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Iranzo A, Cochen De Cock V, Fantini ML, Pérez-Carbonell L, Trotti LM. Sleep and sleep disorders in people with Parkinson's disease. Lancet Neurol 2024:S1474-4422(24)00170-4. [PMID: 38942041 DOI: 10.1016/s1474-4422(24)00170-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 04/02/2024] [Accepted: 04/16/2024] [Indexed: 06/30/2024]
Abstract
Sleep disorders are common in people with Parkinson's disease. These disorders, which increase in frequency throughout the course of the neurodegenerative disease and impair quality of life, include insomnia, excessive daytime sleepiness, circadian disorders, obstructive sleep apnoea, restless legs syndrome, and rapid eye movement (REM) sleep behaviour disorder. The causes of these sleep disorders are complex and multifactorial, including the degeneration of the neural structures that modulate sleep, the detrimental effect of some medications on sleep, the parkinsonian symptoms that interfere with mobility and comfort in bed, and comorbidities that disrupt sleep quality and quantity. The clinical evaluation of sleep disorders include both subjective (eg, questionnaires or diaries) and objective (eg, actigraphy or video polysomnography) assessments. The management of patients with Parkinson's disease and a sleep disorder is challenging and should be individualised. Treatment can include education aiming at changes in behaviour (ie, sleep hygiene), cognitive behavioural therapy, continuous dopaminergic stimulation at night, and specific medications. REM sleep behaviour disorder can occur several years before the onset of parkinsonism, suggesting that the implementation of trials of neuroprotective therapies should focus on people with this sleep disorder.
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Affiliation(s)
- Alex Iranzo
- Sleep Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Universitat de Barcelona, Barcelona, Spain; IDIBAPS, Universitat de Barcelona, Barcelona, Spain; CIBERNED, Universitat de Barcelona, Barcelona, Spain.
| | - Valerie Cochen De Cock
- Sleep and Neurology Department, Beau Soleil Clinic, Montpellier, France; EuroMov Digital Health in Motion, University of Montpellier, IMT Mines Ales, Montpellier, France
| | - María Livia Fantini
- Neurophysiology Unit, Neurology Department, Université Clermont Auvergne, CNRS, Institut Pascal, Clermont-Ferrand University Hospital, Clermont-Ferrand, France
| | - Laura Pérez-Carbonell
- Sleep Disorders Centre, Guy's and St Thomas' NHS Foundation Trust, King's College London, London, UK
| | - Lynn Marie Trotti
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA; Emory Sleep Center, Emory University School of Medicine, Atlanta, GA, USA
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Hähnel T, Raschka T, Sapienza S, Klucken J, Glaab E, Corvol JC, Falkenburger BH, Fröhlich H. Progression subtypes in Parkinson's disease identified by a data-driven multi cohort analysis. NPJ Parkinsons Dis 2024; 10:95. [PMID: 38698004 PMCID: PMC11066039 DOI: 10.1038/s41531-024-00712-3] [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: 11/15/2023] [Accepted: 04/16/2024] [Indexed: 05/05/2024] Open
Abstract
The progression of Parkinson's disease (PD) is heterogeneous across patients, affecting counseling and inflating the number of patients needed to test potential neuroprotective treatments. Moreover, disease subtypes might require different therapies. This work uses a data-driven approach to investigate how observed heterogeneity in PD can be explained by the existence of distinct PD progression subtypes. To derive stable PD progression subtypes in an unbiased manner, we analyzed multimodal longitudinal data from three large PD cohorts and performed extensive cross-cohort validation. A latent time joint mixed-effects model (LTJMM) was used to align patients on a common disease timescale. Progression subtypes were identified by variational deep embedding with recurrence (VaDER). In each cohort, we identified a fast-progressing and a slow-progressing subtype, reflected by different patterns of motor and non-motor symptoms progression, survival rates, treatment response, features extracted from DaTSCAN imaging and digital gait assessments, education, and Alzheimer's disease pathology. Progression subtypes could be predicted with ROC-AUC up to 0.79 for individual patients when a one-year observation period was used for model training. Simulations demonstrated that enriching clinical trials with fast-progressing patients based on these predictions can reduce the required cohort size by 43%. Our results show that heterogeneity in PD can be explained by two distinct subtypes of PD progression that are stable across cohorts. These subtypes align with the brain-first vs. body-first concept, which potentially provides a biological explanation for subtype differences. Our predictive models will enable clinical trials with significantly lower sample sizes by enriching fast-progressing patients.
