1
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Hamad AA, Amer BE, Hawas Y, Mabrouk MA, Meshref M. Masitinib as a neuroprotective agent: a scoping review of preclinical and clinical evidence. Neurol Sci 2024; 45:1861-1873. [PMID: 38105307 PMCID: PMC11021265 DOI: 10.1007/s10072-023-07259-w] [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: 10/18/2023] [Accepted: 12/08/2023] [Indexed: 12/19/2023]
Abstract
OBJECTIVES Masitinib, originally developed as a tyrosine kinase inhibitor for cancer treatment, has shown potential neuroprotective effects in various neurological disorders by modulating key pathways implicated in neurodegeneration. This scoping review aimed to summarize the current evidence of masitinib's neuroprotective activities from preclinical to clinical studies. METHODS This scoping review was conducted following the guidelines described by Arksey and O'Malley and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The inclusion criteria covered all original studies reporting on the neuroprotective effects of masitinib, including clinical studies, animal studies, and in vitro studies. RESULTS A total of 16 studies met the inclusion criteria and were included in the review. These comprised five randomized controlled trials (RCTs), one post-hoc analysis study, one case report, and nine animal studies. The RCTs focused on Alzheimer's disease (two studies), multiple sclerosis (two studies), and amyotrophic lateral sclerosis (one study). Across all included studies, masitinib consistently demonstrated neuroprotective properties. However, the majority of RCTs reported concerns regarding the safety profile of masitinib. Preclinical studies revealed the neuroprotective mechanisms of masitinib, which include inhibition of certain kinases interfering with cell proliferation and survival, reduction of neuroinflammation, and exhibition of antioxidant activity. CONCLUSION The current evidence suggests a promising therapeutic benefit of masitinib in neurodegenerative diseases. However, further research is necessary to validate and expand upon these findings, particularly regarding the precise mechanisms through which masitinib exerts its therapeutic effects. Future studies should also focus on addressing the safety concerns associated with masitinib use.
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Affiliation(s)
| | | | - Yousef Hawas
- Faculty of Medicine, Tanta University, Tanta, Egypt
| | - Manar Alaa Mabrouk
- Faculty of Medicine, Fayoum University, Fayoum, Egypt
- Medical Research Group of Egypt, Negida Academy, Arlington, MA, USA
| | - Mostafa Meshref
- Department of Neurology, Faculty of Medicine, Al-Azhar University, Cairo, Egypt
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2
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Chen Q, Zhou T, Zhang C, Zhong X. Exploring relevant factors of cognitive impairment in the elderly Chinese population using Lasso regression and Bayesian networks. Heliyon 2024; 10:e27069. [PMID: 38449590 PMCID: PMC10915566 DOI: 10.1016/j.heliyon.2024.e27069] [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: 08/23/2023] [Revised: 02/12/2024] [Accepted: 02/23/2024] [Indexed: 03/08/2024] Open
Abstract
Older adults are highly susceptible to developing cognitive impairment(CI). Various factors contribute to the prevalence of CI, but the potential relationships among these factors remain unclear. This study aims to explore the relevant factors associated with CI in Chinese older adults and analyze the potential relationships between CI and these factors.We analyzed the data on 6886 older adults aged≥60 from the China Health and Retirement Longitudinal Study (CHARLS) 2018. Lasso regression was initially used to screening variables. Bayesian Networks(BNs) were used to identify the correlates of CI and potential associations between factors. After screening with Lasso regression, 11 variables were finally included in the BNs. The BNs, by establishing a complex network relationship, revealed that age, education, and indoor air pollution were the direct correlates affecting the occurrence of CI in older adults. It also indicated that marital status indirectly influenced CI through age, and residence indirectly linked to CI through two pathways: indoor air pollution and education.Our findings underscore the effectiveness of BNs in unveiling the intricate network linkages among CI and its associated factors, holding promising applications. It can serve as a reference for public health departments to address the prevention of CI in the elderly.
