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Purks JL, Arbatti L, Hosamath A, Amara AW, Anderson KE, Chahine L, Eberly SW, Kinel D, Mantri S, Mathur S, Oakes D, Standaert DG, Weintraub D, Shoulson I, Marras C. Cognitive Symptoms in Cross-Sectional Parkinson Disease Cohort Evaluated by Human-in-the-Loop Machine Learning and Natural Language Processing. Neurol Clin Pract 2024; 14:e200334. [PMID: 38962394 PMCID: PMC11221914 DOI: 10.1212/cpj.0000000000200334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 04/12/2024] [Indexed: 07/05/2024]
Abstract
Background and Objectives Cognitive impairment is experienced by up to 80% of people with Parkinson disease (PD). Little is known regarding the subjective experience and frequency of bothersome cognitive problems across the range of disease duration as expressed directly in patients' own words. We describe the types and frequency of bothersome cognitive symptoms reported verbatim by patients with PD. Methods Through the online Fox Insight study and the Parkinson Disease Patient Report of Problems, we asked patients with PD to self-report by keyboard entry up to five most bothersome problems and how these problems affect their functioning. Human-in-the-loop curation, natural language processing, and machine learning were used to categorize responses into 8 cognitive symptoms: memory, concentration/attention, cognitive slowing, language/word finding, mental alertness/awareness, visuospatial abilities, executive abilities/working memory, and cognitive impairment not otherwise specified. Associations between cognitive symptoms and demographic and disease-related variables were examined in our cross-sectional cohort using multivariate logistic regression. Results Among 25,192 participants (55% men) of median age 67 years and 3 years since diagnosis (YSD), 8,001 (32%) reported a cognitive symptom at baseline. The 3 most frequently reported symptoms were memory (13%), language/word finding (12%), and concentration/attention (9%). Depression was significantly associated with bothersome cognitive problems in all domains except visuospatial abilities. Predictors of reporting any cognitive symptom in PD were depression (adjusted OR 1.5), increasing MDS-UPDRS Part II score (OR 1.4 per 10-point increment), higher education (OR 1.2 per year), and YSD 1, 2, 6-7, and 8-9 vs 0 YSD. Among individuals with at least one cognitive symptom, posterior cortical-related cognitive symptoms (i.e., visuospatial, memory, and language) were reported by 17% (n = 4325), frontostriatal-related symptoms (i.e., executive abilities, concentration/attention) by 7% (n = 1,827), and both by 14.2% (n = 1,020). Odds of reporting posterior cortical symptoms vs frontostriatal symptoms increased with age and MDS-UPDRS part II score, but not depression. Discussion Nearly one-third of participants with PD, even early in the disease course, report cognitive symptoms as among their most bothersome problems. Online verbatim reporting analyzed by human-in-the-loop curation, natural language processing, and machine learning is feasible on a large scale and allows a detailed examination of the nature and distribution of cognitive symptoms in PD.
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Affiliation(s)
- Jennifer L Purks
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - Lakshmi Arbatti
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - Abhishek Hosamath
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - Amy W Amara
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - Karen E Anderson
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - Lana Chahine
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - Shirley W Eberly
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - Daniel Kinel
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - Sneha Mantri
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - Soania Mathur
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - David Oakes
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - David G Standaert
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - Daniel Weintraub
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - Ira Shoulson
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
| | - Connie Marras
- Department of Neurology (JLP, DK, IS), University of Rochester, NY; Grey Matter Technologies (LA, AH, IS), a wholly owned subsidiary of Modality.ai, San Francisco, CA; Department of Neurology (AWA), University of Colorado Anschutz Medical Campus, Aurora; Departments of Psychiatry and Neurology (KEA), Georgetown University, Washington, DC; Department of Neurology (LC), University of Pittsburgh, PA; Department of Biostatistics and Computational Biology (SWE, DO), University of Rochester, NY; Department of Neurology (Sneha Mantri), Duke University, Durham, NC; PD Avengers (Soania Mathur), Toronto, Ontario, Canada; Department of Neurology (DGS), University of Alabama at Birmingham; Departments of Psychiatry and Neurology (DW), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; and Edmond J Safra Program in Parkinson's Disease (CM), University Health Network, University of Toronto, Ontario, Canada
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Xue X, Mei S, Huang A, Wu Z, Zeng J, Song H, An J, Zhang L, Liu G, Zhou L, Cai Y, Xu B, Xu E, Chan P. Alzheimer's Disease Related Biomarkers Were Associated with Amnestic Cognitive Impairment in Parkinson's Disease: A Cross-Sectional Cohort Study. Brain Sci 2024; 14:787. [PMID: 39199480 PMCID: PMC11352303 DOI: 10.3390/brainsci14080787] [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: 06/09/2024] [Revised: 07/05/2024] [Accepted: 07/16/2024] [Indexed: 09/01/2024] Open
Abstract
BACKGROUND Cognitive impairment is common in patients with Parkinson's disease (PD) and occurs through multiple mechanisms, including Alzheimer's disease (AD) pathology and the involvement of α-synucleinopathies. We aimed to investigate the pathological biomarkers of both PD and AD in plasma and neuronal extracellular vesicles (EVs) and their association with different types of cognitive impairment in PD patients. METHODS A total of 122 patients with PD and 30 healthy controls were included in this cross-sectional cohort study between March 2021 and July 2023. Non-dementia PD patients were divided into amnestic and non-amnestic groups according to the memory domain of a neuropsychological assessment. Plasma and neuronal EV biomarkers, including α-synuclein (α-syn), beta-amyloid (Aβ), total tau (T-tau), phosphorylated tau181 (p-tau181), and glial fibrillary acidic protein (GFAP), were measured using a single-molecule array and a chemiluminescence immunoassay, respectively. RESULTS Neuronal EV but not plasma α-syn levels, were significantly increased in PD as compared to healthy controls, and they were positively associated with UPDRS part III scores and the severity of cognitive impairment. A lower plasma Aβ42 level and higher neuronal EV T-tau level were found in the amnestic PD group compared to the non-amnestic PD group. CONCLUSIONS The results of the current study demonstrate that neuronal EV α-syn levels can be a sensitive biomarker for assisting in the diagnosis and disease severity prediction of PD. Both AD and PD pathologies are important factors in cognitive impairment associated with PD, and AD pathologies are more involved in amnestic memory deficit in PD.
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Affiliation(s)
- Xiaofan Xue
- Department of Neurology and Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China; (X.X.); (S.M.); (A.H.); (Z.W.); (J.Z.); (B.X.); (E.X.)
- Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100043, China;
| | - Shanshan Mei
- Department of Neurology and Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China; (X.X.); (S.M.); (A.H.); (Z.W.); (J.Z.); (B.X.); (E.X.)
| | - Anqi Huang
- Department of Neurology and Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China; (X.X.); (S.M.); (A.H.); (Z.W.); (J.Z.); (B.X.); (E.X.)
| | - Zhiyue Wu
- Department of Neurology and Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China; (X.X.); (S.M.); (A.H.); (Z.W.); (J.Z.); (B.X.); (E.X.)
| | - Jingrong Zeng
- Department of Neurology and Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China; (X.X.); (S.M.); (A.H.); (Z.W.); (J.Z.); (B.X.); (E.X.)
| | - Haixia Song
- Department of Neurology, The People’s Hospital of Shijiazhuang, Shijiazhuang 050000, China;
| | - Jing An
- Department of Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China;
| | - Lijuan Zhang
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing 100053, China;
| | - Guozhen Liu
- Parkinson’s Disease Cloud Medical Technology Company, Beijing 100055, China;
| | - Lichun Zhou
- Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100043, China;
| | - Yanning Cai
- Department of Clinical Biobank and Central Laboratory, Xuanwu Hospital of Capital Medical University, Beijing 100053, China;
| | - Baolei Xu
- Department of Neurology and Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China; (X.X.); (S.M.); (A.H.); (Z.W.); (J.Z.); (B.X.); (E.X.)
| | - Erhe Xu
- Department of Neurology and Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China; (X.X.); (S.M.); (A.H.); (Z.W.); (J.Z.); (B.X.); (E.X.)
| | - Piu Chan
- Department of Neurology and Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China; (X.X.); (S.M.); (A.H.); (Z.W.); (J.Z.); (B.X.); (E.X.)
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Rao S, Cai Y, Zhong Z, Gou T, Wang Y, Liao S, Qiu P, Kuang W. Prevalence, cognitive characteristics, and influencing factors of amnestic mild cognitive impairment among older adults residing in an urban community in Chengdu, China. Front Neurol 2024; 15:1336385. [PMID: 38356893 PMCID: PMC10864602 DOI: 10.3389/fneur.2024.1336385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 01/16/2024] [Indexed: 02/16/2024] Open
Abstract
Objective Dementia is a significant public health concern, and mild cognitive impairment (MCI) serves as a transitional stage between normal aging and dementia. Among the various types of MCI, amnestic MCI (aMCI) has been identified as having a higher likelihood of progressing to Alzheimer's dimension. However, limited research has been conducted on the prevalence of aMCI in China. Therefore, the objective of this study is to investigate the prevalence of aMCI, examine its cognitive characteristics, and identify associated risk factors. Methods In this cross-sectional study, we investigated a sample of 368 older adults aged 60 years and above in the urban communities of Chengdu, China. The participants underwent a battery of neuropsychological assessments, including the Mini-Mental State Examination (MMSE), the Clinical Dementia Rating (CDR), Auditory Verbal Learning Test (AVLT), Wechsler's Logical Memory Task (LMT), Boston Naming Test (BNT) and Trail Making Test Part A (TMT-A). Social information was collected by standard questionnaire. Multiple logistic regression analysis was utilized to screen for the risk and protective factors of aMCI. Results The data analysis included 309 subjects with normal cognitive function and 59 with aMCI, resulting in a prevalence of 16.0% for aMCI. The average age of participants was 69.06 ± 7.30 years, with 56.0% being females. After controlling for age, gender and education, the Spearman partial correlation coefficient between various cognitive assessments and aMCI ranged from -0.52 for the long-term delayed recall scores in AVLT to 0.19 for the time-usage scores in TMT-A. The results indicated that all cognitive domains, except for naming scores (after semantic cue of BNT) and error quantity (in TMT-A), showed statistically significant associations with aMCI. Furthermore, the multiple logistic regression analysis revealed that older age (OR = 1.044, 95%CI: 1.002~1.087), lower educational level, and diabetes (OR = 2.450, 95%CI: 1.246~4.818) were risk factors of aMCI. Conclusion This study found a high prevalence of aMCI among older adults in Chengdu, China. Individuals with aMCI exhibited lower cognitive function in memory, language, and executive domains, with long-term delayed recall showing the strongest association. Clinicians should prioritize individuals with verbal learning and memory difficulties, especially long-term delayed recall, in clinical practice.
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Affiliation(s)
- Shan Rao
- Department of Psychiatry, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Chengdu Jinxin Mental Diseases Hospital, Chengdu, Sichuan, China
| | - Yan Cai
- Evidence-Based Nursing Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhujun Zhong
- Department of Epidemiology and Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China
| | - Tianyuan Gou
- Chengdu Jinxin Mental Diseases Hospital, Chengdu, Sichuan, China
| | - Yangyang Wang
- Department of Epidemiology and Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China
| | - Shiyi Liao
- Department of Epidemiology and Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China
| | - Peiyuan Qiu
- Department of Epidemiology and Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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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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Alissa N, Rehan R, Al-Sharman A, Latrous M, Aburub AS, El-Salem K, Morris L, Khalil H. Cognitive status and sleep quality can explain the fear of falling and fall history in people with Parkinson's disease. Int J Rehabil Res 2023; 46:338-343. [PMID: 37581294 DOI: 10.1097/mrr.0000000000000596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2023]
Abstract
Fear of falling (FOF) is highly prevalent in people with Parkinson's disease (PwPD) and contributes to high fall risk. Studies reporting on the relationship between falls, FOF, and non-motor factors such as cognitive function and sleep quality in Parkinson's disease are limited. This study aimed to investigate (1) the relationship of cognitive function and sleep quality with FOF, and history of falls in PwPD; (2) differences in cognitive function and sleep quality between Parkinson's disease fallers and non-fallers; and (3) a cut-off score for cognitive function and sleep quality to discriminate Parkinson's disease fallers from non-fallers. Fifty PwPD were assessed for FOF [Falls Efficacy Scale-International (FES-I)], cognition [Montréal Cognitive Assessment (MOCA)], sleep quality [Pittsburgh Sleep Quality Index (PSQI)], and falls history. The MOCA is significantly associated with FES-I scores ( R2 = 0.429, P < 0.0001). Both MOCA ( P = 0.012) and PSQI ( P = 0.027) were associated with falls history even after adjusting for confounding factors (age, sex, L-dopa use, Parkinson's disease severity). Both MOCA and PSQI scores were able to distinguish fallers from non-fallers with cut-off scores of 15.5 and 7.5, respectively. Although our findings revealed that both cognitive function and sleep quality are important factors influencing falls and FOF in PwPD, it remains to be determined if addressing cognitive impairments and poor sleep quality may favorably impact balance before integrating such screenings into fall prevention programs.
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Affiliation(s)
- Nesreen Alissa
- Department of Physical Therapy and Rehabilitation Science, School of Medicine, University of Maryland, Baltimore, Baltimore, Maryland, USA
| | - Reem Rehan
- Department of Rehabilitation Sciences, Faculty of Applied Medical Sciences, Jordan University of Science and Technology, Irbid, Jordan
| | - Alham Al-Sharman
- Department of Rehabilitation Sciences, Faculty of Applied Medical Sciences, Jordan University of Science and Technology, Irbid, Jordan
- Department of Physical Therapy, College of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates
| | - Mariem Latrous
- Department of Physical Therapy and Rehabilitation Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Ala' S Aburub
- Department of Rehabilitation Sciences, Faculty of Applied Medical Sciences, Jordan University of Science and Technology, Irbid, Jordan
- Department of Physiotherapy, Israa University, Amman
| | - Khalid El-Salem
- Department of Neurosciences, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan
| | - Linzette Morris
- Department of Physical Therapy and Rehabilitation Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Hanan Khalil
- Department of Physical Therapy and Rehabilitation Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
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Cao Z, Wu C, Hong H, Huang P, Zhou C, Guan X, Wu H, Duanmu X, Xu X, Zhang M. Predictability of inter-regional cerebral perfusion similarity on dopamine responsiveness and the moderation role of cognition in PD patients. Neuroimage 2023; 279:120305. [PMID: 37562719 DOI: 10.1016/j.neuroimage.2023.120305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 07/09/2023] [Accepted: 07/31/2023] [Indexed: 08/12/2023] Open
Abstract
BACKGROUND Large heterogeneity can be found in dopamine responsiveness of patients with Parkinson's disease (PD). Instantly and objectively understanding dopamine responsiveness of patients may help clinical practice. PURPOSE This PD study explored the predictability of off-state inter-regional cerebral blood flow (CBF) perfusion similarity on patient's dopamine responsiveness and tested whether the predictive power could be moderated by patient's cognitive status. MATERIALS AND METHOD The PD cohort with 192 patients (containing off state and on state (PD-off and PD-on)) and the normal control (NC) cohort with 92 subjects were included. The intra-individual CBF relative variation networks were constructed and compared between PD-off and PD-on, PD-off and NC to identify the alterations caused by dopamine depletion. Based on that, regression analysis of off-state inter-regional CBF perfusion similarity on patient's dopamine responsiveness was performed. Finally, moderation analysis was conducted to test the moderation role of cognition on the regression model. RESULTS In the PD-off cohort, a total of 82 edges in the network were identified that affected by dopamine depletion. Off-state inter-regional CBF perfusion similarity was found that had a significant influence on patient's dopamine responsiveness. Cognitive status was validated that positively moderated the relationship between off-state inter-regional CBF perfusion similarity and dopamine responsiveness. CONCLUSION Dopamine responsiveness of PD patient could be predicted by off-state inter-regional CBF perfusion similarity. Patient's cognitive status might have a positive moderation effect on his/her dopamine responsiveness.