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Affiliation(s)
- Tom Hähnel
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
- Department of Neurology, Medical Faculty and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
| | - Tamara Raschka
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany
- Bonn-Aachen International Center for IT, University of Bonn, Bonn, Germany
| | - Stefano Sapienza
- Biomedical Data Science, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
- Luxembourg Institute of Health (LIH), Strassen, Luxembourg
| | - Jochen Klucken
- Biomedical Data Science, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
- Luxembourg Institute of Health (LIH), Strassen, Luxembourg
- Centre Hospitalier de Luxembourg (CHL), Strassen, Luxembourg
| | - Enrico Glaab
- Biomedical Data Science, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Jean-Christophe Corvol
- Sorbonne Université, Paris Brain Institute - ICM, Inserm, CNRS, Assistance Publique Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Department of Neurology, Paris, France
| | - Björn H Falkenburger
- Department of Neurology, Medical Faculty and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
- German Center for Neurodegenerative Diseases (DZNE), Dresden, Germany
| | - Holger Fröhlich
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany
- Bonn-Aachen International Center for IT, University of Bonn, Bonn, Germany
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Liu L, Shi Z, Gan J, Liu S, Wen C, Yang Y, Yang F, Ji Y. Characterization of de novo Dementia with Lewy Body with different duration of rapid eye movement sleep behavior disorder. Sleep Med 2024; 114:101-108. [PMID: 38176204 DOI: 10.1016/j.sleep.2023.12.025] [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: 10/16/2023] [Revised: 12/06/2023] [Accepted: 12/25/2023] [Indexed: 01/06/2024]
Abstract
BACKGROUND Cognitive disorder, parkinsonism, autonomic dysfunction (AuD) and rapid eye movement sleep behavior disorder (RBD) can occur prior to or simultaneously with Dementia with Lewy Body (DLB) onset. RBD is generally linked with progressive neurodegenerative traits. However, associations between RBD with DLB, RBD without DLB, and RBD duration effects on DLB symptoms remain unclear. OBJECTIVES To examine DLB symptom frequency and subtypes in RBD, and explore the effects of different RBD onset times on symptoms in de novo DLB patients. METHODS In this multicenter investigation, we consecutively recruited 271 de novo DLB patients. All had standardized clinical and comprehensive neuropsychological evaluations. Subgroup analyses, performed based on the duration of RBD confirmed by polysomnography before the DLB diagnosis, we compared the proportion of patients with cognitive impairment, parkinsonism, and AuD features between groups. RESULTS Parkinsonism and AuD incidences were significantly elevated in DLB patients with RBD when compared with patients without RBD. Subgroup analyses indicated no significant differences in parkinsonism between DLB patients who developed RBD ≥10 years prior to the DLB diagnosis and DLB patients without RBD. The incidence of non-tremor-predominant parkinsonism and AuD was significantly higher in DLB patients whose RBD duration before the DLB diagnosis was <10 years when compared with DLB patients without RBD. CONCLUSIONS We identified significant symptom and phenotypic variability between DLB patients with and without RBD. Also, different RBD duration effects before the DLB diagnosis had a significant impact on symptomatic phenotypes, suggesting the existence of a slowly progressive DLB neurodegenerative subtype.
