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Wang X, Luo L, Zhao J, Guo X, Tao L, Zhang F, Liu X, Gao B, Luo Y. Associations between sleep duration trajectories and cognitive decline: A longitudinal cohort study in China. Arch Gerontol Geriatr 2024; 124:105445. [PMID: 38733919 DOI: 10.1016/j.archger.2024.105445] [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: 01/27/2024] [Revised: 03/24/2024] [Accepted: 04/13/2024] [Indexed: 05/13/2024]
Abstract
OBJECT The relationship between sleep duration trajectories and cognitive decline remains uncertain. This study aims to examine the connections between various patterns of sleep duration and cognitive function. METHODS Group-based trajectory modeling (GBTM) was employed to identify longitudinal trajectories of sleep duration over four-year follow-up period, while considering age, sex and nap duration as adjustments. Logistic regression was utilized to analyze the association between sleep trajectories and cognition, with odds ratios (OR) and 95 % confidence intervals (CI) reported. Subgroup analyses based on various demographic characteristics were conducted to explore potential differences in sleep trajectories and cognitive decline across different population subgroups. RESULTS A total of 5061 participants were followed for four years, and three sleep duration trajectories were identified: high increasing (n = 2101, 41.6 %), stable increasing (n = 2087, 40.7 %), and low decreasing (n = 873, 17.7 %). After adjustment for basic demographic information, health status, and baseline cognition, the high increasing trajectory was found to be associated with cognitive decline in terms of global cognition (OR:1.52,95 %CI:1.18-1.96), mental intactness (OR:1.36,95 %CI:1.07-1.73) and episodic memory (OR:1.33, 95 %CI:1.05-1.67), as compared to stable increasing trajectory. These associations were particularly prominent among the non-elderly population (≤65 years) and those without depressive symptoms. CONCLUSION This study suggests that both high increasing and low decreasing sleep duration trajectories are linked to cognitive decline, as compared to the stable increasing trajectory. Long-term attention to changes in sleep duration facilitates early prevention of cognitive decline.
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Affiliation(s)
- Xiaonan Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, PR China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, PR China
| | - Lili Luo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, PR China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, PR China
| | - Jianxi Zhao
- School of Applied Science, Beijing Information Science and Technology University, Beijing, 100192, China
| | - Xiuhua Guo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, PR China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, PR China
| | - Lixin Tao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, PR China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, PR China
| | - Feng Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, PR China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, PR China
| | - Xiangtong Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, PR China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, PR China
| | - Bo Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, PR China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, PR China
| | - Yanxia Luo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, PR China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, PR China.
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Cumming D, Kozhemiako N, Thurm AE, Farmer CA, Purcell S, Buckley AW. Spindle chirp and other sleep oscillatory features in young children with autism. Sleep Med 2024; 119:320-328. [PMID: 38733760 DOI: 10.1016/j.sleep.2024.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 05/01/2024] [Accepted: 05/02/2024] [Indexed: 05/13/2024]
Abstract
OBJECTIVES To determine whether spindle chirp and other sleep oscillatory features differ in young children with and without autism. METHODS Automated processing software was used to re-assess an extant set of polysomnograms representing 121 children (91 with autism [ASD], 30 typically-developing [TD]), with an age range of 1.35-8.23 years. Spindle metrics, including chirp, and slow oscillation (SO) characteristics were compared between groups. SO and fast and slow spindle (FS, SS) interactions were also investigated. Secondary analyses were performed assessing behavioural data associations, as well as exploratory cohort comparisons to children with non-autism developmental delay (DD). RESULTS Posterior FS and SS chirp was significantly more negative in ASD than TD. Both groups had comparable intra-spindle frequency range and variance. Frontal and central SO amplitude were decreased in ASD. In contrast to previous manual findings, no differences were detected in other spindle or SO metrics. The ASD group displayed a higher parietal coupling angle. No differences were observed in phase-frequency coupling. The DD group demonstrated lower FS chirp and higher coupling angle than TD. Parietal SS chirp was positively associated with full developmental quotient. CONCLUSIONS For the first time spindle chirp was investigated in autism and was found to be significantly more negative than in TD in this large cohort of young children. This finding strengthens previous reports of spindle and SO abnormalities in ASD. Further investigation of spindle chirp in healthy and clinical populations across development will help elucidate the significance of this difference and better understand this novel metric.
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Affiliation(s)
- Drew Cumming
- National Institute of Mental Health, NIH, Bethesda, MD, USA
| | | | - Audrey E Thurm
- National Institute of Mental Health, NIH, Bethesda, MD, USA
| | | | - Shaun Purcell
- Brigham and Women's Hospital & Harvard Medical School, Boston, MA, USA
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3
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Lin GJ, Xu JJ, Peng XR, Yu J. Subjective sleep more predictive of global cognitive function than objective sleep in older adults: A specification curve analysis. Sleep Med 2024; 119:155-163. [PMID: 38678759 DOI: 10.1016/j.sleep.2024.04.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 04/03/2024] [Accepted: 04/21/2024] [Indexed: 05/01/2024]
Abstract
OBJECTIVES Sleep is associated with cognitive function in older adults. In the current study, we examined this relationship from subjective and objective perspectives, and determined the robustness and dimensional specificity of the associations using a comprehensive modelling approach. METHODS Multiple dimensions of subjective (sleep quality and daytime sleepiness) and objective sleep (sleep stages, sleep parameters, sleep spindles, and slow oscillations), as well as subjectively reported and objectively measured cognitive function were collected from 55 older adults. Specification curve analysis was used to examine the robustness of correlations for the effects of sleep on cognitive function. RESULTS Robust associations were found between sleep and objectively measured cognitive function, but not with subjective cognitive complaints. In addition, subjective sleep showed robust and consistent associations with global cognitive function, whereas objective sleep showed a more domain-specific association with episodic memory. Specifically, subjective sleep quality and daytime sleepiness correlated with global cognitive function, and objective sleep parameters correlated with episodic memory. CONCLUSIONS Overall, associations between sleep and cognitive function in older adults depend on how they are measured and which specific dimensions of sleep and domains of cognitive function are considered. It highlights the importance of focusing on specific associations to ameliorate the detrimental effects of sleep disturbance on cognitive function in later life.
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Affiliation(s)
- Guo-Jun Lin
- Faculty of Psychology, Southwest University, Tiansheng Road, Beibei District, Chongqing, 400715, China
| | - Jia-Jie Xu
- Faculty of Psychology, Southwest University, Tiansheng Road, Beibei District, Chongqing, 400715, China
| | - Xue-Rui Peng
- Chair of Lifespan Developmental Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden 01062, Germany; Centre for Tactile Internet with Human-in-the-Loop, Technische Universität Dresden, Dresden 01062, Germany; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
| | - Jing Yu
- Faculty of Psychology, Southwest University, Tiansheng Road, Beibei District, Chongqing, 400715, China.
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Shuster AE, Chen PC, Niknazar H, McDevitt EA, Lopour B, Mednick SC. Novel Electrophysiological Signatures of Learning and Forgetting in Human Rapid Eye Movement Sleep. J Neurosci 2024; 44:e1517232024. [PMID: 38670803 PMCID: PMC11170679 DOI: 10.1523/jneurosci.1517-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 03/27/2024] [Accepted: 03/29/2024] [Indexed: 04/28/2024] Open
Abstract
Despite the known behavioral benefits of rapid eye movement (REM) sleep, discrete neural oscillatory events in human scalp electroencephalography (EEG) linked with behavior have not been discovered. This knowledge gap hinders mechanistic understanding of the function of sleep, as well as the development of biophysical models and REM-based causal interventions. We designed a detection algorithm to identify bursts of activity in high-density, scalp EEG within theta (4-8 Hz) and alpha (8-13 Hz) bands during REM sleep. Across 38 nights of sleep, we characterized the burst events (i.e., count, duration, density, peak frequency, amplitude) in healthy, young male and female human participants (38; 21F) and investigated burst activity in relation to sleep-dependent memory tasks: hippocampal-dependent episodic verbal memory and nonhippocampal visual perceptual learning. We found greater burst count during the more REM-intensive second half of the night (p < 0.05), longer burst duration during the first half of the night (p < 0.05), but no differences across the night in density or power (p > 0.05). Moreover, increased alpha burst power was associated with increased overnight forgetting for episodic memory (p < 0.05). Furthermore, we show that increased REM theta burst activity in retinotopically specific regions was associated with better visual perceptual performance. Our work provides a critical bridge between discrete REM sleep events in human scalp EEG that support cognitive processes and the identification of similar activity patterns in animal models that allow for further mechanistic characterization.
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Affiliation(s)
| | - Pin-Chun Chen
- University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Hamid Niknazar
- Sleep and Cognition Lab, University of California, Irvine, California 92697
| | | | - Beth Lopour
- Sleep and Cognition Lab, University of California, Irvine, California 92697
| | - Sara C Mednick
- Sleep and Cognition Lab, University of California, Irvine, California 92697
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5
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Di Marco T, Scammell TE, Sadeghi K, Datta AN, Little D, Tjiptarto N, Djonlagic I, Olivieri A, Zammit G, Krystal A, Pathmanathan J, Donoghue J, Hubbard J, Dauvilliers Y. Hyperarousal features in the sleep architecture of individuals with and without insomnia. J Sleep Res 2024:e14256. [PMID: 38853521 DOI: 10.1111/jsr.14256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/08/2024] [Accepted: 05/20/2024] [Indexed: 06/11/2024]
Abstract
Sleep architecture encodes relevant information on the structure of sleep and has been used to assess hyperarousal in insomnia. This study investigated whether polysomnography-derived sleep architecture displays signs of hyperarousal in individuals with insomnia compared with individuals without insomnia. Data from Phase 3 clinical trials, private clinics and a cohort study were analysed. A comprehensive set of sleep architecture features previously associated with hyperarousal were retrospectively analysed focusing on sleep-wake transition probabilities, electroencephalographic spectra and sleep spindles, and enriched with a novel machine learning algorithm called the Wake Electroencephalographic Similarity Index. This analysis included 1710 individuals with insomnia and 1455 individuals without insomnia. Results indicate that individuals with insomnia had a higher likelihood of waking from all sleep stages, and showed increased relative alpha during Wake and N1 sleep and increased theta power during Wake when compared with individuals without insomnia. Relative delta power was decreased and Wake Electroencephalographic Similarity Index scores were elevated across all sleep stages except N3, suggesting more wake-like activity during these stages in individuals with insomnia. Additionally, sleep spindle density was decreased, and spindle dispersion was increased in individuals with insomnia. These findings suggest that insomnia is characterized by a dysfunction in sleep quality with a continuous hyperarousal, evidenced by changes in sleep-wake architecture.
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Affiliation(s)
- Tobias Di Marco
- Idorsia Pharmaceuticals Ltd, Allschwil, Switzerland
- Department of Clinical Research, University of Basel, Basel, Switzerland
| | - Thomas E Scammell
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | | | | | - David Little
- Beacon Biosignals, Inc., Boston, Massachusetts, USA
| | | | - Ina Djonlagic
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | | | - Gary Zammit
- Clinilabs Drug Development Corporation, New York, New York, USA
| | - Andrew Krystal
- University of California, San Francisco, California, USA
| | | | | | | | - Yves Dauvilliers
- Centre National de Référence Narcolepsie, Unité du Sommeil, CHU Montpellier, Hôpital Gui-de-Chauliac, Université de Montpellier, INSERM INM, Montpellier, France
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6
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Xing M, Zhang L, Li J, Li Z, Yu Q, Li W. Development and validation of a novel sleep health score in the sleep heart health study. Eur J Intern Med 2024:S0953-6205(24)00189-4. [PMID: 38729786 DOI: 10.1016/j.ejim.2024.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 04/14/2024] [Accepted: 05/03/2024] [Indexed: 05/12/2024]
Abstract
BACKGROUND There is a lack of consensus in evaluating multidimensional sleep health, especially concerning its implication for mortality. A validated multidimensional sleep health score is the foundation of effective interventions. METHODS We obtained data from 5706 participants in the Sleep Heart Health Study. First, random forest-recursive feature elimination algorithm was used to select potential predictive variables. Second, a sleep composite score was developed based on the regression coefficients from a Cox proportional hazards model evaluating the associations between selected sleep-related variables and mortality. Last, we validated the score by constructing Cox proportional hazards models to assess its association with mortality. RESULTS The mean age of participants was 63.2 years old, and 47.6% (2715/5706) were male. Six sleep variables, including average oxygen saturation (%), spindle density (C3), sleep efficiency (%), spindle density (C4), percentage of fast spindles (%) and percentage of rapid eye movement (%) were selected to construct this multidimensional sleep health score. The average sleep composite score in participants was 6.8 of 22 (lower is better). Participants with a one-point increase in sleep composite score had an 10% higher risk of death (hazard ratio = 1.10, 95% confidence interval: 1.08-1.12). CONCLUSIONS This study constructed and validated a novel multidimensional sleep health score to better predict death based on sleep, with significant associations between sleep composite score and all-cause mortality. Integrating questionnaire information and sleep microstructures, our sleep composite score is more appropriately applied for mortality risk stratification.
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Affiliation(s)
- Muqi Xing
- Department of Big Data in Health Science, School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Lingzhi Zhang
- Department of Big Data in Health Science, School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jiahui Li
- Department of Big Data in Health Science, School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Zihan Li
- Department of Big Data in Health Science, School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Qi Yu
- Department of Big Data in Health Science, School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wenyuan Li
- Department of Big Data in Health Science, School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
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Sun W, Cheung FTW, Chan NY, Zhang J, Chan JWY, Chan KCC, Wing YK, Li SX. The impacts of intra-individual daily sleep variability on daytime functioning and sleep architecture in healthy young adults: An experimental study. J Sleep Res 2024; 33:e13967. [PMID: 37366548 DOI: 10.1111/jsr.13967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 05/17/2023] [Accepted: 05/30/2023] [Indexed: 06/28/2023]
Abstract
Sleep variability is commonly seen in the young populations. This study aimed to examine the impacts of experimentally induced sleep variability on sleepiness, mood, cognitive performance and sleep architectures among young adults. Thirty-six healthy individuals (aged 18-22 years) were randomly assigned to either variable sleep schedule (n = 20) or control (n = 16) groups. The protocol involved 1 week of regular sleep (time in bed = 7.5 hr) in the home setting, followed by one adaptation night (time in bed = 7.5 hr), one baseline night (time in bed = 7.5 hr), and 6 nights of sleep manipulation in the laboratory monitored by polysomnography (three cycles of variable sleep schedule by changing daily time in bed alternating between 6 hr and 9 hr for variable sleep schedule group versus fixed sleep schedule with daily time in bed for 7.5 hr for control group). Sleepiness, mood, sustained attention, processing speed, response inhibition and working memory were measured every morning and evening. The variable sleep schedule group reported a higher level of sleepiness, especially in the mornings, and increased negative mood in the evenings. There were no significant differences in positive mood, cognitive performance and sleep macro- and micro-structures. Our results showed the negative effects of sleep variability on daytime functioning especially sleepiness and negative mood, suggesting the need to address variable sleep schedules through sleep intervention.
