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Sivaranjini S, Sujatha CM. Analysis of cognitive dysfunction in Parkinson's disease using voxel based morphometry and radiomics. Cogn Process 2024:10.1007/s10339-024-01197-x. [PMID: 38714621 DOI: 10.1007/s10339-024-01197-x] [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: 08/19/2023] [Accepted: 04/19/2024] [Indexed: 05/10/2024]
Abstract
Cognitive impairment in Parkinson's disease (PD) is associated with changes in the brain anatomical structures. The objective of this study, is to identify the atrophy patterns based on the severity of cognitive decline and evaluate the disease progression. In this study, gray matter alterations are analysed in 135 PD subjects under 3 cognitive domains (91 Cognitively normal PD (NC-PD), 25 PD with Mild Cognitive Impairment (PD-MCI) and 19 PD with Dementia (PD-D)) by comparing them with 58 Healthy Control (HC) subjects. Voxel Based Morphometry (VBM) is used to segment the gray matter regions in magnetic resonance images and analyse the atrophy patterns statistically. Significant patterns of gray matter variations observed in the middle temporal and medial frontal region differentiate between HC and PD subject groups based on the severity of cognitive decline. Abnormalities in gray matter is substantiated through radiomic features extracted from the significant gray matter clusters. Significant radiomic features of the clusters are able to differentiate between the HC and PD-D subjects with an accuracy of 81.82%. Higher atrophy levels identified in PD-D subjects compared to NC-PD and PD-MCI group enables early diagnosis and treatment procedures. The combined and comprehensive analysis of gray matter alterations through VBM and radiomic features gives better assessment of cognitive impairment in PD.
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Affiliation(s)
- S Sivaranjini
- Department of Electronics and Communication Engineering, College of Engineering (CEG), Anna University, Chennai, India.
| | - C M Sujatha
- Department of Electronics and Communication Engineering, College of Engineering (CEG), Anna University, Chennai, India
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2
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Li X, Yin Y, Zhang H. Nonlinear association between self-reported sleep duration and cognitive function among middle-aged and older adults in China: The moderating effect of informal care. Sleep Med 2024; 115:226-234. [PMID: 38377839 DOI: 10.1016/j.sleep.2024.02.028] [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: 11/21/2023] [Revised: 01/24/2024] [Accepted: 02/13/2024] [Indexed: 02/22/2024]
Abstract
BACKGROUND Cognitive impairment is a major public health problem urgently to be solved. This study aims to examine the association between sleep duration and cognitive function and its two subdimensions: episodic memory and mental status, and to explore the moderating effects of informal care on these associations among middle-aged and older adults in China. METHODS Data was drawn from China Health and Retirement Longitudinal Study (CHARLS) 2011, 2013, 2015 and 2018 datasets. Sleep duration and informal care were self-reported. Cognitive function was measured using CHARLS Harmonized Cognitive Assessment Protocol. Effects of informal care on sleep duration-cognitive function were assessed using Generalized Estimating Equations models. RESULTS The relationships between sleep duration and cognitive function, episodic memory, and mental status were all found to follow an inverted U-shaped pattern. Spouse care weakened the adverse effects of extreme sleep duration on cognitive function while the children care amplified them. Further, we only observed the moderating effects of spouse and children care on the association between sleep duration and episodic memory, but not mental status. CONCLUSIONS The relationships between sleep duration and cognitive function, along with its different dimensions, are nonlinear in nature. The impacts of sleep duration on cognitive function and its dimensions are contingent upon the levels of informal care received and the sources of that care. We provide valuable insights into the complex interplay between sleep duration, informal care, and cognitive function.
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Affiliation(s)
- Xuezhu Li
- School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yujie Yin
- Department of Management, Marketing and Information Systems, Hong Kong Baptist University, Hong Kong, 999077, China
| | - Hui Zhang
- School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
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3
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Nabizadeh F, Pirahesh K, Azami M, Moradkhani A, Sardaripour A, Ramezannezhad E. T1 and T2 weighted lesions and cognition in multiple Sclerosis: A systematic review and meta-analysis. J Clin Neurosci 2024; 119:1-7. [PMID: 37952373 DOI: 10.1016/j.jocn.2023.11.014] [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: 08/16/2023] [Revised: 11/01/2023] [Accepted: 11/07/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND Considering the different results regarding the correlation between Magnetic Resonance Imaging (MRI) structural measures and cognitive dysfunction in patients with MS, we aimed to perform a systematic review and meta-analysis study to investigate the correlation between T1 and T2 weighted lesions and cognitive scores to find the most robust MRI markers for cognitive function in MS population. METHODS The literature of this paper was identified through a comprehensive search of electronic datasets including PubMed, Scopus, Web of Science, and Embase in February 2022. Studies that reported the correlation between cognitive status and T1 and T2 weighted lesions in MS patients were selected. RESULTS 21 studies with a total of 3771 MS patients with mean ages ranging from 30 to 57 years were entered into our study. Our analysis revealed that the volume of T1 lesions was significantly correlated with Symbol Digit Modality test (SDMT) (r: -0.30, 95 %CI: -0.59, -0.01) and Paced Auditory Serial-Addition Task (PASAT) scores (r: -0.23, 95 %CI: -0.36, -0.10). We investigated the correlation between T2 lesions and cognitive scores. The pooled estimates of z scores were significant for SDMT (r: -0.27, 95 %CI: -0.51, -0.03) and PASAT (r: -0.27, 95 %CI: -0.41, -0.13). CONCLUSION In conclusion, our systematic review and meta-analysis study provides strong evidence of the correlation between T1 and T2 lesions and cognitive function in MS patients. Further research is needed to explore the potential mechanisms underlying this relationship and to develop targeted interventions to improve cognitive outcomes in MS patients.