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Affiliation(s)
- Lixin Liu
- Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin Medical University, Tianjin, China; The Psycho Department of Beijing Geriatric Hospital, Beijing, China
| | - Zhihong Shi
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin Key Laboratory of Cerebrovascular and of Neurodegenerative Diseases, Tianjin Dementia Institute, Tianjin, China
| | - Jinghuan Gan
- Department of Neurology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Shuai Liu
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin Key Laboratory of Cerebrovascular and of Neurodegenerative Diseases, Tianjin Dementia Institute, Tianjin, China
| | - Chen Wen
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yaqi Yang
- Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin Medical University, Tianjin, China
| | - Fan Yang
- Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin Medical University, Tianjin, China
| | - Yong Ji
- Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin Medical University, Tianjin, China; Department of Neurology, Tianjin Huanhu Hospital, Tianjin Key Laboratory of Cerebrovascular and of Neurodegenerative Diseases, Tianjin Dementia Institute, Tianjin, China.
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Sang S, Ba Y, Yang N. Longitudinal faster anxiety progression of GBA variant carriers in the early Parkinson's disease cohort. Front Neurosci 2024; 18:1353759. [PMID: 38327847 PMCID: PMC10847242 DOI: 10.3389/fnins.2024.1353759] [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: 12/11/2023] [Accepted: 01/02/2024] [Indexed: 02/09/2024] Open
Abstract
Objective Anxiety symptoms are prevalent neuropsychiatric manifestations in Parkinson's disease (PD) and impact the development of motor complications. Our aim was to evaluate the association of GBA variants with the anxiety development in early PD cohort. Methods This cohort study used data from the Parkinson Progression Marker Initiative. The primary outcome anxiety was assessed by State-Trait Anxiety Inventory (STAI). The association between GBA and longitudinal change in the STAI total score was examined using linear mixed-effects model, and the association between GBA and anxiety progression was examined using Cox survival analysis. Results A total of 385 patients with PD were included in this study, 39 of them were GBA variant carriers and 346 were idiopathic PD without GBA variants. Patients with GBA variants had faster annual increase in anxiety score (β = 0.44; 95% CI, 0.18 to 0.71; p < 0.001) and were at higher risk of anxiety progression (HR 1.87; 95% CI, 1.03 to 3.41; p = 0.03,). Higher baseline scores for Scales for Outcomes in Parkinson's Disease-Autonomic (SCOPA-AUT), which indicated the autonomic dysfunction, also independently predicted faster increase in anxiety score (β = 0.48; 95%CI, 0.19 to 0.69; p < 0.001) and higher incidence of anxiety development (HR = 1.05; 95% CI, 1.01 to 1.08; p = 0.008). Interpretation These findings suggest that longitudinal anxiety symptoms worsening was faster in PD patients who were GBA variant carriers and have dysautonomia, and this association was enhanced if they have both.
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Affiliation(s)
- Shushan Sang
- Department of Otolaryngology-Head and Neck Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yunpeng Ba
- Department of Otolaryngology-Head and Neck Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Nannan Yang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Kalinderi K, Papaliagkas V, Fidani L. The Genetic Landscape of Sleep Disorders in Parkinson's Disease. Diagnostics (Basel) 2024; 14:106. [PMID: 38201415 PMCID: PMC10795795 DOI: 10.3390/diagnostics14010106] [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: 11/29/2023] [Revised: 12/30/2023] [Accepted: 12/31/2023] [Indexed: 01/12/2024] Open
Abstract
Parknson's disease (PD) is the second most common neurodegenerative disease, affecting 1% of people aged over 60. PD is characterized by a wide range of motor symptoms, however the clinical spectrum of PD covers a wide range of non-motor symptoms, as well. Sleep disorders are among the most common non-motor symptoms of PD, can occur at any stage of the disease and significantly affect quality of life. These include rapid eye movement sleep behavior disorder (RBD), restless legs syndrome (RLS), excessive daytime sleepiness (EDS), insomnia, obstructive sleep apnea (OSA) and circadian rhythm disturbances. One of the main challenges in PD research is identifying individuals during the prodromal phase of the disease. Combining genetic and prodromal data may aid the early identification of individuals susceptible to PD. This review highlights current data regarding the genetic component of sleep disorders in PD patients, focusing on genes that have currently been associated with this PD co-morbidity.
