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de Groot ER, Dudink J, Austin T. Sleep as a driver of pre- and postnatal brain development. Pediatr Res 2024:10.1038/s41390-024-03371-5. [PMID: 38956219 DOI: 10.1038/s41390-024-03371-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 06/11/2024] [Accepted: 06/17/2024] [Indexed: 07/04/2024]
Abstract
In 1966, Howard Roffwarg proposed the ontogenic sleep hypothesis, relating neural plasticity and development to rapid eye movement (REM) sleep, a hypothesis that current fetal and neonatal sleep research is still exploring. Recently, technological advances have enabled researchers to automatically quantify neonatal sleep architecture, which has caused a resurgence of research in this field as attempts are made to further elucidate the important role of sleep in pre- and postnatal brain development. This article will review our current understanding of the role of sleep as a driver of brain development and identify possible areas for future research. IMPACT: The evidence to date suggests that Roffwarg's ontogenesis hypothesis of sleep and brain development is correct. A better understanding of the relationship between sleep and the development of functional connectivity is needed. Reliable, non-invasive tools to assess sleep in the NICU and at home need to be tested in a real-world environment and the best way to promote healthy sleep needs to be understood before clinical trials promoting and optimizing sleep quality in neonates could be undertaken.
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Affiliation(s)
- Eline R de Groot
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Jeroen Dudink
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Topun Austin
- NeoLab, Evelyn Perinatal Imaging Centre, The Rosie Hospital, Cambridge University Hospitals, Cambridge, UK.
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Wang X, de Groot ER, Tataranno ML, van Baar A, Lammertink F, Alderliesten T, Long X, Benders MJNL, Dudink J. Machine Learning-Derived Active Sleep as an Early Predictor of White Matter Development in Preterm Infants. J Neurosci 2024; 44:e1024232023. [PMID: 38124010 PMCID: PMC10860564 DOI: 10.1523/jneurosci.1024-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 09/15/2023] [Accepted: 09/19/2023] [Indexed: 12/23/2023] Open
Abstract
White matter dysmaturation is commonly seen in preterm infants admitted to the neonatal intensive care unit (NICU). Animal research has shown that active sleep is essential for early brain plasticity. This study aimed to determine the potential of active sleep as an early predictor for subsequent white matter development in preterm infants. Using heart and respiratory rates routinely monitored in the NICU, we developed a machine learning-based automated sleep stage classifier in a cohort of 25 preterm infants (12 females). The automated classifier was subsequently applied to a study cohort of 58 preterm infants (31 females) to extract active sleep percentage over 5-7 consecutive days during 29-32 weeks of postmenstrual age. Each of the 58 infants underwent high-quality T2-weighted magnetic resonance brain imaging at term-equivalent age, which was used to measure the total white matter volume. The association between active sleep percentage and white matter volume was examined using a multiple linear regression model adjusted for potential confounders. Using the automated classifier with a superior sleep classification performance [mean area under the receiver operating characteristic curve (AUROC) = 0.87, 95% CI 0.83-0.92], we found that a higher active sleep percentage during the preterm period was significantly associated with an increased white matter volume at term-equivalent age [β = 0.31, 95% CI 0.09-0.53, false discovery rate (FDR)-adjusted p-value = 0.021]. Our results extend the positive association between active sleep and early brain development found in animal research to human preterm infants and emphasize the potential benefit of sleep preservation in the NICU setting.
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Affiliation(s)
- Xiaowan Wang
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
| | - Eline R de Groot
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
| | - Maria Luisa Tataranno
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht 3584 CX, The Netherlands
| | - Anneloes van Baar
- Child and Adolescent Studies, Utrecht University, Utrecht 3584 CS, The Netherlands
| | - Femke Lammertink
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
| | - Thomas Alderliesten
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht 3584 CX, The Netherlands
| | - Xi Long
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven 5612 AZ, The Netherlands
| | - Manon J N L Benders
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht 3584 CX, The Netherlands
| | - Jeroen Dudink
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht 3584 CX, The Netherlands
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Ramasubbu K, Ramanathan G, Venkatraman G, Rajeswari VD. Sleep-associated insulin resistance promotes neurodegeneration. Mol Biol Rep 2023; 50:8665-8681. [PMID: 37580496 DOI: 10.1007/s11033-023-08710-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 07/25/2023] [Indexed: 08/16/2023]
Abstract
Lifestyle modification can lead to numerous health issues closely associated with sleep. Sleep deprivation and disturbances significantly affect inflammation, immunity, neurodegeneration, cognitive depletion, memory impairment, neuroplasticity, and insulin resistance. Sleep significantly impacts brain and memory formation, toxin excretion, hormonal function, metabolism, and motor and cognitive functions. Sleep restriction associated with insulin resistance affects these functions by interfering with the insulin signalling pathway, neurotransmission, inflammatory pathways, and plasticity of neurons. So, in this review, We discuss the evidence that suggests that neurodegeneration occurs via sleep and is associated with insulin resistance, along with the insulin signalling pathways involved in neurodegeneration and neuroplasticity, while exploring the role of hormones in these conditions.
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Affiliation(s)
- Kanagavalli Ramasubbu
- Department of Bio-Medical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India
| | - Gnanasambandan Ramanathan
- Department of Bio-Medical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India
| | - Ganesh Venkatraman
- Department of Bio-Medical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India
| | - V Devi Rajeswari
- Department of Bio-Medical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.
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