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Affiliation(s)
- Fardin Nabizadeh
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran; School of Medicine, Tehran University of Medical Science, Tehran, Iran.
| | - Kasra Pirahesh
- Student Research Committee, School of Medicine, Kurdistan University of Medical Science, Sanandaj, Iran
| | - Mobin Azami
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Science, Tehran, Iran
| | - Asra Moradkhani
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Science, Tehran, Iran
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Jellinger KA. Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks. Int J Mol Sci 2023; 25:498. [PMID: 38203667 PMCID: PMC10778722 DOI: 10.3390/ijms25010498] [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: 11/23/2023] [Revised: 12/11/2023] [Accepted: 12/27/2023] [Indexed: 01/12/2024] Open
Abstract
Cognitive impairment (CI) is a characteristic non-motor feature of Parkinson disease (PD) that poses a severe burden on the patients and caregivers, yet relatively little is known about its pathobiology. Cognitive deficits are evident throughout the course of PD, with around 25% of subtle cognitive decline and mild CI (MCI) at the time of diagnosis and up to 83% of patients developing dementia after 20 years. The heterogeneity of cognitive phenotypes suggests that a common neuropathological process, characterized by progressive degeneration of the dopaminergic striatonigral system and of many other neuronal systems, results not only in structural deficits but also extensive changes of functional neuronal network activities and neurotransmitter dysfunctions. Modern neuroimaging studies revealed multilocular cortical and subcortical atrophies and alterations in intrinsic neuronal connectivities. The decreased functional connectivity (FC) of the default mode network (DMN) in the bilateral prefrontal cortex is affected already before the development of clinical CI and in the absence of structural changes. Longitudinal cognitive decline is associated with frontostriatal and limbic affections, white matter microlesions and changes between multiple functional neuronal networks, including thalamo-insular, frontoparietal and attention networks, the cholinergic forebrain and the noradrenergic system. Superimposed Alzheimer-related (and other concomitant) pathologies due to interactions between α-synuclein, tau-protein and β-amyloid contribute to dementia pathogenesis in both PD and dementia with Lewy bodies (DLB). To further elucidate the interaction of the pathomechanisms responsible for CI in PD, well-designed longitudinal clinico-pathological studies are warranted that are supported by fluid and sophisticated imaging biomarkers as a basis for better early diagnosis and future disease-modifying therapies.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, A-1150 Vienna, Austria
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Zilberter Y, Tabuena DR, Zilberter M. NOX-induced oxidative stress is a primary trigger of major neurodegenerative disorders. Prog Neurobiol 2023; 231:102539. [PMID: 37838279 DOI: 10.1016/j.pneurobio.2023.102539] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 10/10/2023] [Indexed: 10/16/2023]
Abstract
Neurodegenerative diseases (NDDs) causing cognitive impairment and dementia are difficult to treat due to the lack of understanding of primary initiating factors. Meanwhile, major sporadic NDDs share many risk factors and exhibit similar pathologies in their early stages, indicating the existence of common initiation pathways. Glucose hypometabolism associated with oxidative stress is one such primary, early and shared pathology, and a likely major cause of detrimental disease-associated cascades; targeting this common pathology may therefore be an effective preventative strategy for most sporadic NDDs. However, its exact cause and trigger remain unclear. Recent research suggests that early oxidative stress caused by NADPH oxidase (NOX) activation is a shared initiating mechanism among major sporadic NDDs and could prove to be the long-sought ubiquitous NDD trigger. We focus on two major NDDs - Alzheimer's disease (AD) and Parkinson's disease (PD), as well as on acquired epilepsy which is an increasingly recognized comorbidity in NDDs. We also discuss available data suggesting the relevance of the proposed mechanisms to other NDDs. We delve into the commonalities among these NDDs in neuroinflammation and NOX involvement to identify potential therapeutic targets and gain a deeper understanding of the underlying causes of NDDs.
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Affiliation(s)
- Yuri Zilberter
- Aix-Marseille Université, INSERM UMR1106, Institut de Neurosciences des Systèmes, Marseille, France
| | - Dennis R Tabuena
- Gladstone Institute of Neurological Disease, San Francisco, CA, USA
| | - Misha Zilberter
- Gladstone Institute of Neurological Disease, San Francisco, CA, USA.
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Mantovani E, Zucchella C, Argyriou AA, Tamburin S. Treatment for cognitive and neuropsychiatric non-motor symptoms in Parkinson's disease: current evidence and future perspectives. Expert Rev Neurother 2023; 23:25-43. [PMID: 36701529 DOI: 10.1080/14737175.2023.2173576] [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] [Indexed: 01/27/2023]
Abstract
INTRODUCTION Non-motor symptoms (NMS) affect patients with Parkinson's disease (PD) from the prodromal to the advanced stages. NMS phenotypes greatly vary and have a huge impact on patients' and caregivers' quality of life (QoL). The management of cognitive and neuropsychiatric NMS remains an unmet need. AREAS COVERED The authors, herein, review the dopaminergic and non-dopaminergic pathogenesis, clinical features, assessment, and pharmacological and non-pharmacological treatments of cognitive and neuropsychiatric NMS in PD. They discuss the current evidence and report the findings of an overview of ongoing trials on pharmacological and selected non-pharmacological strategies. EXPERT OPINION The treatment of cognitive and neuropsychiatric NMS in PD is poorly explored, and therapeutic options are unsatisfactory. Pharmacological treatment of cognitive NMS is based on symptomatic active principles used in Alzheimer's disease. Dopamine agonists, selective serotonin, and serotonin-norepinephrine reuptake inhibitors have some evidence on PD-related depression. Clozapine, quetiapine, and pimavanserin may be considered for psychosis in PD. Evidence on the treatment of other neuropsychiatric NMS is limited or lacking. Addressing pathophysiological and clinical issues, which hamper solid evidence on the treatment of cognitive and neuropsychiatric NMS, may reduce the impact on QoL for PD patients and their caregivers.
