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Deng Q, Li Y, Sun Z, Gao X, Zhou J, Ma G, Qu WM, Li R. Sleep disturbance in rodent models and its sex-specific implications. Neurosci Biobehav Rev 2024; 164:105810. [PMID: 39009293 DOI: 10.1016/j.neubiorev.2024.105810] [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: 12/11/2023] [Revised: 07/08/2024] [Accepted: 07/10/2024] [Indexed: 07/17/2024]
Abstract
Sleep disturbances, encompassing altered sleep physiology or disorders like insomnia and sleep apnea, profoundly impact physiological functions and elevate disease risk. Despite extensive research, the underlying mechanisms and sex-specific differences in sleep disorders remain elusive. While polysomnography serves as a cornerstone for human sleep studies, animal models provide invaluable insights into sleep mechanisms. However, the availability of animal models of sleep disorders is limited, with each model often representing a specific sleep issue or mechanism. Therefore, selecting appropriate animal models for sleep research is critical. Given the significant sex differences in sleep patterns and disorders, incorporating both male and female subjects in studies is essential for uncovering sex-specific mechanisms with clinical relevance. This review provides a comprehensive overview of various rodent models of sleep disturbance, including sleep deprivation, sleep fragmentation, and circadian rhythm dysfunction. We evaluate the advantages and disadvantages of each model and discuss sex differences in sleep and sleep disorders, along with potential mechanisms. We aim to advance our understanding of sleep disorders and facilitate sex-specific interventions.
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Affiliation(s)
- Qi Deng
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Yuhong Li
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Zuoli Sun
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Xiang Gao
- Shanxi Bethune Hospital, Shanxi, China
| | | | - Guangwei Ma
- Peking University Sixth Hospital, Beijing, China
| | - Wei-Min Qu
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China; Department of Pharmacology, School of Basic Medical Sciences, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Rena Li
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
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Hammadi HA, Hameed WA, Fakhri MA, Khazaal HM, Abood FK, Hameed EK, Al-Ameri LT. Does Parkinson's disease affect sleep quality? Ir J Med Sci 2024; 193:2035-2039. [PMID: 38625658 DOI: 10.1007/s11845-024-03689-3] [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: 01/29/2024] [Accepted: 04/11/2024] [Indexed: 04/17/2024]
Abstract
BACKGROUND Parkinson's disease (PD) is a common neurodegenerative disease that is linked to several motor and nonmotor symptoms, including sleep disturbances. Patient quality of life has been shown to be disproportionally impacted by disease. OBJECTIVES To investigate sleep quality among individuals with PD, and to assess the severity of sleep disturbances and their impact on daytime activities. SUBJECTS AND METHODS A case‒control with 44 patients with Parkinson's disease and 80 apparently healthy control participants was recruited from several hospitals and clinics. Each participant provided a thorough medical history and underwent a physical examination, and a questionnaire comprising the standard PSQI was used to assess sleep quality. Independent samples t test and Spearman's correlation analysis were used with a p value equal to or less than 0.05 which was considered significant. RESULTS The mean global PSQI score was 11.55 ± 4.412 for PD patients and 5.73 ± 3.22 for the control group with significant p value, Sleep latency onset was 75.57 min for PD patients and 22.81 min for the control group with significant p value. There was no significant correlation between age and other sleep-related variables. A total of 86.4% of patients with Parkinson's disease suffered from varying degrees of daytime dysfunction compared to 61.25% of the controls. CONCLUSION Parkinson's disease patients had poorer sleep quality than the controls. Age and sex were not found to be expected as a factor for sleep quality in patients with Parkinson's disease. Daytime dysfunction rates are high in patients with Parkinson's disease.
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Hart M, Conrad J, Barrett E, Legg K, Ivey G, Lee PHU, Yung YC, Shim JW. X-linked hydrocephalus genes: Their proximity to telomeres and high A + T content compared to Parkinson's disease. Exp Neurol 2023; 366:114433. [PMID: 37156332 PMCID: PMC10330542 DOI: 10.1016/j.expneurol.2023.114433] [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: 01/05/2023] [Revised: 04/15/2023] [Accepted: 05/05/2023] [Indexed: 05/10/2023]
Abstract
Proximity to telomeres (i) and high adenine and thymine (A + T) content (ii) are two factors associated with high mutation rates in human chromosomes. We have previously shown that >100 human genes when mutated to cause congenital hydrocephalus (CH) meet either factor (i) or (ii) at 91% matching, while two factors are poorly satisfied in human genes associated with familial Parkinson's disease (fPD) at 59%. Using the sets of mouse, rat, and human chromosomes, we found that 7 genes associated with CH were located on the X chromosome of mice, rats, and humans. However, genes associated with fPD were in different autosomes depending on species. While the contribution of proximity to telomeres in the autosome was comparable in CH and fPD, high A + T content played a pivotal contribution in X-linked CH (43% in all three species) than in fPD (6% in rodents or 13% in humans). Low A + T content found in fPD cases suggests that PARK family genes harbor roughly 3 times higher chances of methylations in CpG sites or epigenetic changes than X-linked genes.