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Affiliation(s)
- Kallirhoe Kalinderi
- Laboratory of Medical Biology-Genetics, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
| | - Vasileios Papaliagkas
- Department of Biomedical Sciences, School of Health Sciences, International Hellenic University, 57400 Thessaloniki, Greece;
| | - Liana Fidani
- Laboratory of Medical Biology-Genetics, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
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Fetene SM, Haile TG, Dadi A. Effect of adverse perinatal outcomes on postpartum maternal mental health in low-income and middle-income countries: a protocol for systematic review. BMJ Open 2023; 13:e074447. [PMID: 38101849 PMCID: PMC10729045 DOI: 10.1136/bmjopen-2023-074447] [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: 04/06/2023] [Accepted: 11/20/2023] [Indexed: 12/17/2023] Open
Abstract
INTRODUCTION More than three-fourths of adverse perinatal outcomes (preterm, small for gestational age, low birth weight, congenital anomalies, stillbirth and neonatal death) occur in low-income and middle-income countries. These adverse perinatal outcomes can have both short-term and long-term consequences on maternal mental health. Even though there are few empirical studies on the effect of perinatal loss on maternal mental illness, comprehensive information on the impact of adverse perinatal outcomes in resource-limited settings is scarce. Therefore, we aim to systematically review and synthesise evidence on the effect of adverse perinatal outcomes on maternal mental health. METHODS AND ANALYSIS The primary outcome of our review will be postpartum maternal mental illness (anxiety, depression, post-traumatic stress disorder and postpartum psychosis) following adverse perinatal outcomes. All peer-reviewed primary studies published in English will be retrieved from databases: PubMed, MEDLINE, CINAHL Ultimate (EBSCO), PsycINFO, Embase, Scopus and Global Health through the three main searching terms-adverse perinatal outcomes, maternal mental illness and settings, with a variant of subject headings and keywords. We will follow the Joanna Briggs Institute critical appraisal checklist to assess the quality of the studies we are including. The review findings will be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement. Estimate-based meta-analysis will be performed. We will assess heterogeneity between studies using the I2 statistics and publication bias will be checked using funnel plots and Egger's test. A subgroup analysis will be conducted to explore potential sources of heterogeneity (if available). Finally, the certainty of the evidence will be evaluated using the Grading of Recommendations, Assessment, Development and Evaluation approach. ETHICS AND DISSEMINATION Since this systematic review does not involve human participants, ethical approval is not required. The review will be submitted for publication in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER CRD42023405980.
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Affiliation(s)
| | | | - Abel Dadi
- Menzies School of Health Research, Charles Darwin University, Casuarina, Northern Territory, Australia
- Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
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Lima MMS, Targa ADS, Dos Santos Lima GZ, Cavarsan CF, Torterolo P. Macro and micro-sleep dysfunctions as translational biomarkers for Parkinson's disease. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2023; 174:187-209. [PMID: 38341229 DOI: 10.1016/bs.irn.2023.08.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2024]
Abstract
Sleep disturbances are highly prevalent among patients with Parkinson's disease (PD) and often appear from the early-phase disease or prodromal stages. In this chapter, we will discuss the current evidence addressing the links between sleep dysfunctions in PD, focusing most closely on those data from animal and mathematical/computational models, as well as in human-based studies that explore the electrophysiological and molecular mechanisms by which PD and sleep may be intertwined, whether as predictors or consequences of the disease. It is possible to clearly state that leucine-rich repeat kinase 2 gene (LRRK2) is significantly related to alterations in sleep architecture, particularly affecting rapid eye movement (REM) sleep and non-REM sleep, thus impacting sleep quality. Also, decreases in gamma power, observed after dopaminergic lesions, correlates negatively with the degree of injury, which brings other levels of understanding the impacts of the disease. Besides, abnormal synchronized oscillations among basal ganglia nuclei can be detrimental for information processing considering both motor and sleep-related processes. Altogether, despite clear advances in the field, it is still difficult to definitely establish a comprehensive understanding of causality among all the sleep dysfunctions with the disease itself. Although, certainly, the search for biomarkers is helping in shortening this road towards a better and faster diagnosis, as well as looking for more efficient treatments.