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Affiliation(s)
- Elisa Mantovani
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Chiara Zucchella
- Section of Neurology, Department of Neurosciences, Verona University Hospital, Verona, Italy
| | - Andreas A Argyriou
- Department of Neurology, "Agios Andreas" State General Hospital of Patras, Patras, Greece
| | - Stefano Tamburin
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
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Suo X, Lei D, Li N, Peng J, Chen C, Li W, Qin K, Kemp GJ, Peng R, Gong Q. Brain functional network abnormalities in parkinson's disease with mild cognitive impairment. Cereb Cortex 2022; 32:4857-4868. [PMID: 35078209 PMCID: PMC9923713 DOI: 10.1093/cercor/bhab520] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 12/18/2021] [Accepted: 12/19/2021] [Indexed: 11/13/2022] Open
Abstract
Mild cognitive impairment in Parkinson's disease (PD-M) is related to a high risk of dementia. This study explored the whole-brain functional networks in early-stage PD-M. Forty-one patients with PD classified as cognitively normal (PD-N, n = 17) and PD-M (n = 24) and 24 demographically matched healthy controls (HC) underwent clinical and neuropsychological evaluations and resting-state functional magnetic resonance imaging. The global, regional, and modular topological characteristics were assessed in the brain functional networks, and their relationships to cognitive scores were tested. At the global level, PD-M and PD-N exhibited higher characteristic path length and lower clustering coefficient, local and global efficiency relative to HC. At the regional level, PD-M and PD-N showed lower nodal centrality in sensorimotor regions relative to HC. At the modular level, PD-M showed lower intramodular connectivity in default mode and cerebellum modules, and lower intermodular connectivity between default mode and frontoparietal modules than PD-N, correlated with Montreal Cognitive Assessment scores. Early-stage PD patients showed weaker small-worldization of brain networks. Modular connectivity alterations were mainly observed in patients with PD-M. These findings highlight the shared and distinct brain functional network dysfunctions in PD-M and PD-N, and yield insight into the neurobiology of cognitive decline in PD.
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Affiliation(s)
- Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH 45227, USA
| | - Nannan Li
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Jiaxin Peng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Chaolan Chen
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L69 3GE, UK
| | - Rong Peng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China.,Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian 361022, China
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He L, Zhang F, Zhu Y, Lu M. A crosstalk between circular RNA, microRNA, and messenger RNA in the development of various brain cognitive disorders. Front Mol Neurosci 2022; 15:960657. [PMID: 36329693 PMCID: PMC9622787 DOI: 10.3389/fnmol.2022.960657] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 07/28/2022] [Indexed: 11/23/2022] Open
Abstract
Patients with Alzheimer's disease (AD), Parkinson's disease (PD), traumatic brain injury (TBI), stroke, and postoperative neurocognitive disorder (POND) are commonly faced with neurocognitive disorders with limited therapeutic options. Some non-coding ribonucleic acids (ncRNAs) are involved in the development of various brain cognitive disorders. Circular RNAs (circRNAs), a typical group of ncRNAs, can function as competitive endogenous RNAs (ceRNAs) to dysregulate shared microRNAs (miRNAs) at post-transcription level, inhibiting regulation of miRNAs on their targeted messenger RNAs (mRNAs). circRNAs are abundant in central nervous system (CNS) diseases and cause brain disorders, but the exact roles of circRNAs are unclear. The crosstalk between circRNA, miRNA, and mRNA plays an important role in the pathogenesis of these neurocognitive dysfunction diseases and abnormal conditions including AD, PD, stroke, TBI, and POND. In this review, we summarized the participation of circRNA in neuroglial damage and inflammation. Finally, we aimed to highlight the regulatory mechanisms of circRNA–miRNA–mRNA networks in the development of various brain cognitive disorders and provide new insights into the therapeutics of these diseases.
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Affiliation(s)
- Liang He
- Department of Anesthesiology, Yan'an Hospital of Kunming City, Kunming Medical University, Kunming, China
- *Correspondence: Liang He
| | - Furong Zhang
- Department of Anesthesiology, Yan'an Hospital of Kunming City, Kunming Medical University, Kunming, China
| | - Yuling Zhu
- Department of Anesthesiology, Yan'an Hospital of Kunming City, Kunming Medical University, Kunming, China
| | - Meilin Lu
- Department of Anesthesiology, The First Affiliated Hospital of Kunming Medical University, Kunming, China
- Meilin Lu
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Morphological basis of Parkinson disease-associated cognitive impairment: an update. J Neural Transm (Vienna) 2022; 129:977-999. [PMID: 35726096 DOI: 10.1007/s00702-022-02522-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 05/25/2022] [Indexed: 12/15/2022]
Abstract
Cognitive impairment is one of the most salient non-motor symptoms of Parkinson disease (PD) that poses a significant burden on the patients and carers as well as being a risk factor for early mortality. People with PD show a wide spectrum of cognitive dysfunctions ranging from subjective cognitive decline and mild cognitive impairment (MCI) to frank dementia. The mean frequency of PD with MCI (PD-MCI) is 25.8% and the pooled dementia frequency is 26.3% increasing up to 83% 20 years after diagnosis. A better understanding of the underlying pathological processes will aid in directing disease-specific treatment. Modern neuroimaging studies revealed considerable changes in gray and white matter in PD patients with cognitive impairment, cortical atrophy, hypometabolism, dopamine/cholinergic or other neurotransmitter dysfunction and increased amyloid burden, but multiple mechanism are likely involved. Combined analysis of imaging and fluid markers is the most promising method for identifying PD-MCI and Parkinson disease dementia (PDD). Morphological substrates are a combination of Lewy- and Alzheimer-associated and other concomitant pathologies with aggregation of α-synuclein, amyloid, tau and other pathological proteins in cortical and subcortical regions causing destruction of essential neuronal networks. Significant pathological heterogeneity within PD-MCI reflects deficits in various cognitive domains. This review highlights the essential neuroimaging data and neuropathological changes in PD with cognitive impairment, the amount and topographical distribution of pathological protein aggregates and their pathophysiological relevance. Large-scale clinicopathological correlative studies are warranted to further elucidate the exact neuropathological correlates of cognitive impairment in PD and related synucleinopathies as a basis for early diagnosis and future disease-modifying therapies.
