Short sleep is held to cause poorer brain health, but is short sleep associated with higher rates of brain structural decline? Analysing 8,153 longitudinal MRIs from 3,893 healthy adults, we found no evidence for an association between sleep duration and brain atrophy. In contrast, cross-sectional analyses (51,295 observations) showed inverse U-shaped relationships, where a duration of 6.5 (95% confidence interval, (5.7, 7.3)) hours was associated with the thickest cortex and largest volumes relative to intracranial volume. This fits converging evidence from research on mortality, health and cognition that points to roughly seven hours being associated with good health. Genome-wide association analyses suggested that genes associated with longer sleep for below-average sleepers were linked to shorter sleep for above-average sleepers. Mendelian randomization did not yield evidence for causal impacts of sleep on brain structure. The combined results challenge the notion that habitual short sleep causes brain atrophy, suggesting that normal brains promote adequate sleep duration-which is shorter than current recommendations.
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http://dx.doi.org/10.1038/s41562-023-01707-5 | DOI Listing |
Mol Neurobiol
January 2025
Department of Neurology, Huai'an First People's Hospital, The Affiliated Huai'an No.1 People's Hospital of Nanjing Medical University, No.1 Huanghe West Road, Huai'an, 223300, Jiangsu, China.
A comprehensive genome-wide association study (GWAS) has validated the identification of the Plexin-A 4 (PLXNA4) gene as a novel susceptibility factor for Alzheimer's disease (AD). Nonetheless, the precise role of PLXNA4 gene polymorphisms in the pathophysiology of AD remains to be established. Consequently, this study is aimed at exploring the relationship between PLXNA4 gene polymorphisms and neuroimaging phenotypes intimately linked to AD.
View Article and Find Full Text PDFNeurology
January 2025
APHP- Salpêtrière Hospital, DMU BioGem, CNRS, INSERM, Paris Brain Institute, Sorbonne University.
Background And Objectives: Brain energy deficiency occurs at the early stage of Huntington disease (HD). Triheptanoin, a drug that targets the Krebs cycle, can restore a normal brain energetic profile in patients with HD. In this study, we aimed at assessing its efficacy on clinical and neuroimaging structural measures in HD.
View Article and Find Full Text PDFJ Neuroimaging
January 2025
Department of Radiology, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.
Background And Purpose: Endovascular thrombectomy (EVT) is the standard for acute ischemic stroke from large vessel occlusion, but post-EVT functional independence varies. Brain atrophy, linked to higher cerebrospinal fluid volume (CSFV), may affect outcomes. Baseline CSFV could predict EVT benefit by assessing brain health.
View Article and Find Full Text PDFBrain Commun
December 2024
Medical Research Council (MRC) Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK.
We investigated semantic cognition in the logopenic variant of primary progressive aphasia, including (i) the status of verbal and non-verbal semantic performance; and (ii) whether the semantic deficit reflects impaired semantic control. Our hypothesis that individuals with logopenic variant of primary progressive aphasia would exhibit semantic control impairments was motivated by the anatomical overlap between the temporoparietal atrophy typically associated with logopenic variant of primary progressive aphasia and lesions associated with post-stroke semantic aphasia and Wernicke's aphasia, which cause heteromodal semantic control impairments. We addressed the presence, type (semantic representation and semantic control; verbal and non-verbal), and progression of semantic deficits in logopenic variant of primary progressive aphasia.
View Article and Find Full Text PDFJ Alzheimers Dis
January 2025
Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Background: Single-subject voxel-based morphometry (VBM) is a powerful technique for reader-independent detection of brain atrophy in structural magnetic resonance imaging (MRI) to support the (differential) diagnosis and staging of neurodegenerative diseases in individual patients. However, VBM is sensitive to the MRI scanner platform and details of the acquisition sequence. To mitigate this limitation, we recently proposed and validated a convolutional neural network (CNN)-based VBM which does not rely on a normative reference database.
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