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Affiliation(s)
- Marcelo M S Lima
- Neurophysiology Laboratory, Department of Physiology, Federal University of Paraná, Curitiba, Paraná, Brazil.
| | - Adriano D S Targa
- CIBER of Respiratory diseases (CIBERES), Institute of Health Carlos III, Madrid, Spain; Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, Biomedical Research Institute of Lleida (IRBLleida), Lleida, Spain
| | - Gustavo Z Dos Santos Lima
- Science and Technology School, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - Clarissa F Cavarsan
- College of Pharmacy, University of Rhode Island, Kingston, RI, United States
| | - Pablo Torterolo
- Laboratory of Sleep Neurobiology, Department of Physiology, School of Medicine, Universidad de la República, Montevideo, Uruguay
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Du L, He X, Fan X, Wei X, Xu L, Liang T, Wang C, Ke Y, Yung WH. Pharmacological interventions targeting α-synuclein aggregation triggered REM sleep behavior disorder and early development of Parkinson's disease. Pharmacol Ther 2023; 249:108498. [PMID: 37499913 DOI: 10.1016/j.pharmthera.2023.108498] [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: 04/28/2023] [Revised: 06/24/2023] [Accepted: 07/18/2023] [Indexed: 07/29/2023]
Abstract
Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia characterized by elevated motor behaviors and dream enactments in REM sleep, often preceding the diagnosis of Parkinson's disease (PD). As RBD could serve as a biomarker for early PD developments, pharmacological interventions targeting α-synuclein aggregation triggered RBD could be applied toward early PD progression. However, robust therapeutic guidelines toward PD-induced RBD are lacking, owing in part to a historical paucity of effective treatments and trials. We reviewed the bidirectional links between α-synuclein neurodegeneration, progressive sleep disorders, and RBD. We highlighted the correlation between RBD development, α-synuclein aggregation, and neuronal apoptosis in key brainstem regions involved in REM sleep atonia maintenance. The current pharmacological intervention strategies targeting RBD and their effects on progressive PD are discussed, as well as current treatments for progressive neurodegeneration and their effects on RBD. We also evaluated emerging and potential pharmacological solutions to sleep disorders and developing synucleinopathies. This review provides insights into the mechanisms and therapeutic targets underlying RBD and PD, and explores bidirectional treatment effects for both diseases, underscoring the need for further research in this area.
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Affiliation(s)
- Lida Du
- Institute of Molecular Medicine & Innovative Pharmaceutics, Qingdao University, Qingdao, China; School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China.
| | - Xiaoli He
- Institute of Medical Plant Development, Peking Union Medical College, Beijing, China
| | - Xiaonuo Fan
- Department of Biology, Boston University, Boston, USA
| | - Xiaoya Wei
- Harvard T.H. Chan School of Public Health, Boston, USA
| | - Linhao Xu
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China; Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tuo Liang
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China; Institute of Neurological and Psychiatric Disorders, Shenzhen Bay Laboratory, Shenzhen, China
| | - Chunbo Wang
- Institute of Molecular Medicine & Innovative Pharmaceutics, Qingdao University, Qingdao, China
| | - Ya Ke
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Wing-Ho Yung
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China; Department of Neuroscience, City University of Hong Kong, Hong Kong, China.