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Garon M, Weis L, Fiorenzato E, Pistonesi F, Cagnin A, Bertoldo A, Anglani M, Cecchin D, Antonini A, Biundo R. Quantification of Brain β-Amyloid Load in Parkinson's Disease With Mild Cognitive Impairment: A PET/MRI Study. Front Neurol 2022; 12:760518. [PMID: 35300351 PMCID: PMC8921107 DOI: 10.3389/fneur.2021.760518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 12/24/2021] [Indexed: 11/13/2022] Open
Abstract
Background Mild cognitive impairment in Parkinson's disease (PD-MCI) is associated with faster cognitive decline and conversion to dementia. There is uncertainty about the role of β-amyloid (Aβ) co-pathology and its contribution to the variability in PD-MCI profile and cognitive progression. Objective To study how presence of Aβ affects clinical and cognitive manifestations as well as regional brain volumes in PD-MCI. Methods Twenty-five PD-MCI patients underwent simultaneous PET/3T-MRI with [18F]flutemetamol and a clinical and neuropsychological examination allowing level II diagnosis. We tested pairwise differences in motor, clinical, and cognitive features with Mann–Whitney U test. We calculated [18F]flutemetamol (FMM) standardized uptake value ratios (SUVR) in striatal and cortical ROIs, and we performed a univariate linear regression analysis between the affected cognitive domains and the mean SUVR. Finally, we investigated differences in cortical and subcortical brain regional volumes with magnetic resonance imaging (MRI). Results There were 8 Aβ+ and 17 Aβ- PD-MCI. They did not differ for age, disease duration, clinical, motor, behavioral, and global cognition scores. PD-MCI-Aβ+ showed worse performance in the overall executive domain (p = 0.037). Subcortical ROIs analysis showed significant Aβ deposition in PD-MCI-Aβ+ patients in the right caudal and rostral middle frontal cortex, in precuneus, in left paracentral and pars triangularis (p < 0.0001), and bilaterally in the putamen (p = 0.038). Cortical regions with higher amyloid load correlated with worse executive performances (p < 0.05). Voxel-based morphometry (VBM) analyses showed no between groups differences. Conclusions Presence of cerebral Aβ worsens executive functions, but not motor and global cognitive abilities in PD-MCI, and it is not associated with middle-temporal cortex atrophy. These findings, together with the observation of significant proportion of PD-MCI-Aβ-, suggest that Aβ may not be the main pathogenetic determinant of cognitive deterioration in PD-MCI, but it would rather aggravate deficits in domains vulnerable to Parkinson primary pathology.
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Affiliation(s)
- Michela Garon
- Parkinson and Movement Disorders Unit, Department of Neuroscience, University of Padua, Padua, Italy
| | - Luca Weis
- Parkinson and Movement Disorders Unit, Department of Neuroscience, University of Padua, Padua, Italy
| | | | - Francesca Pistonesi
- Parkinson and Movement Disorders Unit, Department of Neuroscience, University of Padua, Padua, Italy
| | - Annachiara Cagnin
- Department of Neuroscience, University of Padua, Padua, Italy.,Padova Neuroscience Center, University of Padua, Padua, Italy
| | - Alessandra Bertoldo
- Padova Neuroscience Center, University of Padua, Padua, Italy.,Department of Information Engineering, University of Padua, Padua, Italy
| | | | - Diego Cecchin
- Padova Neuroscience Center, University of Padua, Padua, Italy.,Nuclear Medicine Unit, Department of Medicine - DIMED, Padua University Hospital, Padua, Italy
| | - Angelo Antonini
- Parkinson and Movement Disorders Unit, Department of Neuroscience, University of Padua, Padua, Italy.,Padova Neuroscience Center, University of Padua, Padua, Italy.,Study Center for Neurodegeneration, University of Padua, Padua, Italy
| | - Roberta Biundo
- Department of General Psychology, University of Padua, Padua, Italy.,Study Center for Neurodegeneration, University of Padua, Padua, Italy
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Kang SH, Chung SJ, Lee J, Koh SB. Independent effect of neurogenic orthostatic hypotension on mild cognitive impairment in Parkinson's disease. Clin Auton Res 2021; 32:43-50. [PMID: 34841452 DOI: 10.1007/s10286-021-00841-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 11/18/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE Orthostatic hypotension (OH) is an associative or causative factor of cognitive impairment in Parkinson's disease (PD). However, the association between mild cognitive impairment (MCI) and neurogenic OH directly associated with the presence of alpha-synuclein in PD remains unclear. We aimed to evaluate the relationship between MCI and neurogenic OH in patients with de novo PD. We also investigated the patterns of neuropsychological performance according to neurogenic OH. METHODS A total of 456 patients with PD-normal cognition (PD-NC, n = 204) or PD-MCI (n = 252) were recruited from multiple centers in Korea. All patients underwent comprehensive neuropsychological tests and tilt-table tests to evaluate cognitive function and neurogenic OH. We used logistic regression analysis and multivariate analysis of covariance to determine the association between MCI and neurogenic OH and the pattern of neuropsychological performance according to neurogenic OH. RESULTS Neurogenic OH (odds ratio = 3.66, 95% confidence interval 2.06 to 6.47) was independently associated with MCI in patients with de novo PD, regardless of orthostatic symptoms, while nonneurogenic OH was not. Patients with PD with neurogenic OH exhibited worse performance in frontal-executive function and visual memory function than those without neurogenic OH. CONCLUSION Our findings provide insight into neurogenic OH as an important clinical factor with cognitive impairment in individuals with PD and vice versa. Therefore, the evaluation of cognitive function is necessary in PD patients with neurogenic OH.
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Affiliation(s)
- Sung Hoon Kang
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Korea
| | - Su Jin Chung
- Department of Neurology, Myongji Hospital, Hanyang University College of Medicine, Goyang, Korea
| | - Jungyeun Lee
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Korea.