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Affiliation(s)
- Wanqi Sun
- Sleep Research Clinic and Laboratory, Department of Psychology, The University of Hong Kong, Hong Kong, China
- Shanghai Mental Health Center, Shanghai, China
| | - Forrest Tin Wai Cheung
- Sleep Research Clinic and Laboratory, Department of Psychology, The University of Hong Kong, Hong Kong, China
| | - Ngan Yin Chan
- Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Jihui Zhang
- Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
- Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Joey Wing Yan Chan
- Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Kate Ching Ching Chan
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Yun Kwok Wing
- Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Shirley Xin Li
- Sleep Research Clinic and Laboratory, Department of Psychology, The University of Hong Kong, Hong Kong, China
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China
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8
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Hajipour M, Hirsch Allen AJ, Beaudin AE, Raneri JK, Jen R, Foster GE, Fogel S, Kendzerska T, Series F, Skomro RP, Robillard R, Kimoff RJ, Hanly PJ, Fels S, Singh A, Azarbarzin A, Ayas NT. All Obstructive Sleep Apnea Events Are Not Created Equal: The Relationship between Event-related Hypoxemia and Physiologic Response. Ann Am Thorac Soc 2024; 21:794-802. [PMID: 38252424 PMCID: PMC11109914 DOI: 10.1513/annalsats.202309-777oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 01/22/2024] [Indexed: 01/23/2024] Open
Abstract
Rationale: Obstructive sleep apnea (OSA) severity is typically assessed by the apnea-hypopnea index (AHI), a frequency-based metric that allocates equal weight to all respiratory events. However, more severe events may have a greater physiologic impact. Objectives: The purpose of this study was to determine whether the degree of event-related hypoxemia would be associated with the postevent physiologic response. Methods: Patients with OSA (AHI, ⩾5/h) from the multicenter Canadian Sleep and Circadian Network cohort were studied. Using mixed-effect linear regression, we examined associations between event-related hypoxic burden (HBev) assessed by the area under the event-related oxygen saturation recording with heart rate changes (ΔHRev), vasoconstriction (vasoconstriction burden [VCBev] assessed with photoplethysmography), and electroencephalographic responses (power ratio before and after events). Results: Polysomnographic recordings from 658 patients (median [interquartile range] age, 55.00 [45.00, 64.00] yr; AHI, 27.15 [14.90, 64.05] events/h; 42% female) were included in the analyses. HBev was associated with an increase in all physiologic responses after controlling for age, sex, body mass index, sleep stage, total sleep time, and study centers; for example, 1 standard deviation increase in HBev was associated with 0.21 [95% confidence interval, 0.2, 0.22], 0.08 [0.08, 0.09], and 0.22 [0.21, 0.23] standard deviation increases in ΔHRev, VCBev, and β-power ratio, respectively. Conclusions: Increased event-related hypoxic burden was associated with greater responses across a broad range of physiologic signals. Future metrics that incorporate information about the variability of these physiologic responses may have promise in providing a more nuanced assessment of OSA severity.
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Affiliation(s)
| | | | | | - Jill K. Raneri
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Sleep Centre, Foothills Medical Centre, Calgary, Alberta, Canada
| | | | - Glen E. Foster
- School of Health and Exercise Sciences, University of British Columbia, Kelowna, British Columbia, Canada
| | | | - Tetyana Kendzerska
- Department of Medicine, Faculty of Medicine, The Ottawa Hospital Research Institute, and
| | - Fréderic Series
- Department of Medicine, Faculty of Medicine, Université Laval, Quebec City, Quebec, Canada
| | - Robert P. Skomro
- Department of Medicine, Faculty of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Rebecca Robillard
- Department of Medicine, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - R. John Kimoff
- Respiratory Division and Sleep Laboratory, McGill University Health Centre, Montreal, Quebec, Canada; and
| | - Patrick J. Hanly
- Hotchkiss Brain Institute, and
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Sleep Centre, Foothills Medical Centre, Calgary, Alberta, Canada
| | - Sidney Fels
- Department of Electrical and Computer Engineering, Faculty of Applied Science, University of British Columbia, Vancouver, British Columbia, Canada
| | - Amrit Singh
- Department of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine, and
| | - Ali Azarbarzin
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts
| | - Najib T. Ayas
- Department of Experimental Medicine
- Department of Medicine
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9
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Huang T. Low Delta Wave Activity During Sleep Promotes Cardiovascular Disease Risk: What's Next? J Am Coll Cardiol 2024; 83:1685-1687. [PMID: 38658107 DOI: 10.1016/j.jacc.2024.03.358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 03/06/2024] [Indexed: 04/26/2024]
Affiliation(s)
- Tianyi Huang
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA; Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA.
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10
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Kizilkilic EK, Karadeniz D, Senel GB. Attention and executive function impairments in obstructive sleep apnea are associated with decreased sleep spindles. Acta Neurol Belg 2024:10.1007/s13760-024-02534-9. [PMID: 38563875 DOI: 10.1007/s13760-024-02534-9] [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: 08/08/2023] [Accepted: 03/13/2024] [Indexed: 04/04/2024]
Abstract
INTRODUCTION Sleep spindles play a key role in sleep-mediated cognitive processes. Cognitive functions are well-known to be affected in obstructive sleep apnea (OSA). Here, we analyzed attention and executive functions in patients with OSA and investigated the relationship between sleep spindles and cognitive abilities. METHODS Sixty patients with OSA (18-65 years, 19 females and 41 males) and a control group (n = 41) including age-and sex-matched healthy individuals were consecutively and prospectively enrolled. All participants had a full-night polysomnography, and sleep spindles were analyzed using a semi-automated program. For the evaluation of short-term memory, attention and executive functions, Stroop test, forward and backward digit span tests were applied to all participants upon awakening following polysomnography. RESULTS Scores of forward and backward digit span and Stroop tests were worse in OSA patients in compared to those in controls. Mean density of sleep spindles was decreased in OSA patients than those in controls (p = 0.044). A positive correlation was found between fast sleep spindle frequency and forward digit span (r = 2.222; p = 0.038) and backward digit span test scores (r = 2,157; p = 0.042) in OSA patients. In patients with moderate to severe OSA, sleep spindle density was positively correlated with forward (r = 2.323, p = 0.029) and backward (r = 2.500, p = 0.016) DSTs, and the duration of sleep spindles had positive correlation with backward DST (r = 2.452, p = 0.010). CONCLUSION Our findings demonstrated that the disturbances in sleep spindle characteristics in OSA are associated with the cognitive impairments in attention, short-term memory, and executive functions, especially in patients with moderate to severe OSA.
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Affiliation(s)
- Esra Kochan Kizilkilic
- Department of Neurology, Cerrahpasa Faculty of Medicine, Istanbul University, Cerrahpasa, Istanbul, Turkey.
| | - Derya Karadeniz
- Department of Neurology, Cerrahpasa Faculty of Medicine, Istanbul University, Cerrahpasa, Istanbul, Turkey
| | - Gulcin Benbir Senel
- Department of Neurology, Cerrahpasa Faculty of Medicine, Istanbul University, Cerrahpasa, Istanbul, Turkey
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11
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Ujma PP, Bódizs R. Sleep alterations as a function of 88 health indicators. BMC Med 2024; 22:134. [PMID: 38519958 PMCID: PMC10960465 DOI: 10.1186/s12916-024-03358-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 03/14/2024] [Indexed: 03/25/2024] Open
Abstract
BACKGROUND Alterations in sleep have been described in multiple health conditions and as a function of several medication effects. However, evidence generally stems from small univariate studies. Here, we apply a large-sample, data-driven approach to investigate patterns between in sleep macrostructure, quantitative sleep EEG, and health. METHODS We use data from the MrOS Sleep Study, containing polysomnography and health data from a large sample (N = 3086) of elderly American men to establish associations between sleep macrostructure, the spectral composition of the electroencephalogram, 38 medical disorders, 2 health behaviors, and the use of 48 medications. RESULTS Of sleep macrostructure variables, increased REM latency and reduced REM duration were the most common findings across health indicators, along with increased sleep latency and reduced sleep efficiency. We found that the majority of health indicators were not associated with objective EEG power spectral density (PSD) alterations. Associations with the rest were highly stereotypical, with two principal components accounting for 85-95% of the PSD-health association. PC1 consists of a decrease of slow and an increase of fast PSD components, mainly in NREM. This pattern was most strongly associated with depression/SSRI medication use and age-related disorders. PC2 consists of changes in mid-frequency activity. Increased mid-frequency activity was associated with benzodiazepine use, while decreases were associated with cardiovascular problems and associated medications, in line with a recently proposed hypothesis of immune-mediated circadian demodulation in these disorders. Specific increases in sleep spindle frequency activity were associated with taking benzodiazepines and zolpidem. Sensitivity analyses supported the presence of both disorder and medication effects. CONCLUSIONS Sleep alterations are present in various health conditions.
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Affiliation(s)
| | - Róbert Bódizs
- Institute of Behavioural Sciences, Semmelweis University, Budapest, Hungary
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Páez A, Frimpong E, Mograss M, Dang-Vu TT. The effectiveness of exercise interventions targeting sleep in older adults with cognitive impairment or Alzheimer's disease and related dementias (AD/ADRD): A systematic review and meta-analysis. J Sleep Res 2024:e14189. [PMID: 38462491 DOI: 10.1111/jsr.14189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 01/30/2024] [Accepted: 02/16/2024] [Indexed: 03/12/2024]
Abstract
Sleep loss is associated with reduced health and quality of life, and increased risk of Alzheimer's disease and related dementias. Up to 66% of persons with Alzheimer's disease and related dementias experience poor sleep, which can predict or accelerate the progression of cognitive decline. Exercise is a widely accessible intervention for poor sleep that can protect against functional and cognitive decline. No previous systematic reviews have investigated the effectiveness of exercise for sleep in older adults with mild cognitive impairment or Alzheimer's disease and related dementias. We systematically reviewed controlled interventional studies of exercise targeting subjectively or objectively (polysomnography/actigraphy) assessed sleep in persons with mild cognitive impairment or Alzheimer's disease and related dementias. We conducted searches in PubMed, Embase, Scopus and Cochrane-Library (n = 6745). Nineteen randomised and one non-randomised controlled interventional trials were included, representing the experiences of 3278 persons with mild cognitive impairment or Alzheimer's disease and related dementias. Ten had low-risk, nine moderate-risk, and one high-risk of bias. Six studies with subjective and eight with objective sleep outcomes were meta-analysed (random-effects model). We found moderate- to high-quality evidence for the beneficial effects of exercise on self-reported and objectively-measured sleep outcomes in persons with mild cognitive impairment or Alzheimer's disease and related dementias. However, no studies examined key potential moderators of these effects, such as sex, napping or medication use. Our results have important implications for clinical practice. Sleep may be one of the most important modifiable risk factors for a range of health conditions, including cognitive decline and the progression of Alzheimer's disease and related dementias. Given our findings, clinicians may consider adding exercise as an effective intervention or adjuvant strategy for improving sleep in older persons with mild cognitive impairment or Alzheimer's disease and related dementias.
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Affiliation(s)
- Arsenio Páez
- Sleep, Cognition and Neuroimaging Laboratory, Department of Health, Kinesiology and Applied Physiology, Concordia University, Montreal, Quebec, Canada
- Nuffield Department for Primary Care Health Sciences, University of Oxford, Oxford, UK
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montreal, Quebec, Canada
| | - Emmanuel Frimpong
- Sleep, Cognition and Neuroimaging Laboratory, Department of Health, Kinesiology and Applied Physiology, Concordia University, Montreal, Quebec, Canada
| | - Melodee Mograss
- Sleep, Cognition and Neuroimaging Laboratory, Department of Health, Kinesiology and Applied Physiology, Concordia University, Montreal, Quebec, Canada
- Department of Psychology, Concordia University, Montreal, Quebec, Canada
| | - Thien Thanh Dang-Vu
- Sleep, Cognition and Neuroimaging Laboratory, Department of Health, Kinesiology and Applied Physiology, Concordia University, Montreal, Quebec, Canada
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montreal, Quebec, Canada
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Wei R, Ganglberger W, Sun H, Hadar P, Gollub R, Pieper S, Billot B, Au R, Eugenio Iglesias J, Cash SS, Kim S, Shin C, Westover MB, Joseph Thomas R. Linking brain structure, cognition, and sleep: insights from clinical data. Sleep 2024; 47:zsad294. [PMID: 37950486 PMCID: PMC10851868 DOI: 10.1093/sleep/zsad294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 10/13/2023] [Indexed: 11/12/2023] Open
Abstract
STUDY OBJECTIVES To use relatively noisy routinely collected clinical data (brain magnetic resonance imaging (MRI) data, clinical polysomnography (PSG) recordings, and neuropsychological testing), to investigate hypothesis-driven and data-driven relationships between brain physiology, structure, and cognition. METHODS We analyzed data from patients with clinical PSG, brain MRI, and neuropsychological evaluations. SynthSeg, a neural network-based tool, provided high-quality segmentations despite noise. A priori hypotheses explored associations between brain function (measured by PSG) and brain structure (measured by MRI). Associations with cognitive scores and dementia status were studied. An exploratory data-driven approach investigated age-structure-physiology-cognition links. RESULTS Six hundred and twenty-three patients with sleep PSG and brain MRI data were included in this study; 160 with cognitive evaluations. Three hundred and forty-two participants (55%) were female, and age interquartile range was 52 to 69 years. Thirty-six individuals were diagnosed with dementia, 71 with mild cognitive impairment, and 326 with major depression. One hundred and fifteen individuals were evaluated for insomnia and 138 participants had an apnea-hypopnea index equal to or greater than 15. Total PSG delta power correlated positively with frontal lobe/thalamic volumes, and sleep spindle density with thalamic volume. rapid eye movement (REM) duration and amygdala volume were positively associated with cognition. Patients with dementia showed significant differences in five brain structure volumes. REM duration, spindle, and slow-oscillation features had strong associations with cognition and brain structure volumes. PSG and MRI features in combination predicted chronological age (R2 = 0.67) and cognition (R2 = 0.40). CONCLUSIONS Routine clinical data holds extended value in understanding and even clinically using brain-sleep-cognition relationships.
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Affiliation(s)
- Ruoqi Wei
- Division of Pulmonary Critical Care & Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Wolfgang Ganglberger
- McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Sleep and Health Zurich, University of Zurich, Zurich, Switzerland
| | - Haoqi Sun
- McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Peter N Hadar
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Randy L Gollub
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | | | - Benjamin Billot
- Computer Science and Artificial Intelligence Lab, MIT, Boston, MA, USA
| | - Rhoda Au
- Anatomy& Neurobiology, Neurology, Medicine and Epidemiology, Boston University Chobanian & Avedisian School of Medicine and School of Public Health, Boston University, Boston, MA, USA
| | - Juan Eugenio Iglesias
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
- Isomics, Inc. Cambridge, MA, USA
- Center for Medical Image Computing, University College London, London, UK
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Soriul Kim
- Institute of Human Genomic Study, College of Medicine, Kore University, Seoul, Republic of Korea
| | - Chol Shin
- Institute of Human Genomic Study, College of Medicine, Kore University, Seoul, Republic of Korea
- Biomedical Research Center, Korea University Ansan Hospital, Ansan, Republic of Korea
| | - M Brandon Westover
- McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Robert Joseph Thomas
- Division of Pulmonary Critical Care & Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
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14
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Taporoski TP, Beijamini F, Alexandria S, Aaby D, von Schantz M, Pereira AC, Knutson KL. Gender differences in the relationship between sleep and age in a Brazilian cohort: the Baependi Heart Study. J Sleep Res 2024:e14154. [PMID: 38286415 DOI: 10.1111/jsr.14154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 12/07/2023] [Accepted: 01/13/2024] [Indexed: 01/31/2024]
Abstract
Gender and age are well-established determinants of health and sleep health that influence overall health, which also often varies by gender and age. Sleep architecture is an important component of sleep health. The goal of this analysis was to examine whether associations between age and sleep stages differ by gender in the absence of moderate-severe obstructive sleep apnea (OSA) in a rural setting in Brazil. This study conducted polysomnography recordings in the Baependi Heart Study, a cohort of Brazilian adults. Our sample included 584 women and 309 men whose apnea-hypopnea index was ≤15 events/h. We used splines to distinguish non-linear associations between age, total sleep time, wake after sleep onset (WASO), N2, N3, and rapid-eye-movement sleep. The mean (standard deviation; range) age was 47 (14; 18-89) years. All sleep outcomes were associated with age. Compared to men, women had more N3 sleep and less WASO after adjusting for age. Model-based comparisons between genders at specific ages showed statistically higher mean WASO for men at ages 60 (+13.6 min) and 70 years (+19.5 min) and less N3 for men at ages 50 (-13.2 min), 60 (-19.0 min), and 70 years (-19.5 min) but no differences at 20, 30, 40 or 80 years. The other sleep measures did not differ by gender at any age. Thus, even in the absence of moderate-severe OSA, sleep architecture was associated with age across adulthood, and there were gender differences in WASO and N3 at older ages in this rural community.