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Affiliation(s)
- Zhengye Cao
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Chenqing Wu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Cheng Zhou
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Haoting Wu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Xiaojie Duanmu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.
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Yang J, Pourzinal D, Byrne GJ, McMahon KL, Copland DA, O'Sullivan JD, Mitchell L, Dissanayaka NN. Global assessment, cognitive profile, and characteristics of mild cognitive impairment in Parkinson's disease. Int J Geriatr Psychiatry 2023; 38:e5955. [PMID: 37318156 DOI: 10.1002/gps.5955] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 06/07/2023] [Indexed: 06/16/2023]
Abstract
BACKGROUND Cognitive deficits are evident throughout the course of Parkinson's disease (PD), with 24% of patients experiencing subtle cognitive disturbances at the time of diagnosis, and with up to 80% of patients developing PD dementia (PDD) at advanced stages of the disease PD patients with mild cognitive impairment (MCI), an at-risk phenotype of PDD, present with heterogeneous clinical characteristics that complicate the management of PD. OBJECTIVES This study aims to examine the characteristics of PD-MCI by using the Movement Disorder Society (MDS) diagnostic criteria and evaluate the validity of global cognitive scales in identifying PD-MCI. METHODS Seventy-nine (79) PD patients completed neuropsychological assessments and a comprehensive cognitive battery. PD-MCI was classified according to the level 2 MDS task force criteria. Mini-Mental State Examination (sMMSE), Montreal Cognitive Assessment (MoCA) and Parkinson's Disease Cognitive Rating Scale (PDCRS) were examined against a level 2 dichotomised PD-MCI diagnosis. Characteristics of PD-MCI were evaluated using logistic regression analysis. RESULTS Twenty-seven patients met criteria for PD-MCI (34%). The MoCA and PDCRS demonstrated high validity to screen for PD-MCI. Impairments in multiple cognitive domains were observed in 77.8% of PD-MCI patients. There were significantly more males in the PD-MCI group compared to PD patients without MCI (p < 0.01). CONCLUSIONS PD patients with MCI exhibited impairments in the attention/working memory, executive function and memory domains. Heterogeneous cognitive characteristics in PD warrant further investigation into specific cognitive subtypes to advance understanding and effective evaluation of PD-MCI.
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Affiliation(s)
- Jihyun Yang
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, Queensland, Australia
| | - Dana Pourzinal
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, Queensland, Australia
| | - Gerard J Byrne
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, Queensland, Australia
- Mental Health Service, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia
| | - Katie L McMahon
- School of Clinical Sciences, Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, Queensland, Australia
| | - David A Copland
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, Queensland, Australia
- School of Health & Rehabilitation Sciences, The University of Queensland, St Lucia, Queensland, Australia
| | - John D O'Sullivan
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, Queensland, Australia
- Department of Neurology, Royal Brisbane & Women's Hospital, Herston, Queensland, Australia
| | - Leander Mitchell
- School of Psychology, The University of Queensland, St Lucia, Queensland, Australia
| | - Nadeeka N Dissanayaka
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, Queensland, Australia
- Department of Neurology, Royal Brisbane & Women's Hospital, Herston, Queensland, Australia
- School of Psychology, The University of Queensland, St Lucia, Queensland, Australia
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8
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Yu RL, Wu RM. Mild cognitive impairment in patients with Parkinson’s disease: An updated mini-review and future outlook. Front Aging Neurosci 2022; 14:943438. [PMID: 36147702 PMCID: PMC9485585 DOI: 10.3389/fnagi.2022.943438] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 08/15/2022] [Indexed: 12/04/2022] Open
Abstract
Mild cognitive impairment (MCI) is one of the common non-motor symptoms in patients with Parkinson’s disease (PD). MCI is the transition stage between normal aging and full-blown dementia and is also a powerful predictor of dementia. Although the concept of MCI has been used to describe some of the PD symptoms for many years, there is a lack of consistent diagnostic criteria. Moreover, because of the diverse patterns of the cognitive functions, each cognitive impairment will have a different progression. In this review, we overviewed the diagnostic criteria for PD-MCI, primarily focused on the heterogeneity of PD-MCI patients’ cognitive function, including various types of cognitive functions and their progression rates. A review of this topic is expected to be beneficial for clinical diagnosis, early intervention, and treatment. In addition, we also discussed the unmet needs and future vision in this field.
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Affiliation(s)
- Rwei-Ling Yu
- College of Medicine, Institute of Behavioral Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Ruey-Meei Wu
- Department of Neurology, College of Medicine, National Taiwan University Hospital, National Taiwan University, Taipei, Taiwan
- *Correspondence: Ruey-Meei Wu,
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9
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Xu H, Gu L, Zhang S, Wu Y, Wei X, Wang C, Xu Y, Guo Y. N200 and P300 component changes in Parkinson’s disease: a meta-analysis. Neurol Sci 2022; 43:6719-6730. [DOI: 10.1007/s10072-022-06348-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 08/11/2022] [Indexed: 11/28/2022]
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10
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Jeon J, Kim K, Baek K, Chung SJ, Yoon J, Kim YJ. Accuracy of Machine Learning Using the Montreal Cognitive Assessment for the Diagnosis of Cognitive Impairment in Parkinson’s Disease. J Mov Disord 2022; 15:132-139. [PMID: 35670022 PMCID: PMC9171310 DOI: 10.14802/jmd.22012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 04/13/2022] [Indexed: 11/24/2022] Open
Abstract
Objective The Montreal Cognitive Assessment (MoCA) is recommended for assessing general cognition in Parkinson’s disease (PD). Several cutoffs of MoCA scores for diagnosing PD with cognitive impairment (PD-CI) have been proposed, with varying sensitivity and specificity. This study investigated the utility of machine learning algorithms using MoCA cognitive domain scores for improving diagnostic performance for PD-CI. Methods In total, 2,069 MoCA results were obtained from 397 patients with PD enrolled in the Parkinson’s Progression Markers Initiative database with a diagnosis of cognitive status based on comprehensive neuropsychological assessments. Using the same number of MoCA results randomly sampled from patients with PD with normal cognition or PD-CI, discriminant validity was compared between machine learning (logistic regression, support vector machine, or random forest) with domain scores and a cutoff method. Results Based on cognitive status classification using a dataset that permitted sampling of MoCA results from the same individual (n = 221 per group), no difference was observed in accuracy between the cutoff value method (0.74 ± 0.03) and machine learning (0.78 ± 0.03). Using a more stringent dataset that excluded MoCA results (n = 101 per group) from the same patients, the accuracy of the cutoff method (0.66 ± 0.05), but not that of machine learning (0.74 ± 0.07), was significantly reduced. Inclusion of cognitive complaints as an additional variable improved the accuracy of classification using the machine learning method (0.87–0.89). Conclusion Machine learning analysis using MoCA domain scores is a valid method for screening cognitive impairment in PD.
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Affiliation(s)
- Junbeom Jeon
- Department of Computer Engineering, Hallym University, Chuncheon, Korea
| | - Kiyong Kim
- Department of Electronic Engineering, Kyonggi University, Suwon, Korea
| | - Kyeongmin Baek
- Department of Computer Engineering, Hallym University, Chuncheon, Korea
| | - Seok Jong Chung
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
- Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, Korea
| | - Jeehee Yoon
- Department of Computer Engineering, Hallym University, Chuncheon, Korea
| | - Yun Joong Kim
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
- Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, Korea
- Corresponding author: Yun Joong Kim, MD, PhD Department of Neurology, Yongin Severance Hospital, 363 Dongbaekjukjeon-daero, Giheung-gu, Yongin 16995, Korea / Tel: +82-31-5189-8140 / Fax: +82-31-5189-8565 / E-mail:
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11
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Mapping Actuarial Criteria for Parkinson’s Disease-Mild Cognitive Impairment onto Data-Driven Cognitive Phenotypes. Brain Sci 2021; 12:brainsci12010054. [PMID: 35053799 PMCID: PMC8773733 DOI: 10.3390/brainsci12010054] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 12/05/2021] [Accepted: 12/22/2021] [Indexed: 11/17/2022] Open
Abstract
Prevalence rates for mild cognitive impairment in Parkinson’s disease (PD-MCI) remain variable, obscuring the diagnosis’ predictive utility of greater dementia risk. A primary factor of this variability is inconsistent operationalization of normative cutoffs for cognitive impairment. We aimed to determine which cutoff was optimal for classifying individuals as PD-MCI by comparing classifications against data-driven PD cognitive phenotypes. Participants with idiopathic PD (n = 494; mean age 64.7 ± 9) completed comprehensive neuropsychological testing. Cluster analyses (K-means, Hierarchical) identified cognitive phenotypes using domain-specific composites. PD-MCI criteria were assessed using separate cutoffs (−1, −1.5, −2 SD) on ≥2 tests in a domain. Cutoffs were compared using PD-MCI prevalence rates, MCI subtype frequencies (single/multi-domain, executive function (EF)/non-EF impairment), and validity against the cluster-derived cognitive phenotypes (using chi-square tests/binary logistic regressions). Cluster analyses resulted in similar three-cluster solutions: Cognitively Average (n = 154), Low EF (n = 227), and Prominent EF/Memory Impairment (n = 113). The −1.5 SD cutoff produced the best model of cluster membership (PD-MCI classification accuracy = 87.9%) and resulted in the best alignment between PD-MCI classification and the empirical cognitive profile containing impairments associated with greater dementia risk. Similar to previous Alzheimer’s work, these findings highlight the utility of comparing empirical and actuarial approaches to establish concurrent validity of cognitive impairment in PD.
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12
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Altmann CF, Trubelja K, Emmans D, Jost WH. Time-course of decline in different cognitive domains in Parkinson's disease: a retrospective study. J Neural Transm (Vienna) 2021; 129:1179-1187. [PMID: 34817687 DOI: 10.1007/s00702-021-02441-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 11/04/2021] [Indexed: 11/25/2022]
Abstract
Cognitive impairment and dementia are common non-motor symptoms in Parkinson's disease (PD). To elucidate the potentially typical progression of cognitive decline in PD and its variation, we retrospectively surveyed neuropsychological data obtained at the Parkinson-Klinik Ortenau, Germany in the years 1996-2015. Many of the patients in the surveyed period were repeatedly admitted to our clinic and we were thus able to compile neuropsychological re-test data for 252 patients obtained at varying time intervals. Neuropsychological testing was conducted with the NAI (Nürnberger Alters-Inventar). This battery provides sub-tests that examine cognitive processing speed, executive function, working memory, and verbal/visual memory functions. The re-test time span varied across patients from below 1 year up to about 12 years. Most patients were seen twice, but some patients were tested up to eight times. The steepest rates of cognitive decline were observed for the NAI sub-tests Trail-Making, Maze Test, and Stroop-Word Reading/Color Naming. Intermediate rates of decline were found for Digit Span, Word List-Immediate Recall, and Picture Test. Stroop Test-Interference, Word List-Delayed Recognition, and Figure Test exhibited the slowest decline rates. We did not observe a significant effect of age at diagnosis or gender on the rate of decline. In sum, this study retrospectively evaluated cognitive decline in a sample of patients with PD. Our data suggest a broad cognitive decline that particularly affects the cognitive capacities for processing speed, executive functions, and immediate memory functions.
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Affiliation(s)
| | - Kristian Trubelja
- Department of Neurology, Rhön Klinikum, 97616, Bad Neustadt an der Saale, Germany
| | - David Emmans
- Parkinson-Klinik Ortenau, Kreuzbergstr. 12-16, 77709, Wolfach, Germany
| | - Wolfgang H Jost
- Parkinson-Klinik Ortenau, Kreuzbergstr. 12-16, 77709, Wolfach, Germany
- Department of Neurology, University of Saarland, Homburg/Saar, Germany
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13
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Dissanayaka NN, Forbes EJ, Yang JHJ, Pourzinal D, O'Sullivan JD, Mitchell LK, Copland DA, McMahon KL, Byrne GJ. Anxiety disorders are associated with verbal memory impairment in patients with Parkinson's disease without dementia. J Neurol 2021; 269:1600-1609. [PMID: 34347150 DOI: 10.1007/s00415-021-10736-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: 04/07/2021] [Revised: 07/25/2021] [Accepted: 07/26/2021] [Indexed: 11/28/2022]
Abstract
INTRODUCTION Preliminary evidence has demonstrated a link between anxiety and memory impairment in Parkinson's disease (PD). This study further investigated this association using the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria for anxiety disorders and a standardized cognitive test battery. METHODS A convenience sample of 89 PD patients without dementia was recruited from neurology outpatient clinics. A cross-sectional design was applied. Participants completed two semi-structured interviews. The first interview diagnosed DSM-5 anxiety disorders, unspecified anxiety disorder, and no anxiety. The second interview applied a neurocognitive test battery comprising two tests for each domain. Logistic regression models compared cognitive characteristics associated with anxiety disorders to no anxiety. RESULTS Clinically significant anxiety was associated with immediate verbal memory impairment compared to the no anxiety group (OR, 95% CI 0.52, 0.30-0.89; p = 0.018), controlling for sex and age. The anxiety disorders group demonstrated immediate (OR, 95% CI 0.46, 0.26-0.83; p = 0.010) and delayed (OR, 95% CI 0.63, 0.40-0.99; p = 0.047) verbal memory impairments compared to those without anxiety, controlling for sex and age. This association remained for immediate (OR, 95% CI 0.43, 0.22-0.84; p = 0.013), but not delayed verbal memory impairment (OR, 95% CI 0.65, 0.39-1.06; p = 0.081) when additionally controlling for disease severity, education and levodopa dose. CONCLUSION These findings present first evidence that anxiety disorders are associated with verbal memory impairment in PD and have implications for the management and treatment of anxiety in PD.