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Affiliation(s)
- Qiao Chen
- College of Public Health, Chongqing Medical University, Chongqing, 400016, China
- Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing, China
| | - Tianyi Zhou
- College of Public Health, Chongqing Medical University, Chongqing, 400016, China
| | - Cong Zhang
- College of Public Health, Chongqing Medical University, Chongqing, 400016, China
| | - Xiaoni Zhong
- College of Public Health, Chongqing Medical University, Chongqing, 400016, China
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3
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Mizutani Y, Ohdake R, Tatebe H, Higashi A, Shima S, Ueda A, Ito M, Tokuda T, Watanabe H. Associations of Alzheimer's-related plasma biomarkers with cognitive decline in Parkinson's disease. J Neurol 2023; 270:5461-5474. [PMID: 37480401 PMCID: PMC10576723 DOI: 10.1007/s00415-023-11875-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Revised: 07/10/2023] [Accepted: 07/11/2023] [Indexed: 07/24/2023]
Abstract
BACKGROUND Parkinson's disease (PD) is associated with cognitive decline through multiple mechanisms, including Alzheimer's disease (AD) pathology and cortical Lewy body involvement. However, its underlying mechanisms remain unclear. Recently, AD-related plasma biomarkers have emerged as potential tools for predicting abnormal pathological protein accumulation. We aimed to investigate the association between AD-related plasma biomarkers and cognitive decline in PD patients. METHODS Plasma biomarkers were measured in 70 PD patients (49 with nondemented Parkinson's disease (PDND) and 21 with Parkinson's disease dementia (PDD)) and 38 healthy controls (HCs) using a single-molecule array. The study evaluated (1) the correlation between plasma biomarkers and clinical parameters, (2) receiver operating characteristic curves and areas under the curve to evaluate the discrimination capacity of plasma biomarkers among groups, and (3) a generalized linear model to analyze associations with Addenbrooke's Cognitive Examination-Revised and Montreal Cognitive Assessment-Japanese version scores. RESULTS Plasma glial fibrillary acidic protein significantly correlated with cognitive function tests, including all subdomains, with a notable increase in the PDD group compared with the HC and PDND groups, while plasma neurofilament light chain captured both cognitive decline and disease severity in the PDND and PDD groups. Plasma beta-amyloid 42/40 and pholphorylated-tau181 indicated AD pathology in the PDD group, but plasma beta-amyloid 42/40 was increased in the PDND group compared with HCs and decreased in the PDD group compared with the PDND group. CONCLUSIONS AD-related plasma biomarkers may predict cognitive decline in PD and uncover underlying mechanisms suggesting astrocytic pathologies related to cognitive decline in PD.
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Affiliation(s)
- Yasuaki Mizutani
- Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakugo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan
| | - Reiko Ohdake
- Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakugo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan
| | - Harutsugu Tatebe
- Department of Functional Brain Imaging, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Chiba, Japan
| | - Atsuhiro Higashi
- Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakugo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan
| | - Sayuri Shima
- Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakugo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan
| | - Akihiro Ueda
- Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakugo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan
| | - Mizuki Ito
- Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakugo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan
| | - Takahiko Tokuda
- Department of Functional Brain Imaging, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Chiba, Japan
| | - Hirohisa Watanabe
- Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakugo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan.
