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Son DY, Kwon HB, Lee DS, Jin HW, Jeong JH, Kim J, Choi SH, Yoon H, Lee MH, Lee YJ, Park KS. Changes in physiological network connectivity of body system in narcolepsy during REM sleep. Comput Biol Med 2021; 136:104762. [PMID: 34399195 DOI: 10.1016/j.compbiomed.2021.104762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 08/09/2021] [Accepted: 08/09/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Narcolepsy is marked by pathologic symptoms including excessive daytime drowsiness and lethargy, even with sufficient nocturnal sleep. There are two types of narcolepsy: type 1 (with cataplexy) and type 2 (without cataplexy). Unlike type 1, for which hypocretin is a biomarker, type 2 narcolepsy has no adequate biomarker to identify the causality of narcoleptic phenomenon. Therefore, we aimed to establish new biomarkers for narcolepsy using the body's systemic networks. METHOD Thirty participants (15 with type 2 narcolepsy, 15 healthy controls) were included. We used the time delay stability (TDS) method to examine temporal information and determine relationships among multiple signals. We quantified and analyzed the network connectivity of nine biosignals (brainwaves, cardiac and respiratory information, muscle and eye movements) during nocturnal sleep. In particular, we focused on the differences in network connectivity between groups according to sleep stages and investigated whether the differences could be potential biomarkers to classify both groups by using a support vector machine. RESULT In rapid eye movement sleep, the narcolepsy group displayed more connections than the control group (narcolepsy connections: 24.47 ± 2.87, control connections: 21.34 ± 3.49; p = 0.022). The differences were observed in movement and cardiac activity. The performance of the classifier based on connectivity differences was a 0.93 for sensitivity, specificity and accuracy, respectively. CONCLUSION Network connectivity with the TDS method may be used as a biomarker to identify differences in the systemic networks of patients with narcolepsy type 2 and healthy controls.
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Affiliation(s)
- Dong Yeon Son
- Interdisciplinary Program in Bioengineering, College of Engineering, Seoul National University, Seoul, 03080, South Korea; Integrated Major in Innovative Medical Science, College of Medicine, Seoul National University, Seoul, 03080, South Korea
| | - Hyun Bin Kwon
- Interdisciplinary Program in Bioengineering, College of Engineering, Seoul National University, Seoul, 03080, South Korea
| | - Dong Seok Lee
- Interdisciplinary Program in Bioengineering, College of Engineering, Seoul National University, Seoul, 03080, South Korea
| | - Hyung Won Jin
- Interdisciplinary Program in Bioengineering, College of Engineering, Seoul National University, Seoul, 03080, South Korea; Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, 03080, South Korea
| | - Jong Hyeok Jeong
- Interdisciplinary Program in Bioengineering, College of Engineering, Seoul National University, Seoul, 03080, South Korea; Integrated Major in Innovative Medical Science, College of Medicine, Seoul National University, Seoul, 03080, South Korea
| | - Jeehoon Kim
- Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul, 03080, South Korea
| | - Sang Ho Choi
- School of Computer and Information Engineering, Kwangwoon University, Seoul, 01897, South Korea
| | - Heenam Yoon
- Department of Human-Centered Artificial Intelligence, Sangmyung University, Seoul, 03016, South Korea
| | - Mi Hyun Lee
- Department of Neuropsychiatry and Center for Sleep and Chronobiology, Seoul National University Hospital, Seoul, 03080, South Korea
| | - Yu Jin Lee
- Department of Neuropsychiatry and Center for Sleep and Chronobiology, Seoul National University Hospital, Seoul, 03080, South Korea
| | - Kwang Suk Park
- Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, 03080, South Korea; Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul, 03080, South Korea.
