Background: While the association between sleep quality and brain health is well established, the role of aging in this relationship is largely unknown. This study aimed to examine the interaction between sleep and age on cortical thickness using samples from large-scale cohort studies. Age was examined in both linear and non-linear (quadratic) terms, in order to determine the presence of critical age ranges that may exhibit more significant sleep-related brain structural changes.
Method: Sample included 700 adults (mean age 59.63 [age range 36-90], 55.9% female) from the Human Connectome Project-Aging (HCP-A). Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). Magnetic resonance imaging (MRI) data was obtained from T1-weighted structural images using a 3T scanner, and cortical thickness indices were derived using the FreeSurfer pipeline. The interaction between sleep and age on cortical thickness was tested using the moderation analysis using linear regression models, with sex, race, and use of sleep medication as covariates. The same analyses are planned on a separate dataset from the Nathan Klein Institute (NKI) cohort in order to replicate these findings.
Result: There was a significant interaction term between the PSQI and non-linear age term (age) on the insula (b=0.67, CI=0.03-1.30, p=.04) and the middle temporal cortical thickness (b=0.58, CI=0.03-1.13, p=.04), indicating that sleep quality may be associated with cortical thickness distinctly in different age groups. A visual examination of this relationship indicated that cortical thickness for individuals between the ages 53 and 78.
Conclusion: Age may have a significant role in the relationship between sleep and cortical thickness. Middle-aged and older adults may be most vulnerable to sleep-related changes in the brain structures. These findings will be tested using a separate dataset.
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http://dx.doi.org/10.1002/alz.093110 | DOI Listing |
J Headache Pain
January 2025
Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
Inter-individual variability in symptoms and the dynamic nature of brain pathophysiology present significant challenges in constructing a robust diagnostic model for migraine. In this study, we aimed to integrate different types of magnetic resonance imaging (MRI), providing structural and functional information, and develop a robust machine learning model that classifies migraine patients from healthy controls by testing multiple combinations of hyperparameters to ensure stability across different migraine phases and longitudinally repeated data. Specifically, we constructed a diagnostic model to classify patients with episodic migraine from healthy controls, and validated its performance across ictal and interictal phases, as well as in a longitudinal setting.
View Article and Find Full Text PDFCalcif Tissue Int
January 2025
Research Centre in Physical Activity, Health and Leisure (CIAFEL), Faculty of Sport, University of Porto, (FADEUP), Rua Dr. Plácido Costa 91, 4200-450, Porto, Portugal.
Swimming is a popular sport with several health benefits, but its effects on bone quality are controversial possibly due to distinct effects on different anatomical regions. Our aim was to investigate the effect of 8-month swimming on bone growth, mass, geometry, trabecular microarchitecture and osteocyte density of the lumbar vertebrae, femur and tibia of male rats. Wistar rat models were assigned to either a swimming (n = 10; 2h/d, 5 d/week) or a physically active control group (n = 10) for 8 months, after which they were sacrificed and their lumbar vertebrae, femur and tibia assessed for bone mass, cortical geometry, trabecular microarchitecture and osteocyte density through µ-CT and histology.
View Article and Find Full Text PDFEBioMedicine
January 2025
Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Sweden; Department of Psychiatry, Cognition and Old Age Psychiatry, Sahlgrenska University Hospital, Region Västra Götaland, Mölndal, Sweden.
Background: A better understanding of body-brain links may provide insights on targets for preventing cognitive decline. The aim was to explore associations of body composition with neuroimaging biomarkers and cognitive function among dementia-free 70-year-olds.
Methods: Dual-energy X-ray absorptiometry body composition measures in relation to neuroimaging measures of cortical thickness, hippocampal volume, small vessel disease, predicted brain age, and cognitive performance were explored in a cross-sectional study of 674 dementia-free 70-year-olds from the Swedish Gothenburg H70 Birth Cohort study.
Dev Cogn Neurosci
December 2024
Division of Psychology and Language Sciences, UCL, London WC1H 0AP, UK. Electronic address:
Executive functions can be classified into processes of inhibition, working memory and shifting, which together support flexible and goal-directed behaviour and are crucial for both current and later-life outcomes. A large body of literature has identified distinct brain regions critical to performing each of these functions. These findings are however predicated on a piecemeal and single-task approach.
View Article and Find Full Text PDFJAMA Netw Open
December 2024
Department of Psychological and Brain Sciences, Washington University in St Louis, Missouri.
Importance: The extent to which neuroanatomical variability associated with early substance involvement, which is associated with subsequent risk for substance use disorder development, reflects preexisting risk and/or consequences of substance exposure remains poorly understood.
Objective: To examine neuroanatomical features associated with early substance use initiation and to what extent associations may reflect preexisting vulnerability.
Design, Setting, And Participants: Cohort study using data from baseline through 3-year follow-up assessments of the ongoing longitudinal Adolescent Brain Cognitive Development Study.
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