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4
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Li XY, Chen MJ, Liang XN, Yao RX, Shen B, Wu B, Li G, Sun YM, Wu JJ, Liu FT, Yang YJ, Wang J. PDQ-8: A Simplified and Effective Tool Measuring Life Quality in Progressive Supranuclear Palsy. JOURNAL OF PARKINSON'S DISEASE 2023; 13:83-91. [PMID: 36591660 PMCID: PMC9912724 DOI: 10.3233/jpd-223553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
BACKGROUND The self-reported quality of life (QoL) should be carefully listened to in progressive supranuclear palsy (PSP) from the patient-centered perspective. However, there was still a lack of short QoL measurement tool in atypical parkinsonism. OBJECTIVE We aimed to test whether the short Parkinson's Disease Questionnaire-8 (PDQ-8) was effective in assessing QoL in PSP, comparing with Progressive Supranuclear Palsy Quality of Life Scale (PSP-QoL) and Parkinson's Disease Questionnaire-39 (PDQ-39). METHODS 132 patients with clinical diagnosed PSP, including PSP-Richardson syndrome (RS) subtype (n = 71) and PSP-non-RS subtype (n = 61) were recruited for clinical evaluation including QoL assessment. The detailed QoL profiles and possibility of using PDQ-8 were systemically analyzed. The determinants to the QoL were then calculated by multivariate linear regression analysis. RESULTS The PSP-QoL total score summary index (SI) was 22.8 (10.1, 41.1), while the PDQ-8 and PDQ-39 total SI score were 28.1 (12.5, 46.9) and 29.5 (15.4, 49.4). Mobility, activities of daily life, cognition and communication were the main affected QoL subdomains (median SI: 40.0, 31.3, 25.0 and 25.0 respectively). PSP-RS subtype showed more severe damage physically (p<0.001) and mentally (p = 0.002) compared to other subtypes. More importantly, the strong relevance of PDQ-8 and recommended PSP QoL tools were confirmed (p<0.001). In addition, disease severity, depression and daytime sleepiness were proved to be critical determinants for QoL in PSP. CONCLUSIONS PDQ-8 could be an easy, reliable, and valid tool to evaluate QoL in patients with PSP. Besides motor symptoms, more attention should be paid to non-motor impairment such as depression in PSP.
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Affiliation(s)
- Xin-Yi Li
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Ming-Jia Chen
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiao-Niu Liang
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China,Institute of Neurology, Fudan University, Shanghai, China
| | - Rui-Xin Yao
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Bo Shen
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Bin Wu
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Gen Li
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Yi-Min Sun
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jian-Jun Wu
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Feng-Tao Liu
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Yu-Jie Yang
- Key Laboratory of Arrhythmias, Ministry of Education, Department of Medical Genetics, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China,Correspondence to: Prof Jian Wang, Department of Neurology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China. Tel.: +86 13321934789; E-mail: and Dr. Yu-Jie Yang, Key Laboratory of Arrhythmias, Ministry of Education, Department of Medical Genetics, Shanghai East Hospital, School of Medicine, Tonji University, Shanghai, China. Tel.: +86 13917793964; E-mail:
| | - Jian Wang
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China,Correspondence to: Prof Jian Wang, Department of Neurology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China. Tel.: +86 13321934789; E-mail: and Dr. Yu-Jie Yang, Key Laboratory of Arrhythmias, Ministry of Education, Department of Medical Genetics, Shanghai East Hospital, School of Medicine, Tonji University, Shanghai, China. Tel.: +86 13917793964; E-mail:
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5
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Sanchez-Luengos I, Lucas-Jiménez O, Ojeda N, Peña J, Gómez-Esteban JC, Gómez-Beldarrain MÁ, Vázquez-Picón R, Foncea-Beti N, Ibarretxe-Bilbao N. Predictors of health-related quality of life in Parkinson's disease: the impact of overlap between health-related quality of life and clinical measures. Qual Life Res 2022; 31:3241-3252. [PMID: 35842497 PMCID: PMC9546987 DOI: 10.1007/s11136-022-03187-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/28/2022] [Indexed: 12/01/2022]
Abstract
PURPOSE This study aimed to determine predictors of health-related quality of life (HRQoL) in Parkinson's disease (PD) and to explore their predictive value before and after controlling overlapping items between HRQoL and clinical variables. METHODS One hundred and eight PD patients underwent motor, anxiety, depression, apathy, fatigue, and neurocognition assessment. HRQoL was assessed by the Parkinson's Disease Questionnaire-39 (PDQ-39). In order to determine predictors of HRQoL in PD, stepwise multiple regression analyses were performed in two ways: before and after removing the emotional well-being dimension from PDQ-39 to control the overlap between depression and anxiety, and HRQoL. RESULTS HRQoL total index was predicted by anxiety, fatigue, motor symptoms, and depression, explaining 26.9%, 7.2%, 2.8%, and 1.9% of the variance. However, after removing overlapping items, HRQoL total index was predicted by fatigue (16.5%), anxiety (6.1%), motor symptoms (3.9%), and neurocognition (2.5%), but not depression. Regarding HRQoL dimensions, mobility and activities of daily living were predicted by fatigue (19.7% and 5%) and UPDRS-III (4% and 10.2%); emotional well-being by fatigue (7.9%); social support by anxiety (12.2%) and UPDRS-III (8.6%); communication by neurocognition (5.3%) and UPDRS-III (3.4%); cognition by anxiety (10.6%) and bodily discomfort by anxiety (23%) and fatigue (4.1%). CONCLUSION These findings showed the importance of identifying and controlling overlapping items of HRQoL and clinical measures to perform an accurate interpretation. HRQoL dimensions showed different predictors before and after controlling the overlap. Based on these results fatigue, anxiety, motor symptoms, and neurocognition, but not depression are the main predictors of HRQoL in PD patients.