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Affiliation(s)
- Nadeeka N Dissanayaka
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Building 71/918 Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD, 4029, Australia. .,School of Psychology, The University of Queensland, Brisbane, Australia. .,Department of Neurology, Royal Brisbane and Women's Hospital, Brisbane, Australia.
| | - Elana J Forbes
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Building 71/918 Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD, 4029, Australia.,School of Psychology, The University of Queensland, Brisbane, Australia
| | - Ji Hyun J Yang
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Building 71/918 Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD, 4029, Australia
| | - Dana Pourzinal
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Building 71/918 Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD, 4029, Australia
| | - John D O'Sullivan
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Building 71/918 Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD, 4029, Australia.,Department of Neurology, Royal Brisbane and Women's Hospital, Brisbane, Australia
| | | | - David A Copland
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Building 71/918 Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD, 4029, Australia.,School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia
| | - Katie L McMahon
- School of Clinical Sciences, Queensland University of Technology, Brisbane, Australia
| | - Gerard J Byrne
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Building 71/918 Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD, 4029, Australia.,Mental Health Service, Royal Brisbane and Women's Hospital, Brisbane, Australia
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14
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Kim R, Park S, Yoo D, Jun JS, Jeon B. Impact of the apolipoprotein E ε4 allele on early Parkinson's disease progression. Parkinsonism Relat Disord 2021; 83:66-70. [PMID: 33484977 DOI: 10.1016/j.parkreldis.2021.01.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 12/11/2020] [Accepted: 01/05/2021] [Indexed: 12/21/2022]
Abstract
OBJECTIVE Emerging evidence shows that apolipoprotein E (APOE) ε4 exacerbates alpha-synuclein pathology. We aimed to investigate whether the APOE ε4 allele contributes to early Parkinson's disease (PD) progression. METHODS This cohort study included 361 early PD patients who were classified as APOE ε4 carriers (n = 90) and noncarriers (n = 271). The patients underwent yearly motor and nonmotor assessments covering neuropsychiatric, sleep-related, and autonomic symptoms over 5 years of follow-up. Dopamine transporter (DAT) imaging was conducted at baseline and the 1-, 2-, and 4-year follow-up visits. RESULTS The APOE ε4 carriers had steeper declines in the Montreal Cognitive Assessment score (p=0.005) and the semantic fluency test score (p=0.012) than the noncarriers. No significant between-group differences in the longitudinal changes in motor, other nonmotor, and DAT imaging variables were observed. CONCLUSIONS Our exploratory analyses show that only cognitive performance was negatively affected by the APOE ε4 allele in the progression of early PD. More specifically, this allele was associated with poorer performance in semantic verbal fluency among cognitive domains.
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Affiliation(s)
- Ryul Kim
- Department of Neurology, Inha University Hospital, Incheon, South Korea
| | - Sangmin Park
- Department of Neurology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, South Korea
| | - Dallah Yoo
- Department of Neurology, Kyung Hee University Medical Center, Seoul, South Korea
| | - Jin-Sun Jun
- Department of Neurology, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, South Korea.
| | - Beomseok Jeon
- Department of Neurology, College of Medicine, Seoul National University Hospital, Seoul, South Korea
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15
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Wilson H, de Natale ER, Politis M. Nucleus basalis of Meynert degeneration predicts cognitive impairment in Parkinson's disease. HANDBOOK OF CLINICAL NEUROLOGY 2021; 179:189-205. [DOI: 10.1016/b978-0-12-819975-6.00010-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
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Cruz-Almeida Y, Crowley SJ, Tanner J, Price CC. Pain Severity and Interference in Different Parkinson's Disease Cognitive Phenotypes. J Pain Res 2020; 13:3493-3497. [PMID: 33402845 PMCID: PMC7778379 DOI: 10.2147/jpr.s270669] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2020] [Accepted: 10/29/2020] [Indexed: 01/17/2023] Open
Abstract
INTRODUCTION Chronic pain is prevalent in idiopathic Parkinson's disease (PD) with many individuals also experiencing cognitive deficits negatively impacting everyday life. METHODS In this study, we examine differences in pain severity and interference between 113 nondemented individuals with idiopathic PD who were statistically classified as having low executive function (n=24), low memory function (n=35), no cognitive deficits (n=54). The individuals with PD were also compared to matched non-PD controls (n=64). RESULTS PD participants with low executive function reported significantly higher pain interference (p<0.05), despite reporting similar pain severity levels compared to other phenotypes. These differences remained statistically significant, even after accounting for important confounders such as anxiety and depression (p<0.05). DISCUSSION Pain interference in those with lower executive function may represent a target for psychosocial interventions for individuals with pain and PD.
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Affiliation(s)
- Yenisel Cruz-Almeida
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, USA
| | - Samuel J Crowley
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Jared Tanner
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Catherine C Price
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
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Havlík F, Mana J, Dušek P, Jech R, Růžička E, Kopeček M, Georgi H, Bezdicek O. Brief Visuospatial Memory Test-Revised: normative data and clinical utility of learning indices in Parkinson’s disease. J Clin Exp Neuropsychol 2020; 42:1099-1110. [DOI: 10.1080/13803395.2020.1845303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Affiliation(s)
- Filip Havlík
- Department of Neurology and Centre of Clinical Neuroscience, Charles University, First Faculty of Medicine and General University Hospital in Prague, Prague, Czech Republic
- Department of Science and Research, Prague College of Psychosocial Studies, Prague, Czech Republic
| | - Josef Mana
- Department of Neurology and Centre of Clinical Neuroscience, Charles University, First Faculty of Medicine and General University Hospital in Prague, Prague, Czech Republic
- Department of Science and Research, Prague College of Psychosocial Studies, Prague, Czech Republic
| | - Petr Dušek
- Department of Neurology and Centre of Clinical Neuroscience, Charles University, First Faculty of Medicine and General University Hospital in Prague, Prague, Czech Republic
| | - Robert Jech
- Department of Neurology and Centre of Clinical Neuroscience, Charles University, First Faculty of Medicine and General University Hospital in Prague, Prague, Czech Republic
| | - Evžen Růžička
- Department of Neurology and Centre of Clinical Neuroscience, Charles University, First Faculty of Medicine and General University Hospital in Prague, Prague, Czech Republic
| | - Miloslav Kopeček
- National Institute of Mental Health, Klecany, Czech Republic
- Department of Psychiatry, Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Hana Georgi
- Department of Science and Research, Prague College of Psychosocial Studies, Prague, Czech Republic
| | - Ondrej Bezdicek
- Department of Neurology and Centre of Clinical Neuroscience, Charles University, First Faculty of Medicine and General University Hospital in Prague, Prague, Czech Republic
- Department of Science and Research, Prague College of Psychosocial Studies, Prague, Czech Republic
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18
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Campbell MC, Myers PS, Weigand AJ, Foster ER, Cairns NJ, Jackson JJ, Lessov‐Schlaggar CN, Perlmutter JS. Parkinson disease clinical subtypes: key features & clinical milestones. Ann Clin Transl Neurol 2020; 7:1272-1283. [PMID: 32602253 PMCID: PMC7448190 DOI: 10.1002/acn3.51102] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 05/15/2020] [Accepted: 05/22/2020] [Indexed: 12/20/2022] Open
Abstract
OBJECTIVES Based on multi-domain classification of Parkinson disease (PD) subtypes, we sought to determine the key features that best differentiate subtypes and the utility of PD subtypes to predict clinical milestones. METHODS Prospective cohort of 162 PD participants with ongoing, longitudinal follow-up. Latent class analysis (LCA) delineated subtypes based on score patterns across baseline motor, cognitive, and psychiatric measures. Discriminant analyses identified key features that distinguish subtypes at baseline. Cox regression models tested PD subtype differences in longitudinal conversion to clinical milestones, including deep brain stimulation (DBS), dementia, and mortality. RESULTS LCA identified distinct subtypes: "motor only" (N = 63) characterized by primary motor deficits; "psychiatric & motor" (N = 17) characterized by prominent psychiatric symptoms and moderate motor deficits; "cognitive & motor" (N = 82) characterized by impaired cognition and moderate motor deficits. Depression, executive function, and apathy best discriminated subtypes. Since enrollment, 22 had DBS, 48 developed dementia, and 46 have died. Although there were no subtype differences in rate of DBS, dementia occurred at a higher rate in the "cognitive & motor" subtype. Surprisingly, mortality risk was similarly elevated for both "cognitive & motor" and "psychiatric & motor" subtypes compared to the "motor only" subtype (relative risk = 3.15, 2.60). INTERPRETATION Psychiatric and cognitive features, rather than motor deficits, distinguish clinical PD subtypes and predict greater risk of subsequent dementia and mortality. These results emphasize the value of multi-domain assessments to better characterize clinical variability in PD. Further, differences in dementia and mortality rates demonstrate the prognostic utility of PD subtypes.
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Affiliation(s)
- Meghan C. Campbell
- Department of NeurologyWashington University School of MedicineSt. LouisMO
- Department of RadiologyWashington University School of MedicineSt. LouisMO
| | - Peter S. Myers
- Department of NeurologyWashington University School of MedicineSt. LouisMO
| | - Alexandra J. Weigand
- Department of Psychological and Brain SciencesWashington University in St. LouisSt. LouisMO
| | - Erin R. Foster
- Department of NeurologyWashington University School of MedicineSt. LouisMO
- Program in Occupational TherapyWashington University School of MedicineSt. LouisMO
- Department of PsychiatryWashington University School of MedicineSt. LouisMO
| | - Nigel J. Cairns
- Department of NeurologyWashington University School of MedicineSt. LouisMO
- College of Medicine and HealthUniversity of ExeterExeterUK
| | - Joshua J. Jackson
- Department of Psychological and Brain SciencesWashington University in St. LouisSt. LouisMO
| | | | - Joel S. Perlmutter
- Department of NeurologyWashington University School of MedicineSt. LouisMO
- Department of RadiologyWashington University School of MedicineSt. LouisMO
- Program in Occupational TherapyWashington University School of MedicineSt. LouisMO
- Department of NeuroscienceWashington University School of MedicineSt. LouisMO
- Program in Physical TherapyWashington University School of MedicineSt. LouisMO
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19
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Bernard BA, Carns D, Stebbins GT, Goldman JG, Goetz CG. Relationship of Movement Disorders Society-Unified Parkinson's Disease Rating Scale Nonmotor Symptoms to Cognitive Functioning in Patients with Parkinson's Disease. Mov Disord Clin Pract 2020; 7:279-283. [PMID: 32258225 DOI: 10.1002/mdc3.12902] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 01/02/2020] [Accepted: 01/20/2020] [Indexed: 01/26/2023] Open
Abstract
Background Few studies assess the relationships between nonmotor aspects of experiences of daily living and cognitive functioning in Parkinson's disease (PD). Objective To evaluate the relationships among the Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part I items and neuropsychological tests in PD.Methods: We assessed 151 PD patients with the MDS-UPDRS part I and a battery of cognitive tests focused on the following 5 cognitive domains: attention/working memory, executive functioning, recent memory, language, visuoperception. Raw scores for individual cognitive tests were transformed to z scores, and cognitive domain scores were calculated by averaging z scores within each domain. Individual items from the MDS-UPDRS part I were entered in a stepwise linear regression analysis assessing item contribution to cognitive domain scores. Results The MDS-UPDRS part I item scores for hallucinations and psychosis and light headedness on standing predicted attention/working memory domain scores (P = 0.004). These same item scores, along with apathy, depressed mood, and dopamine dysregulation syndrome, predicted executive functioning (P = 0.044). The apathy and dopamine dysregulation syndrome items predicted language (P = 0.006). In addition, the cognitive impairment and sleep items were predictors of recent memory (P = 0.031). None of the items were predictors of visuoperception (P = 0.006). Other part I items were not significantly related to cognitive domain scores. Conclusions Specific nonmotor MDS-UPDRS part I items, particularly mood, behavior, and autonomic-related items, exhibited significant relationships with cognitive domains. The highest number of items were predictive of the executive functioning domain, which is the hallmark cognitive dysfunction in PD.
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Affiliation(s)
- Bryan A Bernard
- Department of Neurological Sciences Rush University Medical Center Chicago Illinois USA
| | - Danielle Carns
- Department of Neurology University of Miami Miller School of Medicine Miami Florida USA
| | - Glenn T Stebbins
- Department of Neurological Sciences Rush University Medical Center Chicago Illinois USA
| | - Jennifer G Goldman
- Parkinson's Disease and Movement Disorders, Shirley Ryan AbilityLab and Departments of Physical Medicine and Rehabilitation and Neurology Northwestern University Feinberg School of Medicine Chicago Illinois USA
| | - Christopher G Goetz
- Department of Neurological Sciences Rush University Medical Center Chicago Illinois USA
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20
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Wang W, Mei M, Gao Y, Huang B, Qiu Y, Zhang Y, Wang L, Zhao J, Huang Z, Wang L, Nie K. Changes of brain structural network connection in Parkinson’s disease patients with mild cognitive dysfunction: a study based on diffusion tensor imaging. J Neurol 2019; 267:933-943. [DOI: 10.1007/s00415-019-09645-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 11/15/2019] [Accepted: 11/18/2019] [Indexed: 12/21/2022]
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21
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Joshi R, Bronstein JM, Keener A, Alcazar J, Yang DD, Joshi M, Hermanowicz N. PKG Movement Recording System Use Shows Promise in Routine Clinical Care of Patients With Parkinson's Disease. Front Neurol 2019; 10:1027. [PMID: 31632333 PMCID: PMC6779790 DOI: 10.3389/fneur.2019.01027] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 09/10/2019] [Indexed: 01/03/2023] Open
Abstract
Parkinson's disease (PD) is a debilitating, neurodegenerative disorder that affects nearly one million people. It's hallmark signs and symptoms include slow movements, rigidity, tremor, and unstable posture. Additionally, non-motor symptoms such as sleeplessness, depression, cognitive impairment, impulse control behaviors (ICB) have been reported. Today, treatment regimens to modify disease progression do not exist and as such, treatment is focused on symptom relief. Additionally, physicians are challenged to base their diagnoses and treatment plans on unreliable self-reported symptoms, even when used in conjunction to validated assessments such as the Unified Parkinson's Disease Rating Scale (UPDRS) and clinical exams. Wearable technology may provide clinicians objective measures of motor problems to supplement current subjective methods. Global Kinetics Corporation (GKC) has developed a watch-device called the Personal KinetiGraph (PKG) that records movements and provides patients medication dosing reminders. A separate clinician-use report supplies longitudinal motor and event data. The PKG was FDA-cleared in September 2016. We studied 63 PD patients during 85 routine care visits in 2 US academic institutions, evaluating the clinical utility of the PKG. Patients wore a PKG for 6 continuous days before their visit. Next, PKG data was uploaded to produce a report. In clinic, physicians discussed PD symptoms with patients and conducted a motor examination prior to reviewing the PKG report and comparing it to their initial assessments. Lastly, patient, caregiver and physician satisfaction surveys were conducted by each user. Across all visits when patients did not report bradykinesia or dyskinesia, the PKG reported these symptoms (50 and 33% of the time, respectively). The PKG provided insights for treatment plans in 50 (79%) patients across 71 (84%) visits. Physicians found improved patient dialogue in 50 (59%) visits, improved ability to assess treatment impact in 32 (38%) visits, and improved motor assessment in 28 (33%) visits. Patients stated in 82% of responses that they agreed or strongly agreed in PKG training, usability, performance, and satisfaction. In 39% of responses, they also reported a very valuable impact on their care. PKG use in 63 PD patients within our clinical practice showed clinically relevant utility in many areas.