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12
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Sivaranjini S, Sujatha CM. Morphological analysis of subcortical structures for assessment of cognitive dysfunction in Parkinson's disease using multi-atlas based segmentation. Cogn Neurodyn 2021; 15:835-845. [PMID: 34603545 PMCID: PMC8448821 DOI: 10.1007/s11571-021-09671-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 01/27/2021] [Accepted: 02/25/2021] [Indexed: 12/16/2022] Open
Abstract
Cognitive impairment in Parkinson's Disease (PD) is the most prevalent non-motor symptom that requires analysis of anatomical associations to cognitive decline in PD. The objective of this study is to analyse the morphological variations of the subcortical structures to assess cognitive dysfunction in PD. In this study, T1 MR images of 58 Healthy Control (HC) and 135 PD subjects categorised as 91 Cognitively normal PD (NC-PD), 25 PD with Mild Cognitive Impairment (PD-MCI) and 19 PD with Dementia (PD-D) subjects, based on cognitive scores are utilised. The 132 anatomical regions are segmented using spatially localized multi-atlas model and volumetric analysis is carried out. The morphological alterations through textural features are captured to differentiate among the HC and PD subjects under different cognitive domains. The volumetric differences in the segmented subcortical structures of accumbens, amygdala, caudate, putamen and thalamus are able to predict cognitive impairment in PD. The volumetric distribution of the subcortical structures in PD-MCI subjects exhibit an overlap with the HC group due to lack of spatial specificity in their atrophy levels. The 3D GLCM features extracted from the significant subcortical structures could discriminate HC, NC-PD, PD-MCI and PD-D subjects with better classification accuracies. The disease related atrophy levels of the subcortical structures captured through morphological analysis provide sensitive evaluation of cognitive impairment in PD.
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Affiliation(s)
- S. Sivaranjini
- Department of Electronics and Communication Engineering, College of Engineering (CEG), Anna University, Chennai, India
| | - C. M. Sujatha
- Department of Electronics and Communication Engineering, College of Engineering (CEG), Anna University, Chennai, India
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13
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Brain age and Alzheimer's-like atrophy are domain-specific predictors of cognitive impairment in Parkinson's disease. Neurobiol Aging 2021; 109:31-42. [PMID: 34649002 DOI: 10.1016/j.neurobiolaging.2021.08.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 08/27/2021] [Accepted: 08/31/2021] [Indexed: 11/20/2022]
Abstract
Recently, it was shown that patients with Parkinson's disease (PD) who exhibit an "Alzheimer's disease (AD)-like" pattern of brain atrophy are at greater risk for future cognitive decline. This study aimed to investigate whether this association is domain-specific and whether atrophy associated with brain aging also relates to cognitive impairment in PD. SPARE-AD, an MRI index capturing AD-like atrophy, and atrophy-based estimates of brain age were computed from longitudinal structural imaging data of 178 PD patients and 84 healthy subjects from the LANDSCAPE cohort. All patients underwent an extensive neuropsychological test battery. Patients diagnosed with mild cognitive impairment or dementia were found to have higher SPARE-AD scores as compared to patients with normal cognition and healthy controls. All patient groups showed increased brain age. SPARE-AD predicted impairment in memory, language and executive functions, whereas advanced brain age was associated with deficits in attention and working memory. Data suggest that SPARE-AD and brain age are differentially related to domain-specific cognitive decline in PD. The underlying pathomechanisms remain to be determined.
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14
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Suo X, Lei D, Li N, Li J, Peng J, Li W, Yang J, Qin K, Kemp GJ, Peng R, Gong Q. Topologically convergent and divergent morphological gray matter networks in early-stage Parkinson's disease with and without mild cognitive impairment. Hum Brain Mapp 2021; 42:5101-5112. [PMID: 34322939 PMCID: PMC8449106 DOI: 10.1002/hbm.25606] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 06/07/2021] [Accepted: 06/26/2021] [Indexed: 02/05/2023] Open
Abstract
Patients with Parkinson's disease with mild cognitive impairment (PD‐M) progress to dementia more frequently than those with normal cognition (PD‐N), but the underlying neurobiology remains unclear. This study aimed to define the specific morphological brain network alterations in PD‐M, and explore their potential diagnostic value. Twenty‐four PD‐M patients, 17 PD‐N patients, and 29 healthy controls (HC) underwent a structural MRI scan. Similarity between interregional gray matter volume distributions was used to construct individual morphological brain networks. These were analyzed using graph theory and network‐based statistics (NBS), and their relationship to neuropsychological tests was assessed. Support vector machine (SVM) was used to perform individual classification. Globally, compared with HC, PD‐M showed increased local efficiency (p = .001) in their morphological networks, while PD‐N showed decreased normalized path length (p = .008). Locally, similar nodal deficits were found in the rectus and lingual gyrus, and cerebellum of both PD groups relative to HC; additionally in PD‐M nodal deficits involved several frontal and parietal regions, correlated with cognitive scores. NBS found that similar connections were involved in the default mode and cerebellar networks of both PD groups (to a greater extent in PD‐M), while PD‐M, but not PD‐N, showed altered connections involving the frontoparietal network. Using connections identified by NBS, SVM allowed discrimination with high accuracy between PD‐N and HC (90%), PD‐M and HC (85%), and between the two PD groups (65%). These results suggest that default mode and cerebellar disruption characterizes PD, more so in PD‐M, whereas frontoparietal disruption has diagnostic potential.