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Affiliation(s)
| | - Olaia Lucas-Jiménez
- Department of Psychology, Faculty of Health Sciences, University of Deusto, Bilbao, Spain
| | - Natalia Ojeda
- Department of Psychology, Faculty of Health Sciences, University of Deusto, Bilbao, Spain
| | - Javier Peña
- Department of Psychology, Faculty of Health Sciences, University of Deusto, Bilbao, Spain
| | | | | | | | - Nerea Foncea-Beti
- Department of Neurology, Hospital of Galdakao, Galdakao-Usansolo, Spain
| | - Naroa Ibarretxe-Bilbao
- Department of Psychology, Faculty of Health Sciences, University of Deusto, Bilbao, Spain
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6
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Meng D, Jin Z, Chen K, Yu X, Wang Y, Du W, Wei J, Xi J, Fang B. Quality of life predicts rehabilitation prognosis in Parkinson's disease patients: Factors influence rehabilitation prognosis: Factors influence rehabilitation prognosis. Brain Behav 2022; 12:e2579. [PMID: 35429406 PMCID: PMC9120870 DOI: 10.1002/brb3.2579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 02/14/2022] [Accepted: 03/20/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Rehabilitation has been reported to improve the quality of life (QoL) of patients with Parkinson's disease (PD). Nevertheless, not all patients are satisfied with rehabilitation outcomes and could achieve a significant improvement in QoL. OBJECTIVE To detect possible predictors of QoL improvement in patients with PD after rehabilitation. METHODS A total of 86 PD patients were included and followed up for 3 months with a 39-item Parkinson's Disease Questionnaire summary index (PDQ-39 SI) as the primary endpoint. All patients received 2 weeks of multidisciplinary intensive rehabilitation treatment (MIRT). Changes in patients' QoL were assessed using the PDQ-39 at baseline and at the 3-month follow-up. The reliable change index (RCI) was adapted to determine the individual QoL outcome. The predictors of QoL outcome were detected using logistic regression analysis. RESULTS After a 3-month follow-up, PDQ-39 SI decreased significantly from 22.95 ± 9.75 to 18.73 ± 10.32 (P < 0.001). Scores for QoL improved (RCI>10.9) after rehabilitation for 18.6% of the patients, and 74.4% of patients reported an unchanged QoL (-10.9≤RCI≤10.9), while 7.0% of patients reported a worsening of QoL (RCI<-10.9). Among the baseline parameters, the PDQ-39 SI was a baseline predictor for changes in QoL in the logistic regression model (OR: 1.15, CI: 1.07-1.24, P < 0.001). CONCLUSIONS MIRT could improve QoL for some patients with PD, and PDQ-39 score at baseline is the most important predictor for QoL improvements after rehabilitation for this patients.