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Affiliation(s)
| | - Jeffrey M Bronstein
- Department of Neurology, University of California, Los Angeles School of Medicine, Los Angeles, CA, United States
| | - A Keener
- Department of Neurology, University of California, Los Angeles School of Medicine, Los Angeles, CA, United States
| | - Jaclyn Alcazar
- Department of Neurology, University of California, Irvine, Irvine, CA, United States
| | - Diane D Yang
- Department of Neurology, University of California, Los Angeles School of Medicine, Los Angeles, CA, United States
| | - Maya Joshi
- Clinical Partners Group, Santa Monica, CA, United States
| | - Neal Hermanowicz
- Department of Neurology, University of California, Irvine, Irvine, CA, United States
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22
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Regional neuropathology distribution and verbal fluency impairments in Parkinson's disease. Parkinsonism Relat Disord 2019; 65:73-78. [PMID: 31109728 DOI: 10.1016/j.parkreldis.2019.05.014] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 03/11/2019] [Accepted: 05/09/2019] [Indexed: 11/22/2022]
Abstract
BACKGROUND Verbal fluency deficits are common in patients with Parkinson's disease. The association of these impairments with regional neuropathological changes is unexplored. OBJECTIVES Determine if patients with verbal fluency impairments have greater neuropathological burden in frontal, temporal, and limbic regions and if Lewy bodies or neurofibrillary tangles were associated with verbal fluency impairments. METHODS Data was derived from the Arizona Study of Aging and Neurodegenerative Disorders. 47 individuals who completed phonemic and semantic verbal fluency tasks and met clinicopathological criteria for Parkinson's disease (with and without comorbid Alzheimer's disease) were included. Impairment on fluency tasks was defined by normative data, and the density of neuropathology in temporal, limbic, and frontal regions was compared between groups. RESULTS Individuals with semantic fluency impairments had greater total pathology (Lewy bodies + neurofibrillary tangles) in limbic structures (W = 320.0, p = .033, rpb = .33), while those who had phonemic fluency impairments had increased total neuropathology in frontal (W = 364.5, p = .011, rpb = .37), temporal (W = 356.5, p = .022, rpb = .34), and limbic regions (W = 357.0, p = .024, rpb = .34). Greater Lewy body density was found in those with verbal fluency impairments, though trends for greater neurofibrillary tangle density were noted as well. CONCLUSIONS Impaired phonemic fluency was associated with higher Lewy body and tangle burden in frontal, temporal, and limbic regions, while impaired semantic fluency was associated with greater limbic pathology. Though neurofibrillary tangles trended higher in several regions in those with impaired verbal fluency, higher Lewy body density in general was associated with verbal fluency deficits. Implications for research and clinical practice are discussed.
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23
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Mostile G, Giuliano L, Monastero R, Luca A, Cicero CE, Donzuso G, Dibilio V, Baschi R, Terranova R, Restivo V, Sofia V, Zappia M, Nicoletti A. Electrocortical networks in Parkinson's disease patients with Mild Cognitive Impairment. The PaCoS study. Parkinsonism Relat Disord 2019; 64:156-162. [PMID: 30981665 DOI: 10.1016/j.parkreldis.2019.03.027] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2018] [Revised: 03/27/2019] [Accepted: 03/30/2019] [Indexed: 01/03/2023]
Abstract
INTRODUCTION Parkinson's Disease (PD) is frequently associated with cognitive dysfunction ranging from Mild Cognitive Impairment (PD-MCI) to dementia. Few electrophysiological studies are available evaluating potential pathogenetic mechanisms linked to cognitive impairment in PD since its initial phases. The objective of the study is to analyze electrocortical networks related with cognitive decline in PD-MCI for identifying possible early electrophysiological markers of cognitive impairment in PD. METHODS From the PaCoS (Parkinson's disease Cognitive impairment Study) cohort, a sample of 102 subjects including 46 PD-MCI and 56 PD with normal cognition (PD-NC) was selected based on the presence of a neuropsychological assessment and at least one EEG recording. EEG signal epochs were analysed using Independent Component Analysis LORETA and spectral analysis by computing the Power Spectral Density (PSD) of site-specific signal epochs. RESULTS LORETA analysis revealed significant differences in PD-MCI patients compared to PD-NC, with a decreased network involving alpha activity over the occipital lobe, an increased network involving beta activity over the frontal lobe associated with a reduction over the parietal lobe, an increased network involving theta and delta activity over the frontal lobe and a reduction of networks involving theta and delta activity in the parietal lobe. Quantitative EEG analysis showed a significant decrease of alpha PSD over the occipital regions and an increase of delta PSD over the left temporal region in PD-MCI as compared to PD-NC. CONCLUSION Electrocortical abnormalities detected in PD-MCI patients may represent the instrumental counterpart of early cognitive decline in PD.
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Affiliation(s)
- Giovanni Mostile
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Loretta Giuliano
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Roberto Monastero
- Department of Biomedicine, Neuroscience and Advanced Diagnostics, Section of Neurology, University of Palermo, Via La Loggia 1, 90129, Palermo, Italy
| | - Antonina Luca
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Calogero Edoardo Cicero
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Giulia Donzuso
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Valeria Dibilio
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Roberta Baschi
- Department of Biomedicine, Neuroscience and Advanced Diagnostics, Section of Neurology, University of Palermo, Via La Loggia 1, 90129, Palermo, Italy
| | - Roberta Terranova
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Vincenzo Restivo
- Department of Sciences for Health Promotion and Mother-Child Care, University of Palermo, Via Del Vespro 133, 90127, Palermo, Italy
| | - Vito Sofia
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Mario Zappia
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Alessandra Nicoletti
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy.
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Nie K, Gao Y, Mei M, Guo M, Huang Z, Wang L, Zhao J, Zhang Y, Wang L. The clinical characteristics and cognitive features of mild cognitive impairment in Parkinson's disease and the analysis of relevant factors. J Clin Neurosci 2019; 63:142-148. [PMID: 30732989 DOI: 10.1016/j.jocn.2019.01.021] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Revised: 12/14/2018] [Accepted: 01/18/2019] [Indexed: 12/24/2022]
Abstract
The purpose of this work is to investigate the clinical characteristics, cognitive impairment features, and subgroup types of Parkinson's disease (PD) subjects with mild cognitive impairment (PD-MCI) in the Chinese population and to analyze relevant risk factors for PD-MCI. A total of 234 non-dementia PD subjects were collected. Standardized neuropsychological assessments of overall cognitive level and four cognitive domains (memory, executive function, attention and visuospatial function) were performed using MDS Task Force diagnostic criteria for PD-MCI. PD-MCI subjects were further divided into four subgroups: nonamnestic single-domain impairment type (PD-naMCI-SD), nonamnestic multiple-domain impairment type (PD-naMCI-MD), amnestic single-domain impairment type (PD-aMCI-SD), and amnestic multiple-domain impairment type (PD-aMCI-MD). The clinical characteristics of and risk factors for all subgroups were analyzed. PD-MCI was found in 45.3% of the non-dementia PD subjects. Differences between the PD-MCI and PD with normal cognition groups with respect to age, age of onset, years of education, and motor symptom severity were significant (P < 0.05). The single-domain impairment type was the largest PD-MCI subgroup (52.83%). Memory and executive function impairment were most frequent (22.64% and 20.75%, respectively). Among the four subgroups, the number of years of education was significantly different (P = 0.003). The overall cognitive function in amnestic multiple-domain impairment type was significantly worse compared with that in those with single-domain impairment type. Regression analysis results showed that old age, high UPDRS-III score, and hyperhomocysteinemia were risk factors for PD-MCI, whereas high education level was a protective factor. Early prevention of MCI-related risk factors provides effective means to retard cognitive decline in PD patients.
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Affiliation(s)
- Kun Nie
- Department of Neurology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Er Road, Guangzhou, Guangdong Province 510080, PR China
| | - Yuyuan Gao
- Department of Neurology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Er Road, Guangzhou, Guangdong Province 510080, PR China
| | - Mingjin Mei
- Department of Neurology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Er Road, Guangzhou, Guangdong Province 510080, PR China
| | - Manli Guo
- Department of Neurology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Er Road, Guangzhou, Guangdong Province 510080, PR China
| | - Zhiheng Huang
- Department of Neurology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Er Road, Guangzhou, Guangdong Province 510080, PR China
| | - Limin Wang
- Department of Neurology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Er Road, Guangzhou, Guangdong Province 510080, PR China
| | - Jiehao Zhao
- Department of Neurology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Er Road, Guangzhou, Guangdong Province 510080, PR China
| | - Yuhu Zhang
- Department of Neurology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Er Road, Guangzhou, Guangdong Province 510080, PR China.
| | - Lijuan Wang
- Department of Neurology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Er Road, Guangzhou, Guangdong Province 510080, PR China.
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25
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Pantall A, Suresparan P, Kapa L, Morris R, Yarnall A, Del Din S, Rochester L. Postural Dynamics Are Associated With Cognitive Decline in Parkinson's Disease. Front Neurol 2018; 9:1044. [PMID: 30568629 PMCID: PMC6290334 DOI: 10.3389/fneur.2018.01044] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2018] [Accepted: 11/19/2018] [Indexed: 11/25/2022] Open
Abstract
Early features of Parkinson's disease (PD) include both motor and cognitive changes, suggesting shared common pathways. A common motor dysfunction is postural instability, a known predictor of falls, which have a major impact on quality of life. Understanding mechanisms of postural dynamics in PD and specifically how they relate to cognitive changes is essential for developing effective interventions. The aims of this study were to examine the changes that occur in postural metrics over time and explore the relationship between postural and cognitive dysfunction. The study group consisted of 35 people (66 ± 8years, 12 female, UPDRS III: 22.5 ± 9.6) diagnosed with PD who were recruited as part of the Incidence of Cognitive Impairment in Cohorts with Longitudinal Evaluation—PD Gait (ICICLE-GAIT) study. Postural and cognitive assessments were performed at 18, 36, and 54 months after enrolment. Participants stood still for 120 s, eyes open and arms by their side. Postural dynamics were measured using metrics derived from a single tri-axial accelerometer (Axivity AX3, York, UK) on the lower back. Accelerometry metrics included jerk (derivative of acceleration), root mean square, frequency, and ellipsis (acceleration area). Cognition was evaluated by neuropsychological tests including the Montreal Cognitive Assessment (MoCA) and digit span. There was a significant decrease in accelerometry parameters, greater in the anteroposterior direction, and a decline in cognitive function over time. Accelerometry metrics were positively correlated with lower cognitive function and increased geriatric depression score and negatively associated with a qualitative measure of balance confidence. In conclusion, people with PD showed reduced postural dynamics that may represent a postural safety strategy. Associations with cognitive function and depression, both symptoms that may pre-empt motor symptoms, suggest shared neural pathways. Further studies, involving neuroimaging, may determine how these postural parameters relate to underlying neural and clinical correlates.
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Affiliation(s)
- Annette Pantall
- Clinical Ageing Research Unit, Institute of Neuroscience, Newcastle University Institute of Ageing, Newcastle upon Tyne, United Kingdom
| | - Piriya Suresparan
- Clinical Ageing Research Unit, Institute of Neuroscience, Newcastle University Institute of Ageing, Newcastle upon Tyne, United Kingdom
| | - Leanne Kapa
- Clinical Ageing Research Unit, Institute of Neuroscience, Newcastle University Institute of Ageing, Newcastle upon Tyne, United Kingdom
| | - Rosie Morris
- Clinical Ageing Research Unit, Institute of Neuroscience, Newcastle University Institute of Ageing, Newcastle upon Tyne, United Kingdom.,Department of Neurology, Oregon Health and Science University, Portland, OR, United States
| | - Alison Yarnall
- The Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, United Kingdom
| | - Silvia Del Din
- Clinical Ageing Research Unit, Institute of Neuroscience, Newcastle University Institute of Ageing, Newcastle upon Tyne, United Kingdom
| | - Lynn Rochester
- Clinical Ageing Research Unit, Institute of Neuroscience, Newcastle University Institute of Ageing, Newcastle upon Tyne, United Kingdom.,The Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, United Kingdom
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26
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Díaz-Hung ML, Ruiz-Fuentes JL, Díaz-García A, León-Martínez R, Alberti-Amador E, Pavón-Fuentes N, Blanco-Lezcano L. Impairment in exploratory behavior is associated with arc gene overexpression in the dorsolateral striatum of rats with nigral injection of l-buthionine sulfoximine. Neurosci Lett 2018; 687:26-30. [PMID: 30223000 DOI: 10.1016/j.neulet.2018.09.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Revised: 09/06/2018] [Accepted: 09/13/2018] [Indexed: 01/01/2023]
Abstract
The aims of the present work were to evaluate the exploratory activity in Sprague-Dawley rats, as well as to analyze the nigral and striatal mRNA expression of the plasticity-related genes bdnf and arc after L-buthionine sulfoximine (BSO) injection into substantia nigra compacta. Lesioned rats traveled less distance in open field but did not show a decline in the novel object recognition test. On the other hand, RT-PCR analysis showed overexpression of striatal arc 24 h post-lesion; no significant changes in bdnf expression were observed in nigral or striatal tissue. These results suggest that intranigral BSO injection causes impairment in exploratory behavior in these rats, by affecting locomotion, which is associated with changes in striatal synaptic plasticity.