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Affiliation(s)
- Tâmara P Taporoski
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | | | - Shaina Alexandria
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - David Aaby
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Malcolm von Schantz
- Faculty of Health and Life Sciences, Northumbria University, Newcastle Upon Tyne, UK
| | - Alexandre C Pereira
- Incor, University of São Paulo School of Medicine, São Paulo, Brazil
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Kristen L Knutson
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
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15
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Nance RM, Fohner AE, McClelland RL, Redline S, Nick Bryan R, Desiderio L, Habes M, Longstreth WT, Schwab RJ, Wiemken AS, Heckbert SR. The Association of Upper Airway Anatomy with Brain Structure: The Multi-Ethnic Study of Atherosclerosis. Brain Imaging Behav 2024:10.1007/s11682-023-00843-w. [PMID: 38194040 DOI: 10.1007/s11682-023-00843-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/21/2023] [Indexed: 01/10/2024]
Abstract
Sleep apnea, affecting an estimated 1 in 4 American adults, has been reported to be associated with both brain structural abnormality and impaired cognitive function. Obstructive sleep apnea is known to be affected by upper airway anatomy. To better understand the contribution of upper airway anatomy to pathways linking sleep apnea with impaired cognitive function, we investigated the association of upper airway anatomy with structural brain abnormalities. Based in the Multi-Ethnic Study of Atherosclerosis, a longitudinal cohort study of community-dwelling adults, a comprehensive sleep study and an MRI of the upper airway and brain were performed on 578 participants. Machine learning models were used to select from 74 upper airway measures those measures most associated with selected regional brain volumes and white matter hyperintensity volume. Linear regression assessed associations between the selected upper airway measures, sleep measures, and brain structure. Maxillary divergence was positively associated with hippocampus volume, and mandible length was negatively associated with total white and gray matter volume. Both coefficients were small (coefficients per standard deviation 0.063 mL, p = 0.04, and - 7.0 mL, p < 0.001 respectively), and not affected by adjustment for sleep study measures. Self-reported snoring >2 times per week was associated with larger hippocampus volume (coefficient 0.164 mL, p = 0.007), and higher percentage of time in the N3 sleep stage was associated with larger total white and gray matter volume (4.8 mL, p = 0.004). Despite associations of two upper airway anatomy measures with brain volume, the evidence did not suggest that these upper airway and brain structure associations were acting primarily through the pathway of sleep disturbance.
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Affiliation(s)
- Robin M Nance
- University of Washington, Seattle, WA, USA.
- , 325 9th Ave, Box 359931, Seattle, WA, 98104, USA.
| | - Alison E Fohner
- Department of Epidemiology & Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | | | - Susan Redline
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - R Nick Bryan
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Mohamad Habes
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - W T Longstreth
- Departments of Neurology and Epidemiology, University of Washington, Seattle, WA, USA
| | - Richard J Schwab
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew S Wiemken
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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16
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Sui R, Li J, Shi Y, Yuan S, Wang H, Liao J, Gao X, Han D, Li Y, Wang X. Associations Between Sleep Spindle Metrics, Age, Education and Executive Function in Young Adult and Middle-Aged Patients with Obstructive Sleep Apnea. Nat Sci Sleep 2024; 16:1-15. [PMID: 38213412 PMCID: PMC10778138 DOI: 10.2147/nss.s436824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 12/18/2023] [Indexed: 01/13/2024] Open
Abstract
Purpose This study aimed to investigate the association between sleep spindle metrics and executive function in individuals with obstructive sleep apnea (OSA). Furthermore, we examined the association of age and education on executive function. Patients and Methods A total of 230 (40.90 ± 8.83 years, F/M = 45/185) participants were enrolled. Overnight electroencephalogram (C3-M2) recording detected sleep spindles by a novel U-Net-type neural network that integrates temporal information with time-frequency images. Sleep spindle metrics, including frequency (Hz), overall density (events/min), fast density (events/min), slow density (events/min), duration (sec) and amplitude (µV), were measured. Executive function was assessed using standardized neuropsychological tests. Associations between sleep spindle metrics, executive function, and demographic factors were analyzed using multivariate linear regression. Results In fully adjusted linear regression models, higher overall sleep spindle density (TMT-A, B=-1.279, p=0.009; TMT-B, B=-1.813, p=0.008), fast sleep spindle density (TMT-A, B=-1.542, p=0.048; TMT-B, B=-2.187, p=0.036) and slow sleep spindle density (TMT-A, B=-1.731, p=0.037; TMT-B, B=-2.449, p=0.034) were associated with better executive function. And the sleep spindle duration both during N2 sleep time (TMT-A, B=-13.932, p=0.027; TMT-B, B=-19.001, p=0.034) and N3 sleep time (TMT-B, B=-29.916, p=0.009; Stroop-incongruous, B=-21.303, p=0.035) was independently associated with better executive function in this population. Additionally, age and education were found to be highly associated with executive function. Conclusion Specific sleep spindle metrics, higher overall density, fast density and slow density during N2 sleep time, and longer duration during N2 and N3 sleep time, are independent and sensitive indicators of better executive function in young adult and middle-aged patients with OSA. Further research is needed to explore the underlying mechanisms and clinical implications of these findings.
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Affiliation(s)
- Rongcui Sui
- Department of Otorhinolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of China
- Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, People’s Republic of China
- Key Laboratory of Otolaryngology-Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, People’s Republic of China
| | - Jie Li
- Department of Electronic Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, People’s Republic of China
| | - Yunhan Shi
- Department of Otorhinolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of China
- Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, People’s Republic of China
- Key Laboratory of Otolaryngology-Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, People’s Republic of China
| | - Shizhen Yuan
- Department of Otorhinolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of China
- Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, People’s Republic of China
- Key Laboratory of Otolaryngology-Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, People’s Republic of China
| | - Huijun Wang
- Department of Otorhinolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of China
- Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, People’s Republic of China
- Key Laboratory of Otolaryngology-Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, People’s Republic of China
| | - Jianhong Liao
- Department of Otorhinolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of China
- Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, People’s Republic of China
- Key Laboratory of Otolaryngology-Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, People’s Republic of China
| | - Xiang Gao
- Department of Otorhinolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of China
- Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, People’s Republic of China
- Key Laboratory of Otolaryngology-Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, People’s Republic of China
| | - Demin Han
- Department of Otorhinolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of China
- Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, People’s Republic of China
- Key Laboratory of Otolaryngology-Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, People’s Republic of China
| | - Yanru Li
- Department of Otorhinolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of China
- Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, People’s Republic of China
- Key Laboratory of Otolaryngology-Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, People’s Republic of China
| | - Xingjun Wang
- Department of Electronic Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, People’s Republic of China
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Bender AC, Jaleel A, Pellerin KR, Moguilner S, Sarkis RA, Cash SS, Lam AD. Altered Sleep Microarchitecture and Cognitive Impairment in Patients With Temporal Lobe Epilepsy. Neurology 2023; 101:e2376-e2387. [PMID: 37848332 PMCID: PMC10752648 DOI: 10.1212/wnl.0000000000207942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 08/28/2023] [Indexed: 10/19/2023] Open
Abstract
BACKGROUND AND OBJECTIVES To investigate the spatiotemporal characteristics of sleep waveforms in temporal lobe epilepsy (TLE) and examine their association with cognition. METHODS In this retrospective, cross-sectional study, we examined overnight EEG data from adult patients with TLE and nonepilepsy comparisons (NECs) admitted to the epilepsy monitoring unit at Mass General Brigham hospitals. Automated algorithms were used to characterize sleep macroarchitecture (sleep stages) and microarchitecture (spindles, slow oscillations [SOs]) on scalp EEG and to detect hippocampal interictal epileptiform discharges (hIEDs) from foramen ovale electrodes simultaneously recorded in a subset of patients with TLE. We examined the association of sleep features and hIEDs with memory and executive function from clinical neuropsychological evaluations. RESULTS A total of 81 adult patients with TLE and 28 NEC adult patients were included with similar mean ages. There were no significant differences in sleep macroarchitecture between groups, including relative time spent in each sleep stage, sleep efficiency, and sleep fragmentation. By contrast, the spatiotemporal characteristics of sleep microarchitecture were altered in TLE compared with NEC and were associated with cognitive impairments. Specifically, we observed a ∼30% reduction in spindle density in patients with TLE compared with NEC, which was significantly associated with worse memory performance. Spindle-SO coupling strength was also reduced in TLE and, in contrast to spindles, was associated with diminished executive function. We found no significant association between sleep macroarchitectural and microarchitectural parameters and hIEDs. DISCUSSION There is a fundamental alteration of sleep microarchitecture in TLE, characterized by a reduction in spindle density and spindle-SO coupling, and these changes may contribute to neurocognitive comorbidity in this disorder.
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Affiliation(s)
- Alex C Bender
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA.
| | - Afareen Jaleel
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA
| | - Kyle R Pellerin
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA
| | - Sebastian Moguilner
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA
| | - Rani A Sarkis
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA
| | - Sydney S Cash
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA
| | - Alice D Lam
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA
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18
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Reid MJ, Quigg M, Finan PH. Sleep-EEG in comorbid pain and insomnia: implications for the treatment of pain disorders. Pain Rep 2023; 8:e1101. [PMID: 37899939 PMCID: PMC10599985 DOI: 10.1097/pr9.0000000000001101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 05/20/2023] [Indexed: 10/31/2023] Open
Abstract
Introduction Patients with chronic pain experience a high prevalence of comorbid insomnia, which is associated with functional impairment. Recent advances in sleep electroencephalography (sleep-EEG) may clarify the mechanisms that link sleep and chronic pain. In this clinical update, we outline current advancements in sleep-EEG assessments for pain and provide research recommendations. Results Promising preliminary work suggests that sleep-EEG spectral bands, particularly beta, gamma, alpha, and delta power, may create candidate neurophysiological signatures of pain, and macro-architectural parameters (e.g., total sleep time, arousals, and sleep continuity) may facilitate EEG-derived sleep phenotyping and may enable future stratification in the treatment of pain. Conclusion Integration of measures obtained through sleep-EEG represent feasible and scalable approaches that could be adopted in the future. We provide research recommendations to progress the field towards a deeper understanding of their utility and potential future applications in clinical practice.
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Affiliation(s)
- Matthew J. Reid
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Mark Quigg
- Department of Neurology, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Patrick H. Finan
- Department of Neurology, University of Virginia School of Medicine, Charlottesville, VA, USA
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19
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Nance RM, Fohner AE, McClelland RL, Redline S, Bryan RN, Fitzpatrick A, Habes M, Longstreth WT, Schwab RJ, Wiemken AS, Heckbert SR. The association of upper airway anatomy with cognitive test performance: the Multi-Ethnic Study of Atherosclerosis. BMC Neurol 2023; 23:394. [PMID: 37907860 PMCID: PMC10617161 DOI: 10.1186/s12883-023-03443-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 10/19/2023] [Indexed: 11/02/2023] Open
Abstract
BACKGROUND Numerous upper airway anatomy characteristics are risk factors for sleep apnea, which affects 26% of older Americans, and more severe sleep apnea is associated with cognitive impairment. This study explores the pathophysiology and links between upper airway anatomy, sleep, and cognition. METHODS Participants in the Multi-Ethnic Study of Atherosclerosis underwent an upper airway MRI, polysomnography to assess sleep measures including the apnea-hypopnea index (AHI) and completed the Cognitive Abilities Screening Instrument (CASI). Two model selection techniques selected from among 67 upper airway measures those that are most strongly associated with CASI score. The associations of selected upper airway measures with AHI, AHI with CASI score, and selected upper airway anatomy measures with CASI score, both alone and after adjustment for AHI, were assessed using linear regression. RESULTS Soft palate volume, maxillary divergence, and upper facial height were significantly positively associated with higher CASI score, indicating better cognition. The coefficients were small, with a 1 standard deviation (SD) increase in these variables being associated with a 0.83, 0.75, and 0.70 point higher CASI score, respectively. Additional adjustment for AHI very slightly attenuated these associations. Larger soft palate volume was significantly associated with higher AHI (15% higher AHI (95% CI 2%,28%) per SD). Higher AHI was marginally associated with higher CASI score (0.43 (95% CI 0.01,0.85) per AHI doubling). CONCLUSIONS Three upper airway measures were weakly but significantly associated with higher global cognitive test performance. Sleep apnea did not appear to be the mechanism through which these upper airway and cognition associations were acting. Further research on the selected upper airway measures is recommended.
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Affiliation(s)
- Robin M Nance
- University of Washington, 325 9th Ave, Box 359931, Seattle, 98104, USA.
| | - Alison E Fohner
- Department of Epidemiology & Cardiovascular Health Research Unit, University of Washington, Seattle, USA
| | | | - Susan Redline
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - R Nick Bryan
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | | | - Mohamad Habes
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - W T Longstreth
- Departments of Neurology and Epidemiology, University of Washington, Seattle, USA
| | - Richard J Schwab
- Department of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Andrew S Wiemken
- Department of Medicine, University of Pennsylvania, Philadelphia, USA
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Skourti E, Simos P, Zampetakis A, Koutentaki E, Zaganas I, Alexopoulou C, Vgontzas A, Basta M. Long-term associations between objective sleep quality and quantity and verbal memory performance in normal cognition and mild cognitive impairment. Front Neurosci 2023; 17:1265016. [PMID: 37928739 PMCID: PMC10620682 DOI: 10.3389/fnins.2023.1265016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 09/29/2023] [Indexed: 11/07/2023] Open
Abstract
Introduction Although the link between sleep and memory function is well established, associations between sleep macrostructure and memory function in normal cognition and Mild Cognitive Impairment remain unclear. We aimed to investigate the longitudinal associations of baseline objectively assessed sleep quality and duration, as well as time in bed, with verbal memory capacity over a 7-9 year period. Participants are a well-characterized subsample of 148 persons (mean age at baseline: 72.8 ± 6.7 years) from the Cretan Aging Cohort. Based on comprehensive neuropsychiatric and neuropsychological evaluation at baseline, participants were diagnosed with Mild Cognitive Impairment (MCI; n = 79) or found to be cognitively unimpaired (CNI; n = 69). Sleep quality/quantity was estimated from a 3-day consecutive actigraphy recording, whereas verbal memory capacity was examined using the Rey Auditory Verbal Learning Test (RAVLT) and the Greek Passage Memory Test at baseline and follow-up. Panel models were applied to the data using AMOS including several sociodemographic and clinical covariates. Results Sleep efficiency at baseline directly predicted subsequent memory performance in the total group (immediate passage recall: β = 0.266, p = 0.001; immediate word list recall: β = 0.172, p = 0.01; delayed passage retrieval: β = 0.214, p = 0.002) with the effects in Passage Memory reaching significance in both clinical groups. Wake after sleep onset time directly predicted follow-up immediate passage recall in the total sample (β = -0.211, p = 0.001) and in the MCI group (β = -0.235, p = 0.02). In the total sample, longer 24-h sleep duration was associated with reduced memory performance indirectly through increased sleep duration at follow-up (immediate passage recall: β = -0.045, p = 0.01; passage retention index: β = -0.051, p = 0.01; RAVLT-delayed recall: β = -0.048, p = 0.009; RAVLT-retention index:β = -0.066, p = 0.004). Similar indirect effects were found for baseline 24-h time in bed. Indirect effects of sleep duration/time in bed were found predominantly in the MCI group. Discussion Findings corroborate and expand previous work suggesting that poor sleep quality and long sleep duration predict worse memory function in elderly. Timely interventions to improve sleep could help prevent or delay age-related memory decline among non-demented elderly.