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Affiliation(s)
- Detao Meng
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Zhaohui Jin
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Keke Chen
- Beijing Rehabilitation Medical College, Capital Medical University, Beijing, China
| | - Xin Yu
- Beijing Rehabilitation Medical College, Capital Medical University, Beijing, China
| | - Yixuan Wang
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Wenjun Du
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Jingran Wei
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Jianing Xi
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Boyan Fang
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
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7
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Holden HM, Schweer CN, Tröster AI. Impact of Mild Cognitive Impairment on Quality of Life in Young and Typical Onset Parkinson's Disease. Mov Disord Clin Pract 2022; 9:69-75. [PMID: 35005067 DOI: 10.1002/mdc3.13353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 09/15/2021] [Accepted: 09/30/2021] [Indexed: 11/09/2022] Open
Abstract
Introduction Younger age of onset and mild cognitive impairment (MCI) are both independently associated with poorer quality of life (QOL) in Parkinson's disease (PD). Objectives The primary objective was to determine whether MCI differentially impacts QOL in young-onset PD (YOPD) and typical-onset PD (TOPD). Methods YOPD patients (n = 77) were diagnosed at age 50 or younger, TOPD (n = 77) were diagnosed after age 50, and the groups were matched for cognitive status, education, and disease duration. Patients' cognitive status was classified as MCI or cognitively normal (CN) based on MDS Level II criteria. QOL was assessed using the Parkinson's Disease Questionnaire (PDQ-39). ANCOVAs were conducted for each PDQ-39 subscale, with age of onset and cognitive status as between-subjects factors and several covariates included. Results An interaction for the Cognition domain revealed that in TOPD, PD-MCI patients reported poorer QOL than CN patients, whereas there was no effect of MCI on cognitive satisfaction in YOPD. There was a main effect of age on Emotional Well-Being, as YOPD reported poorer QOL than TOPD in this domain. There were main effects of cognitive status, with PD-MCI patients reporting worse QOL than CN patients in the domains of Social Support, Communication, ADLs, and Mobility. Conclusions The interaction revealed that PD-MCI has a greater impact on degree of cognitive concerns ("cognitive QOL") in TOPD versus YOPD. A more nuanced understanding of the effects of age of onset, MCI, and their interactions on QOL in PD will inform interventions aimed at improving quality of life in this population.
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Affiliation(s)
- Heather M Holden
- Department of Clinical Neuropsychology Barrow Neurological Institute Phoenix Arizona USA
| | - Corrin N Schweer
- Department of Clinical Neuropsychology Barrow Neurological Institute Phoenix Arizona USA
| | - Alexander I Tröster
- Department of Clinical Neuropsychology Barrow Neurological Institute Phoenix Arizona USA
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8
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Wang L, Zhou C, Cheng W, Rolls ET, Huang P, Ma N, Liu Y, Zhang Y, Guan X, Guo T, Wu J, Gao T, Xuan M, Gu Q, Xu X, Zhang B, Gong W, Du J, Zhang W, Feng J, Zhang M. Dopamine depletion and subcortical dysfunction disrupt cortical synchronization and metastability affecting cognitive function in Parkinson's disease. Hum Brain Mapp 2021; 43:1598-1610. [PMID: 34904766 PMCID: PMC8886656 DOI: 10.1002/hbm.25745] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/28/2021] [Accepted: 11/29/2021] [Indexed: 12/14/2022] Open
Abstract
Parkinson's disease (PD) is primarily characterized by the loss of dopaminergic cells and atrophy in subcortical regions. However, the impact of these pathological changes on large-scale dynamic integration and segregation of the cortex are not well understood. In this study, we investigated the effect of subcortical dysfunction on cortical dynamics and cognition in PD. Spatiotemporal dynamics of the phase interactions of resting-state blood-oxygen-level-dependent signals in 159 PD patients and 152 normal control (NC) individuals were estimated. The relationships between subcortical atrophy, subcortical-cortical fiber connectivity impairment, cortical synchronization/metastability, and cognitive performance were then assessed. We found that cortical synchronization and metastability in PD patients were significantly decreased. To examine whether this is an effect of dopamine depletion, we investigated 45 PD patients both ON and OFF dopamine replacement therapy, and found that cortical synchronization and metastability are significantly increased in the ON state. The extent of cortical synchronization and metastability in the OFF state reflected cognitive performance and mediates the difference in cognitive performance between the PD and NC groups. Furthermore, both the thalamic volume and thalamocortical fiber connectivity had positive relationships with cortical synchronization and metastability in the dopaminergic OFF state, and mediate the difference in cortical synchronization between the PD and NC groups. In addition, thalamic volume also reflected cognitive performance, and cortical synchronization/metastability mediated the relationship between thalamic volume and cognitive performance in PD patients. Together, these results highlight that subcortical dysfunction and reduced dopamine levels are responsible for decreased cortical synchronization and metastability, further affecting cognitive performance in PD. This might lead to biomarkers being identified that can predict if a patient is at risk of developing dementia.