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Zhou Y, Wang Y, Wan J, Zhao Y, Pan H, Zeng Q, Zhou X, He R, Zhou X, Xiang Y, Zhou Z, Chen B, Sun Q, Xu Q, Tan J, Shen L, Jiang H, Yan X, Li J, Guo J, Tang B, Wu H, Liu Z. Mutational spectrum and clinical features of GBA1 variants in a Chinese cohort with Parkinson's disease. NPJ Parkinsons Dis 2023; 9:129. [PMID: 37658046 PMCID: PMC10474275 DOI: 10.1038/s41531-023-00571-4] [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: 04/20/2023] [Accepted: 08/16/2023] [Indexed: 09/03/2023] Open
Abstract
GBA1 variants are important risk factors for Parkinson's disease (PD). Most studies assessing GBA1-related PD risk have been performed in European-derived populations. Although the coding region of the GBA1 gene in the Chinese population has been analyzed, the sample sizes were not adequate. In this study, we aimed to investigate GBA1 variants in a large Chinese cohort of patients with PD and healthy control and explore the associated clinical characteristics. GBA1 variants in 4034 patients and 2931 control participants were investigated using whole-exome and whole-genome sequencing. The clinical features of patients were evaluated using several scales. Regression analysis, chi-square, and Fisher exact tests were used to analyze GBA1 variants and the clinical symptoms of different groups. We identified 104 variants, including 8 novel variants, expanding the spectrum of GBA1 variants. The frequency of GBA1 variants in patients with PD was 7.46%, higher than that in the control (1.81%) (P < 0.001, odds ratio [OR] = 4.38, 95% confidence interval [CI]: 3.26-5.89). Among patients, 176 (4.36%) had severe variants, 34 (0.84%) carried mild variants, three (0.07%) had risk variants, and 88 (2.18%) carried unknown variants. Our study, for the first time, found that p.G241R (P = 0.007, OR = 15.3, 95% CI: 1.25-261.1) and p.S310G (P = 0.005, OR = 4.86, 95% CI: 1.52-28.04) variants increased the risk of PD. Patients with GBA1 variants exhibited an earlier onset age and higher risk of probable rapid-eye-movement sleep behavior disorder, olfactory dysfunction, depression, and autonomic dysfunction than patients without GBA1 variants.
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Affiliation(s)
- Yangjie Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yige Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Juan Wan
- Department of Neurology, & Multi-Omics Research Center for Brain Disorders, The First Affiliated Hospital, University of South China, Hengyang, Hunan, China
| | - Yuwen Zhao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Hongxu Pan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Qian Zeng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xun Zhou
- Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Runcheng He
- Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xiaoxia Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yaqin Xiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zhou Zhou
- Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Bin Chen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Qiying Sun
- Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Qian Xu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jieqiong Tan
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Lu Shen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Changsha, Hunan, China
- Bioinformatics Center & National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Hong Jiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Changsha, Hunan, China
| | - Xinxiang Yan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jinchen Li
- Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
- Bioinformatics Center & National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jifeng Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Changsha, Hunan, China
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Neurology, & Multi-Omics Research Center for Brain Disorders, The First Affiliated Hospital, University of South China, Hengyang, Hunan, China
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Changsha, Hunan, China
- Bioinformatics Center & National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Heng Wu
- Department of Neurology, & Multi-Omics Research Center for Brain Disorders, The First Affiliated Hospital, University of South China, Hengyang, Hunan, China.
- Clinical Research Center for Immune-Related Encephalopathy of Hunan Province, Hengyang, Hunan, China.
| | - Zhenhua Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Changsha, Hunan, China.
- Bioinformatics Center & National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China.