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Affiliation(s)
- Madeline Hart
- Department of Biomedical Engineering, Marshall University, Huntington, WV, United States
| | - Joshua Conrad
- Department of Biomedical Engineering, Marshall University, Huntington, WV, United States
| | - Emma Barrett
- Department of Biomedical Engineering, Marshall University, Huntington, WV, United States
| | - Kaitlyn Legg
- Department of Biomedical Engineering, Marshall University, Huntington, WV, United States
| | - Gabrielle Ivey
- Department of Biomedical Engineering, Marshall University, Huntington, WV, United States
| | - Peter H U Lee
- Department of Cardiothoracic Surgery, Southcoast Health, Fall River, MA, United States; Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, United States
| | - Yun C Yung
- Department of Neuroscience, The Scintillon Research Institute, San Diego, CA, United States
| | - Joon W Shim
- Department of Biomedical Engineering, Marshall University, Huntington, WV, United States.
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Raheel K, Deegan G, Di Giulio I, Cash D, Ilic K, Gnoni V, Chaudhuri KR, Drakatos P, Moran R, Rosenzweig I. Sex differences in alpha-synucleinopathies: a systematic review. Front Neurol 2023; 14:1204104. [PMID: 37545736 PMCID: PMC10398394 DOI: 10.3389/fneur.2023.1204104] [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: 04/11/2023] [Accepted: 06/13/2023] [Indexed: 08/08/2023] Open
Abstract
Background Past research indicates a higher prevalence, incidence, and severe clinical manifestations of alpha-synucleinopathies in men, leading to a suggestion of neuroprotective properties of female sex hormones (especially estrogen). The potential pathomechanisms of any such effect on alpha-synucleinopathies, however, are far from understood. With that aim, we undertook to systematically review, and to critically assess, contemporary evidence on sex and gender differences in alpha-synucleinopathies using a bench-to-bedside approach. Methods In this systematic review, studies investigating sex and gender differences in alpha-synucleinopathies (Rapid Eye Movement (REM) Behavior Disorder (RBD), Parkinson's Disease (PD), Dementia with Lewy Bodies (DLB), Multiple System Atrophy (MSA)) from 2012 to 2022 were identified using electronic database searches of PubMed, Embase and Ovid. Results One hundred sixty-two studies were included; 5 RBD, 6 MSA, 20 DLB and 131 PD studies. Overall, there is conclusive evidence to suggest sex-and gender-specific manifestation in demographics, biomarkers, genetics, clinical features, interventions, and quality of life in alpha-synucleinopathies. Only limited data exists on the effects of distinct sex hormones, with majority of studies concentrating on estrogen and its speculated neuroprotective effects. Conclusion Future studies disentangling the underlying sex-specific mechanisms of alpha-synucleinopathies are urgently needed in order to enable novel sex-specific therapeutics.