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Affiliation(s)
- Linbo Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Cheng Zhou
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China.,Department of Computer Science, University of Warwick, Coventry, UK
| | - Edmund T Rolls
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China.,Department of Computer Science, University of Warwick, Coventry, UK
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ningning Ma
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Yuchen Liu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Yajuan Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tao Guo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jingjing Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ting Gao
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Min Xuan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Quanquan Gu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Baorong Zhang
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Weikang Gong
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Jingnan Du
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China.,Department of Computer Science, University of Warwick, Coventry, UK
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Che NN, Jiang QH, Ding GX, Chen SY, Zhao ZX, Li X, Malik RA, Ma JJ, Yang HQ. Corneal nerve fiber loss relates to cognitive impairment in patients with Parkinson’s disease. NPJ Parkinsons Dis 2021; 7:80. [PMID: 34504084 PMCID: PMC8429586 DOI: 10.1038/s41531-021-00225-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 08/10/2021] [Indexed: 11/27/2022] Open
Abstract
Cognitive impairment in Parkinson’s disease (PD) adversely influences quality of life. There is currently no available biomarker to predict cognitive decline in PD. Corneal confocal microscopy (CCM) has been used as a non-invasive tool for quantifying small nerve damage in PD. The present study investigated whether corneal nerve measures were associated with cognitive function in PD. Patients with PD were classified into those with normal cognitive function (PD-CN), mild cognitive impairment (PD-MCI), and dementia (PDD). Corneal nerve fiber density (CNFD), corneal nerve branch density (CNBD), and corneal nerve fiber length (CNFL) were quantified with CCM and compared with a control group. Sixty-five PD patients and thirty controls were studied. CNFD was decreased and CNBD was increased in PD patients compared to controls (P < 0.05). CNBD and CNBD/CNFD ratio was higher in PD-CN compared to controls. CNFD was positively correlated with the Montreal cognitive assessment (MoCA) score (r = 0.683, P < 0.001), but negatively associated with unified Parkinson disease rating scale (UPDRS)-part III (r = −0.481, P < 0.001) and total UPDRS scores (r = −0.401, P = 0.001) in PD patients. There was no correlation between CNFD and Levodopa equivalent daily dose (LEDD) (r = 0.176, P = 0.161). CNFD, CNBD, CNFL, and CNBD/CNFD ratio was lower with increasing Hoehn and Yahr stage. PD patients show evidence of corneal nerve loss compared with controls and corneal nerve parameters are associated with the severity of cognitive and motor dysfunction in PD. CCM could serve as an objective in vivo ophthalmic imaging technique to assess neurodegeneration in PD.
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Zhou XY, Lu JY, Liu FT, Wu P, Zhao J, Ju ZZ, Tang YL, Shi QY, Lin HM, Wu JJ, Yen TC, Zuo CT, Sun YM, Wang J. In Vivo 18 F-APN-1607 Tau Positron Emission Tomography Imaging in MAPT Mutations: Cross-Sectional and Longitudinal Findings. Mov Disord 2021; 37:525-534. [PMID: 34842301 DOI: 10.1002/mds.28867] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 11/01/2021] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Frontotemporal lobar degeneration with tauopathy caused by MAPT (microtubule-associated protein tau) mutations is a highly heterogenous disorder. The ability to visualize and longitudinally monitor tau deposits may be beneficial to understand disease pathophysiology and predict clinical trajectories. OBJECTIVE The aim of this study was to investigate the cross-sectional and longitudinal 18 F-APN-1607 positron emission tomography/computed tomography (PET/CT) imaging findings in MAPT mutation carriers. METHODS Seven carriers of MAPT mutations (six within exon 10 and one outside of exon 10) and 15 healthy control subjects were included. All participants underwent 18 F-APN-1607 PET/CT at baseline. Three carriers of exon 10 mutations received follow-up 18 F-APN-1607 PET/CT scans. Standardized uptake value ratio (SUVR) maps were obtained using the cerebellar gray matter as the reference region. SUVR values observed in MAPT mutation carriers were normalized to data from healthy control subjects. A regional SUVR z score ≥ 2 was used as the criterion to define positive 18 F-APN-1607 PET/CT