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Affiliation(s)
- Eleni Skourti
- Division of Psychiatry and Behavioral Sciences, School of Medicine, University of Crete, Heraklion, Greece
| | - Panagiotis Simos
- Division of Psychiatry and Behavioral Sciences, School of Medicine, University of Crete, Heraklion, Greece
- Computational Biomedicine Lab, Institute of Computer Science, Foundation for Research and Technology-Hellas, Heraklion, Greece
- Department of Psychiatry, University Hospital of Heraklion, Crete, Greece
| | - Alexandros Zampetakis
- Division of Psychiatry and Behavioral Sciences, School of Medicine, University of Crete, Heraklion, Greece
| | - Eirini Koutentaki
- Department of Psychiatry, University Hospital of Heraklion, Crete, Greece
| | - Ioannis Zaganas
- Division of Neurology and Sensory Organs, School of Medicine, University of Crete, Heraklion, Greece
| | | | - Alexandros Vgontzas
- Division of Psychiatry and Behavioral Sciences, School of Medicine, University of Crete, Heraklion, Greece
- Department of Psychiatry, University Hospital of Heraklion, Crete, Greece
- Sleep Research and Treatment Center, Department of Psychiatry and Behavioral Health, Penn State Health Milton S. Hershey Medical Center, College of Medicine, Pennsylvania State University, Hershey, PA, United States
| | - Maria Basta
- Division of Psychiatry and Behavioral Sciences, School of Medicine, University of Crete, Heraklion, Greece
- Department of Psychiatry, University Hospital of Heraklion, Crete, Greece
- Sleep Research and Treatment Center, Department of Psychiatry and Behavioral Health, Penn State Health Milton S. Hershey Medical Center, College of Medicine, Pennsylvania State University, Hershey, PA, United States
- Day Care Center for Alzheimer’s Disease “Nefeli”, University Hospital of Heraklion, Crete, Greece
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21
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Parker JL, Appleton SL, Adams RJ, Melaku YA, D'Rozario AL, Wittert GA, Martin SA, Catcheside PG, Lechat B, Teare AJ, Toson B, Vakulin A. The association between sleep spindles and cognitive function in middle-aged and older men from a community-based cohort study. Sleep Health 2023; 9:774-785. [PMID: 37268483 DOI: 10.1016/j.sleh.2023.03.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 03/27/2023] [Accepted: 03/28/2023] [Indexed: 06/04/2023]
Abstract
OBJECTIVES Previous studies examining associations between sleep spindles and cognitive function attempted to account for obstructive sleep apnea without consideration for potential moderating effects. To elucidate associations between sleep spindles, cognitive function, and obstructive sleep apnea, this study of community-dwelling men examined cross-sectional associations between sleep spindle metrics and daytime cognitive function outcomes following adjustment for obstructive sleep apnea and potential obstructive sleep apnea moderating effects. METHODS Florey Adelaide Male Ageing Study participants (n = 477, 41-87 years) reporting no previous obstructive sleep apnea diagnosis underwent home-based polysomnography (2010-2011). Cognitive testing (2007-2010) included the inspection time task (processing speed), trail-making tests A (TMT-A) (visual attention) and B (trail-making test-B) (executive function), and Fuld object memory evaluation (episodic memory). Frontal spindle metrics (F4-M1) included occurrence (count), average frequency (Hz), amplitude (µV), and overall (11-16 Hz), slow (11-13 Hz), and fast (13-16 Hz) spindle density (number/minute during N2 and N3 sleep). RESULTS In fully adjusted linear regression models, lower N2 sleep spindle occurrence was associated with longer inspection times (milliseconds) (B = -0.43, 95% confidence interval [-0.74, -0.12], p = .006), whereas higher N3 sleep fast spindle density was associated with worse TMT-B performance (seconds) (B = 18.4, 95% confidence interval [1.62, 35.2], p = .032). Effect moderator analysis revealed that in men with severe obstructive sleep apnea (apnea-hypopnea index ≥30/hour), slower N2 sleep spindle frequency was associated with worse TMT-A performance (χ2 = 12.5, p = .006). CONCLUSIONS Specific sleep spindle metrics were associated with cognitive function, and obstructive sleep apnea severity moderated these associations. These observations support the utility of sleep spindles as useful cognitive function markers in obstructive sleep apnea, which warrants further longitudinal investigation.
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Affiliation(s)
- Jesse L Parker
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia, Australia.
| | - Sarah L Appleton
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia, Australia.
| | - Robert J Adams
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia, Australia; Respiratory and Sleep Services, Southern Adelaide Local Health Network, Adelaide, South Australia, Australia.
| | - Yohannes Adama Melaku
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia, Australia.
| | - Angela L D'Rozario
- CIRUS, Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, University of Sydney, Sydney, New South Wales, Australia; The University of Sydney, Faculty of Science, School of Psychology, Sydney, New South Wales, Australia.
| | - Gary A Wittert
- Australian Institute of Family Studies, Melbourne, Victoria, Australia; Freemasons Centre for Male Health and Wellbeing, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia.
| | - Sean A Martin
- Australian Institute of Family Studies, Melbourne, Victoria, Australia; Freemasons Centre for Male Health and Wellbeing, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia.
| | - Peter G Catcheside
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia, Australia.
| | - Bastien Lechat
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia, Australia.
| | - Alison J Teare
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia, Australia.
| | - Barbara Toson
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia, Australia.
| | - Andrew Vakulin
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia, Australia; CIRUS, Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, University of Sydney, Sydney, New South Wales, Australia.
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22
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Ujma PP, Bódizs R, Dresler M, Simor P, Purcell S, Stone KL, Yaffe K, Redline S. Multivariate prediction of cognitive performance from the sleep electroencephalogram. Neuroimage 2023; 279:120319. [PMID: 37574121 PMCID: PMC10661862 DOI: 10.1016/j.neuroimage.2023.120319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 08/06/2023] [Accepted: 08/10/2023] [Indexed: 08/15/2023] Open
Abstract
Human cognitive performance is a key function whose biological foundations have been partially revealed by genetic and brain imaging studies. The sleep electroencephalogram (EEG) is tightly linked to structural and functional features of the central nervous system and serves as another promising biomarker. We used data from MrOS, a large cohort of older men and cross-validated regularized regression to link sleep EEG features to cognitive performance in cross-sectional analyses. In independent validation samples 2.5-10% of variance in cognitive performance can be accounted for by sleep EEG features, depending on the covariates used. Demographic characteristics account for more covariance between sleep EEG and cognition than health variables, and consequently reduce this association by a greater degree, but even with the strictest covariate sets a statistically significant association is present. Sigma power in NREM and beta power in REM sleep were associated with better cognitive performance, while theta power in REM sleep was associated with worse performance, with no substantial effect of coherence and other sleep EEG metrics. Our findings show that cognitive performance is associated with the sleep EEG (r = 0.283), with the strongest effect ascribed to spindle-frequency activity. This association becomes weaker after adjusting for demographic (r = 0.186) and health variables (r = 0.155), but its resilience to covariate inclusion suggest that it also partially reflects trait-like differences in cognitive ability.
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Affiliation(s)
- Péter P Ujma
- Semmelweis University, Institute of Behavioural Sciences, Budapest, Hungary.
| | - Róbert Bódizs
- Semmelweis University, Institute of Behavioural Sciences, Budapest, Hungary
| | - Martin Dresler
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center Nijmegen, Nijmegen, the Netherlands
| | - Péter Simor
- Institute of Psychology, Eötvös Loránd University, Budapest, Hungary
| | - Shaun Purcell
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Harvard University, USA
| | - Katie L Stone
- California Pacific Medical Center Research Institute, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
| | - Kristine Yaffe
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA; Department of Psychiatry, University of California, San Francisco, California, USA; Department of Neurology, University of California, San Francisco, California, USA; San Francisco VA Medical Center, San Francisco, California, USA
| | - Susan Redline
- Brigham and Women's Hospital, Harvard University, Boston, MA, USA
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23
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Kianersi S, Redline S, Mongraw-Chaffin M, Huang T. Associations of Slow-Wave Sleep With Prevalent and Incident Type 2 Diabetes in the Multi-Ethnic Study of Atherosclerosis. J Clin Endocrinol Metab 2023; 108:e1044-e1055. [PMID: 37084404 PMCID: PMC10686689 DOI: 10.1210/clinem/dgad229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 04/17/2023] [Accepted: 04/17/2023] [Indexed: 04/23/2023]
Abstract
CONTEXT N3 sleep (i.e., slow-wave sleep), a marker of deep restorative sleep, is implicated in hormonal and blood pressure regulation and may impact cardiometabolic health. OBJECTIVE We conducted cross-sectional and prospective analyses to test whether a higher proportion and longer duration of N3 sleep are associated with reduced type 2 diabetes risk. METHODS A subsample of participants from the Multi-Ethnic Study of Atherosclerosis completed 1-night polysomnography at Exam 5 (2010-2013) and were prospectively followed until Exam 6 (2016-2018). We used modified Poisson regression to examine the cross-sectional associations of N3 proportion and duration with prevalent diabetes and Cox proportional hazards models to estimate risk of diabetes according to N3 measures. RESULTS In cross-sectional analyses (n = 2026, mean age: 69 years), diabetes prevalence was 28% (n = 572). Compared with the first quartile (Q1) of the N3 proportion (<2.0%), participants in Q4 (≥15.4%) were 29% (95% CI 0.58, 0.87) less likely to have prevalent diabetes (P trend = .0016). The association attenuated after adjustment for demographics, lifestyles, and sleep-related factors (P trend = .3322). In prospective analyses of 1251 participants and 129 incident cases over 6346 person-years of follow-up, a curvilinear relationship was observed between N3 proportion and incident diabetes risk. In the fully adjusted model, the hazard ratio (95% CI) of developing diabetes vs Q1 was 0.47 (0.26, 0.87) for Q2, 0.34 (0.15, 0.77) for Q3, and 0.32 (0.10, 0.97) for Q4 (P nonlinearity = .0213). The results were similar for N3 duration. CONCLUSION Higher N3 proportion and longer N3 duration were prospectively associated with lower type 2 diabetes risk in a nonlinear fashion among older American adults.
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Affiliation(s)
- Sina Kianersi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Susan Redline
- Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Morgana Mongraw-Chaffin
- Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Tianyi Huang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA
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24
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Xia Y, Wang G, Xiao L, Du Y, Lin S, Nan C, Weng S. Effects of Early Adverse Life Events on Depression and Cognitive Performance from the Perspective of the Heart-Brain Axis. Brain Sci 2023; 13:1174. [PMID: 37626530 PMCID: PMC10452582 DOI: 10.3390/brainsci13081174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/30/2023] [Accepted: 08/04/2023] [Indexed: 08/27/2023] Open
Abstract
Early adverse life events (EALs) increase susceptibility to depression and impair cognitive performance, but the physiological mechanisms are still unclear. The target of this article is to clarify the impact of adverse childhood experiences on emotional and cognitive performance from the perspective of the heart-brain axis. We used the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) to test cognitive function and the Childhood Trauma Questionnaire (CTQ) to assess adverse childhood experiences. Heart rate variability (HRV) and electroencephalograms (EEG) were acquired at rest. We observed that subjects with depression had experienced more traumatic events during their childhood. Furthermore, they exhibited lower heart rate variability and higher power in the delta, theta, and alpha frequency bands. Moreover, heart rate variability partially mediated the association between childhood trauma exposure and depressive symptoms. Our findings suggested that adverse life events in childhood could influence the development of depression in adulthood, which might be linked to cardiac autonomic dysfunction and altered brain function.
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Affiliation(s)
- Yujie Xia
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Rd., Wuhan 430060, China; (Y.X.)
| | - Gaohua Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Rd., Wuhan 430060, China; (Y.X.)
- Institute of Neuropsychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Rd., Wuhan 430060, China
- Taikang Center for Life and Medical Sciences, Wuhan University, China Donghu Road No. 115, Wuhan 430071, China
| | - Ling Xiao
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Rd., Wuhan 430060, China; (Y.X.)
- Institute of Neuropsychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Rd., Wuhan 430060, China
| | - Yiwei Du
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Rd., Wuhan 430060, China; (Y.X.)
| | - Shanshan Lin
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Rd., Wuhan 430060, China; (Y.X.)
| | - Cai Nan
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Rd., Wuhan 430060, China; (Y.X.)
| | - Shenhong Weng
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Rd., Wuhan 430060, China; (Y.X.)
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25
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Adra N, Dümmer LW, Paixao L, Tesh RA, Sun H, Ganglberger W, Westmeijer M, Da Silva Cardoso M, Kumar A, Ye E, Henry J, Cash SS, Kitchener E, Leveroni CL, Au R, Rosand J, Salinas J, Lam AD, Thomas RJ, Westover MB. Decoding information about cognitive health from the brainwaves of sleep. Sci Rep 2023; 13:11448. [PMID: 37454163 PMCID: PMC10349883 DOI: 10.1038/s41598-023-37128-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 06/16/2023] [Indexed: 07/18/2023] Open
Abstract
Sleep electroencephalogram (EEG) signals likely encode brain health information that may identify individuals at high risk for age-related brain diseases. Here, we evaluate the correlation of a previously proposed brain age biomarker, the "brain age index" (BAI), with cognitive test scores and use machine learning to develop and validate a series of new sleep EEG-based indices, termed "sleep cognitive indices" (SCIs), that are directly optimized to correlate with specific cognitive scores. Three overarching cognitive processes were examined: total, fluid (a measure of cognitive processes involved in reasoning-based problem solving and susceptible to aging and neuropathology), and crystallized cognition (a measure of cognitive processes involved in applying acquired knowledge toward problem-solving). We show that SCI decoded information about total cognition (Pearson's r = 0.37) and fluid cognition (Pearson's r = 0.56), while BAI correlated only with crystallized cognition (Pearson's r = - 0.25). Overall, these sleep EEG-derived biomarkers may provide accessible and clinically meaningful indicators of neurocognitive health.
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Affiliation(s)
- Noor Adra
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA
| | - Lisa W Dümmer
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
- University of Groningen, Groningen, The Netherlands
| | - Luis Paixao
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
- Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Ryan A Tesh
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA
| | - Haoqi Sun
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA
| | - Wolfgang Ganglberger
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
- Sleep and Health Zurich, University of Zurich, Zurich, Switzerland
| | - Mike Westmeijer
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
- Utrecht University, Utrecht, The Netherlands
| | - Madalena Da Silva Cardoso
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
| | - Anagha Kumar
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
| | - Elissa Ye
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
| | - Jonathan Henry
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
| | - Erin Kitchener
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA
| | | | - Rhoda Au
- Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Jonathan Rosand
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA
| | - Joel Salinas
- New York University Grossman School of Medicine, New York, NY, USA
| | - Alice D Lam
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA
| | - Robert J Thomas
- Division of Pulmonary, Critical Care, and Sleep, Department of Medicine, Beth Israel Deaconess Medical Center (BIDMC), Boston, MA, USA
| | - M Brandon Westover
- Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA.
- Clinical Data Animation Center (CDAC), MGH, Boston, MA, USA.
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, MA, 02114, USA.