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Affiliation(s)
- Kausar Raheel
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, United Kingdom
| | - Gemma Deegan
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, United Kingdom
- BRAIN, Imaging Centre, CNS, King’s College London, London, United Kingdom
| | - Irene Di Giulio
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, United Kingdom
- School of Basic and Medical Biosciences, Faculty of Life Science and Medicine, King’s College London, London, United Kingdom
| | - Diana Cash
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, United Kingdom
- BRAIN, Imaging Centre, CNS, King’s College London, London, United Kingdom
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, United Kingdom
| | - Katarina Ilic
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, United Kingdom
- BRAIN, Imaging Centre, CNS, King’s College London, London, United Kingdom
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, United Kingdom
| | - Valentina Gnoni
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, United Kingdom
- Center for Neurodegenerative Diseases and the Aging Brain, University of Bari Aldo Moro, Lecce, Italy
| | - K. Ray Chaudhuri
- Movement Disorders Unit, King’s College Hospital and Department of Clinical and Basic Neurosciences, Institute of Psychiatry, Psychology and Neuroscience and Parkinson Foundation Centre of Excellence, King’s College London, London, United Kingdom
| | - Panagis Drakatos
- School of Basic and Medical Biosciences, Faculty of Life Science and Medicine, King’s College London, London, United Kingdom
- Sleep Disorders Centre, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Rosalyn Moran
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, United Kingdom
| | - Ivana Rosenzweig
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, United Kingdom
- Sleep Disorders Centre, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
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Circadian disruption and sleep disorders in neurodegeneration. Transl Neurodegener 2023; 12:8. [PMID: 36782262 PMCID: PMC9926748 DOI: 10.1186/s40035-023-00340-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 02/03/2023] [Indexed: 02/15/2023] Open
Abstract
Disruptions of circadian rhythms and sleep cycles are common among neurodegenerative diseases and can occur at multiple levels. Accumulating evidence reveals a bidirectional relationship between disruptions of circadian rhythms and sleep cycles and neurodegenerative diseases. Circadian disruption and sleep disorders aggravate neurodegeneration and neurodegenerative diseases can in turn disrupt circadian rhythms and sleep. Importantly, circadian disruption and various sleep disorders can increase the risk of neurodegenerative diseases. Thus, harnessing the circadian biology findings from preclinical and translational research in neurodegenerative diseases is of importance for reducing risk of neurodegeneration and improving symptoms and quality of life of individuals with neurodegenerative disorders via approaches that normalize circadian in the context of precision medicine. In this review, we discuss the implications of circadian disruption and sleep disorders in neurodegenerative diseases by summarizing evidence from both human and animal studies, focusing on the bidirectional links of sleep and circadian rhythms with prevalent forms of neurodegeneration. These findings provide valuable insights into the pathogenesis of neurodegenerative diseases and suggest a promising role of circadian-based interventions.
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McCarter SJ, Camerucci E, Mullan AF, Stang CD, Turcano P, St. Louis EK, Boeve BF, Savica R. Sleep Disorders in Early-Onset Parkinsonism: A Population-Based Study. JOURNAL OF PARKINSON'S DISEASE 2023; 13:1175-1183. [PMID: 37742659 PMCID: PMC10657686 DOI: 10.3233/jpd-230045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/25/2023] [Indexed: 09/26/2023]
Abstract
BACKGROUND Sleep disturbances are common in parkinsonian disorders; however, whether sleep disorders affect individuals with early-onset parkinsonism and whether they differ from individuals with typical-onset parkinsonism is unknown. OBJECTIVE To compare the prevalence and incidence of sleep disorders before and after parkinsonian motor symptom onset between individuals with early onset parkinsonism (age ≤50 at motor symptom onset) and typical-onset parkinsonism (age >50 at motor symptom onset). METHODS We used a population-based, 1991 to 2015 incident-cohort study of parkinsonism including 38 patients with early-onset and 1,001 patients with typical-onset parkinsonism. Presence or absence and type of sleep disorder as well as the relationship between motor and sleep symptoms were abstracted from the medical records. Rates of sleep disorders before and after onset of parkinsonism were compared with logistic regression and Cox proportional hazards models. RESULTS The prevalence of sleep disorders prior to the onset of parkinsonism in early vs. typical parkinsonism (24% vs. 16% p = 0.19) and incidence of sleep disorders after parkinsonism onset (5.85 cases per 100 person-years vs. 4.11 cases per 100 person-years; HR 1.15 95% CI: 0.74-1.77) were similar between the two groups. Early-onset parkinsonism had a higher risk for developing post-motor insomnia compared with typical-onset parkinsonism (HR 1.73, 95% CI: 1.02-2.93); the risk for developing all other sleep disorders considered was similar between groups. CONCLUSION Sleep disorders are common in individuals with early-onset parkinsonism and occur with similar frequency to those with typical-onset parkinsonism, except for insomnia, which was more frequent in the early-onset group.