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Affiliation(s)
- Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Du Lei
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China.,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio, USA
| | - Nannan Li
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Junying Li
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Jiaxin Peng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Jing Yang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
| | - Rong Peng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
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15
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Liu H, Deng B, Xie F, Yang X, Xie Z, Chen Y, Yang Z, Huang X, Zhu S, Wang Q. The influence of white matter hyperintensity on cognitive impairment in Parkinson's disease. Ann Clin Transl Neurol 2021; 8:1917-1934. [PMID: 34310081 PMCID: PMC8419402 DOI: 10.1002/acn3.51429] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/05/2021] [Accepted: 07/02/2021] [Indexed: 01/11/2023] Open
Abstract
The aim of this meta‐analysis was to review systematically and to identify the relationship between the severity and location of white matter hyperintensities (WMHs) and the degree of cognitive decline in patients with Parkinson’s disease (PD). We searched the PubMed, EMBASE, Web of Science, Ovid, and Cochrane Library databases for clinical trials of the severity and location of WMHs on the degree of cognitive impairment in PD through October 2020. We conducted the survey to compare the association of WMH burden in patients with PD with mild cognitive impairment (PD‐MCI) versus those with normal cognition (PD‐NC) and in patients with PD with dementia (PDD) versus those with PD without dementia (PD‐ND). Nine studies with PD‐MCI versus PD‐NC and 10 studies with PDD versus PD‐ND comparisons were included. The WMH burden in PD‐MCI patients was significantly different compared to that in PD‐NC patients (standard mean difference, SMD = 0.39, 95% CI: 0.12 to 0.66, p = 0.005), while there was no correlation shown in the age‐matched subgroup of the comparison. In addition, PDD patients had a significantly higher burden of WMHs (SMD = 0.8, 95% CI: 0.44 to 1.71, p < 0.0001), especially deep white matter hyperintensities (SMD = 0.54, 95% CI: 0.36 to 0.73, p < 0.00001) and periventricular hyperintensities (SMD = 0.70, 95% CI: 0.36 to 1.04, p < 0.0001), than PD‐NC patients, regardless of the adjustment of age. WMHs might be imaging markers for cognitive impairment in PDD but not in PD‐MCI, regardless of age, vascular risk factors, or race. Further prospective studies are needed to validate the conclusions.
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Affiliation(s)
- Hailing Liu
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China.,Department of Neurology, Maoming People's Hospital, Maoming, Guangdong, China
| | - Bin Deng
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Fen Xie
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Xiaohua Yang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Zhenchao Xie
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Yonghua Chen
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Zhi Yang
- Department of Neurology, Maoming People's Hospital, Maoming, Guangdong, China
| | - Xiyan Huang
- Department of Rehabilitation, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Shuzhen Zhu
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Qing Wang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
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16
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Laansma MA, Bright JK, Al-Bachari S, Anderson TJ, Ard T, Assogna F, Baquero KA, Berendse HW, Blair J, Cendes F, Dalrymple-Alford JC, de Bie RMA, Debove I, Dirkx MF, Druzgal J, Emsley HCA, Garraux G, Guimarães RP, Gutman BA, Helmich RC, Klein JC, Mackay CE, McMillan CT, Melzer TR, Parkes LM, Piras F, Pitcher TL, Poston KL, Rango M, Ribeiro LF, Rocha CS, Rummel C, Santos LSR, Schmidt R, Schwingenschuh P, Spalletta G, Squarcina L, van den Heuvel OA, Vriend C, Wang JJ, Weintraub D, Wiest R, Yasuda CL, Jahanshad N, Thompson PM, van der Werf YD. International Multicenter Analysis of Brain Structure Across Clinical Stages of Parkinson's Disease. Mov Disord 2021; 36:2583-2594. [PMID: 34288137 PMCID: PMC8595579 DOI: 10.1002/mds.28706] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 06/07/2021] [Accepted: 06/09/2021] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Brain structure abnormalities throughout the course of Parkinson's disease have yet to be fully elucidated. OBJECTIVE Using a multicenter approach and harmonized analysis methods, we aimed to shed light on Parkinson's disease stage-specific profiles of pathology, as suggested by in vivo neuroimaging. METHODS Individual brain MRI and clinical data from 2357 Parkinson's disease patients and 1182 healthy controls were collected from 19 sources. We analyzed regional cortical thickness, cortical surface area, and subcortical volume using mixed-effects models. Patients grouped according to Hoehn and Yahr stage were compared with age- and sex-matched controls. Within the patient sample, we investigated associations with Montreal Cognitive Assessment score. RESULTS Overall, patients showed a thinner cortex in 38 of 68 regions compared with controls (dmax = -0.20, dmin = -0.09). The bilateral putamen (dleft = -0.14, dright = -0.14) and left amygdala (d = -0.13) were smaller in patients, whereas the left thalamus was larger (d = 0.13). Analysis of staging demonstrated an initial presentation of thinner occipital, parietal, and temporal cortices, extending toward rostrally located cortical regions with increased disease severity. From stage 2 and onward, the bilateral putamen and amygdala were consistently smaller with larger differences denoting each increment. Poorer cognition was associated with widespread cortical thinning and lower volumes of core limbic structures. CONCLUSIONS Our findings offer robust and novel imaging signatures that are generally incremental across but in certain regions specific to disease stages. Our findings highlight the importance of adequately powered multicenter collaborations.