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Affiliation(s)
- M L Díaz-Hung
- International Center for Neurological Restoration (CIREN), Havana, Cuba.
| | | | - A Díaz-García
- Pharmaceutics Biological Laboratories (LABIOFAM), Havana, Cuba
| | - R León-Martínez
- Departament of Molecular and Celular Biology, Faculty of Biology, Pontifical Catholic University of Chile, Santiago de Chile, Chile
| | - E Alberti-Amador
- International Center for Neurological Restoration (CIREN), Havana, Cuba
| | - N Pavón-Fuentes
- International Center for Neurological Restoration (CIREN), Havana, Cuba
| | - L Blanco-Lezcano
- International Center for Neurological Restoration (CIREN), Havana, Cuba
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27
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Babaei F, Mirzababaei M, Nassiri-Asl M. Quercetin in Food: Possible Mechanisms of Its Effect on Memory. J Food Sci 2018; 83:2280-2287. [DOI: 10.1111/1750-3841.14317] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2018] [Accepted: 11/07/2018] [Indexed: 12/18/2022]
Affiliation(s)
- Fatemeh Babaei
- Dept. of Clinical Biochemistry; Qazvin Univ. of Medical Sciences; Qazvin Iran
| | - Mohammadreza Mirzababaei
- Dept. of Clinical Biochemistry, Faculty of Medical Sciences; Tarbiat Modares Univ.; 14115-111 Tehran Iran
| | - Marjan Nassiri-Asl
- Cellular and Molecular Research Center; Qazvin Univ. of Medical Sciences; 341197-5981 Qazvin Iran
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Wu L, Liu FT, Ge JJ, Zhao J, Tang YL, Yu WB, Yu H, Anderson T, Zuo CT, Chen L, Wang J. Clinical characteristics of cognitive impairment in patients with Parkinson's disease and its related pattern in 18 F-FDG PET imaging. Hum Brain Mapp 2018; 39:4652-4662. [PMID: 29999569 DOI: 10.1002/hbm.24311] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Revised: 05/12/2018] [Accepted: 06/27/2018] [Indexed: 01/26/2023] Open
Abstract
This study aimed to characterize the clinical features and the related cerebral glucose metabolism pattern of cognitive impairments in Parkinson's disease (PD) with positron emission tomography (PET) imaging. We recruited 168 PD patients and 100 age-matched healthy controls of similar education and gender distribution. All of those enrolled underwent clinical assessment including the unified Parkinson's disease rating scale motor score, Hoehn and Yahr scale, and comprehensive neuropsychological tests including domains of executive function, attention, memory, visuospatial function, and language. Demographics and the results of cognitive measures were compared between patients and healthy controls. Cognition status was classified as PD patients with dementia (PD-D), PD patients with mild cognitive impairment (PD-MCI), or PD patients with normal cognition (PD-NC). In 53 PD patients who underwent 18 F-fluorodeoxyglucose (18 F-FDG) PET imaging, correlations between Z-score values of the different cognitive domains and cerebral 18 F-FDG uptake were assessed using statistical parametric mapping (SPM8) corrected for age and motor severity. A total of 23.2% of PD patients were PD-MCI and 8.9% were PD-D. In the group of PD-MCI, 96.3% showed multiple-domain deficits, with executive function and attention impairment most predominantly involved. All the cognitive domain scores with the exception of language correlated with 18 F-FDG metabolisms, primarily in posterior temporo-parieto-occipital association cortical areas. This study found that cognitive impairment in PD particularly encompasses frontal/executive deficits. Posterior cortical areas, containing multiple neurotransmitters and neural circuits, may play an important role in the pathogenesis of cognitive impairment in PD.
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Affiliation(s)
- Lei Wu
- Department of Neurology & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Feng-Tao Liu
- Department of Neurology & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jing-Jie Ge
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jue Zhao
- Department of Neurology & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Yi-Lin Tang
- Department of Neurology & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Wen-Bo Yu
- Department of Neurology & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Huan Yu
- Department of Neurology & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Tim Anderson
- Department of Medicine, University of Otago, New Zealand Brain Research Institute, and Brain Research New Zealand, Christchurch, New Zealand
| | - Chuan-Tao Zuo
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Ling Chen
- Department of Neurology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Jian Wang
- Department of Neurology & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
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Protective Activity of Erythropoyetine in the Cognition of Patients with Parkinson's Disease. Behav Sci (Basel) 2018; 8:51. [PMID: 29862060 PMCID: PMC5981245 DOI: 10.3390/bs8050051] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Accepted: 05/18/2018] [Indexed: 12/02/2022] Open
Abstract
Introduction: Treatment strategies in Parkinson’s disease (PD) can improve a patient’s quality of life but cannot stop the progression of PD. We are looking for different alternatives that modify the natural course of the disease and recent research has demonstrated the neuroprotective properties of erythropoietin. In Cuba, the Center for Molecular Immunology (CIM) is a cutting edge scientific center where the recombinant form (EPOrh) and recombinant human erythropoietin with low sialic acid (NeuroEPO) are produced. We performed two clinical trials to evaluate the safety and tolerability of these two drugs in PD patients. In this paper we want to show the positive results of the additional cognitive tests employed, as part of the comprehensive assessment. Materials and method: Two studies were conducted in PD patients from the outpatient clinic of CIREN, including n = 10 and n = 26 patients between 60 and 66 years of age, in stages 1 to 2 of the Hoehn and Yahr Scale. The first study employed recombinant human (rhEPO) and the second an intranasal formulation of neuroEPO. All patients were evaluated with a battery of neuropsychological scales composed to evaluate global cognitive functioning, executive function, and memory. Results: The general results in both studies showed a positive response to the cognitive functions in PD patients, who were undergoing pharmacological treatment with respect to the evaluation (p < 0.05) before the intervention. Conclusions: Erythropoietin has a discrete positive effect on the cognitive functions of patients with Parkinson’s disease, which could be interpreted as an effect of the neuroprotective properties of this molecules. To confirm the results another clinical trial phase III with neuroEPO is in progress, also designed to discard any influence of a placebo effect on cognition.
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Bezdicek O, Ballarini T, Růžička F, Roth J, Mueller K, Jech R, Schroeter ML. Mild cognitive impairment disrupts attention network connectivity in Parkinson's disease: A combined multimodal MRI and meta-analytical study. Neuropsychologia 2018; 112:105-115. [PMID: 29540317 DOI: 10.1016/j.neuropsychologia.2018.03.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Revised: 02/09/2018] [Accepted: 03/06/2018] [Indexed: 01/28/2023]
Abstract
Mild cognitive impairment (MCI) affects approximately one-third of non-demented Parkinson's Disease (PD) patients. We aimed at investigating the neural correlates of MCI in PD combining multimodal magnetic resonance imaging (MRI) with large-scale data from the literature. We analyzed 31 PD patients and 30 matched controls. The standard neuropsychological assessment of PD-MCI covered memory, attention, executive functions, language and visuospatial abilities. Following validated criteria, 16 patients were classified as showing MCI. Whole-brain functional connectivity and structural volume changes were assessed, respectively, by means of eigenvector centrality (EC) and voxel-based morphometry. To address the involvement of specific functional brain networks, we validated our results by building a meta-analytic co-activation map (MACM) based on the previous literature and then testing its overlap with the parcellation of functional networks derived from 1000 healthy controls. The EC comparison between PD with normal cognition and controls showed a selective decline in interconnectedness in the bilateral lentiform nuclei. Differently, comparing PD with MCI and controls revealed additional changes in non-motor areas. Directly comparing PD with and without MCI, we found a reduced interconnectedness in the bilateral superior parietal lobules and precuneus. No differences in brain volume were detected comparing these patient groups. The MACM and overlap analyses showed that the observed connectivity changes were localized in the hubs of the dorsal attention network. Notably, this aligned with the predominant attention deficit observed in our sample. Overall, functional impairment in the dorsal attention network seems to be the hallmark of MCI due to PD, thus extending previous findings of brain connectivity disruption in non-motor networks.
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Affiliation(s)
- Ondrej Bezdicek
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Czech Republic.
| | - Tommaso Ballarini
- Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, Leipzig 04103, Germany
| | - Filip Růžička
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Czech Republic
| | - Jan Roth
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Czech Republic
| | - Karsten Mueller
- Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, Leipzig 04103, Germany
| | - Robert Jech
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Czech Republic
| | - Matthias L Schroeter
- Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, Leipzig 04103, Germany; Clinic for Cognitive Neurology, University Clinic, Liebigstr. 16D, Leipzig 04103 Germany; FTLD Consortium, Ulm, Germany
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Goldman JG, Holden SK, Litvan I, McKeith I, Stebbins GT, Taylor JP. Evolution of diagnostic criteria and assessments for Parkinson's disease mild cognitive impairment. Mov Disord 2018; 33:503-510. [DOI: 10.1002/mds.27323] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2017] [Revised: 01/01/2018] [Accepted: 01/04/2018] [Indexed: 12/16/2022] Open
Affiliation(s)
- Jennifer G. Goldman
- Department of Neurological Sciences, Section of Parkinson Disease and Movement Disorders; Rush University Medical Center; Chicago Illinois USA
| | - Samantha K. Holden
- Department of Neurology; University of Colorado, Department of Neurology; Aurora Colorado USA
| | - Irene Litvan
- Department of Neurosciences; University of California San Diego, Department of Neurosciences; San Diego California USA
| | - Ian McKeith
- Institute of Neuroscience; Newcastle University; Newcastle upon Tyne United Kingdom
| | - Glenn T. Stebbins
- Department of Neurological Sciences, Section of Parkinson Disease and Movement Disorders; Rush University Medical Center; Chicago Illinois USA
| | - John-Paul Taylor
- Institute of Neuroscience; Newcastle University; Newcastle upon Tyne United Kingdom
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Abstract
BACKGROUND We apply recently recommended Parkinson's disease mild cognitive impairment (PD-MCI) classification criteria from the movement disorders society (MDS) to PD patients and controls and compare diagnoses to that of short global cognitive scales at baseline and over time. We also examine baseline prevalence of neuropsychiatric symptoms across different definitions of MCI. METHODS 51 PD patients and 50 controls were classified as cognitively normal, MCI, or demented using MDS criteria (1.5 or 2.0 SD below normative values), Clinical Dementia Rating Scale (CDR), and the Dementia Rating Scale (DRS). All subject had parallel assessment with the Neuropsychiatric inventory (NPI). RESULTS We confirmed that PD-MCI (a) is frequent, (b) increases the risk of PDD, and (c) affects multiple cognitive domains. We highlight the predictive variability of different criteria, suggesting the need for further refinement and standardization. When a common dementia outcome was used, the Level II MDS optimal testing battery with impairment defined as two SD below norms in 2+ tests performs the best. Neuropsychiatric symptoms were more common in PD across all baseline and longitudinal cognitive classifications. CONCLUSIONS Our results advance previous findings on the utility of MDS PD-MCI criteria for PD patients and controls at baseline and over time. Additionally, we emphasize the possible utility of other cognitive scales and neuropsychiatric symptoms.
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Gaßner H, Marxreiter F, Steib S, Kohl Z, Schlachetzki JCM, Adler W, Eskofier BM, Pfeifer K, Winkler J, Klucken J. Gait and Cognition in Parkinson's Disease: Cognitive Impairment Is Inadequately Reflected by Gait Performance during Dual Task. Front Neurol 2017; 8:550. [PMID: 29123499 PMCID: PMC5662548 DOI: 10.3389/fneur.2017.00550] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Accepted: 09/28/2017] [Indexed: 01/20/2023] Open
Abstract
Introduction Cognitive and gait deficits are common symptoms in Parkinson’s disease (PD). Motor-cognitive dual tasks (DTs) are used to explore the interplay between gait and cognition. However, it is unclear if DT gait performance is indicative for cognitive impairment. Therefore, the aim of this study was to investigate if cognitive deficits are reflected by DT costs of spatiotemporal gait parameters. Methods Cognitive function, single task (ST) and DT gait performance were investigated in 67 PD patients. Cognition was assessed by the Montreal Cognitive Assessment (MoCA) followed by a standardized, sensor-based gait test and the identical gait test while subtracting serial 3’s. Cognitive impairment was defined by a MoCA score <26. DT costs in gait parameters [(DT − ST)/ST × 100] were calculated as a measure of DT effect on gait. Correlation analysis was used to evaluate the association between MoCA performance and gait parameters. In a linear regression model, DT gait costs and clinical confounders (age, gender, disease duration, motor impairment, medication, and depression) were correlated to cognitive performance. In a subgroup analysis, we compared matched groups of cognitively impaired and unimpaired PD patients regarding differences in ST, DT, and DT gait costs. Results Correlation analysis revealed weak correlations between MoCA score and DT costs of gait parameters (r/rSp ≤ 0.3). DT costs of stride length, swing time variability, and maximum toe clearance (|r/rSp| > 0.2) were included in a regression analysis. The parameters only explain 8% of the cognitive variance. In combination with clinical confounders, regression analysis showed that these gait parameters explained 30% of MoCA performance. Group comparison revealed strong DT effects within both groups (large effect sizes), but significant between-group effects in DT gait costs were not observed. Conclusion These findings suggest that DT gait performance is not indicative for cognitive impairment in PD. DT effects on gait parameters were substantial in cognitively impaired and unimpaired patients, thereby potentially overlaying the effect of cognitive impairment on DT gait costs. Limits of the MoCA in detecting motor-function specific cognitive performance or variable individual response to the DT as influencing factors cannot be excluded. Therefore, DT gait parameters as marker for cognitive performance should be carefully interpreted in the clinical context.
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Affiliation(s)
- Heiko Gaßner
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Franz Marxreiter
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Simon Steib
- Institute for Sport Science and Sport, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Zacharias Kohl
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Johannes C M Schlachetzki
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Werner Adler
- Department of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Bjoern M Eskofier
- Chair for Machine Learning and Data Analytics, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Klaus Pfeifer
- Institute for Sport Science and Sport, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Jürgen Winkler
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Jochen Klucken
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
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LaBelle DR, Walsh RR, Banks SJ. Latent Cognitive Phenotypes in De Novo Parkinson's Disease: A Person-Centered Approach. J Int Neuropsychol Soc 2017; 23:551-563. [PMID: 28651678 PMCID: PMC6435330 DOI: 10.1017/s1355617717000406] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
OBJECTIVES Cognitive impairment is an important aspect of Parkinson's disease (PD), but there is considerable heterogeneity in its presentation. This investigation aims to identify and characterize latent cognitive phenotypes in early PD. METHODS Latent class analysis, a data-driven, person-centered, cluster analysis was performed on cognitive data from the Parkinson's Progressive Markers Initiative baseline visit. This analytic method facilitates identification of naturally occurring endophenotypes. Resulting classes were compared across biomarker, symptom, and demographic data. RESULTS Six cognitive phenotypes were identified. Three demonstrated consistent performance across indicators, representing poor ("Weak-Overall"), average ("Typical-Overall"), and strong ("Strong-Overall") cognition. The remaining classes demonstrated unique patterns of cognition, characterized by "Strong-Memory," "Weak-Visuospatial," and "Amnestic" profiles. The Amnestic class evidenced greater tremor severity and anosmia, but was unassociated with biomarkers linked with Alzheimer's disease. The Weak-Overall class was older and reported more non-motor features associated with cognitive decline, including anxiety, depression, autonomic dysfunction, anosmia, and REM sleep behaviors. The Strong-Overall class was younger, more female, and reported less dysautonomia and anosmia. Classes were unrelated to disease duration, functional independence, or available biomarkers. CONCLUSIONS Latent cognitive phenotypes with focal patterns of impairment were observed in recently diagnosed individuals with PD. Cognitive profiles were found to be independent of traditional biomarkers and motoric indices of disease progression. Only globally impaired class was associated with previously reported indicators of cognitive decline, suggesting this group may drive the effects reported in studies using variable-based analysis. Longitudinal and neuroanatomical characterization of classes will yield further insight into the evolution of cognitive change in the disease. (JINS, 2017, 23, 551-563).
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Affiliation(s)
- Denise R LaBelle
- Neurology Department Cleveland Clinic Lou Ruvo Center for Brain Health,Las Vegas,Nevada
| | - Ryan R Walsh
- Neurology Department Cleveland Clinic Lou Ruvo Center for Brain Health,Las Vegas,Nevada
| | - Sarah J Banks
- Neurology Department Cleveland Clinic Lou Ruvo Center for Brain Health,Las Vegas,Nevada
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Sauerbier A, Rosa-Grilo M, Qamar MA, Chaudhuri KR. Nonmotor Subtyping in Parkinson's Disease. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2017; 133:447-478. [PMID: 28802928 DOI: 10.1016/bs.irn.2017.05.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Nonmotor symptoms are integral to Parkinson's disease. Several subtypes dominated by specific nonmotor symptoms have emerged. In this chapter, the rationale behind nonmotor subtyping and currently proposed nonmotor subgroups within Parkinson's disease based on data-driven cluster analysis and clinical observations will be summarized. Furthermore, the concept of seven clinical nonmotor subtypes will be discussed in detail including the clinical presentation, potential biomarkers, and the clinical relevance. In future, nonmotor subtypes will possibly play a major role within the aim to achieve personalized medicine.