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Affiliation(s)
- Stuart J. McCarter
- Mayo Clinic Department of Neurology, Rochester, MN, USA
- Mayo Clinic Center for Sleep Medicine, Rochester, MN, USA
| | | | - Aidan F. Mullan
- Mayo Clinic Department of Quantitative Health Sciences, Rochester, MN, USA
| | - Cole D. Stang
- Mayo Clinic Department of Neurology, Rochester, MN, USA
| | | | - Erik K. St. Louis
- Mayo Clinic Department of Neurology, Rochester, MN, USA
- Mayo Clinic Center for Sleep Medicine, Rochester, MN, USA
| | | | - Rodolfo Savica
- Mayo Clinic Department of Neurology, Rochester, MN, USA
- Mayo Clinic Department of Quantitative Health Sciences, Rochester, MN, USA
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Deng P, Xu K, Zhou X, Xiang Y, Xu Q, Sun Q, Li Y, Yu H, Wu X, Yan X, Guo J, Tang B, Liu Z. Constructing prediction models for excessive daytime sleepiness by nomogram and machine learning: A large Chinese multicenter cohort study. Front Aging Neurosci 2022; 14:938071. [PMID: 35966776 PMCID: PMC9372350 DOI: 10.3389/fnagi.2022.938071] [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: 05/06/2022] [Accepted: 07/12/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveAlthough risk factors for excessive daytime sleepiness (EDS) have been reported, there are still few cohort-based predictive models for EDS in Parkinson’s disease (PD). This 1-year longitudinal study aimed to develop a predictive model of EDS in patients with PD using a nomogram and machine learning (ML).Materials and methodsA total of 995 patients with PD without EDS were included, and clinical data during the baseline period were recorded, which included basic information as well as motor and non-motor symptoms. One year later, the presence of EDS in this population was re-evaluated. First, the baseline characteristics of patients with PD with or without EDS were analyzed. Furthermore, a Cox proportional risk regression model and XGBoost ML were used to construct a prediction model of EDS in PD.ResultsAt the 1-year follow-up, EDS occurred in 260 of 995 patients with PD (26.13%). Baseline features analysis showed that EDS correlated significantly with age, age of onset (AOO), hypertension, freezing of gait (FOG). In the Cox proportional risk regression model, we included high body mass index (BMI), late AOO, low motor score on the 39-item Parkinson’s Disease Questionnaire (PDQ-39), low orientation score on the Mini-Mental State Examination (MMSE), and absence of FOG. Kaplan–Meier survival curves showed that the survival prognosis of patients with PD in the high-risk group was significantly worse than that in the low-risk group. XGBoost demonstrated that BMI, AOO, PDQ-39 motor score, MMSE orientation score, and FOG contributed to the model to different degrees, in decreasing order of importance, and the overall accuracy of the model was 71.86% after testing.ConclusionIn this study, we showed that risk factors for EDS in patients with PD include high BMI, late AOO, a low motor score of PDQ-39, low orientation score of MMSE, and lack of FOG, and their importance decreased in turn. Our model can predict EDS in PD with relative effectivity and accuracy.
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Affiliation(s)
- Penghui Deng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Kun Xu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Xiaoxia Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yaqin Xiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Qian Xu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Qiying Sun
- Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, China
| | - Yan Li
- Research Institute, Hunan Kechuang Information Technology Joint-Stock Co., Ltd., Changsha, China
| | - Haiqing Yu
- Research Institute, Hunan Kechuang Information Technology Joint-Stock Co., Ltd., Changsha, China
| | - Xinyin Wu
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Xinxiang Yan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Jifeng Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
- Hunan Key Laboratory of Medical Genetics, Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, China
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
- Hunan Key Laboratory of Medical Genetics, Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, China
| | - Zhenhua Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
- Hunan Key Laboratory of Medical Genetics, Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, China
- *Correspondence: Zhenhua Liu,
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Sex Differences in Parkinson’s Disease: From Bench to Bedside. Brain Sci 2022; 12:brainsci12070917. [PMID: 35884724 PMCID: PMC9313069 DOI: 10.3390/brainsci12070917] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 07/08/2022] [Accepted: 07/09/2022] [Indexed: 02/01/2023] Open
Abstract
Background: Parkinson’s disease (PD) is the second most common neurodegenerative disorder after Alzheimer’s disease and gender differences have been described on several aspects of PD. In the present commentary, we aimed to collect and discuss the currently available evidence on gender differences in PD regarding biomarkers, genetic factors, motor and non-motor symptoms, therapeutic management (including pharmacological and surgical treatment) as well as preclinical studies. Methods: A systematic literature review was performed by searching the Pubmed and Scopus databases with the search strings “biomarkers”, “deep brain stimulation”, “female”, “gender”, “genetic”, “levodopa”, “men”, “male”, “motor symptoms”, “non-motor symptoms”, “Parkinson disease”, “sex”, “surgery”, and “women”. Results: The present review confirms the existence of differences between men and women in Parkinson Disease, pointing out new information regarding evidence from animal models, genetic factors, biomarkers, clinical features and pharmacological and surgical treatment. Conclusions: The overall goal is to acquire new informations about sex and gender differences in Parkinson Disease, in order to develop tailored intervetions.
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