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Summary: Hippocampal atrophy is a prominent neurodegenerative feature of Alzheimer's disease and related dementias. Alterations in circadian rhythms can exacerbate cognitive aging and neurodegeneration. This study aimed to examine how dim light melatonin onset and melatonin levels are associated with hippocampal volume in cognitively healthy individuals. We studied data from 52 later‐life adults (mean age ± SD = 70.0 ± 6.3 years). T1‐weighted anatomical images from 3.0 T magnetic resonance imaging data were collected and processed using the BRAINSTools toolbox. Dim light melatonin onset was used to assess circadian timing. The area under the curve was calculated to quantify melatonin concentration levels 6 hr before bedtime, and 14‐day wrist actigraphy data were used to assess habitual bedtime. Multiple linear regression modelling with hippocampal volume as the dependent variable was used to analyse the data adjusting for age and sex. The average dim light melatonin onset was 19:45 hours (SD = 84 min), and area under the curve of melatonin levels 6 hr before habitual bedtime was 38.4 pg ml−1 × hr (SD = 29.3). We found that later dim light melatonin onset time (b = 0.16, p = 0.005) and greater area under the curve of melatonin levels 6 hr before habitual bedtime (b = 0.05, p = 0.046) were associated with greater adjusted hippocampal volume. The time between dim light melatonin onset and the midpoint of sleep timing was not associated with hippocampal volume. The findings suggest that earlier circadian timing (dim light melatonin onset) and reduced melatonin may be associated with reduced hippocampal volume in older adults. Future research will help researchers utilize circadian rhythm information to delay brain aging. [ABSTRACT FROM AUTHOR]

Summary: Sleep behaviour is an important contributing factor in healthy human ageing and cognitive function. Previous studies have linked sleep deficiency with cognitive decline in older adults. However, there is need for more prospective investigations that focus on specific domains of cognitive function. The present study analysed cross‐sectional and prospective associations between self‐reported sleep and cognitive function in the Midlife in the United States (MIDUS) study. Weekday and weekend sleep duration and habitual sleep quality were obtained via questionnaire data. Brief Test of Adult Cognition by Telephone was conducted to assess overall cognitive function, as well as episodic memory and executive function. We found significant trend for both long weekday and weekend sleep (>8 hr) and lower episodic memory scores in the overall sample. Sex‐specific cross‐sectional analysis demonstrated men with longer weekend sleep duration have lower overall cognitive function scores, and a negative association between weekend sleep and episodic memory scores. Women demonstrated a positive association between weekend sleep duration and executive function scores. There was no prospective significance for overall or sex‐specific analysis. Our present results suggest that sleep duration may contribute to cognitive function, and future studies should include objective sleep measurements and focus on the potential cognitive benefits of improving sleep to further elucidate this association. [ABSTRACT FROM AUTHOR]

Summary The accurate estimation of circadian phase in the real‐world has a variety of applications, including chronotherapeutic drug delivery, reduction of fatigue, and optimal jet lag or shift work scheduling. Recent work has developed and adapted algorithms to predict time‐consuming and costly laboratory circadian phase measurements using mathematical models with actigraphy or other wearable data. Here, we validate and extend these results in a home‐based cohort of later‐life adults, ranging in age from 58 to 86 years. Analysis of this population serves as a valuable extension to our understanding of phase prediction, since key features of circadian timekeeping (including circadian amplitude, response to light stimuli, and susceptibility to circadian misalignment) may become altered in older populations and when observed in real‐life settings. We assessed the ability of four models to predict ground truth dim light melatonin onset, and found that all the models could generate predictions with mean absolute errors of approximately 1.4 h or below using actigraph activity data. Simulations of the model with activity performed as well or better than the light‐based modelling predictions, validating previous findings in this novel cohort. Interestingly, the models performed comparably to actigraph‐derived sleep metrics, with the higher‐order and nonphotic activity‐based models in particular demonstrating superior performance. This work provides evidence that circadian rhythms can be reasonably estimated in later‐life adults living in home settings through mathematical modelling of data from wearable devices. [ABSTRACT FROM AUTHOR]