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Menozzi E, Toffoli M, Schapira AHV. Targeting the GBA1 pathway to slow Parkinson disease: Insights into clinical aspects, pathogenic mechanisms and new therapeutic avenues. Pharmacol Ther 2023; 246:108419. [PMID: 37080432 DOI: 10.1016/j.pharmthera.2023.108419] [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: 02/07/2023] [Revised: 03/31/2023] [Accepted: 04/17/2023] [Indexed: 04/22/2023]
Abstract
The GBA1 gene encodes the lysosomal enzyme glucocerebrosidase (GCase), which is involved in sphingolipid metabolism. Biallelic variants in GBA1 cause Gaucher disease (GD), a lysosomal storage disorder characterised by loss of GCase activity and aberrant intracellular accumulation of GCase substrates. Carriers of GBA1 variants have an increased risk of developing Parkinson disease (PD), with odds ratio ranging from 2.2 to 30 according to variant severity. GBA1 variants which do not cause GD in homozygosis can also increase PD risk. Patients with PD carrying GBA1 variants show a more rapidly progressive phenotype compared to non-carriers, emphasising the need for disease modifying treatments targeting the GBA1 pathway. Several mechanisms secondary to GCase dysfunction are potentially responsible for the pathological changes leading to PD. Misfolded GCase proteins induce endoplasmic reticulum stress and subsequent unfolded protein response and impair the autophagy-lysosomal pathway. This results in α-synuclein accumulation and spread, and promotes neurodegenerative changes. Preclinical evidence also shows that products of GCase activity can promote accumulation of α-synuclein, however there is no convincing evidence of substrate accumulation in GBA1-PD brains. Altered lipid homeostasis secondary to loss of GCase activity could also contribute to PD pathology. Treatments that target the GBA1 pathway could reverse these pathological processes and halt/slow the progression of PD. These range from augmentation of GCase activity via GBA1 gene therapy, restoration of normal intracellular GCase trafficking via molecular chaperones, and substrate reduction therapy. This review discusses the pathways associated with GBA1-PD and related novel GBA1-targeted interventions for PD treatment.
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Affiliation(s)
- Elisa Menozzi
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, United States of America
| | - Marco Toffoli
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, United States of America
| | - Anthony H V Schapira
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, United States of America.
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Who is at Risk of Parkinson Disease? Refining the Preclinical Phase of GBA1 and LRRK2 Variant Carriers: a Clinical, Biochemical, and Imaging Approach. Curr Neurol Neurosci Rep 2023; 23:121-130. [PMID: 36881256 PMCID: PMC10119235 DOI: 10.1007/s11910-023-01259-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/23/2023] [Indexed: 03/08/2023]
Abstract
PURPOSE OF REVIEW Genetic variants in GBA1 and LRRK2 genes are the commonest genetic risk factor for Parkinson disease (PD); however, the preclinical profile of GBA1 and LRRK2 variant carriers who will develop PD is unclear. This review aims to highlight the more sensitive markers that can stratify PD risk in non-manifesting GBA1 and LRRK2 variant carriers. RECENT FINDINGS Several case-control and a few longitudinal studies evaluated clinical, biochemical, and neuroimaging markers within cohorts of non-manifesting carriers of GBA1 and LRRK2 variants. Despite similar levels of penetrance of PD in GBA1 and LRRK2 variant carriers (10-30%), these individuals have distinct preclinical profiles. GBA1 variant carriers at higher risk of PD can present with prodromal symptoms suggestive of PD (hyposmia), display increased α-synuclein levels in peripheral blood mononuclear cells, and show dopamine transporter abnormalities. LRRK2 variant carriers at higher risk of PD might show subtle motor abnormalities, but no prodromal symptoms, higher exposure to some environmental factors (non-steroid anti-inflammatory drugs), and peripheral inflammatory profile. This information will help clinicians tailor appropriate screening tests and counseling and facilitate researchers in the development of predictive markers, disease-modifying treatments, and selection of healthy individuals who might benefit from preventive interventions.