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Affiliation(s)
- Anna Sauerbier
- Parkinson's Centre of Excellence, King's College Hospital Foundation Trust, London, United Kingdom; Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, United Kingdom.
| | - Miguel Rosa-Grilo
- Parkinson's Centre of Excellence, King's College Hospital Foundation Trust, London, United Kingdom; Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, United Kingdom
| | - Mubasher A Qamar
- Parkinson's Centre of Excellence, King's College Hospital Foundation Trust, London, United Kingdom; Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, United Kingdom
| | - K Ray Chaudhuri
- Parkinson's Centre of Excellence, King's College Hospital Foundation Trust, London, United Kingdom; Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, United Kingdom
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Davis MY, Johnson CO, Leverenz JB, Weintraub D, Trojanowski JQ, Chen-Plotkin A, Van Deerlin VM, Quinn JF, Chung KA, Peterson-Hiller AL, Rosenthal LS, Dawson TM, Albert MS, Goldman JG, Stebbins GT, Bernard B, Wszolek ZK, Ross OA, Dickson DW, Eidelberg D, Mattis PJ, Niethammer M, Yearout D, Hu SC, Cholerton BA, Smith M, Mata IF, Montine TJ, Edwards KL, Zabetian CP. Association of GBA Mutations and the E326K Polymorphism With Motor and Cognitive Progression in Parkinson Disease. JAMA Neurol 2017; 73:1217-1224. [PMID: 27571329 DOI: 10.1001/jamaneurol.2016.2245] [Citation(s) in RCA: 175] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Importance Parkinson disease (PD) is heterogeneous in symptom manifestation and rate of progression. Identifying factors that influence disease progression could provide mechanistic insight, improve prognostic accuracy, and elucidate novel therapeutic targets. Objective To determine whether GBA mutations and the E326K polymorphism modify PD symptom progression. Design, Setting, and Participants The entire GBA coding region was screened for mutations and E326K in 740 patients with PD enrolled at 7 sites from the PD Cognitive Genetics Consortium. Detailed longitudinal motor and cognitive assessments were performed with patients in the on state. Main Outcomes and Measures Linear regression was used to test for an association between GBA genotype and motor progression, with the Movement Disorder Society-sponsored version of the Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS III) score at the last assessment as the outcome and GBA genotype as the independent variable, with adjustment for levodopa equivalent dose, sex, age, disease duration, MDS-UPDRS III score at the first assessment, duration of follow-up, and site. Similar methods were used to examine the association between genotype and tremor and postural instability and gait difficulty (PIGD) scores. To examine the effect of GBA genotype on cognitive progression, patients were classified into those with conversion to mild cognitive impairment or dementia during the study (progression) and those without progression. The association between GBA genotype and progression status was then tested using logistic regression, adjusting for sex, age, disease duration, duration of follow-up, years of education, and site. Results Of the total sample of 733 patients who underwent successful genotyping, 226 (30.8%) were women and 507 (69.2%) were men (mean [SD] age, 68.1 [8.8] years). The mean (SD) duration of follow-up was 3.0 (1.7) years. GBA mutations (β = 4.65; 95% CI, 1.72-7.58; P = .002), E326K (β = 3.42; 95% CI, 0.66-6.17; P = .02), and GBA variants combined as a single group (β = 4.01; 95% CI, 1.95-6.07; P = 1.5 × 10-4) were associated with a more rapid decline in MDS-UPDRS III score. Combined GBA variants (β = 0.38; 95% CI, 0.23-0.53; P = .01) and E326K (β = 0.64; 95% CI, 0.43-0.86; P = .002) were associated with faster progression in PIGD scores, but not in tremor scores. A significantly higher proportion of E326K carriers (10 of 21 [47.6%]; P = .01) and GBA variant carriers (15 of 39 [38.5%]; P = .04) progressed to mild cognitive impairment or dementia. Conclusions and Relevance GBA variants predict a more rapid progression of cognitive dysfunction and motor symptoms in patients with PD, with a greater effect on PIGD than tremor. Thus, GBA variants influence the heterogeneity in symptom progression observed in PD.
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Affiliation(s)
- Marie Y Davis
- Veterans Affairs Puget Sound Health Care System, Seattle, Washington2Department of Neurology, University of Washington School of Medicine, Seattle
| | - Catherine O Johnson
- Department of Neurology, University of Washington School of Medicine, Seattle
| | - James B Leverenz
- Lou Ruvo Center for Brain Health, Neurological Institute, Cleveland Clinic, Cleveland, Ohio
| | - Daniel Weintraub
- Department of Psychiatry, University of Pennsylvania, Philadelphia
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia
| | | | - Vivianna M Van Deerlin
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia
| | - Joseph F Quinn
- Portland Veterans Affairs Medical Center, Portland, Oregon8Department of Neurology, Oregon Health and Science University, Portland
| | - Kathryn A Chung
- Portland Veterans Affairs Medical Center, Portland, Oregon8Department of Neurology, Oregon Health and Science University, Portland
| | - Amie L Peterson-Hiller
- Portland Veterans Affairs Medical Center, Portland, Oregon8Department of Neurology, Oregon Health and Science University, Portland
| | - Liana S Rosenthal
- Neurodegeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland10Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Ted M Dawson
- Neurodegeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland10Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland11Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland12Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Marilyn S Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jennifer G Goldman
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
| | - Glenn T Stebbins
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
| | - Bryan Bernard
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
| | | | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida
| | | | - David Eidelberg
- Center for Neurosciences, Feinstein Institute for Medical Research, Manhasset, New York17Department of Neurology, Northwell Health, Manhasset, New York
| | - Paul J Mattis
- Center for Neurosciences, Feinstein Institute for Medical Research, Manhasset, New York17Department of Neurology, Northwell Health, Manhasset, New York
| | - Martin Niethammer
- Center for Neurosciences, Feinstein Institute for Medical Research, Manhasset, New York
| | - Dora Yearout
- Veterans Affairs Puget Sound Health Care System, Seattle, Washington2Department of Neurology, University of Washington School of Medicine, Seattle
| | - Shu-Ching Hu
- Veterans Affairs Puget Sound Health Care System, Seattle, Washington2Department of Neurology, University of Washington School of Medicine, Seattle
| | - Brenna A Cholerton
- Veterans Affairs Puget Sound Health Care System, Seattle, Washington18Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle
| | - Megan Smith
- Department of Epidemiology, University of California, Irvine, School of Medicine
| | - Ignacio F Mata
- Veterans Affairs Puget Sound Health Care System, Seattle, Washington2Department of Neurology, University of Washington School of Medicine, Seattle
| | - Thomas J Montine
- Department of Pathology, University of Washington School of Medicine, Seattle
| | - Karen L Edwards
- Department of Epidemiology, University of California, Irvine, School of Medicine
| | - Cyrus P Zabetian
- Veterans Affairs Puget Sound Health Care System, Seattle, Washington2Department of Neurology, University of Washington School of Medicine, Seattle
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Collins K, Rohl B, Morgan S, Huey ED, Louis ED, Cosentino S. Mild Cognitive Impairment Subtypes in a Cohort of Elderly Essential Tremor Cases. J Int Neuropsychol Soc 2017; 23:390-399. [PMID: 28367776 PMCID: PMC5896575 DOI: 10.1017/s1355617717000170] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
OBJECTIVES Individuals with essential tremor (ET) exhibit a range of cognitive deficits generally conceptualized as "dysexecutive" or "fronto-subcortical," and thought to reflect disrupted cortico-cerebellar networks. In light of emerging evidence that ET increases risk for Alzheimer's disease (AD), it is critical to more closely examine the nature of specific cognitive deficits in ET, with particular attention to amnestic deficits that may signal early AD. METHODS We performed a cross-sectional analysis of baseline data from 128 ET cases (age 80.4±9.5 years) enrolled in a longitudinal, clinical-pathological study. Cases underwent a comprehensive battery of motor-free neuropsychological tests and a functional assessment to inform clinical diagnoses of normal cognition (ET-NC), mild cognitive impairment (MCI) (ET-MCI), or dementia (ET-D). ET-MCI was subdivided into subtypes including: amnestic single-domain (a-MCI), amnestic multi-domain (a-MCI+), non-amnestic single-domain (na-MCI), or non-amnestic multi-domain (na-MCI+). RESULTS Ninety-one (71.1%) cases were ET-NC, 24 (18.8%) were ET-MCI, and 13 (10.2%) were ET-D. Within MCI, the a-MCI+ subtype was the most common (13/24; 54.2%) followed by a-MCI (4/24; 16.7%), na-MCI+ (4/24; 16.7%), and na-MCI (3/24; 12.5%). Cases with amnestic MCI demonstrated lower recognition memory Z-scores (-2.4±1.7) than non-amnestic groups (-0.9±1.2) (p=.042). CONCLUSIONS Amnestic MCI, defined by impaired memory recall but associated with lower memory storage scores, was the most frequent MCI subtype in our study. Such impairment has not been explicitly discussed in the context of ET and may be an early hallmark of AD. Results have implications for the prognosis of specific cognitive deficits in ET. (JINS, 2017, 23, 390-399).
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Affiliation(s)
- Kathleen Collins
- Division of Movement Disorders, Department of Neurology, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Brittany Rohl
- Division of Movement Disorders, Department of Neurology, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Sarah Morgan
- Division of Movement Disorders, Department of Neurology, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Edward D. Huey
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Elan D. Louis
- Division of Movement Disorders, Department of Neurology, Yale School of Medicine, Yale University, New Haven, CT, USA
- Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, CT, USA
- Center for Neuroepidemiology and Clinical Neurological Research, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Stephanie Cosentino
- Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY, USA
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Bezdicek O, Sulc Z, Nikolai T, Stepankova H, Kopecek M, Jech R, Růžička E. A parsimonious scoring and normative calculator for the Parkinson’s disease mild cognitive impairment battery. Clin Neuropsychol 2017; 31:1231-1247. [DOI: 10.1080/13854046.2017.1293161] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Affiliation(s)
- Ondrej Bezdicek
- Department of Neurology and Centre of Clinical Neuroscience, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
- National Institute of Mental Health, Klecany, Czech Republic
| | - Zdenek Sulc
- National Institute of Mental Health, Klecany, Czech Republic
| | - Tomas Nikolai
- Department of Neurology and Centre of Clinical Neuroscience, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
| | - Hana Stepankova
- National Institute of Mental Health, Klecany, Czech Republic
| | | | - Robert Jech
- Department of Neurology and Centre of Clinical Neuroscience, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
| | - Evžen Růžička
- Department of Neurology and Centre of Clinical Neuroscience, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
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Mack J, Marsh L. Parkinson's Disease: Cognitive Impairment. FOCUS (AMERICAN PSYCHIATRIC PUBLISHING) 2017; 15:42-54. [PMID: 31975839 PMCID: PMC6519621 DOI: 10.1176/appi.focus.20160043] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Cognitive deficits are important and emerging clinical targets for psychiatrists caring for patients with Parkinson's disease (PD), a neurodegenerative disorder commonly accompanied by mood and psychotic disturbances and identified by its progressive motor abnormalities. Over the course of the disease and across all its stages, virtually every individual with PD experiences some degree of cognitive deficit, ranging from mild cognitive impairment to dementia. Across this spectrum, cognitive impairments affect functioning and quality of life, often more than motor aspects of the disease. Advances in treatments for motor deficits in PD now render the clinical significance of cognitive dysfunction more obvious, including its impact on psychiatric presentations and their treatment. Since cognitive dysfunction is underdetected and undertreated in clinical practice, holistic psychiatric care of PD patients warrants appreciation of the clinical presentation, biopsychosocial features, and treatment of cognitive impairment. Future directions for research and clinical care also discussed.
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Affiliation(s)
- Joel Mack
- Dr. Mack is with the Department of Psychiatry, Veterans Affairs Portland Health Care System and the Department of Psychiatry, Oregon Health & Science University, Portland, Oregon. Dr. Marsh is with the Mental Health Care Line, Michael E. DeBakey Veterans Affairs Medical Center, and the Departments of Psychiatry and Neurology, Baylor College of Medicine, Houston, Texas. Send correspondence to Dr. Marsh (e-mail: )
| | - Laura Marsh
- Dr. Mack is with the Department of Psychiatry, Veterans Affairs Portland Health Care System and the Department of Psychiatry, Oregon Health & Science University, Portland, Oregon. Dr. Marsh is with the Mental Health Care Line, Michael E. DeBakey Veterans Affairs Medical Center, and the Departments of Psychiatry and Neurology, Baylor College of Medicine, Houston, Texas. Send correspondence to Dr. Marsh (e-mail: )
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Murakami H, Nohara T, Shozawa H, Owan Y, Kuroda T, Yano S, Kezuka M, Kawamura M, Ono K. Effects of dopaminergic drug adjustment on executive function in different clinical stages of Parkinson's disease. Neuropsychiatr Dis Treat 2017; 13:2719-2726. [PMID: 29123404 PMCID: PMC5661838 DOI: 10.2147/ndt.s145916] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Effects of dopaminergic medication on executive function in patients with Parkinson's disease (PD) are inconsistent. OBJECTIVE We examined the effect of dopaminergic medication on executive function in 24 drug-naïve PD patients (de novo group) and in 21 PD patients on chronic dopaminergic medication (chronic medication group). METHODS PD patients without dementia were included in this study. For the de novo group patients, dopaminergic medication was initiated, and the dose was increased to improve motor symptoms. For the chronic medication group patients, dopaminergic medication was adjusted to relieve clinical problems. All participants were tested prior to and at 4-7 months after the drug initiation/adjustment. Executive function was assessed by using the Behavioral Assessment of the Dysexecutive Syndrome (BADS). Motor function was assessed by using the Unified Parkinson's Disease Rating Scale (UPDRS; part III). Improvement in executive function was compared with a simultaneous change in levodopa equivalent doses (LED) of dopaminergic medication and with improvement in motor functions. RESULTS The mean standardized BADS scores showed no significant improvement in both the groups. In the de novo group, percent improvement in the standardized BADS scores showed a significant positive correlation with the LED, but not with percent improvement in UPDRS part III. In the chronic medication group, percent improvement in the standardized BADS scores was negatively correlated with change in the LED, but not with percent improvement in UPDRS part III. Multiple regression analysis using improvement in the standardized BADS score as a dependent variable and patient's background factors (ie, age, education, disease duration, and motor and executive assessments at baseline) as independent variable showed that improvement in the executive assessment is significantly correlated with the LED only in the de novo group. CONCLUSION Effects of dopaminergic drug adjustment on executive function differ according to the patient's clinical stage and depend on LED in de novo stage.