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Adamantidis AR, Schmidt MH, Carter ME, Burdakov D, Peyron C, Scammell TE. A circuit perspective on narcolepsy. Sleep 2021; 43:5699663. [PMID: 31919524 PMCID: PMC7215265 DOI: 10.1093/sleep/zsz296] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 11/13/2019] [Indexed: 01/25/2023] Open
Abstract
The sleep disorder narcolepsy is associated with symptoms related to either boundary state control that include excessive daytime sleepiness and sleep fragmentation, or rapid eye movement (REM) sleep features including cataplexy, sleep paralysis, hallucinations, and sleep-onset REM sleep events (SOREMs). Although the loss of Hypocretin/Orexin (Hcrt/Ox) peptides or their receptors have been associated with the disease, here we propose a circuit perspective of the pathophysiological mechanisms of these narcolepsy symptoms that encompasses brain regions, neuronal circuits, cell types, and transmitters beyond the Hcrt/Ox system. We further discuss future experimental strategies to investigate brain-wide mechanisms of narcolepsy that will be essential for a better understanding and treatment of the disease.
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Affiliation(s)
- A R Adamantidis
- Department of Neurology, Centre for Experimental Neurology, Inselspital University Hospital Bern, University of Bern, Bern, Switzerland.,Department of Biomedical Research, Inselspital University Hospital Bern, University of Bern, Bern, Switzerland
| | - M H Schmidt
- Department of Neurology, Centre for Experimental Neurology, Inselspital University Hospital Bern, University of Bern, Bern, Switzerland.,Ohio Sleep Medicine Institute, Dublin, OH
| | - M E Carter
- Department of Biology, Program in Neuroscience, Williams College, Williamstown, MA
| | - D Burdakov
- Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
| | - C Peyron
- Center for Research in Neuroscience of Lyon, SLEEP team, CNRS UMR5292, INSERM U1028, University Lyon 1, Bron, France
| | - Thomas E Scammell
- Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
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Bastianini S, Alvente S, Berteotti C, Lo Martire V, Silvani A, Swoap SJ, Valli A, Zoccoli G, Cohen G. Accurate discrimination of the wake-sleep states of mice using non-invasive whole-body plethysmography. Sci Rep 2017; 7:41698. [PMID: 28139776 PMCID: PMC5282481 DOI: 10.1038/srep41698] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Accepted: 12/29/2016] [Indexed: 01/11/2023] Open
Abstract
A major limitation in the study of sleep breathing disorders in mouse models of pathology is the need to combine whole-body plethysmography (WBP) to measure respiration with electroencephalography/electromyography (EEG/EMG) to discriminate wake-sleep states. However, murine wake-sleep states may be discriminated from breathing and body movements registered by the WBP signal alone. Our goal was to compare the EEG/EMG-based and the WBP-based scoring of wake-sleep states of mice, and provide formal guidelines for the latter. EEG, EMG, blood pressure and WBP signals were simultaneously recorded from 20 mice. Wake-sleep states were scored based either on EEG/EMG or on WBP signals and sleep-dependent respiratory and cardiovascular estimates were calculated. We found that the overall agreement between the 2 methods was 90%, with a high Cohen's Kappa index (0.82). The inter-rater agreement between 2 experts and between 1 expert and 1 naïve sleep investigators gave similar results. Sleep-dependent respiratory and cardiovascular estimates did not depend on the scoring method. We show that non-invasive discrimination of the wake-sleep states of mice based on visual inspection of the WBP signal is accurate, reliable and reproducible. This work may set the stage for non-invasive high-throughput experiments evaluating sleep and breathing patterns on mouse models of pathophysiology.
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Affiliation(s)
- Stefano Bastianini
- Prism Lab, Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, I-40126, Italy
| | - Sara Alvente
- Prism Lab, Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, I-40126, Italy
| | - Chiara Berteotti
- Prism Lab, Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, I-40126, Italy
| | - Viviana Lo Martire
- Prism Lab, Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, I-40126, Italy
| | - Alessandro Silvani
- Prism Lab, Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, I-40126, Italy
| | - Steven J Swoap
- Department of Biology, Williams College, Williamstown, Massachusetts, MA 01267, USA
| | - Alice Valli
- Prism Lab, Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, I-40126, Italy
| | - Giovanna Zoccoli
- Prism Lab, Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, I-40126, Italy
| | - Gary Cohen
- Department of Women's and Children's Health, Neonatal Unit, Karolinska Institutet, Stockholm, 17176, Sweden
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