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Affiliation(s)
- Max A Laansma
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Joanna K Bright
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Sarah Al-Bachari
- Faculty of Health and Medicine, The University of Lancaster, Lancaster, UK.,Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.,Department of Neurology, Royal Preston Hospital, Preston, UK
| | - Tim J Anderson
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
| | - Tyler Ard
- Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, California, USA
| | - Francesca Assogna
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | | | - Henk W Berendse
- Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jamie Blair
- Department of Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Fernando Cendes
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, Brazil
| | - John C Dalrymple-Alford
- New Zealand Brain Research Institute, Christchurch, New Zealand.,School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand.,Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, Auckland, New Zealand
| | - Rob M A de Bie
- Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Ines Debove
- Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Michiel F Dirkx
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.,Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Jason Druzgal
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, Virginia, USA
| | - Hedley C A Emsley
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.,Lancaster Medical School, Lancaster University, Preston, UK
| | - Gäetan Garraux
- GIGA-CRC In Vivo Imaging, University of Liège, Liège, Belgium.,Department of Neurology, CHU Liège, Liège, Belgium
| | - Rachel P Guimarães
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, Brazil
| | - Boris A Gutman
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA
| | - Rick C Helmich
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.,Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Johannes C Klein
- Department of Clinical Neurosciences, Division of Clinical Neurology, Oxford Parkinson's Disease Centre, Nuffield, University of Oxford, Oxford, UK
| | - Clare E Mackay
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Corey T McMillan
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Tracy R Melzer
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand.,New Zealand Brain Research Institute, Christchurch, New Zealand.,Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, Auckland, New Zealand
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Toni L Pitcher
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand.,New Zealand Brain Research Institute, Christchurch, New Zealand.,Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, Auckland, New Zealand
| | - Kathleen L Poston
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | - Mario Rango
- Excellence Center for Advanced MR Techniques and Parkinson's Disease Center, Neurology Unit, Fondazione IRCCS Cà Granda Maggiore Policlinico Hospital, University of Milan, Milan, Italy
| | - Letícia F Ribeiro
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, Brazil
| | - Cristiane S Rocha
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, Brazil.,Department of Medical Genetics, University of Campinas, Campinas, Brazil
| | - Christian Rummel
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Lucas S R Santos
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, Brazil
| | - Reinhold Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | | | | | - Letizia Squarcina
- Excellence Center for Advanced MR Techniques and Parkinson's Disease Center, Neurology Unit, Fondazione IRCCS Cà Granda Maggiore Policlinico Hospital, University of Milan, Milan, Italy
| | - Odile A van den Heuvel
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Chris Vriend
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jiun-Jie Wang
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan City, Taiwan.,Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Keelung Branch, Keelung City, Taiwan
| | - Daniel Weintraub
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Clarissa L Yasuda
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, Brazil
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Ysbrand D van der Werf
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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17
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Wang E, Jia Y, Ya Y, Xu J, Mao C, Luo W, Fan G, Jiang Z. Patterns of Sulcal depth and cortical thickness in Parkinson's disease. Brain Imaging Behav 2021; 15:2340-2346. [PMID: 34018166 DOI: 10.1007/s11682-020-00428-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2020] [Indexed: 10/21/2022]
Abstract
Previous voxel-based morphometry (VBM) and cortical thickness (CT) studies on Parkinson's disease (PD) have mainly reported the gray matter size reduction, whereas the shape of cortical surface can also change in PD patients. For the first time, we analyzed sulcal depth (SD) patterns in PD patients by using whole brain region of interest (ROI)-based approach. In a cross-sectional study, high-resolution brain structural MRI images were collected from 60 PD patients without dementia and 56 age-and sex-matched healthy controls (HC). SD and CT were estimated using the Computational Anatomy Toolbox (CAT12) and statistically compared between groups on whole brain ROI-based level using statistical parametric mapping 12 (SPM12). Additionally, correlations between regional brain changes and clinical variables were also examined. Compared to HC, PD patients showed lower SD in widespread regions, including temporal (the bilateral transverse temporal, the left inferior temporal, the right middle temporal and the right superior temporal), insular (the left insula), frontal (the left pars triangularis, the left pars opercularis and the left precentral), parietal (the bilateral superior parietal) and occipital (the right cuneus) regions. For CT, only the left pars opercularis showed lower CT in PD patients compared to HC. No regions showed higher SD or CT in PD patients compared to HC. In PD patients, a significant positive correlation was found between SD of the left pars opercularis and MMSE scores, such that lower MMSE scores were related to lower SD of the left pars opercularis. Our results of widespread lower SD, but relatively localized lower CT, indicate that SD seems to be more sensitive to brain changes than CT and may be mainly affected by white matter damage. Hence, SD may be a more promising indicator to investigate the surface shape changes in PD patients. The significant positive correlation between SD of the left pars opercularis and MMSE scores suggests that SD may be prognostic of future cognitive decline.
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Affiliation(s)
- Erlei Wang
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yujing Jia
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yang Ya
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jin Xu
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Chengjie Mao
- Department of Neurology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Weifeng Luo
- Department of Neurology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Guohua Fan
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
| | - Zhen Jiang
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
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18
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Beyond Alzheimer's disease: Can bilingualism be a more generalized protective factor in neurodegeneration? Neuropsychologia 2020; 147:107593. [PMID: 32882240 DOI: 10.1016/j.neuropsychologia.2020.107593] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Revised: 07/10/2020] [Accepted: 08/26/2020] [Indexed: 01/18/2023]
Abstract
Bilingualism has been argued to have an impact on cognition and brain structure. Effects have been reported across the lifespan: from healthy children to ageing adults, including clinical (ageing) populations. It has been argued that active bilingualism may significantly contribute to the delaying of the expression of Alzheimer's disease symptoms. If bilingualism plays an ameliorative role against the expression of neurodegeneration in dementia, it is possible that it could have similar effects for other neurodegenerative disorders, including Multiple Sclerosis, Parkinson's and Huntington's Diseases. To date, however, direct relevant evidence remains limited, not least because the necessary scientific motivations for investigating this with greater depth have not yet been fully articulated. Herein, we provide a roadmap that reviews the relevant literatures, highlighting potential links across neurodegenerative disorders and bilingualism more generally.