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Weerasinghe-Mudiyanselage PD, Kang S, Kim JS, Moon C. Therapeutic Approaches to Non-Motor Symptoms of Parkinson's Disease: A Current Update on Preclinical Evidence. Curr Neuropharmacol 2023; 21:560-577. [PMID: 36200159 PMCID: PMC10207906 DOI: 10.2174/1570159x20666221005090126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 08/30/2022] [Accepted: 09/02/2022] [Indexed: 11/22/2022] Open
Abstract
Despite being classified as a movement disorder, Parkinson's disease (PD) is characterized by a wide range of non-motor symptoms that significantly affect the patients' quality of life. However, clear evidence-based therapy recommendations for non-motor symptoms of PD are uncommon. Animal models of PD have previously been shown to be useful for advancing the knowledge and treatment of motor symptoms. However, these models may provide insight into and assess therapies for non-motor symptoms in PD. This paper highlights non-motor symptoms in preclinical models of PD and the current position regarding preclinical therapeutic approaches for these non-motor symptoms. This information may be relevant for designing future preclinical investigations of therapies for nonmotor symptoms in PD.
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Affiliation(s)
- Poornima D.E. Weerasinghe-Mudiyanselage
- Department of Veterinary Anatomy and Animal Behavior, College of Veterinary Medicine and BK21 FOUR Program, Chonnam National University, Gwangju 61186, South Korea
| | - Sohi Kang
- Department of Veterinary Anatomy and Animal Behavior, College of Veterinary Medicine and BK21 FOUR Program, Chonnam National University, Gwangju 61186, South Korea
| | - Joong-Sun Kim
- Department of Veterinary Anatomy and Animal Behavior, College of Veterinary Medicine and BK21 FOUR Program, Chonnam National University, Gwangju 61186, South Korea
| | - Changjong Moon
- Department of Veterinary Anatomy and Animal Behavior, College of Veterinary Medicine and BK21 FOUR Program, Chonnam National University, Gwangju 61186, South Korea
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MAO-B Polymorphism Associated with Progression in a Chinese Parkinson’s Disease Cohort but Not in the PPMI Cohort. PARKINSON'S DISEASE 2022; 2022:3481102. [PMID: 36164437 PMCID: PMC9509281 DOI: 10.1155/2022/3481102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 08/17/2022] [Indexed: 11/29/2022]
Abstract
Introduction Genetic factors play an important role in Parkinson's disease (PD) risk. However, the genetic contribution to progression in Chinese PD patients has rarely been studied. This study investigated genetic associations with progression based on 30 PD risk loci common in a longitudinal cohort of Chinese PD patients and the Parkinson's Progression Markers Initiative (PPMI) cohort. Methods PD patients from the true world (TW) Chinese PD longitudinal cohort and the PPMI cohort with demographic information and assessment scales were assessed. A panel containing 30 PD risk single nucleotide polymorphisms was tested. Progression rates of each scale were derived from random-effect slope values of mixed-effects regression models. Progression rates of multiple assessments were combined by using principal component analysis (PCA) to derive scores for composite, motor, and nonmotor progression. The association of genetic polymorphism and separate scales or PCA progression was analysed via linear regression. Results In the Chinese PD cohort, MAOB rs1799836 was associated with progression based on the Montreal Cognitive Assessment, the top 3 principal components (PCs) of nonmotor PCA and PC1 of the composite PCA. In the PPMI cohort, both MDS-Unified Parkinson's Disease Rating Scale II and motor PC1 progression were associated with RIT2 rs12456492. The PARK16 haplotype was associated with Geriatric Depression Scale and the State-Trait Anxiety Inventory for Adults progression, and the SNCA haplotype was associated with the Hoehn-Yahr staging progression and motor PC1 progression. Ethnicity-stratified analysis showed that the association between MAOB rs1799836 and PD progression may be specific to Asian or Chinese patients. Conclusion MAOB rs1799836 was associated with the progression of nonmotor symptoms, especially cognitive impairment, and the composite progression of motor and nonmotor symptoms within our Chinese PD cohort. The RIT2 rs12456492 and SNCA haplotypes were associated with motor function decline, and the PARK16 haplotype was associated with progression in mood in the PPMI cohort.
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