐decomposition, and detrended‐fluctuation analyses). The fitting target was chronological age (ChrAge), and the prediction output was defined as CircAge. Model parameters were optimized using cross validation on 47,234 participants not performing shift work and without mental/behavioral or nervous system diseases. The optimized model was applied to all dementia‐free participants with valid CRAR (n = 80,805) to obtain their CircAge. Result CircAge was 1.03±0.01 years older per one‐year older in ChrAge that explained ∼25% of the variance of CircAge (p