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26
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Pase MP, Harrison S, Misialek JR, Kline CE, Cavuoto M, Baril AA, Yiallourou S, Bisson A, Himali D, Leng Y, Yang Q, Seshadri S, Beiser A, Gottesman RF, Redline S, Lopez O, Lutsey PL, Yaffe K, Stone KL, Purcell SM, Himali JJ. Sleep Architecture, Obstructive Sleep Apnea, and Cognitive Function in Adults. JAMA Netw Open 2023; 6:e2325152. [PMID: 37462968 PMCID: PMC10354680 DOI: 10.1001/jamanetworkopen.2023.25152] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 06/07/2023] [Indexed: 07/21/2023] Open
Abstract
Importance Good sleep is essential for health, yet associations between sleep and dementia risk remain incompletely understood. The Sleep and Dementia Consortium was established to study associations between polysomnography (PSG)-derived sleep and the risk of dementia and related cognitive and brain magnetic resonance imaging endophenotypes. Objective To investigate association of sleep architecture and obstructive sleep apnea (OSA) with cognitive function in the Sleep and Dementia Consortium. Design, Setting, and Participants The Sleep and Dementia Consortium curated data from 5 population-based cohorts across the US with methodologically consistent, overnight, home-based type II PSG and neuropsychological assessments over 5 years of follow-up: the Atherosclerosis Risk in Communities study, Cardiovascular Health Study, Framingham Heart Study (FHS), Osteoporotic Fractures in Men Study, and Study of Osteoporotic Fractures. Sleep metrics were harmonized centrally and then distributed to participating cohorts for cohort-specific analysis using linear regression; study-level estimates were pooled in random effects meta-analyses. Results were adjusted for demographic variables, the time between PSG and neuropsychological assessment (0-5 years), body mass index, antidepressant use, and sedative use. There were 5946 participants included in the pooled analyses without stroke or dementia. Data were analyzed from March 2020 to June 2023. Exposures Measures of sleep architecture and OSA derived from in-home PSG. Main Outcomes and Measures The main outcomes were global cognitive composite z scores derived from principal component analysis, with cognitive domains investigated as secondary outcomes. Higher scores indicated better performance. Results Across cohorts, 5946 adults (1875 females [31.5%]; mean age range, 58-89 years) were included. The median (IQR) wake after sleep onset time ranged from 44 (27-73) to 101 (66-147) minutes, and the prevalence of moderate to severe OSA ranged from 16.9% to 28.9%. Across cohorts, higher sleep maintenance efficiency (pooled β per 1% increase, 0.08; 95% CI, 0.03 to 0.14; P < .01) and lower wake after sleep onset (pooled β per 1-min increase, -0.07; 95% CI, -0.13 to -0.01 per 1-min increase; P = .02) were associated with better global cognition. Mild to severe OSA (apnea-hypopnea index [AHI] ≥5) was associated with poorer global cognition (pooled β, -0.06; 95% CI, -0.11 to -0.01; P = .01) vs AHI less than 5; comparable results were found for moderate to severe OSA (pooled β, -0.06; 95% CI, -0.11 to -0.01; P = .02) vs AHI less than 5. Differences in sleep stages were not associated with cognition. Conclusions and Relevance This study found that better sleep consolidation and the absence of OSA were associated with better global cognition over 5 years of follow-up. These findings suggest that the role of interventions to improve sleep for maintaining cognitive function requires investigation.
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Affiliation(s)
- Matthew P. Pase
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
- Harvard T.H. Chan School of Public Health, Massachusetts
- Framingham Heart Study, Framingham, Massachusetts
| | | | - Jeffrey R. Misialek
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis
| | - Christopher E. Kline
- Department of Health and Human Development, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Marina Cavuoto
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - Andree-Ann Baril
- Framingham Heart Study, Framingham, Massachusetts
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Stephanie Yiallourou
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - Alycia Bisson
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Dibya Himali
- Framingham Heart Study, Framingham, Massachusetts
| | - Yue Leng
- Department of Psychiatry and Behavioral Sciences, University of California
| | - Qiong Yang
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Sudha Seshadri
- Framingham Heart Study, Framingham, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio
| | - Alexa Beiser
- Framingham Heart Study, Framingham, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Rebecca F. Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, Maryland
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Oscar Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Pamela L. Lutsey
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis
| | - Kristine Yaffe
- Department of Psychiatry, University of California, San Francisco
- Department of Neurology, University of California, San Francisco
- Department of Epidemiology, University of California, San Francisco
| | - Katie L. Stone
- California Pacific Medical Center, Research Institute, San Francisco
- Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - Shaun M. Purcell
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Jayandra J. Himali
- Framingham Heart Study, Framingham, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio
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Parker JL, Vakulin A, Melaku YA, Wittert GA, Martin SA, D’Rozario AL, Catcheside PG, Lechat B, Toson B, Teare AJ, Appleton SL, Adams RJ. Associations of Baseline Sleep Microarchitecture with Cognitive Function After 8 Years in Middle-Aged and Older Men from a Community-Based Cohort Study. Nat Sci Sleep 2023; 15:389-406. [PMID: 37252206 PMCID: PMC10225127 DOI: 10.2147/nss.s401655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 05/17/2023] [Indexed: 05/31/2023] Open
Abstract
Purpose Prospective studies examining associations between baseline sleep microarchitecture and future cognitive function recruited from small samples with predominantly short follow-up. This study examined sleep microarchitecture predictors of cognitive function (visual attention, processing speed, and executive function) after 8 years in community-dwelling men. Patients and Methods Florey Adelaide Male Ageing Study participants (n=477) underwent home-based polysomnography (2010-2011), with 157 completing baseline (2007-2010) and follow-up (2018-2019) cognitive assessments (trail-making tests A [TMT-A] and B [TMT-B] and the standardized mini-mental state examination [SMMSE]). Whole-night F4-M1 sleep EEG recordings were processed following artifact exclusion, and quantitative EEG characteristics were obtained using validated algorithms. Associations between baseline sleep microarchitecture and future cognitive function (visual attention, processing speed, and executive function) were examined using linear regression models adjusted for baseline obstructive sleep apnoea, other risk factors, and cognition. Results The final sample included men aged (mean [SD]) 58.9 (8.9) years at baseline, overweight (BMI 28.5 [4.2] kg/m2), and well educated (75.2% ≥Bachelor, Certificate, or Trade), with majorly normal baseline cognition. Median (IQR) follow-up was 8.3 (7.9, 8.6) years. In adjusted analyses, NREM and REM sleep EEG spectral power was not associated with TMT-A, TMT-B, or SMMSE performance (all p>0.05). A significant association of higher N3 sleep fast spindle density with worse TMT-B performance (B=1.06, 95% CI [0.13, 2.00], p=0.026) did not persist following adjustment for baseline TMT-B performance. Conclusion In this sample of community-dwelling men, sleep microarchitecture was not independently associated with visual attention, processing speed, or executive function after 8 years.
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Affiliation(s)
- Jesse L Parker
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, SA, Australia
| | - Andrew Vakulin
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, SA, Australia
- CIRUS, Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, University of Sydney, Sydney, NSW, Australia
| | - Yohannes Adama Melaku
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, SA, Australia
| | - Gary A Wittert
- Freemasons Centre for Male Health and Wellbeing, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Sean A Martin
- Freemasons Centre for Male Health and Wellbeing, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Angela L D’Rozario
- CIRUS, Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, University of Sydney, Sydney, NSW, Australia
- The University of Sydney, Faculty of Science, School of Psychology, Sydney, NSW, Australia
| | - Peter G Catcheside
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, SA, Australia
| | - Bastien Lechat
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, SA, Australia
| | - Barbara Toson
- College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
| | - Alison J Teare
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, SA, Australia
| | - Sarah L Appleton
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Robert J Adams
- Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
- Respiratory and Sleep Services, Southern Adelaide Local Health Network, Adelaide, SA, Australia
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Song TA, Chowdhury SR, Malekzadeh M, Harrison S, Hoge TB, Redline S, Stone KL, Saxena R, Purcell SM, Dutta J. AI-Driven sleep staging from actigraphy and heart rate. PLoS One 2023; 18:e0285703. [PMID: 37195925 PMCID: PMC10191307 DOI: 10.1371/journal.pone.0285703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 05/02/2023] [Indexed: 05/19/2023] Open
Abstract
Sleep is an important indicator of a person's health, and its accurate and cost-effective quantification is of great value in healthcare. The gold standard for sleep assessment and the clinical diagnosis of sleep disorders is polysomnography (PSG). However, PSG requires an overnight clinic visit and trained technicians to score the obtained multimodality data. Wrist-worn consumer devices, such as smartwatches, are a promising alternative to PSG because of their small form factor, continuous monitoring capability, and popularity. Unlike PSG, however, wearables-derived data are noisier and far less information-rich because of the fewer number of modalities and less accurate measurements due to their small form factor. Given these challenges, most consumer devices perform two-stage (i.e., sleep-wake) classification, which is inadequate for deep insights into a person's sleep health. The challenging multi-class (three, four, or five-class) staging of sleep using data from wrist-worn wearables remains unresolved. The difference in the data quality between consumer-grade wearables and lab-grade clinical equipment is the motivation behind this study. In this paper, we present an artificial intelligence (AI) technique termed sequence-to-sequence LSTM for automated mobile sleep staging (SLAMSS), which can perform three-class (wake, NREM, REM) and four-class (wake, light, deep, REM) sleep classification from activity (i.e., wrist-accelerometry-derived locomotion) and two coarse heart rate measures-both of which can be reliably obtained from a consumer-grade wrist-wearable device. Our method relies on raw time-series datasets and obviates the need for manual feature selection. We validated our model using actigraphy and coarse heart rate data from two independent study populations: the Multi-Ethnic Study of Atherosclerosis (MESA; N = 808) cohort and the Osteoporotic Fractures in Men (MrOS; N = 817) cohort. SLAMSS achieves an overall accuracy of 79%, weighted F1 score of 0.80, 77% sensitivity, and 89% specificity for three-class sleep staging and an overall accuracy of 70-72%, weighted F1 score of 0.72-0.73, 64-66% sensitivity, and 89-90% specificity for four-class sleep staging in the MESA cohort. It yielded an overall accuracy of 77%, weighted F1 score of 0.77, 74% sensitivity, and 88% specificity for three-class sleep staging and an overall accuracy of 68-69%, weighted F1 score of 0.68-0.69, 60-63% sensitivity, and 88-89% specificity for four-class sleep staging in the MrOS cohort. These results were achieved with feature-poor inputs with a low temporal resolution. In addition, we extended our three-class staging model to an unrelated Apple Watch dataset. Importantly, SLAMSS predicts the duration of each sleep stage with high accuracy. This is especially significant for four-class sleep staging, where deep sleep is severely underrepresented. We show that, by appropriately choosing the loss function to address the inherent class imbalance, our method can accurately estimate deep sleep time (SLAMSS/MESA: 0.61±0.69 hours, PSG/MESA ground truth: 0.60±0.60 hours; SLAMSS/MrOS: 0.53±0.66 hours, PSG/MrOS ground truth: 0.55±0.57 hours;). Deep sleep quality and quantity are vital metrics and early indicators for a number of diseases. Our method, which enables accurate deep sleep estimation from wearables-derived data, is therefore promising for a variety of clinical applications requiring long-term deep sleep monitoring.
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Affiliation(s)
- Tzu-An Song
- University of Massachusetts Amherst, Amherst, MA, United States of America
| | | | - Masoud Malekzadeh
- University of Massachusetts Amherst, Amherst, MA, United States of America
| | - Stephanie Harrison
- California Pacific Medical Center Research Institute, San Francisco, CA, United States of America
| | - Terri Blackwell Hoge
- California Pacific Medical Center Research Institute, San Francisco, CA, United States of America
| | - Susan Redline
- Brigham and Women’s Hospital, Boston, MA, United States of America
| | - Katie L. Stone
- California Pacific Medical Center Research Institute, San Francisco, CA, United States of America
| | - Richa Saxena
- Massachusetts General Hospital, Boston, MA, United States of America
| | - Shaun M. Purcell
- Brigham and Women’s Hospital, Boston, MA, United States of America
| | - Joyita Dutta
- University of Massachusetts Amherst, Amherst, MA, United States of America
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Zhou L, Kong J, Li X, Ren Q. Sex differences in the effects of sleep disorders on cognitive dysfunction. Neurosci Biobehav Rev 2023; 146:105067. [PMID: 36716906 DOI: 10.1016/j.neubiorev.2023.105067] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 01/24/2023] [Accepted: 01/26/2023] [Indexed: 01/29/2023]
Abstract
Sleep is an essential physiological function that sustains human life. Sleep disorders involve problems with the quality, duration, and abnormal behaviour of sleep. Insomnia is the most common sleep disorder, followed by sleep-disordered breathing (SDB). Sleep disorders often occur along with medical conditions or other mental health conditions. Of particular interest to researchers is the role of sleep disorders in cognitive dysfunction. Sleep disorder is a risk factor for cognitive dysfunction, yet the exact pathogenesis is still far from agreement. Little is known about how sex differences influence the changes in cognitive functions caused by sleep disorders. This narrative review examines how sleep disorders might affect cognitive impairment, and then explores the sex-specific consequences of sleep disorders as a risk factor for dementia and the potential underlying mechanisms. Some insights on the direction of further research are also presented.
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Affiliation(s)
- Lv Zhou
- School of Medicine, Southeast University, Nanjing 210009, China
| | - Jingting Kong
- School of Medicine, Southeast University, Nanjing 210009, China
| | - Xiaoli Li
- School of Medicine, Southeast University, Nanjing 210009, China; Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing 210009, China
| | - Qingguo Ren
- School of Medicine, Southeast University, Nanjing 210009, China; Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing 210009, China.
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Associations between objectively measured sleep parameters and cognition in healthy older adults: A meta-analysis. Sleep Med Rev 2023; 67:101734. [PMID: 36577339 DOI: 10.1016/j.smrv.2022.101734] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 11/03/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022]
Abstract
Multiple studies have examined associations between sleep and cognition in older adults, but a majority of these depend on self-reports on sleep and utilize cognitive tests that assess overall cognitive function. The current meta-analysis involved 72 independent studies and sought to quantify associations between objectively measured sleep parameters and cognitive performance in healthy older adults. Both sleep macrostructure (e.g., sleep duration, continuity, and stages) and microstructure (e.g., slow wave activity and spindle activity) were evaluated. For macrostructure, lower restlessness at night was associated with better memory performance (r = 0.43, p = 0.02), while lower sleep onset latency was associated with better executive functioning (r = 0.28, p = 0.03). Greater relative amount of N2 and REM sleep, but not N3, positively correlated with cognitive performance. The association between microstructure and cognition in older adults was marginally significant. This relationship was moderated by age (z = 0.07, p < 0.01), education (z = 0.26, p = 0.03), and percentage of female participants (z = 0.01, p < 0.01). The current meta-analysis emphasizes the importance of considering objective sleep measures to understand the relationship between sleep and cognition in healthy older adults. These results also form a base from which researchers using wearable sleep technology and measuring behavior through computerized testing tools can evaluate their findings.
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Perini F, Wong KF, Lin J, Hassirim Z, Ong JL, Lo J, Ong JC, Doshi K, Lim J. Mindfulness-based therapy for insomnia for older adults with sleep difficulties: a randomized clinical trial. Psychol Med 2023; 53:1038-1048. [PMID: 34193328 PMCID: PMC9975962 DOI: 10.1017/s0033291721002476] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Revised: 04/16/2021] [Accepted: 06/02/2021] [Indexed: 12/20/2022]
Abstract
OBJECTIVE Poor sleep is a modifiable risk factor for multiple disorders. Frontline treatments (e.g. cognitive-behavioral therapy for insomnia) have limitations, prompting a search for alternative approaches. Here, we compare manualized Mindfulness-Based Therapy for Insomnia (MBTI) with a Sleep Hygiene, Education, and Exercise Program (SHEEP) in improving subjective and objective sleep outcomes in older adults. METHODS We conducted a single-site, parallel-arm trial, with blinded assessments collected at baseline, post-intervention and 6-months follow-up. We randomized 127 participants aged 50-80, with a Pittsburgh Sleep Quality Index (PSQI) score ⩾5, to either MBTI (n = 65) or SHEEP (n = 62), both 2 hr weekly group sessions lasting 8 weeks. Primary outcomes included PSQI and Insomnia Severity Index, and actigraphy- and polysomnography-measured sleep onset latency (SOL) and wake after sleep onset (WASO). RESULTS Intention-to-treat analysis showed reductions in insomnia severity in both groups [MBTI: Cohen's effect size d = -1.27, 95% confidence interval (CI) -1.61 to -0.89; SHEEP: d = -0.69, 95% CI -0.96 to -0.43], with significantly greater improvement in MBTI. Sleep quality improved equivalently in both groups (MBTI: d = -1.19; SHEEP: d = -1.02). No significant interaction effects were observed in objective sleep measures. However, only MBTI had reduced WASOactigraphy (MBTI: d = -0.30; SHEEP: d = 0.02), SOLactigraphy (MBTI: d = -0.25; SHEEP: d = -0.09), and WASOPSG (MBTI: d = -0.26; SHEEP (d = -0.18). There was no change in SOLPSG. No participants withdrew because of adverse effects. CONCLUSIONS MBTI is effective at improving subjective and objective sleep quality in older adults, and could be a valid alternative for persons who have failed or do not have access to standard frontline therapies.