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Affiliation(s)
- Hidetomo Murakami
- Department of Neurology, School of Medicine, Showa University, Tokyo, Japan
| | - Tetsuhito Nohara
- Department of Neurology, School of Medicine, Showa University, Tokyo, Japan
| | - Hidenobu Shozawa
- Department of Neurology, School of Medicine, Showa University, Tokyo, Japan
| | - Yoshiyuki Owan
- Department of Neurology, School of Medicine, Showa University, Tokyo, Japan
| | - Takeshi Kuroda
- Department of Neurology, School of Medicine, Showa University, Tokyo, Japan
| | - Satoshi Yano
- Department of Neurology, School of Medicine, Showa University, Tokyo, Japan
| | - Machiko Kezuka
- Department of Neurology, School of Medicine, Showa University, Tokyo, Japan
| | - Mitsuru Kawamura
- Department of Neurology, School of Medicine, Showa University, Tokyo, Japan
| | - Kenjiro Ono
- Department of Neurology, School of Medicine, Showa University, Tokyo, Japan
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Cozac VV, Chaturvedi M, Hatz F, Meyer A, Fuhr P, Gschwandtner U. Increase of EEG Spectral Theta Power Indicates Higher Risk of the Development of Severe Cognitive Decline in Parkinson's Disease after 3 Years. Front Aging Neurosci 2016; 8:284. [PMID: 27965571 PMCID: PMC5126063 DOI: 10.3389/fnagi.2016.00284] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 11/11/2016] [Indexed: 11/25/2022] Open
Abstract
Objective: We investigated quantitative electroencephalography (qEEG) and clinical parameters as potential risk factors of severe cognitive decline in Parkinson’s disease. Methods: We prospectively investigated 37 patients with Parkinson’s disease at baseline and follow-up (after 3 years). Patients had no severe cognitive impairment at baseline. We used a summary score of cognitive tests as the outcome at follow-up. At baseline we assessed motor, cognitive, and psychiatric factors; qEEG variables [global relative median power (GRMP) spectra] were obtained by a fully automated processing of high-resolution EEG (256-channels). We used linear regression models with calculation of the explained variance to evaluate the relation of baseline parameters with cognitive deterioration. Results: The following baseline parameters significantly predicted severe cognitive decline: GRMP theta (4–8 Hz), cognitive task performance in executive functions and working memory. Conclusions: Combination of neurocognitive tests and qEEG improves identification of patients with higher risk of cognitive decline in PD.
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Affiliation(s)
- Vitalii V Cozac
- Department of Neurology, Hospital of the University of Basel Basel, Switzerland
| | - Menorca Chaturvedi
- Department of Neurology, Hospital of the University of BaselBasel, Switzerland; Department of Mathematics and Computer Science, University of BaselBasel, Switzerland
| | - Florian Hatz
- Department of Neurology, Hospital of the University of Basel Basel, Switzerland
| | - Antonia Meyer
- Department of Neurology, Hospital of the University of Basel Basel, Switzerland
| | - Peter Fuhr
- Department of Neurology, Hospital of the University of Basel Basel, Switzerland
| | - Ute Gschwandtner
- Department of Neurology, Hospital of the University of Basel Basel, Switzerland
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Cooper CA, Jain N, Gallagher MD, Weintraub D, Xie SX, Berlyand Y, Espay AJ, Quinn J, Edwards KL, Montine T, Van Deerlin VM, Trojanowski J, Zabetian CP, Chen-Plotkin AS. Common variant rs356182 near SNCA defines a Parkinson's disease endophenotype. Ann Clin Transl Neurol 2016; 4:15-25. [PMID: 28078311 PMCID: PMC5221454 DOI: 10.1002/acn3.371] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Accepted: 10/04/2016] [Indexed: 01/11/2023] Open
Abstract
Objective Parkinson's disease (PD) presents clinically with several motor subtypes that exhibit variable treatment response and prognosis. Here, we investigated genetic variants for their potential association with PD motor phenotype and progression. Methods We screened 10 SNPs, previously associated with PD risk, for association with tremor‐dominant (TD) versus postural‐instability gait disorder (PIGD) motor subtypes. SNPs that correlated with the TD/PIGD ratio in a discovery cohort of 251 PD patients were then evaluated in a multi‐site replication cohort of 559 PD patients. SNPs associated with motor phenotype in both cross‐sectional cohorts were next evaluated for association with (1) rates of motor progression in a longitudinal subgroup of 230 PD patients and (2) brain alpha‐synuclein (SNCA) expression in the GTEx (Genotype‐Tissue Expression project) consortium database. Results Genotype at rs356182, near SNCA, correlated with the TD/PIGD ratio in both the discovery (Bonferroni‐corrected P = 0.04) and replication cohorts (P = 0.02). The rs356182 GG genotype was associated with a more tremor‐predominant phenotype and predicted a slower rate of motor progression (1‐point difference in annual rate of UPDRS‐III motor score change, P = 0.01). The rs356182 genotype was associated with SNCA expression in the cerebellum (P = 0.005). Interpretation Our study demonstrates that the GG genotype at rs356182 provides molecular definition for a clinically important endophenotype associated with (1) more tremor‐predominant motor phenomenology, (2) slower rates of motor progression, and (3) decreased brain expression of SNCA. Such molecularly defined endophenotyping in PD may benefit both clinical trial design and tailoring of clinical care as we enter the era of precision medicine.
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Affiliation(s)
- Christine A Cooper
- Department of Neurology Medical University of South Carolina Charleston South Carolina; Department of Neurology Perelman School of Medicine at the University of Pennsylvania Philadelphia Pennsylvania
| | - Nimansha Jain
- Department of Neurology Perelman School of Medicine at the University of Pennsylvania Philadelphia Pennsylvania
| | - Michael D Gallagher
- Department of Neurology Perelman School of Medicine at the University of Pennsylvania Philadelphia Pennsylvania
| | - Daniel Weintraub
- Department of Psychiatry Perelman School of Medicine at the University of Pennsylvania Philadelphia Pennsylvania
| | - Sharon X Xie
- Department of Biostatistics and Epidemiology Perelman School of Medicine at the University of Pennsylvania Philadelphia Pennsylvania
| | - Yosef Berlyand
- Department of Neurology Perelman School of Medicine at the University of Pennsylvania Philadelphia Pennsylvania; Harvard Medical School Boston Massachusetts
| | - Alberto J Espay
- Department of Neurology University of Cincinnati Cincinnati Ohio
| | - Joseph Quinn
- Department of Neurology Oregon Health and Science University Portland Oregon
| | - Karen L Edwards
- Department of Epidemiology University of California Irvine Irvine California
| | - Thomas Montine
- Department of Pathology University of Washington Seattle Washington
| | - Vivianna M Van Deerlin
- Department of Pathology and Laboratory Medicine Perelman School of Medicine at the University of Pennsylvania Philadelphia Pennsylvania
| | - John Trojanowski
- Department of Pathology and Laboratory Medicine Perelman School of Medicine at the University of Pennsylvania Philadelphia Pennsylvania
| | - Cyrus P Zabetian
- Department of Neurology VA Puget Sound Health Care System University of Washington Seattle Washington
| | - Alice S Chen-Plotkin
- Department of Neurology Perelman School of Medicine at the University of Pennsylvania Philadelphia Pennsylvania
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García AM, Carrillo F, Orozco-Arroyave JR, Trujillo N, Vargas Bonilla JF, Fittipaldi S, Adolfi F, Nöth E, Sigman M, Fernández Slezak D, Ibáñez A, Cecchi GA. How language flows when movements don't: An automated analysis of spontaneous discourse in Parkinson's disease. BRAIN AND LANGUAGE 2016; 162:19-28. [PMID: 27501386 DOI: 10.1016/j.bandl.2016.07.008] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2016] [Revised: 04/20/2016] [Accepted: 07/25/2016] [Indexed: 06/06/2023]
Abstract
To assess the impact of Parkinson's disease (PD) on spontaneous discourse, we conducted computerized analyses of brief monologues produced by 51 patients and 50 controls. We explored differences in semantic fields (via latent semantic analysis), grammatical choices (using part-of-speech tagging), and word-level repetitions (with graph embedding tools). Although overall output was quantitatively similar between groups, patients relied less heavily on action-related concepts and used more subordinate structures. Also, a classification tool operating on grammatical patterns identified monologues as pertaining to patients or controls with 75% accuracy. Finally, while the incidence of dysfluent word repetitions was similar between groups, it allowed inferring the patients' level of motor impairment with 77% accuracy. Our results highlight the relevance of studying naturalistic discourse features to tap the integrity of neural (and, particularly, motor) networks, beyond the possibilities of standard token-level instruments.
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Affiliation(s)
- Adolfo M García
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, Pacheco de Melo 1860, C1126AAB Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Av. Rivadavia 1917, C1033AAJ Buenos Aires, Argentina; Faculty of Elementary and Special Education (FEEyE), National University of Cuyo (UNCuyo), Sobremonte 74, C5500 Mendoza, Argentina.
| | - Facundo Carrillo
- National Scientific and Technical Research Council (CONICET), Av. Rivadavia 1917, C1033AAJ Buenos Aires, Argentina; Department of Computer Science, School of Sciences, University of Buenos Aires, Pabellón I, Ciudad Universitaria, C1428EGA Buenos Aires, Argentina
| | - Juan Rafael Orozco-Arroyave
- Faculty of Engineering, University of Antioquia, Calle 67 N° 53-108, C1226 Medellín, Colombia; Pattern Recognition Lab, Friedrich-Alexander-Universität, Martensstrasse 3, 91058 Erlangen-Nürnberg, Germany
| | - Natalia Trujillo
- Neuroscience Group, Faculty of Medicine, University of Antioquia, Calle 62 N° 52-59, C1226 Medellín, Colombia; School of Public Health, University of Antioquia, Calle 62 N° 52-59, C1226 Medellín, Colombia
| | - Jesús F Vargas Bonilla
- Faculty of Engineering, University of Antioquia, Calle 67 N° 53-108, C1226 Medellín, Colombia
| | - Sol Fittipaldi
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, Pacheco de Melo 1860, C1126AAB Buenos Aires, Argentina
| | - Federico Adolfi
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, Pacheco de Melo 1860, C1126AAB Buenos Aires, Argentina
| | - Elmar Nöth
- Pattern Recognition Lab, Friedrich-Alexander-Universität, Martensstrasse 3, 91058 Erlangen-Nürnberg, Germany
| | - Mariano Sigman
- Laboratory of Integrative Neuroscience, Torcuato Di Tella University, Av. Figueroa Alcorta 7350, C1428BCW Buenos Aires, Argentina
| | - Diego Fernández Slezak
- National Scientific and Technical Research Council (CONICET), Av. Rivadavia 1917, C1033AAJ Buenos Aires, Argentina; Department of Computer Science, School of Sciences, University of Buenos Aires, Pabellón I, Ciudad Universitaria, C1428EGA Buenos Aires, Argentina
| | - Agustín Ibáñez
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, Pacheco de Melo 1860, C1126AAB Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Av. Rivadavia 1917, C1033AAJ Buenos Aires, Argentina; Universidad Autónoma del Caribe, Calle 90, N° 46-112, C2754 Barranquilla, Colombia; Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez, Diagonal Las Torres 2640, Santiago, Chile; Centre of Excellence in Cognition and its Disorders, Australian Research Council (ACR), 16 University Avenue, Macquarie University, Sydney, NSW 2109, Australia
| | - Guillermo A Cecchi
- Computational Biology Center, IBM, T.J. Watson Research Center, Yorktown Heights, 1101 Kitchawan Rd., Yorktwon Heights, New York, NY 10598, USA
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Kalbe E, Rehberg SP, Heber I, Kronenbuerger M, Schulz JB, Storch A, Linse K, Schneider C, Gräber S, Liepelt-Scarfone I, Berg D, Dams J, Balzer-Geldsetzer M, Hilker R, Oberschmidt C, Witt K, Schmidt N, Mollenhauer B, Trenkwalder C, Spottke A, Roeske S, Wittchen HU, Riedel O, Dodel R. Subtypes of mild cognitive impairment in patients with Parkinson's disease: evidence from the LANDSCAPE study. J Neurol Neurosurg Psychiatry 2016; 87:1099-105. [PMID: 27401782 DOI: 10.1136/jnnp-2016-313838] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Accepted: 06/21/2016] [Indexed: 01/07/2023]
Abstract
OBJECTIVE Inconsistent results exist regarding the cognitive profile in patients with Parkinson's disease with mild cognitive impairment (PD-MCI). We aimed at providing data on this topic from a large cohort of patients with PD-MCI. METHODS Sociodemographic, clinical and neuropsychological baseline data from patients with PD-MCI recruited in the multicentre, prospective, observational DEMPARK/LANDSCAPE study were analysed. RESULTS 269 patients with PD-MCI (age 67.8±7.4, Unified Parkinson's Disease Rating Scale (UPDRS-III) scores 23.2±11.6) were included. PD-MCI subtypes were 39.4% non-amnestic single domain, 30.5% amnestic multiple domain, 23.4% non-amnestic multiple domain and 6.7% amnestic single domain. Executive functions were most frequently impaired. The most sensitive tests to detect cognitive dysfunctions were the Modified Card Sorting Test, digit span backwards and word list learning direct recall. Multiple stepwise regression analyses showed that global cognition, gender and age, but not education or disease-related parameters predicted PD-MCI subtypes. CONCLUSIONS This study with the so far largest number of prospectively recruited patients with PD-MCI indicates that non-amnestic PD-MCI is more frequent than amnestic PD-MCI; executive dysfunctions are the most typical cognitive symptom in PD-MCI; and age, gender and global cognition predict the PD-MCI subtype. Longitudinal data are needed to test the hypothesis that patients with PD-MCI with specific cognitive profiles have different risks to develop dementia.
