Sleep plays a vital role in the cognitive processing and maintenance of psychological health, which includes the processing of emotions and the consolidation of memories. Sleep can also have a neuroprotective effect since it helps flush out the body's waste products. Studies have shown that changes in sleep duration have been associated with several diseases along with psychiatric disorders. Insufficient sleep has been associated with increased mortality, while prolonged sleep can lead to dementia.
Study: The brain structure and genetic mechanisms underlying the nonlinear association between sleep duration, cognition and mental health. Image Credit: amenic181 / Shutterstock
Moreover, the aging process has been associated with alterations in sleep patterns, decreased sleep efficiency, and decreased quality as well as quantity of sleep. Consequently, sleep disturbances are prevalent in the aging population and can contribute to cognitive decline and a lower quality of life.
A recent study relevant to this indicated that an inverted U-shaped association exists between global cognitive decline and duration of sleep where duration less than 4 h or more than 10 h was shown to be detrimental. Additionally, a U-shaped association was also observed between nocturnal duration of sleep and cerebrospinal fluid (CSF) biomarkers of amyloid deposition in aged individuals. However, the impact of sleep duration on cognition and mental health is yet to be determined in a large cohort.
Previous studies have also indicated that abnormal sleep in older individuals is associated with adverse changes in brain structure. For example, each hour of reduced sleep duration was found to be associated with a 0.59 percent increase in ventricular volume in individuals who were above 55 years of age. Furthermore, short sleep duration in middle-aged and older adults led to impairment in white matter microstructure. Additionally, a longitudinal study also revealed that sleep disorders could arise due to age-related atrophy of brain regions. There has been some discussion of the possibility of non-linear relationships between sleep and behavior, but most of the existing studies focus on linear relationships between brain structure and sleep duration.
A new study published in the journal Nature Aging used the large cohort of the UK Biobank to focus on the sleep duration of mid-to-late life adults and analyze whether brain and genetic mechanisms impact the non-linear association between sleep duration, cognition, and mental health.
About the study
The study included a total of 498,277 participants who were of European ancestry and were aged between 38 and 73 years. 94.3 percent of the participants were White, 2 percent Asian, 0.3 percent Chinese, 1.6 percent Black, 0.6 percent mixed race, 0.9 percent of other ethnic groups, and 0.3 percent data were kissing.
Neuroimaging data were obtained from 48,511 participants. 156,884 participants were reported to complete the online follow-up mental health questionnaire (MHQ) for 6 to 8 years following the baseline assessment.
Sleep duration measured at baseline was used to analyze the association between online follow-up mental health assessments and cognitive function, while sleep duration measured at neuroimaging visit was used to analyze the association with the structure of the brain.
Depressive symptoms were measured with the help of the Patient Health Questionnaire (PHQ)-4 both at baseline and during neuroimaging visits. Additionally, cognitive tests were administered both at baseline and during the neuroimaging visits.
Thereafter, the polygenic risk score (PRS) was calculated for sleep duration followed by statistical analysis, longitudinal analysis, and mediation analysis that was carried out separately for individuals who sleep less than 7 hours and those who sleep for more than 7 hours. A structural equation model was also estimated for these two groups of individuals. Finally, the interaction between age and sleep duration was analyzed.
The results indicated a positive association of both insufficient and excessive sleep duration with the poor performance of cognitive tasks as well as mental health symptoms such as mental distress, anxiety, depression, trauma, self-harm, and psychotic experiences. Non-linear associations between sleep duration and brain structure were also reported which included the total surface area of the brain, global mean thickness, right hemisphere, cortical gray matter volume, and subcortical gray matter volume. Also, the most significant non-linear relationship between sleep duration and cortical volumes was observed in the group aged 44–59 years which declined with age.
The results also revealed that an increase in age was associated with a decrease in brain volume as well as impairment of cognitive functions. However, an increase in age did not similarly impact mental health symptoms. Longer sleep duration in individuals with less than 7 hours of sleep at baseline was found to be associated with lower PHQ-4 scores and higher fluid intelligence scores while for those with greater than 7 hours of sleep at baseline, it was associated with lower fluid intelligence scores.
Additionally, the results of three mediation pathway analyses indicated that for participants with sleep duration of fewer than 7 hours, the first model showed that PRS was associated with sleep duration while sleep duration was associated with brain structure. PRS of sleep was also reported to adversely impact depressive symptoms. The second model showed that the association between PRS and depressive symptoms was impacted by sleep duration. The third model showed that brain structure could also impact the association between PRS and depressive symptoms.
Mediation pathway for the cognitive function of fluid intelligence for participants with sleep duration of fewer than 7 hours revealed a positive association between PRS and fluid intelligence. Sleep duration was found to be associated with PRS while brain volume was associated with sleep duration and fluid intelligence. The results of mediation analysis between sleep duration and fluid intelligence were similar for participants with sleep duration greater than 7 hours while it was not quite significant for mediation analysis between sleep duration and depressive symptoms.
Furthermore, depressive symptoms and anxiety symptoms were identified as the main components of the mental health latent variable, the volume of the cortex was identified as the main predictor of brain volume, and fluid intelligence was identified as the latent variable for cognitive function.
Accordingly, the current study confirmed non-linear associations between sleep duration and cognitive functions, mental health, and brain structure among middle-aged and older participants from the UK Biobank.
Additionally, non-optimal sleep duration was correlated with poor cognitive function and increased psychiatric symptoms over time. Thus, the current study illustrated the importance of sleep regulation for individual wellbeing.
The study has certain limitations. First, the study included only total sleep duration and did not include other measures of sleep hygiene. Additionally, since sleep duration was assessed via a self-reported questionnaire, bias may have occurred. Third, the study included sleep durations of mostly healthy people. Fourth, the study included MHQs which provided quantitative measures of mental health symptoms but not a diagnosis. Finally, the results of this study might not be fully applicable to other demographic populations.
- Li, Y. et al. (2022). The brain structure and genetic mechanisms underlying the non-linear association between sleep duration, cognition and mental health. Nature Aging. Doi: https://doi.org/10.1038/s43587-022-00210-2. https://www.nature.com/articles/s43587-022-00210-2.
Posted in: Men's Health News | Medical Research News | Women's Health News
Tags: Aging, Anxiety, Brain, Cognitive Function, Cortex, Dementia, Depression, Genetic, Hygiene, Mental Health, Mortality, Neuroimaging, Sleep, Trauma, UK Biobank
Suchandrima has a Bachelor of Science (B.Sc.) degree in Microbiology and a Master of Science (M.Sc.) degree in Microbiology from the University of Calcutta, India. The study of health and diseases was always very important to her. In addition to Microbiology, she also gained extensive knowledge in Biochemistry, Immunology, Medical Microbiology, Metabolism, and Biotechnology as part of her master's degree.
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