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Affiliation(s)
- Francesca Perini
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Kian Foong Wong
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jia Lin
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Zuriel Hassirim
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ju Lynn Ong
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - June Lo
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jason C. Ong
- Feinberg School of Medicine, Northwestern University, Evanston, IL 60208, USA
| | - Kinjal Doshi
- Department of Psychology, Singapore General Hospital, Singapore
| | - Julian Lim
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Psychology, National University of Singapore, Singapore
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Hajipour M, Baumann B, Azarbarzin A, Allen AH, Liu Y, Fels S, Goodfellow S, Singh A, Jen R, Ayas NT. Association of alternative polysomnographic features with patient outcomes in obstructive sleep apnea: a systematic review. J Clin Sleep Med 2023; 19:225-242. [PMID: 36106591 PMCID: PMC9892740 DOI: 10.5664/jcsm.10298] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 09/09/2022] [Accepted: 09/12/2022] [Indexed: 02/04/2023]
Abstract
STUDY OBJECTIVES Polysomnograms (PSGs) collect a plethora of physiologic signals across the night. However, few of these PSG data are incorporated into standard reports, and hence, ultimately, under-utilized in clinical decision making. Recently, there has been substantial interest regarding novel alternative PSG metrics that may help to predict obstructive sleep apnea (OSA)-related outcomes better than standard PSG metrics such as the apnea-hypopnea index. We systematically review the recent literature for studies that examined the use of alternative PSG metrics in the context of OSA and their association with health outcomes. METHODS We systematically searched EMBASE, MEDLINE, and the Cochrane Database of Systematic Reviews for studies published between 2000 and 2022 for those that reported alternative metrics derived from PSG in adults and related them to OSA-related outcomes. RESULTS Of the 186 initial studies identified by the original search, data from 31 studies were ultimately included in the final analysis. Numerous metrics were identified that were significantly related to a broad range of outcomes. We categorized the outcomes into 2 main subgroups: (1) cardiovascular/metabolic outcomes and mortality and (2) cognitive function- and vigilance-related outcomes. Four general categories of alternative metrics were identified based on signals analyzed: autonomic/hemodynamic metrics, electroencephalographic metrics, oximetric metrics, and respiratory event-related metrics. CONCLUSIONS We have summarized the current landscape of literature for alternative PSG metrics relating to risk prediction in OSA. Although promising, further prospective observational studies are needed to verify findings from other cohorts, and to assess the clinical utility of these metrics. CITATION Hajipour M, Baumann B, Azarbarzin A, et al. Association of alternative polysomnographic features with patient outcomes in obstructive sleep apnea: a systematic review. J Clin Sleep Med. 2023;19(2):225-242.
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Affiliation(s)
- Mohammadreza Hajipour
- Department of Experimental Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Brett Baumann
- Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Ali Azarbarzin
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital and Harvard Medical School, Harvard University, Boston, Massachusetts
| | - A.J. Hirsch Allen
- Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Yu Liu
- Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
- Department of Pharmacology, Shanxi Medical University, Taiyuan, China
| | - Sidney Fels
- Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Sebastian Goodfellow
- Department of Critical Care Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Amrit Singh
- Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Rachel Jen
- Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Najib T. Ayas
- Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
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Kroeger D, Vetrivelan R. To sleep or not to sleep - Effects on memory in normal aging and disease. AGING BRAIN 2023; 3:100068. [PMID: 36911260 PMCID: PMC9997183 DOI: 10.1016/j.nbas.2023.100068] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 11/03/2022] [Accepted: 01/20/2023] [Indexed: 01/31/2023] Open
Abstract
Sleep behavior undergoes significant changes across the lifespan, and aging is associated with marked alterations in sleep amounts and quality. The primary sleep changes in healthy older adults include a shift in sleep timing, reduced slow-wave sleep, and impaired sleep maintenance. However, neurodegenerative and psychiatric disorders are more common among the elderly, which further worsen their sleep health. Irrespective of the cause, insufficient sleep adversely affects various bodily functions including energy metabolism, mood, and cognition. In this review, we will focus on the cognitive changes associated with inadequate sleep during normal aging and the underlying neural mechanisms.
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Affiliation(s)
- Daniel Kroeger
- Anatomy, Physiology, and Pharmacology, College of Veterinary Medicine, Auburn University, Auburn, AL 36849, United States
| | - Ramalingam Vetrivelan
- Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, United States
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Lafrenière A, Lina JM, Hernandez J, Bouchard M, Gosselin N, Carrier J. Sleep slow waves' negative-to-positive-phase transition: a marker of cognitive and apneic status in aging. Sleep 2023; 46:zsac246. [PMID: 36219687 PMCID: PMC9832517 DOI: 10.1093/sleep/zsac246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 08/12/2022] [Indexed: 11/07/2022] Open
Abstract
The sleep slow-wave (SW) transition between negative and positive phases is thought to mirror synaptic strength and likely depends on brain health. This transition shows significant age-related changes but has not been investigated in pathological aging. The present study aimed at comparing the transition speed and other characteristics of SW between older adults with amnestic mild cognitive impairment (aMCI) and cognitively normal (CN) controls with and without obstructive sleep apnea (OSA). We also examined the association of SW characteristics with the longitudinal changes of episodic memory and executive functions and the degree of subjective cognitive complaints. aMCI (no/mild OSA = 17; OSA = 15) and CN (no/mild OSA = 20; OSA = 17) participants underwent a night of polysomnography and a neuropsychological evaluation at baseline and 18 months later. Participants with aMCI had a significantly slower SW negative-to-positive-phase transition speed and a higher proportion of SW that are "slow-switchers" than CN participants. These SW measures in the frontal region were significantly correlated with memory decline and cognitive complaints in aMCI and cognitive improvements in CN participants. The transition speed of the SW that are "fast-switchers" was significantly slower in OSA compared to no or mild obstructive sleep apnea participants. The SW transition-related metrics showed opposite correlations with the longitudinal episodic memory changes depending on the participants' cognitive status. These relationships were particularly strong in participants with aMCI. As the changes of the SW transition-related metrics in pathological aging might reflect synaptic alterations, future studies should investigate whether these new metrics covary with biomarker levels of synaptic integrity in this population.
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Affiliation(s)
- Alexandre Lafrenière
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Canada
- Department of Psychology, Université de Montréal, Montreal, Canada
| | - Jean-Marc Lina
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Canada
- Department of Electrical Engineering, École de Technologie Supérieure, Montreal, Canada
- Centre de Recherches Mathématiques, Université de Montréal, Montreal, Canada
| | - Jimmy Hernandez
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Canada
- Department of Neurosciences, Université de Montréal, Montreal, Canada
| | - Maude Bouchard
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Canada
| | - Nadia Gosselin
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Canada
- Department of Psychology, Université de Montréal, Montreal, Canada
| | - Julie Carrier
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Canada
- Department of Psychology, Université de Montréal, Montreal, Canada
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Kavaliotis E, Boardman JM, Clark JW, Ogeil RP, Verdejo-García A, Drummond SPA. The relationship between sleep and appetitive conditioning: A systematic review and meta-analysis. Neurosci Biobehav Rev 2023; 144:105001. [PMID: 36529310 DOI: 10.1016/j.neubiorev.2022.105001] [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: 08/23/2022] [Revised: 11/24/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022]
Abstract
This systematic review and meta-analysis (PROSPERO registration animal/human studies: CRD42021234793/CRD42021234790) examined the relationship between sleep and appetitive conditioning. Inclusion criteria included: a) appetitive conditioning paradigm; b) measure of conditioning; c) sleep measurement and/or sleep loss; d) human and/etor non-human animal samples; and e) written in English. Searches of seven databases returned 3777 publications. The final sample consisted of 42 studies using primarily animal samples and involving food- and drug-related conditioning tasks. We found sleep loss disrupted appetitive conditioning of food rewards (p < 0.001) but potentiated appetitive conditioning of drug rewards (p < 0.001). Furthermore, sleep loss negatively impacted extinction learning irrespective of the reward type. Post-learning sleep was associated with increases in REM sleep (p = 0.02). Findings suggest sleep loss potentiates the impact of psychoactive substances in a manner likely to produce an increased risk of problematic substance use. In obese/overweight populations, sleep loss may be associated with deficits in the conditioning and extinction of reward-related behaviours. Further research should assess the relationship between sleep and appetitive conditioning in humans.
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Affiliation(s)
- Eleni Kavaliotis
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Victoria 3800, Australia
| | - Johanna M Boardman
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Victoria 3800, Australia
| | - Jacob W Clark
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Victoria 3800, Australia
| | - Rowan P Ogeil
- Eastern Health Clinical School and Monash Addiction Research Centre, Faculty of Medicine, Nursing and Health Sciences, Monash University, Victoria 3800, Australia; Turning Point, Eastern Health, Victoria 3121, Australia
| | - Antonio Verdejo-García
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Victoria 3800, Australia
| | - Sean P A Drummond
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Victoria 3800, Australia.
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A Novel In-Home Sleep Monitoring System Based on Fully Integrated Multichannel Front-End Chip and Its Multilevel Analyses. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2023; 11:211-222. [PMID: 36950263 PMCID: PMC10027079 DOI: 10.1109/jtehm.2023.3248621] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 01/17/2023] [Accepted: 02/15/2023] [Indexed: 03/06/2023]
Abstract
OBJECTIVE A novel in-home sleep monitoring system with an 8-channel biopotential acquisition front-end chip is presented and validated via multilevel data analyses and comparision with advanced polysomnography. METHODS AND PROCEDURES The chip includes a cascaded low-noise programmable gain amplifier (PGA) and 24-bit [Formula: see text]-[Formula: see text] analog-to-digital converter (ADC). The PGA is based on three op-amp structure while the ADC adopts cascade of integrator feedforward and feedback (CIFF-B) architecture. An innovative chopper-modulated input-scaling-down technique enhances the dynamic range. The proposed system and commercial polysomnography were used for in-home sleep monitoring of 20 healthy participants. The consistency and significance of the two groups' data were analyzed. RESULTS Fabricated in 180 nm BCD technology, the input-referred noise, input impedance, common-mode rejection ratio, and dynamic range of the acquisition front-end chip were [Formula: see text]Vpp, 1.25 GN), 113.9 dB, and 119.8 dB. The kappa coefficients between the sleep stage labels of the three scorers were 0.80, 0.76, and 0.79. The consistency of the slowing index, multiscale entropy, and percentile features between the two devices reached 0.958, 0.885, and 0.834. The macro sleep architecture characteristics of the two devices were not significantly different (all p [Formula: see text] 0.05). CONCLUSION The proposed chip was applied to develop an in-home sleep monitoring system with significantly reduced size, power, and cost. Multilevel analyses demonstrated that this system collects stable and accurate in-home sleep data. CLINICAL IMPACT The proposed system can be applied for long-term in-home sleep monitoring outside of laboratory environments and sleep disorders screening that with low cost.
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Wu T, Li M, Tian L, Cong P, Huang X, Wu H, Zhang Q, Zhang H, Xiong L. A modified mouse model of perioperative neurocognitive disorders exacerbated by sleep fragmentation. Exp Anim 2023; 72:55-67. [PMID: 36130912 PMCID: PMC9978123 DOI: 10.1538/expanim.22-0053] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
Aging is one of the greatest risk factors for postoperative cognitive dysfunction (POCD), also known as perioperative neurocognitive disorder (PND). Animal models of PND are usually induced in mice over 18 months of age, which imposes expensive economic and time costs for PND-related studies. Sleep disorders, including sleep fragmentation, are reported to aggravate memory impairment in neurocognitive-related diseases such as Alzheimer's disease (AD). Therefore, the aim of the present study was to explore whether a PND model could be constructed in younger mice with the help of fragmented sleep. We found that fragmented sleep followed by laparotomy under isoflurane anesthesia could stably induce PND in 15-month-old mice. To determine whether the neurocognitive decline in this model could be salvaged by clinical treatments, we administered repetitive transcranial magnetic stimulation (rTMS) to the model mice before anesthesia and surgery. We found that 10 days of high-frequency rTMS (HF-rTMS) could improve spatial learning and memory deficits in this modified PND model. We are the first to successfully construct a PND model in younger mice,which is more economical, that can be used as an alternative model for future PND studies.
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Affiliation(s)
- Tingmei Wu
- Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Department of
Anesthesiology and Perioperative Medicine, Shanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine, 1279 Sanmen Road, Hongkou District, Shanghai 200434, P.R.
China
| | - Min Li
- Department of Rehabilitation Medicine, Shanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine, 1279 Sanmen Road, Hongkou District,
Shanghai 200434, P.R. China
| | - Li Tian
- Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Department of
Anesthesiology and Perioperative Medicine, Shanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine, 1279 Sanmen Road, Hongkou District, Shanghai 200434, P.R.
China
| | - Peilin Cong
- Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Department of
Anesthesiology and Perioperative Medicine, Shanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine, 1279 Sanmen Road, Hongkou District, Shanghai 200434, P.R.
China
| | - Xinwei Huang
- Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Department of
Anesthesiology and Perioperative Medicine, Shanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine, 1279 Sanmen Road, Hongkou District, Shanghai 200434, P.R.
China
| | - Huanghui Wu
- Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Department of
Anesthesiology and Perioperative Medicine, Shanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine, 1279 Sanmen Road, Hongkou District, Shanghai 200434, P.R.
China
| | - Qian Zhang
- Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Department of
Anesthesiology and Perioperative Medicine, Shanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine, 1279 Sanmen Road, Hongkou District, Shanghai 200434, P.R.
China
| | - Hong Zhang
- Department of Rehabilitation Medicine, Shanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine, 1279 Sanmen Road, Hongkou District,
Shanghai 200434, P.R. China
| | - Lize Xiong
- Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Department of
Anesthesiology and Perioperative Medicine, Shanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine, 1279 Sanmen Road, Hongkou District, Shanghai 200434, P.R.
China
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Gao C, Scullin MK. Longitudinal trajectories of spectral power during sleep in middle-aged and older adults. AGING BRAIN 2023; 3:100058. [PMID: 36911257 PMCID: PMC9997163 DOI: 10.1016/j.nbas.2022.100058] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 11/09/2022] [Accepted: 11/30/2022] [Indexed: 12/23/2022] Open
Abstract
Age-related changes in sleep appear to contribute to cognitive aging and dementia. However, most of the current understanding of sleep across the lifespan is based on cross-sectional evidence. Using data from the Sleep Heart Health Study, we investigated longitudinal changes in sleep micro-architecture, focusing on whether such age-related changes are experienced uniformly across individuals. Participants were 2,202 adults (ageBaseline = 62.40 ± 10.38, 55.36 % female, 87.92 % White) who completed home polysomnography assessment at two study visits, which were 5.23 years apart (range: 4-7 years). We analyzed NREM and REM spectral power density for each 0.5 Hz frequency bin, including slow oscillation (0.5-1 Hz), delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), sigma (12-15 Hz), and beta-1 (15-20 Hz) bands. Longitudinal comparisons showed a 5-year decline in NREM delta (p <.001) and NREM sigma power density (p <.001) as well as a 5-year increase in theta power density during NREM (p =.001) and power density for all frequency bands during REM sleep (ps < 0.05). In contrast to the notion that sleep declines linearly with advancing age, longitudinal trajectories varied considerably across individuals. Within individuals, the 5-year changes in NREM and REM power density were strongly correlated (slow oscillation: r = 0.46; delta: r = 0.67; theta r = 0.78; alpha r = 0.66; sigma: r = 0.71; beta-1: r = 0.73; ps < 0.001). The convergence in the longitudinal trajectories of NREM and REM activity may reflect age-related neural de-differentiation and/or compensation processes. Future research should investigate the neurocognitive implications of longitudinal changes in sleep micro-architecture and test whether interventions for improving key sleep micro-architecture features (such as NREM delta and sigma activity) also benefit cognition over time.