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Affiliation(s)
- Elke Kalbe
- Medical Psychology, Neuropsychology and Gender Studies, Center for Neuropsychological Diagnostics and Intervention (CeNDI), University Hospital Cologne, Cologne, Germany
| | - Sarah Petra Rehberg
- Medical Psychology, Neuropsychology and Gender Studies, Center for Neuropsychological Diagnostics and Intervention (CeNDI), University Hospital Cologne, Cologne, Germany
| | - Ines Heber
- Department of Neurology, University Hospital, RWTH University Aachen, Aachen, Germany
| | - Martin Kronenbuerger
- Department of Neurology, University Hospital, RWTH University Aachen, Aachen, Germany
| | - Jörg B Schulz
- Department of Neurology, University Hospital, RWTH University Aachen, Aachen, Germany JARA Brain Institute 2, RWTH University and Forschungszentrum Jülich, Germany
| | - Alexander Storch
- Division of Neurodegenerative Diseases, Department of Neurology, Technische Universität Dresden, Dresden, Germany Department of Neurology, University of Rostock, Rostock, Germany
| | - Katharina Linse
- Division of Neurodegenerative Diseases, Department of Neurology, Technische Universität Dresden, Dresden, Germany
| | - Christine Schneider
- Division of Neurodegenerative Diseases, Department of Neurology, Technische Universität Dresden, Dresden, Germany
| | - Susanne Gräber
- German Center of Neurodegenerative Diseases and Hertie Institute for Clinical Brain Research, Tübingen, Germany
| | - Inga Liepelt-Scarfone
- German Center of Neurodegenerative Diseases and Hertie Institute for Clinical Brain Research, Tübingen, Germany
| | - Daniela Berg
- German Center of Neurodegenerative Diseases and Hertie Institute for Clinical Brain Research, Tübingen, Germany Department of Neurology, Christian Albrecht University, Kiel, Germany
| | - Judith Dams
- Department of Neurology, Philipps University Marburg, Marburg, Germany
| | | | - Rüdiger Hilker
- Department of Neurology, J.W. Goethe University, Frankfurt/Main, Germany
| | - Carola Oberschmidt
- Department of Neurology, J.W. Goethe University, Frankfurt/Main, Germany
| | - Karsten Witt
- Department of Neurology, Christian Albrecht University, Kiel, Germany
| | - Nele Schmidt
- Department of Neurology, Christian Albrecht University, Kiel, Germany
| | - Brit Mollenhauer
- Paracelsus-Elena Clinic, Centre of Parkinsonism and Movement Disorders, Kassel, Germany
| | - Claudia Trenkwalder
- Paracelsus-Elena Clinic, Centre of Parkinsonism and Movement Disorders, Kassel, Germany
| | - Annika Spottke
- Department of Neurology, University Hospital Bonn, and German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Sandra Roeske
- Department of Neurology, University Hospital Bonn, and German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Hans-Ulrich Wittchen
- Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Oliver Riedel
- Department of Clinical Epidemiology, Leibniz Institute for Prevention Research and Epidemiology, Bremen, Germany
| | - Richard Dodel
- Department of Neurology, Philipps University Marburg, Marburg, Germany
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45
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Lawrence BJ, Gasson N, Loftus AM. Prevalence and Subtypes of Mild Cognitive Impairment in Parkinson's Disease. Sci Rep 2016; 6:33929. [PMID: 27650569 PMCID: PMC5030649 DOI: 10.1038/srep33929] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Accepted: 09/06/2016] [Indexed: 11/09/2022] Open
Abstract
The current study examined the prevalence and subtypes of Mild Cognitive Impairment (MCI) in an Australian sample of people with Parkinson’s Disease (PD). Seventy participants with PD completed neuropsychological assessments of their cognitive performance, using MDS Task Force Level II diagnostic criteria for PD-MCI. A cut-off score of less than one standard deviation (SD) below normative data determined impaired performance on a neuropsychological test. Of 70 participants, 45 (64%) met Level II diagnostic criteria for PD-MCI. Among those with PD-MCI, 42 (93%) were identified as having multiple domain impairment (28 as amnestic multiple domain and 14 as nonamnestic multiple domain). Single domain impairment was less frequent (2 amnestic/1 nonamnestic). Significant differences were found between the PD-MCI and Normal Cognition groups, across all cognitive domains. Multiple domain cognitive impairment was more frequent than single domain impairment in an Australian sample of people with PD. However, PD-MCI is heterogeneous and current prevalence and subtyping statistics may be an artifact of variable application methods of the criteria (e.g., cut off scores and number of tests). Future longitudinal studies refining the criteria will assist with subtyping the progression of PD-MCI, while identifying individuals who may benefit from pharmacological and nonpharmacological interventions.
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Affiliation(s)
- Blake J Lawrence
- Curtin Neuroscience Laboratory, School of Psychology and Speech Pathology, Curtin University, Kent Street, Bentley, Western Australia, 6102, Australia.,ParkC Collaborative Research Group, Curtin University, Kent Street, Bentley, Western Australia, 6102, Australia
| | - Natalie Gasson
- Curtin Neuroscience Laboratory, School of Psychology and Speech Pathology, Curtin University, Kent Street, Bentley, Western Australia, 6102, Australia.,ParkC Collaborative Research Group, Curtin University, Kent Street, Bentley, Western Australia, 6102, Australia
| | - Andrea M Loftus
- Curtin Neuroscience Laboratory, School of Psychology and Speech Pathology, Curtin University, Kent Street, Bentley, Western Australia, 6102, Australia.,ParkC Collaborative Research Group, Curtin University, Kent Street, Bentley, Western Australia, 6102, Australia
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Biundo R, Weis L, Antonini A. Cognitive decline in Parkinson's disease: the complex picture. NPJ Parkinsons Dis 2016; 2:16018. [PMID: 28725699 PMCID: PMC5516581 DOI: 10.1038/npjparkd.2016.18] [Citation(s) in RCA: 78] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Revised: 06/13/2016] [Accepted: 06/14/2016] [Indexed: 01/02/2023] Open
Abstract
Mild cognitive impairment (PD-MCI) and dementia (PDD) are among the most frequent non-motor symptoms in Parkinson's disease (PD). PD-MCI is six times more likely than age-matched controls to develop dementia and the PDD prevalence is 80% after 15-20 years of disease. Therefore, research has focused on the identification of early dementia biomarkers including specific cognitive at-risk profiles hoping to implement therapeutic interventions when they are most likely to be efficacious. However, given the heterogeneous neuropathological, neurochemical, and neuropsychological nature of cognitive deficits, definition of a comprehensive cognitive model of PDD is a challenge. Evidence from neuroimaging studies using different methods and techniques suggests that in addition to degeneration of the dopaminergic system, other mechanisms have a role including β-amyloid and tau deposition, and that specific cognitive scales could help identifying a malignant profile. Prospective studies combining neuroimaging techniques and specific cognitive tests are required to define the interplay between the various neurodegenerative processes and the contribution of structural disconnection in brain functional networks, heralding the development of dementia in PD.
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Affiliation(s)
- Roberta Biundo
- Parkinson’s Disease and Movement Disorder Department, “IRCCS, San Camillo” Rehabilitation Hospital, Venice-Lido, Italy
| | - Luca Weis
- Parkinson’s Disease and Movement Disorder Department, “IRCCS, San Camillo” Rehabilitation Hospital, Venice-Lido, Italy
| | - Angelo Antonini
- Parkinson’s Disease and Movement Disorder Department, “IRCCS, San Camillo” Rehabilitation Hospital, Venice-Lido, Italy
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Abstract
Dementia is a frequent complication of Parkinson disease (PD) with a yearly incidence of around 10% of patients with PD. Lewy body pathology is the most important factor in the development of Parkinson disease dementia (PDD) and there is evidence for a synergistic effect with β-amyloid. The clinical phenotype in PDD extends beyond the dysexecutive syndrome that is often present in early PD and encompasses deficits in recognition memory, attention, and visual perception. Sleep disturbances, hallucinations, neuroleptic sensitivity, and fluctuations are often present. This review provides an update on current knowledge of PDD including aspects of epidemiology, pathology, clinical presentation, management, and prognosis.
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Affiliation(s)
- Sara Garcia-Ptacek
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden Department of Geriatric Medicine, Memory Clinic, Karolinska University Hospital, Stockholm, Sweden
| | - Milica G Kramberger
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden Department of Neurology, University Medical Centre Ljubljana, Ljubljana, Slovenia
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48
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Bezdicek O, Nikolai T, Michalec J, Růžička F, Havránková P, Roth J, Jech R, Růžička E. The Diagnostic Accuracy of Parkinson's Disease Mild Cognitive Impairment Battery Using the Movement Disorder Society Task Force Criteria. Mov Disord Clin Pract 2016; 4:237-244. [PMID: 30363396 DOI: 10.1002/mdc3.12391] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2015] [Revised: 04/27/2016] [Accepted: 05/10/2016] [Indexed: 11/11/2022] Open
Abstract
Background The aim of the present study was to provide empirical evidence regarding the classification accuracy of the International Parkinson and Movement Disorder Society (MDS) neuropsychological battery (NB) in the determination of Parkinson's disease mild cognitive impairment (PD-MCI). Methods The present cross-sectional study included 106 PD patients subjected to PD-MCI classification at Level I and 120 healthy controls (HCs). All HC and PD subjects were then assessed with MDS-NB at Level II and matched according to age and education using different thresholds (1.5 and 2.0 standard deviations [SDs] below average). Results We found that Level I and II resulted in different classifications of PD-MCI status. Detection thresholds of -1.5 SD and -2.0 SDs at Level II had also a significant impact on the discriminative validity of all measures in the MDS neuropsychological battery, based on area under the curve analyses. Overall, semantic fluency showed the highest potential in all comparisons not only between PD-MCI and HC, but also between PD-MCI and PD with no deficit (PD-ND). Conclusions Our results show that the battery at Level II is applicable and that some measures, such as semantic fluency, have high discriminative validity in the detection of PD-MCI versus PD-ND and HCs.
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Affiliation(s)
- Ondrej Bezdicek
- Charles University in Prague, First Faculty of Medicine and General University Hospital Department of Neurology and Center of Clinical Neuroscience Prague Czech Republic
| | - Tomas Nikolai
- Charles University in Prague, First Faculty of Medicine and General University Hospital Department of Neurology and Center of Clinical Neuroscience Prague Czech Republic
| | - Jiri Michalec
- Charles University in Prague, First Faculty of Medicine and General University Hospital Department of Psychiatry Prague Czech Republic
| | - Filip Růžička
- Charles University in Prague, First Faculty of Medicine and General University Hospital Department of Neurology and Center of Clinical Neuroscience Prague Czech Republic
| | - Petra Havránková
- Charles University in Prague, First Faculty of Medicine and General University Hospital Department of Neurology and Center of Clinical Neuroscience Prague Czech Republic
| | - Jan Roth
- Charles University in Prague, First Faculty of Medicine and General University Hospital Department of Neurology and Center of Clinical Neuroscience Prague Czech Republic
| | - Robert Jech
- Charles University in Prague, First Faculty of Medicine and General University Hospital Department of Neurology and Center of Clinical Neuroscience Prague Czech Republic
| | - Evžen Růžička
- Charles University in Prague, First Faculty of Medicine and General University Hospital Department of Neurology and Center of Clinical Neuroscience Prague Czech Republic
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Besser LM, Litvan I, Monsell SE, Mock C, Weintraub S, Zhou XH, Kukull W. Mild cognitive impairment in Parkinson's disease versus Alzheimer's disease. Parkinsonism Relat Disord 2016; 27:54-60. [PMID: 27089852 DOI: 10.1016/j.parkreldis.2016.04.007] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2015] [Revised: 03/28/2016] [Accepted: 04/08/2016] [Indexed: 12/15/2022]
Abstract
INTRODUCTION No known studies have compared longitudinal characteristics between individuals with incident mild cognitive impairment due to Parkinson's disease (PD-MCI) versus Alzheimer's Disease (AD-MCI). METHODS We used longitudinal data from the National Alzheimer's Coordinating Center's Uniform Data Set to compare 41 PD-MCI and 191 AD-MCI participants according to their demographics, presence of ≥1 APOE e4 allele, and baseline and change over time in clinical characteristics, neuropsychological test scores, and Clinical Dementia Rating sum of boxes (CDR-SB). Multivariable linear regression models with generalized estimating equations were used to account for clustered data and to test for baseline and longitudinal differences in neuropsychological test scores. RESULTS PD-MCI and AD-MCI participants differed by many demographic and clinical characteristics. Significantly fewer PD-MCI participants developed dementia over one year. Compared to AD-MCI participants, PD-MCI participants performed better at baseline and over time on a global measure of cognition (Mini Mental State Exam), memory measures (immediate and delayed Logical Memory), and a language measure (Boston Naming Test), and additionally performed better over time on an attention measure (Digit Span Forward), a language measure (Vegetable List), a processing speed measure (Digit Symbol), and an overall measure of memory and functional impairment (CDR-SB). CONCLUSION Our study provides further evidence that PD-MCI is clinically distinct from AD-MCI and requires different tools for diagnosis and monitoring clinical progression. More importantly, this study suggests that PD-MCI takes longer to convert into dementia than AD-MCI, findings that require replication by other studies.
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Affiliation(s)
- Lilah M Besser
- National Alzheimer's Coordinating Center, University of Washington, 4311 11th Ave NE, Suite 300, Seattle, WA, 98105, USA.
| | - Irene Litvan
- University of California San Diego, Department of Neurosciences, National Parkinson Foundation Movement Disorder Center of Excellence, 8950 Villa La Jolla Drive, Suite C112, La Jolla, CA, 92037, USA.
| | - Sarah E Monsell
- National Alzheimer's Coordinating Center, University of Washington, 4311 11th Ave NE, Suite 300, Seattle, WA, 98105, USA.
| | - Charles Mock
- National Alzheimer's Coordinating Center, University of Washington, 4311 11th Ave NE, Suite 300, Seattle, WA, 98105, USA.
| | - Sandra Weintraub
- Cognitive Neurology and Alzheimer's Disease Center, and Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, 320 E Superior, Searle 11-467, Chicago, IL, 60611, USA.
| | - Xiao-Hua Zhou
- National Alzheimer's Coordinating Center, University of Washington, 4311 11th Ave NE, Suite 300, Seattle, WA, 98105, USA.
| | - Walter Kukull
- National Alzheimer's Coordinating Center, University of Washington, 4311 11th Ave NE, Suite 300, Seattle, WA, 98105, USA.
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Stefanova E, Žiropadja L, Stojković T, Stanković I, Tomić A, Ječmenica-Lukić M, Petrović I, Kostić V. Mild Cognitive Impairment in Early Parkinson's Disease Using the Movement Disorder Society Task Force Criteria: Cross-Sectional Study in Hoehn and Yahr Stage 1. Dement Geriatr Cogn Disord 2016; 40:199-209. [PMID: 26226988 DOI: 10.1159/000433421] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/18/2015] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Mild cognitive impairment (MCI) in Parkinson's disease (PD) is common and confers a higher risk for developing dementia. METHODS In this cross-sectional study of MCI in PD conducted at a university hospital, a comprehensive neuropsychological battery covering five domains (attention/working memory, executive, verbal, and visual memory, language, and visuospatial) was administered to 111 nondemented PD patients in Hoehn and Yahr stage 1 and to 105 healthy matched control subjects (HC). MCI was diagnosed according to level 2 of the Movement Disorder Society Task Force criteria. RESULTS Criteria for MCI associated with PD (PD-MCI) were fulfilled by 24% of PD patients in the initial stage of the disease at the z cutoff scores of -1.5 SD in contrast to 7% of HC fulfilling criteria for MCI. Memory and visuospatial domains were the most commonly affected at -1.5 SD. PD-MCI patients mostly had a multiple-domain MCI subtype (78%). They presented a more severe bradykinesia and higher mood and apathy scores in comparison with cognitively normal PD patients. Basic motor scores predicted performance on some cognitive tests and specific cognitive-motor relationships emerged. CONCLUSIONS MCI, predominantly of a multiple-domain subtype, was quite prevalent even in the initial stage of PD.
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Affiliation(s)
- Elka Stefanova
- Facultie of Medicine, University of Belgrade, Belgrade, Serbia
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