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19
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Carrasco L, Pisa D, Alonso R. Polymicrobial Infections and Neurodegenerative Diseases. CURRENT CLINICAL MICROBIOLOGY REPORTS 2020. [DOI: 10.1007/s40588-020-00139-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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20
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Cognition Deficits in Parkinson's Disease: Mechanisms and Treatment. PARKINSONS DISEASE 2020; 2020:2076942. [PMID: 32269747 PMCID: PMC7128056 DOI: 10.1155/2020/2076942] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 02/08/2020] [Accepted: 02/26/2020] [Indexed: 12/22/2022]
Abstract
Parkinson's disease (PD) is the second most common progressive neurodegenerative disorder mainly in middle-elderly population, which represents diverse nonmotor symptoms (NMS) besides such well-documented motor symptoms as bradykinesia, resting tremor, rigidity, and postural instability. With the advancement of aging trend worldwide, the global prevalence of PD is mounting up year after year. Nowadays, accumulating lines of studies have given a comprehensive and thorough coverage of motor symptoms in PD. Yet much less attention as compared has been paid to the nonmotor symptoms of PD, such as cognition deficits. Of note, a patient with PD who suffers from cognitive impairment may harbour a statistically significantly higher risk of progressing toward dementia, which negatively affects their life expectancy and daily functioning and overall lowers the global quality of life. Furthermore, it is a widely held view that cognitive dysfunction does not just occur in the late stage of PD. On the basis of numerous studies, mild cognitive impairment (MCI) is a harbinger of dementia in PD, which is observed as an intermediate state with considerable variability; some patients remain stable and some even revert to normal cognition. Considered that the timing, profile, and rate of cognitive impairment vary greatly among PD individuals, it is extremely urgent for researchers and clinicians alike to identify and predict future cognitive decline in this population. Simultaneously, early screening and canonical management of PD with cognitive deficits are very imperative to postpone the disease progression and improve the prognosis of patients. In our review, we focus on a description of cognitive decline in PD, expound emphatically the pathological mechanisms underlying cognition deficits in PD, then give a comprehensive overview of specific therapeutic strategies, and finally dissect what fresh insights may bring new exciting prospect for the subfield.
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21
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Pisa D, Alonso R, Carrasco L. Parkinson's Disease: A Comprehensive Analysis of Fungi and Bacteria in Brain Tissue. Int J Biol Sci 2020; 16:1135-1152. [PMID: 32174790 PMCID: PMC7053320 DOI: 10.7150/ijbs.42257] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Accepted: 11/22/2019] [Indexed: 12/21/2022] Open
Abstract
Parkinson's disease (PD) is characterized by motor disorders and the destruction of dopaminergic neurons in the substantia nigra pars compacta. In addition to motor disability, many patients with PD present a spectrum of clinical symptoms, including cognitive decline, psychiatric alterations, loss of smell and bladder dysfunction, among others. Neuroinflammation is one of the most salient features of PD, but the nature of the trigger remains unknown. A plausible mechanism to explain inflammation and the range of clinical symptoms in these patients is the presence of systemic microbial infection. Accordingly, the present study provides extensive evidence for the existence of mixed microbial infections in the central nervous system (CNS) of patients with PD. Assessment of CNS sections by immunohistochemistry using specific antibodies revealed the presence of both fungi and bacteria. Moreover, different regions of the CNS were positive for a variety of microbial morphologies, suggesting infection by a number of microorganisms. Identification of specific fungal and bacterial species in different CNS regions from six PD patients was accomplished using nested PCR analysis and next-generation sequencing, providing compelling evidence of polymicrobial infections in the CNS of PD. Most of the fungal species identified belong to the genera Botrytis, Candida, Fusarium and Malassezia. Some relevant bacterial genera were Streptococcus and Pseudomonas, with most bacterial species belonging to the phyla Actinobacteria and Proteobacteria. Interestingly, we noted similarities and differences between the microbiota present in the CNS of patients with PD and that in other neurodegenerative diseases. Overall, our observations lend strong support to the concept that mixed microbial infections contribute to or are a risk factor for the neuropathology of PD. Importantly, these results provide the basis for effective treatments of this disease using already approved and safe antimicrobial therapeutics.
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Affiliation(s)
| | | | - Luis Carrasco
- Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM). c/Nicolás Cabrera, 1. Universidad Autónoma de Madrid. Cantoblanco. 28049 Madrid. Spain
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22
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Jellinger KA. Neuropathology and pathogenesis of extrapyramidal movement disorders: a critical update-I. Hypokinetic-rigid movement disorders. J Neural Transm (Vienna) 2019; 126:933-995. [PMID: 31214855 DOI: 10.1007/s00702-019-02028-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 06/05/2019] [Indexed: 02/06/2023]
Abstract
Extrapyramidal movement disorders include hypokinetic rigid and hyperkinetic or mixed forms, most of them originating from dysfunction of the basal ganglia (BG) and their information circuits. The functional anatomy of the BG, the cortico-BG-thalamocortical, and BG-cerebellar circuit connections are briefly reviewed. Pathophysiologic classification of extrapyramidal movement disorder mechanisms distinguish (1) parkinsonian syndromes, (2) chorea and related syndromes, (3) dystonias, (4) myoclonic syndromes, (5) ballism, (6) tics, and (7) tremor syndromes. Recent genetic and molecular-biologic classifications distinguish (1) synucleinopathies (Parkinson's disease, dementia with Lewy bodies, Parkinson's disease-dementia, and multiple system atrophy); (2) tauopathies (progressive supranuclear palsy, corticobasal degeneration, FTLD-17; Guamian Parkinson-dementia; Pick's disease, and others); (3) polyglutamine disorders (Huntington's disease and related disorders); (4) pantothenate kinase-associated neurodegeneration; (5) Wilson's disease; and (6) other hereditary neurodegenerations without hitherto detected genetic or specific markers. The diversity of phenotypes is related to the deposition of pathologic proteins in distinct cell populations, causing neurodegeneration due to genetic and environmental factors, but there is frequent overlap between various disorders. Their etiopathogenesis is still poorly understood, but is suggested to result from an interaction between genetic and environmental factors. Multiple etiologies and noxious factors (protein mishandling, mitochondrial dysfunction, oxidative stress, excitotoxicity, energy failure, and chronic neuroinflammation) are more likely than a single factor. Current clinical consensus criteria have increased the diagnostic accuracy of most neurodegenerative movement disorders, but for their definite diagnosis, histopathological confirmation is required. We present a timely overview of the neuropathology and pathogenesis of the major extrapyramidal movement disorders in two parts, the first one dedicated to hypokinetic-rigid forms and the second to hyperkinetic disorders.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, 1150, Vienna, Austria.
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