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Affiliation(s)
- Chenlu Gao
- Department of Psychology and Neuroscience, Baylor University, Waco, TX, USA.,Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Michael K Scullin
- Department of Psychology and Neuroscience, Baylor University, Waco, TX, USA
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Mellow ML, Dumuid D, Wade AT, Stanford T, Olds TS, Karayanidis F, Hunter M, Keage HAD, Dorrian J, Goldsworthy MR, Smith AE. Twenty-four-hour time-use composition and cognitive function in older adults: Cross-sectional findings of the ACTIVate study. Front Hum Neurosci 2022; 16:1051793. [PMID: 36504624 PMCID: PMC9729737 DOI: 10.3389/fnhum.2022.1051793] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 10/31/2022] [Indexed: 11/25/2022] Open
Abstract
Introduction Physical activity, sedentary behaviour and sleep are associated with cognitive function in older adults. However, these behaviours are not independent, but instead make up exclusive and exhaustive components of the 24-h day. Few studies have investigated associations between 24-h time-use composition and cognitive function in older adults. Of these, none have considered how the quality of sleep, or the context of physical activity and sedentary behaviour may impact these relationships. This study aims to understand how 24-h time-use composition is associated with cognitive function across a range of domains in healthy older adults, and whether the level of recreational physical activity, amount of television (TV) watching, or the quality of sleep impact these potential associations. Methods 384 healthy older adults (age 65.5 ± 3.0 years, 68% female, 63% non-smokers, mean education = 16.5 ± 3.2 years) participated in this study across two Australian sites (Adelaide, n = 207; Newcastle, n = 177). Twenty-four-hour time-use composition was captured using triaxial accelerometry, measured continuously across 7 days. Total time spent watching TV per day was used to capture the context of sedentary behaviours, whilst total time spent in recreational physical activity was used to capture the context of physical activity (i.e., recreational accumulation of physical activity vs. other contexts). Sleep quality was measured using a single item extracted from the Pittsburgh Sleep Quality Index. Cognitive function was measured using a global cognition index (Addenbrooke's Cognitive Examination III) and four cognitive domain composite scores (derived from five tests of the Cambridge Neuropsychological Test Automated Battery: Paired Associates Learning; One Touch Stockings of Cambridge; Multitasking; Reaction Time; Verbal Recognition Memory). Pairwise correlations were used to describe independent relationships between time use variables and cognitive outcomes. Then, compositional data analysis regression methods were used to quantify associations between cognition and 24-h time-use composition. Results After adjusting for covariates and false discovery rate there were no significant associations between time-use composition and global cognition, long-term memory, short-term memory, executive function, or processing speed outcomes, and no significant interactions between TV watching time, recreational physical activity engagement or sleep quality and time-use composition for any cognitive outcomes. Discussion The findings highlight the importance of considering all activities across the 24-h day against cognitive function in older adults. Future studies should consider investigating these relationships longitudinally to uncover temporal effects.
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Affiliation(s)
- Maddison L. Mellow
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia
| | - Dorothea Dumuid
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia
| | - Alexandra T. Wade
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia
| | - Ty Stanford
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia
| | - Timothy S. Olds
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia
| | - Frini Karayanidis
- Functional Neuroimaging Laboratory, School of Psychological Sciences, The University of Newcastle, Newcastle, NSW, Australia
- Healthy Minds Research Program, Hunter Medical Research Institute (HMRI), Newcastle, NSW, Australia
| | - Montana Hunter
- Functional Neuroimaging Laboratory, School of Psychological Sciences, The University of Newcastle, Newcastle, NSW, Australia
- Healthy Minds Research Program, Hunter Medical Research Institute (HMRI), Newcastle, NSW, Australia
| | - Hannah A. D. Keage
- Behaviour-Brain-Body Research Centre, Justice and Society, University of South Australia, Adelaide, SA, Australia
| | - Jillian Dorrian
- Behaviour-Brain-Body Research Centre, Justice and Society, University of South Australia, Adelaide, SA, Australia
| | - Mitchell R. Goldsworthy
- Lifespan Human Neurophysiology Group, School of Biomedicine, University of Adelaide, Adelaide, SA, Australia
- Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, SA, Australia
| | - Ashleigh E. Smith
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia
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Chylinski D, Narbutas J, Balteau E, Collette F, Bastin C, Berthomier C, Salmon E, Maquet P, Carrier J, Phillips C, Lina JM, Vandewalle G, Van Egroo M. Frontal grey matter microstructure is associated with sleep slow waves characteristics in late midlife. Sleep 2022; 45:zsac178. [PMID: 35869626 PMCID: PMC9644125 DOI: 10.1093/sleep/zsac178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 07/13/2022] [Indexed: 07/25/2023] Open
Abstract
STUDY OBJECTIVES The ability to generate slow waves (SW) during non-rapid eye movement (NREM) sleep decreases as early as the 5th decade of life, predominantly over frontal regions. This decrease may concern prominently SW characterized by a fast switch from hyperpolarized to depolarized, or down-to-up, state. Yet, the relationship between these fast and slow switcher SW and cerebral microstructure in ageing is not established. METHODS We recorded habitual sleep under EEG in 99 healthy late midlife individuals (mean age = 59.3 ± 5.3 years; 68 women) and extracted SW parameters (density, amplitude, frequency) for all SW as well as according to their switcher type (slow vs. fast). We further used neurite orientation dispersion and density imaging (NODDI) to assess microstructural integrity over a frontal grey matter region of interest (ROI). RESULTS In statistical models adjusted for age, sex, and sleep duration, we found that a lower SW density, particularly for fast switcher SW, was associated with a reduced orientation dispersion of neurites in the frontal ROI (p = 0.018, R2β* = 0.06). In addition, overall SW frequency was positively associated with neurite density (p = 0.03, R2β* = 0.05). By contrast, we found no significant relationships between SW amplitude and NODDI metrics. CONCLUSIONS Our findings suggest that the complexity of neurite organization contributes specifically to the rate of fast switcher SW occurrence in healthy middle-aged individuals, corroborating slow and fast switcher SW as distinct types of SW. They further suggest that the density of frontal neurites plays a key role for neural synchronization during sleep. TRIAL REGISTRATION NUMBER EudraCT 2016-001436-35.
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Affiliation(s)
- Daphne Chylinski
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
| | - Justinas Narbutas
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | - Evelyne Balteau
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
| | - Fabienne Collette
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | - Christine Bastin
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | | | - Eric Salmon
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
- Department of Neurology, University Hospital of Liège, Liège, Belgium
| | - Pierre Maquet
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- Department of Neurology, University Hospital of Liège, Liège, Belgium
| | - Julie Carrier
- CARSM, CIUSSS of Nord-de l’Île-de-Montréal, Montreal, Canada
- Department of Psychology, University of Montreal, Canada
| | - Christophe Phillips
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- GIGA-In Silico Medicine, University of Liège, Liège, Belgium
| | - Jean-Marc Lina
- CARSM, CIUSSS of Nord-de l’Île-de-Montréal, Montreal, Canada
- Department of Psychology, University of Montreal, Canada
| | - Gilles Vandewalle
- Corresponding authors. Gilles Vandewalle, GIGA-Cyclotron Research Centre-In Vivo Imaging, Bâtiment B30, Université de Liège, Allée du Six Août, 8, 4000 Liège, Belgium.
| | - Maxime Van Egroo
- Maxime Van Egroo, Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Universiteitssingel 40, 6229 ER Maastricht, Maastricht, The Netherlands.
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Sleep preferentially consolidates negative aspects of human memory: Well-powered evidence from two large online experiments. Proc Natl Acad Sci U S A 2022; 119:e2202657119. [PMID: 36279434 PMCID: PMC9636942 DOI: 10.1073/pnas.2202657119] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Recent research has called into question whether sleep improves memory, especially for emotional information. However, many of these studies used a relatively small number of participants and focused only on college student samples, limiting both the power of these findings and their generalizability to the wider population. Here, using the well-established emotional memory trade-off task, we investigated sleep’s impact on memory for emotional components of scenes in a large online sample of adults ranging in age from 18 to 59 y. Despite the limitations inherent in using online samples, this well-powered study provides strong evidence that sleep selectively consolidates negative emotional aspects of memory and that this effect generalizes to participants across young adulthood and middle age. Research suggests that sleep benefits memory. Moreover, it is often claimed that sleep selectively benefits memory for emotionally salient information over neutral information. However, not all scientists are convinced by this relationship [e.g., J. M. Siegel. Curr. Sleep Med. Rep., 7, 15–18 (2021)]. One criticism of the overall sleep and memory literature—like other literature—is that many studies are underpowered and lacking in generalizability [M. J. Cordi, B. Rasch. Curr. Opin. Neurobiol., 67, 1–7 (2021)], thus leaving the evidence mixed and confusing to interpret. Because large replication studies are sorely needed, we recruited over 250 participants spanning various age ranges and backgrounds in an effort to confirm sleep’s preferential emotional memory consolidation benefit using a well-established task. We found that sleep selectively benefits memory for negative emotional objects at the expense of their paired neutral backgrounds, confirming our prior work and clearly demonstrating a role for sleep in emotional memory formation. In a second experiment also using a large sample, we examined whether this effect generalized to positive emotional memory. We found that while participants demonstrated better memory for positive objects compared to their neutral backgrounds, sleep did not modulate this effect. This research provides strong support for a sleep-specific benefit on memory consolidation for specifically negative information and more broadly affirms the benefit of sleep for cognition.
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Stokes PA, Rath P, Possidente T, He M, Purcell S, Manoach DS, Stickgold R, Prerau MJ. Transient oscillation dynamics during sleep provide a robust basis for electroencephalographic phenotyping and biomarker identification. Sleep 2022; 46:6701543. [PMID: 36107467 PMCID: PMC9832519 DOI: 10.1093/sleep/zsac223] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/30/2022] [Indexed: 01/19/2023] Open
Abstract
Transient oscillatory events in the sleep electroencephalogram represent short-term coordinated network activity. Of particular importance, sleep spindles are transient oscillatory events associated with memory consolidation, which are altered in aging and in several psychiatric and neurodegenerative disorders. Spindle identification, however, currently contains implicit assumptions derived from what waveforms were historically easiest to discern by eye, and has recently been shown to select only a high-amplitude subset of transient events. Moreover, spindle activity is typically averaged across a sleep stage, collapsing continuous dynamics into discrete states. What information can be gained by expanding our view of transient oscillatory events and their dynamics? In this paper, we develop a novel approach to electroencephalographic phenotyping, characterizing a generalized class of transient time-frequency events across a wide frequency range using continuous dynamics. We demonstrate that the complex temporal evolution of transient events during sleep is highly stereotyped when viewed as a function of slow oscillation power (an objective, continuous metric of depth-of-sleep) and phase (a correlate of cortical up/down states). This two-fold power-phase representation has large intersubject variability-even within healthy controls-yet strong night-to-night stability for individuals, suggesting a robust basis for phenotyping. As a clinical application, we then analyze patients with schizophrenia, confirming established spindle (12-15 Hz) deficits as well as identifying novel differences in transient non-rapid eye movement events in low-alpha (7-10 Hz) and theta (4-6 Hz) ranges. Overall, these results offer an expanded view of transient activity, describing a broad class of events with properties varying continuously across spatial, temporal, and phase-coupling dimensions.
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Affiliation(s)
- Patrick A Stokes
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Preetish Rath
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA,Department of Computer Science, Tufts University, Medford, MA, USA
| | - Thomas Possidente
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Mingjian He
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA,Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Shaun Purcell
- Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA, USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Michael J Prerau
- Corresponding author. Michael J. Prerau, Brigham and Women's Hospital, Division of Sleep and Circadian Disorders, 221 Longwood Avenue, Boston, MA, 02115, USA.
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Seol J, Lee J, Park I, Tokuyama K, Fukusumi S, Kokubo T, Yanagisawa M, Okura T. Bidirectional associations between physical activity and sleep in older adults: a multilevel analysis using polysomnography. Sci Rep 2022; 12:15399. [PMID: 36100642 PMCID: PMC9470065 DOI: 10.1038/s41598-022-19841-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 09/05/2022] [Indexed: 11/09/2022] Open
Abstract
AbstractAlthough recent studies have examined the bidirectional associations between physical activity and sleep parameters, few have focused on older adults utilizing objective assessments, such as polysomnography. This micro-longitudinal observational study included 92 Japanese older adults (aged 65–86 years) who underwent objective evaluations of sleep quality using polysomnography and completed subjective sleep-related questionnaires. Activity levels were assessed using an accelerometer. Polysomnography, subjective sleep-related questionnaires, and accelerometer were administered for 7 consecutive days. Multilevel models (participant-, day-level) were used to examine the temporal associations of objective and subjective sleep parameters with sedentary behavior and physical activity. In the day-level analysis, higher levels of sedentary behavior during daytime were associated with longer rapid eye movement (REM) sleep, shorter REM latency, lower levels of non-REM sleep (stage N3), and reduced delta power during daytime. Higher levels of low-intensity physical activity during daytime were associated with lower levels of REM sleep, longer REM latency, and increased stage N3 sleep in the day-level analysis. Higher levels of moderate-to-vigorous physical activity were associated with increased REM latency. Longer subjective sleep time was associated with increased next-day moderate-to-vigorous physical activity. Thus, low-intensity physical activity may provide objective benefits related to deep sleep parameters in older adults.
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Mander BA, Dave A, Lui KK, Sprecher KE, Berisha D, Chappel-Farley MG, Chen IY, Riedner BA, Heston M, Suridjan I, Kollmorgen G, Zetterberg H, Blennow K, Carlsson CM, Okonkwo OC, Asthana S, Johnson SC, Bendlin BB, Benca RM. Inflammation, tau pathology, and synaptic integrity associated with sleep spindles and memory prior to β-amyloid positivity. Sleep 2022; 45:6603598. [PMID: 35670275 PMCID: PMC9758508 DOI: 10.1093/sleep/zsac135] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Revised: 05/17/2022] [Indexed: 01/25/2023] Open
Abstract
STUDY OBJECTIVES Fast frequency sleep spindles are reduced in aging and Alzheimer's disease (AD), but the mechanisms and functional relevance of these deficits remain unclear. The study objective was to identify AD biomarkers associated with fast sleep spindle deficits in cognitively unimpaired older adults at risk for AD. METHODS Fifty-eight cognitively unimpaired, β-amyloid-negative, older adults (mean ± SD; 61.4 ± 6.3 years, 38 female) enriched with parental history of AD (77.6%) and apolipoprotein E (APOE) ε4 positivity (25.9%) completed the study. Cerebrospinal fluid (CSF) biomarkers of central nervous system inflammation, β-amyloid and tau proteins, and neurodegeneration were combined with polysomnography (PSG) using high-density electroencephalography and assessment of overnight memory retention. Parallelized serial mediation models were used to assess indirect effects of age on fast frequency (13 to <16Hz) sleep spindle measures through these AD biomarkers. RESULTS Glial activation was associated with prefrontal fast frequency sleep spindle expression deficits. While adjusting for sex, APOE ε4 genotype, apnea-hypopnea index, and time between CSF sampling and sleep study, serial mediation models detected indirect effects of age on fast sleep spindle expression through microglial activation markers and then tau phosphorylation and synaptic degeneration markers. Sleep spindle expression at these electrodes was also associated with overnight memory retention in multiple regression models adjusting for covariates. CONCLUSIONS These findings point toward microglia dysfunction as associated with tau phosphorylation, synaptic loss, sleep spindle deficits, and memory impairment even prior to β-amyloid positivity, thus offering a promising candidate therapeutic target to arrest cognitive decline associated with aging and AD.