findings. RESULTS Although the seven study patients had heterogenous clinical phenotypes, all showed a significant 18 F-APN-1607 uptake characterized by high-contrast signals. However, the anatomical localization of tau deposits differed in patients with distinct clinical symptoms. Follow-up imaging data, which were available for three patients, demonstrated worsening trends in patterns of tau accumulation over time, which were paralleled by a significant clinical deterioration. CONCLUSIONS Our data represent a promising step in understanding the usefulness of 18 F-APN-1607 PET/CT imaging for detecting tau accumulation in MAPT mutation carriers. Our preliminary follow-up data also suggest the potential value of 18 F-APN-1607 PET/CT for monitoring the longitudinal trajectories of frontotemporal lobar degeneration caused by MAPT mutations. © 2021 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Xin-Yue Zhou
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jia-Ying Lu
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Feng-Tao Liu
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Ping Wu
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jue Zhao
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Zi-Zhao Ju
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Yi-Lin Tang
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Qing-Yi Shi
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Hua-Mei Lin
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jian-Jun Wu
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | | | - Chuan-Tao Zuo
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Yi-Min Sun
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jian Wang
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
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Han LL, Wang L, Xu ZH, Liang XN, Zhang MW, Fan Y, Sun YM, Liu FT, Yu WB, Tang YL. Disease progression in Parkinson's disease patients with subjective cognitive complaint. Ann Clin Transl Neurol 2021; 8:2096-2104. [PMID: 34595848 PMCID: PMC8528458 DOI: 10.1002/acn3.51461] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 09/03/2021] [Accepted: 09/09/2021] [Indexed: 12/05/2022] Open
Abstract
Objective Little is known about the disease progression of Parkinson's disease patients with subjective cognitive complaint (PD‐SCC). This longitudinal cohort study aims to compare the progression of clinical features and quality of life (QoL) in PD patients with normal cognition (NC), SCC, and mild cognitive impairment (MCI). Methods A total of 383 PD patients were enrolled, including 189 PD‐NC patients, 59 PD‐SCC patients, and 135 PD‐MCI patients, with 1–7 years of follow‐up. Linear mixed models were applied to evaluate longitudinal changes in motor symptoms, nonmotor features (cognitive impairment, depression, and excessive daytime sleepiness), and QoL in PD. Results At baseline, PD‐SCC patients had lower Beck Depression Inventory (BDI) scores and Parkinson's Disease Questionnaire‐39 (PDQ‐39) scores than PD‐NC patients (all p < 0.05). Longitudinal analyses revealed that the PD‐SCC group exhibited faster progression in terms of BDI scores (p = 0.042) and PDQ‐39 scores (p = 0.035) than the PD‐NC group. The PD‐MCI group exhibited faster progression rates in the Epworth Sleepiness Scale scores (p = 0.001) and PDQ‐39 scores (p = 0.005) than the PD‐NC group. In addition, the PD‐SCC group exhibited a greater reduction in attention (Trail Making Test Part A, p = 0.047) and executive function (Stroop Color‐Word Test, p = 0.037) than the PD‐NC group. Interpretation PD‐SCC patients exhibited faster deterioration of depression and QoL than PD‐NC patients, and SCC may be an indicator of initial attention and executive function decline in PD. Our findings provided a more accurate prognosis in PD‐SCC patients.
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Affiliation(s)
- Lin-Lin Han
- Department of Neurology and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Lan Wang
- Department of Neurology, Drum Tower Hospital, Nanjing, 210008, China
| | - Zhi-Heng Xu
- Department of Neurology and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Xiao-Niu Liang
- Department of Neurology and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Meng-Wei Zhang
- Department of Neurology and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Yun Fan
- Department of Neurology and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Yi-Min Sun
- Department of Neurology and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Feng-Tao Liu
- Department of Neurology and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Wen-Bo Yu
- Department of Neurology and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Yi-Lin Tang
- Department of Neurology and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China
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