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Affiliation(s)
- Bryce A Mander
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA.,Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, USA.,Department of Cognitive Sciences, University of California, Irvine, CA, USA
| | - Abhishek Dave
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA.,Department of Cognitive Sciences, University of California, Irvine, CA, USA
| | - Kitty K Lui
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA.,San Diego State University/University of California San Diego, Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Katherine E Sprecher
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA.,Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA.,Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Destiny Berisha
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Miranda G Chappel-Farley
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, USA.,Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Ivy Y Chen
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - Brady A Riedner
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Margo Heston
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA.,Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
| | | | | | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital , Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital , Mölndal, Sweden
| | - Cynthia M Carlsson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA.,Wisconsin Alzheimer's Institute, Madison, WI, USA.,Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Ozioma C Okonkwo
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA.,Wisconsin Alzheimer's Institute, Madison, WI, USA.,Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA.,Wisconsin Alzheimer's Institute, Madison, WI, USA.,Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA.,Wisconsin Alzheimer's Institute, Madison, WI, USA.,Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Barbara B Bendlin
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA.,Wisconsin Alzheimer's Institute, Madison, WI, USA.,Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Ruth M Benca
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA.,Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, USA.,Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA.,Department of Neurobiology and Behavior, University of California, Irvine, CA, USA.,Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA.,Department of Psychiatry and Behavioral Medicine, Wake Forest University, Winston-Salem, NC, USA
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45
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Donnelly NA, Bartsch U, Moulding HA, Eaton C, Marston H, Hall JH, Hall J, Owen MJ, van den Bree MBM, Jones MW. Sleep EEG in young people with 22q11.2 deletion syndrome: A cross-sectional study of slow-waves, spindles and correlations with memory and neurodevelopmental symptoms. eLife 2022; 11:75482. [PMID: 36039635 PMCID: PMC9477499 DOI: 10.7554/elife.75482] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 08/12/2022] [Indexed: 11/20/2022] Open
Abstract
Background Young people living with 22q11.2 Deletion Syndrome (22q11.2DS) are at increased risk of schizophrenia, intellectual disability, attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). In common with these conditions, 22q11.2DS is also associated with sleep problems. We investigated whether abnormal sleep or sleep-dependent network activity in 22q11.2DS reflects convergent, early signatures of neural circuit disruption also evident in associated neurodevelopmental conditions. Methods In a cross-sectional design, we recorded high-density sleep EEG in young people (6-20 years) with 22q11.2DS (n=28) and their unaffected siblings (n=17), quantifying associations between sleep architecture, EEG oscillations (spindles and slow waves) and psychiatric symptoms. We also measured performance on a memory task before and after sleep. Results 22q11.2DS was associated with significant alterations in sleep architecture, including a greater proportion of N3 sleep and lower proportions of N1 and REM sleep than in siblings. During sleep, deletion carriers showed broadband increases in EEG power with increased slow-wave and spindle amplitudes, increased spindle frequency and density, and stronger coupling between spindles and slow-waves. Spindle and slow-wave amplitudes correlated positively with overnight memory in controls, but negatively in 22q11.2DS. Mediation analyses indicated that genotype effects on anxiety, ADHD and ASD were partially mediated by sleep EEG measures. Conclusions This study provides a detailed description of sleep neurophysiology in 22q11.2DS, highlighting alterations in EEG signatures of sleep which have been previously linked to neurodevelopment, some of which were associated with psychiatric symptoms. Sleep EEG features may therefore reflect delayed or compromised neurodevelopmental processes in 22q11.2DS, which could inform our understanding of the neurobiology of this condition and be biomarkers for neuropsychiatric disorders. Funding This research was funded by a Lilly Innovation Fellowship Award (UB), the National Institute of Mental Health (NIMH 5UO1MH101724; MvdB), a Wellcome Trust Institutional Strategic Support Fund (ISSF) award (MvdB), the Waterloo Foundation (918-1234; MvdB), the Baily Thomas Charitable Fund (2315/1; MvdB), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment (IMAGINE) (MR/L011166/1; JH, MvdB and MO), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment 2 (IMAGINE-2) (MR/T033045/1; MvdB, JH and MO); Wellcome Trust Strategic Award 'Defining Endophenotypes From Integrated Neurosciences' Wellcome Trust (100202/Z/12/Z MO, JH). NAD was supported by a National Institute for Health Research Academic Clinical Fellowship in Mental Health and MWJ by a Wellcome Trust Senior Research Fellowship in Basic Biomedical Science (202810/Z/16/Z). CE and HAM were supported by Medical Research Council Doctoral Training Grants (C.B.E. 1644194, H.A.M MR/K501347/1). HMM and UB were employed by Eli Lilly & Co during the study; HMM is currently an employee of Boehringer Ingelheim Pharma GmbH & Co KG. The views and opinions expressed are those of the author(s), and not necessarily those of the NHS, the NIHR or the Department of Health funders.
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Affiliation(s)
- Nicholas A Donnelly
- Centre for Academic Mental Health, University of Bristol, Bristol, United Kingdom.,Avon and Wiltshire Partnership NHS Mental Health Trust, Avon, United Kingdom
| | - Ullrich Bartsch
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, United Kingdom.,Translational Neuroscience, Eli Lilly, Windlesham, United States
| | - Hayley A Moulding
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Christopher Eaton
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Hugh Marston
- Translational Neuroscience, Eli Lilly, Windlesham, United States
| | - Jessica H Hall
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Jeremy Hall
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Michael J Owen
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Marianne B M van den Bree
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
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46
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Sarkis RA, Lucey BP. Moving towards core sleep outcomes in neurodegenerative disease—the time is now. Sleep 2022; 45:6584629. [DOI: 10.1093/sleep/zsac112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Rani A Sarkis
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School , Boston, MA 02115 , USA
| | - Brendan P Lucey
- Department of Neurology, Washington University School of Medicine , St Louis, MO 63110 , USA
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47
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Blackman J, Morrison HD, Lloyd K, Gimson A, Banerjee LV, Green S, Cousins R, Rudd S, Harding S, Coulthard E. The past, present, and future of sleep measurement in mild cognitive impairment and early dementia—towards a core outcome set: a scoping review. Sleep 2022; 45:6563140. [PMID: 35373837 PMCID: PMC9272273 DOI: 10.1093/sleep/zsac077] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 03/28/2022] [Indexed: 11/12/2022] Open
Abstract
Abstract
Study Objectives
Sleep abnormalities emerge early in dementia and may accelerate cognitive decline. Their accurate characterization may facilitate earlier clinical identification of dementia and allow for assessment of sleep intervention efficacy. This scoping review determines how sleep is currently measured and reported in Mild Cognitive Impairment (MCI) and early dementia, as a basis for future core outcome alignment.
Methods
This review follows the PRISMA Guidelines for Scoping Reviews. CINAHL, Embase, Medline, Psychinfo, and British Nursing Index databases were searched from inception—March 12, 2021. Included studies had participants diagnosed with MCI and early dementia and reported on sleep as a key objective/ outcome measure.
Results
Nineteen thousand five hundred and ninety-six titles were returned following duplicate removal with 188 studies [N] included in final analysis. Sleep data was reported on 17 139 unique, diagnostically diverse participants (n). “Unspecified MCI” was the most common diagnosis amongst patients with MCI (n = 5003, 60.6%). Despite technological advances, sleep was measured most commonly by validated questionnaires (n = 12 586, N = 131). Fewer participants underwent polysomnography (PSG) (n = 3492, N = 88) and actigraphy (n = 3359, N = 38) with little adoption of non-PSG electroencephalograms (EEG) (n = 74, N = 3). Sleep outcome parameters were reported heterogeneously. 62/165 (37.6%) were described only once in the literature (33/60 (60%) in interventional studies). There was underrepresentation of circadian (n = 725, N = 25) and micro-architectural (n = 360, N = 12) sleep parameters.
Conclusions
Alongside under-researched areas, there is a need for more detailed diagnostic characterization. Due to outcome heterogeneity, we advocate for international consensus on core sleep outcome parameters to support causal inference and comparison of therapeutic sleep interventions.
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Affiliation(s)
- Jonathan Blackman
- Bristol Medical School, University of Bristol , Bristol , UK
- Bristol Brain Centre, North Bristol NHS Trust , Bristol , UK
| | - Hamish Duncan Morrison
- Bristol Medical School, University of Bristol , Bristol , UK
- Bristol Brain Centre, North Bristol NHS Trust , Bristol , UK
| | - Katherine Lloyd
- Bristol Medical School, University of Bristol , Bristol , UK
- Bristol Brain Centre, North Bristol NHS Trust , Bristol , UK
| | - Amy Gimson
- Bristol Brain Centre, North Bristol NHS Trust , Bristol , UK
| | | | - Sebastian Green
- Bristol Medical School, University of Bristol , Bristol , UK
- Bristol Brain Centre, North Bristol NHS Trust , Bristol , UK
| | - Rebecca Cousins
- Bristol Brain Centre, North Bristol NHS Trust , Bristol , UK
| | - Sarah Rudd
- Library and Knowledge Service, North Bristol NHS Trust , Bristol , UK
| | - Sam Harding
- Research and Innovation, North Bristol NHS Trust , Bristol , UK
| | - Elizabeth Coulthard
- Bristol Medical School, University of Bristol , Bristol , UK
- Bristol Brain Centre, North Bristol NHS Trust , Bristol , UK
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48
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McConnell BV, Kronberg E, Medenblik LM, Kheyfets VO, Ramos AR, Sillau SH, Pulver RL, Bettcher BM. The Rise and Fall of Slow Wave Tides: Vacillations in Coupled Slow Wave/Spindle Pairing Shift the Composition of Slow Wave Activity in Accordance With Depth of Sleep. Front Neurosci 2022; 16:915934. [PMID: 35812239 PMCID: PMC9260314 DOI: 10.3389/fnins.2022.915934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 06/03/2022] [Indexed: 11/21/2022] Open
Abstract
Slow wave activity (SWA) during sleep is associated with synaptic regulation and memory processing functions. Each cycle of non-rapid-eye-movement (NREM) sleep demonstrates a waxing and waning amount of SWA during the transitions between stages N2 and N3 sleep, and the deeper N3 sleep is associated with an increased density of SWA. Further, SWA is an amalgam of different types of slow waves, each identifiable by their temporal coupling to spindle subtypes with distinct physiological features. The objectives of this study were to better understand the neurobiological properties that distinguish different slow wave and spindle subtypes, and to examine the composition of SWA across cycles of NREM sleep. We further sought to explore changes in the composition of NREM cycles that occur among aging adults. To address these goals, we analyzed subsets of data from two well-characterized cohorts of healthy adults: (1) The DREAMS Subjects Database (n = 20), and (2) The Cleveland Family Study (n = 60). Our analyses indicate that slow wave/spindle coupled events can be characterized as frontal vs. central in their relative distribution between electroencephalography (EEG) channels. The frontal predominant slow waves are identifiable by their coupling to late-fast spindles and occur more frequently during stage N3 sleep. Conversely, the central-associated slow waves are identified by coupling to early-fast spindles and favor occurrence during stage N2 sleep. Together, both types of slow wave/spindle coupled events form the composite of SWA, and their relative contribution to the SWA rises and falls across cycles of NREM sleep in accordance with depth of sleep. Exploratory analyses indicated that older adults produce a different composition of SWA, with a shift toward the N3, frontal subtype, which becomes increasingly predominant during cycles of NREM sleep. Overall, these data demonstrate that subtypes of slow wave/spindle events have distinct cortical propagation patterns and differ in their distribution across lighter vs. deeper NREM sleep. Future efforts to understand how slow wave sleep and slow wave/spindle coupling impact memory performance and neurological disease may benefit from examining the composition of SWA to avoid potential confounds that may occur when comparing dissimilar neurophysiological events.
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Affiliation(s)
- Brice V. McConnell
- Department of Neurology, University of Colorado, Denver, Denver, CO, United States
- *Correspondence: Brice V. McConnell,
| | - Eugene Kronberg
- Department of Neurology, University of Colorado, Denver, Denver, CO, United States
| | - Lindsey M. Medenblik
- Department of Neurology, University of Colorado, Denver, Denver, CO, United States
| | - Vitaly O. Kheyfets
- Pediatric Critical Care Medicine, University of Colorado, Denver, Denver, CO, United States
| | - Alberto R. Ramos
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Stefan H. Sillau
- Department of Neurology, University of Colorado, Denver, Denver, CO, United States
| | - Rachelle L. Pulver
- Department of Neurology, University of Colorado, Denver, Denver, CO, United States
| | - Brianne M. Bettcher
- Department of Neurology, University of Colorado, Denver, Denver, CO, United States
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49
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Dzierzewski JM, Perez E, Ravyts SG, Dautovich N. Sleep and Cognition: A Narrative Review Focused on Older Adults. Sleep Med Clin 2022; 17:205-222. [PMID: 35659074 DOI: 10.1016/j.jsmc.2022.02.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Little is known regarding sleep's association with the traditional developmental course of late-life cognitive functioning. As the number of older adults increases worldwide, an enhanced understanding of age-related changes in sleep and cognition is necessary to slow decline and promote optimal aging. This review synthesizes the extant literature on sleep and cognitive function in healthy older adults, older adults with insomnia, and older adults with sleep apnea, incorporating information on the potential promising effects of treating poor sleep on cognitive outcomes in older adults. Unifying theories of the sleep-cognition association, possible mechanisms of action, and important unanswered questions are identified.
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Affiliation(s)
- Joseph M Dzierzewski
- Department of Psychology, Virginia Commonwealth University, 806 West Franklin Street, Room 306, Box 842018, Richmond, VA 23284-2018, USA.
| | - Elliottnell Perez
- Department of Psychology, Virginia Commonwealth University, Box 842018, Richmond, VA 23284-2018, USA
| | - Scott G Ravyts
- Department of Psychology, Virginia Commonwealth University, Box 842018, Richmond, VA 23284-2018, USA
| | - Natalie Dautovich
- Department of Psychology, Virginia Commonwealth University, 800 West Franklin Street, Room 203, Box 842018, Richmond, VA 23284-2018, USA
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50
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Kozhemiako N, Wang J, Jiang C, Wang LA, Gai G, Zou K, Wang Z, Yu X, Zhou L, Li S, Guo Z, Law R, Coleman J, Mylonas D, Shen L, Wang G, Tan S, Qin S, Huang H, Murphy M, Stickgold R, Manoach D, Zhou Z, Zhu W, Hal MH, Purcell SM, Pan JQ. Non-rapid eye movement sleep and wake neurophysiology in schizophrenia. eLife 2022; 11:76211. [PMID: 35578829 PMCID: PMC9113745 DOI: 10.7554/elife.76211] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 04/11/2022] [Indexed: 12/29/2022] Open
Abstract
Motivated by the potential of objective neurophysiological markers to index thalamocortical function in patients with severe psychiatric illnesses, we comprehensively characterized key non-rapid eye movement (NREM) sleep parameters across multiple domains, their interdependencies, and their relationship to waking event-related potentials and symptom severity. In 72 schizophrenia (SCZ) patients and 58 controls, we confirmed a marked reduction in sleep spindle density in SCZ and extended these findings to show that fast and slow spindle properties were largely uncorrelated. We also describe a novel measure of slow oscillation and spindle interaction that was attenuated in SCZ. The main sleep findings were replicated in a demographically distinct sample, and a joint model, based on multiple NREM components, statistically predicted disease status in the replication cohort. Although also altered in patients, auditory event-related potentials elicited during wake were unrelated to NREM metrics. Consistent with a growing literature implicating thalamocortical dysfunction in SCZ, our characterization identifies independent NREM and wake EEG biomarkers that may index distinct aspects of SCZ pathophysiology and point to multiple neural mechanisms underlying disease heterogeneity. This study lays the groundwork for evaluating these neurophysiological markers, individually or in combination, to guide efforts at treatment and prevention as well as identifying individuals most likely to benefit from specific interventions.
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Affiliation(s)
- Nataliia Kozhemiako
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, United States
| | - Jun Wang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Chenguang Jiang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Lei A Wang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Guanchen Gai
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Kai Zou
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Zhe Wang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Xiaoman Yu
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Lin Zhou
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Shen Li
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, United States
| | - Zhenglin Guo
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Robert Law
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, United States
| | - James Coleman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Lu Shen
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Guoqiang Wang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Shuping Tan
- Huilong Guan Hospital, Beijing University, Beijing, China
| | - Shengying Qin
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Michael Murphy
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, United States
| | - Robert Stickgold
- Beth Israel Deaconess Medical Center, Boston, United States.,Department of Psychiatry, Harvard Medical School, Boston, United States
| | - Dara Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Zhenhe Zhou
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Wei Zhu
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Mei-Hua Hal
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, United States
| | - Shaun M Purcell
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, United States.,Department of Psychiatry, Harvard Medical School, Boston, United States
| | - Jen Q Pan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
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