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Xue C, Kowshik SS, Lteif D, Puducheri S, Jasodanand VH, Zhou OT, Walia AS, Guney OB, Zhang JD, Pham ST, Kaliaev A, Andreu-Arasa VC, Dwyer BC, Farris CW, Hao H, Kedar S, Mian AZ, Murman DL, O'Shea SA, Paul AB, Rohatgi S, Saint-Hilaire MH, Sartor EA, Setty BN, Small JE, Swaminathan A, Taraschenko O, Yuan J, Zhou Y, Zhu S, Karjadi C, Alvin Ang TF, Bargal SA, Plummer BA, Poston KL, Ahangaran M, Au R, Kolachalama VB. AI-based differential diagnosis of dementia etiologies on multimodal data. Nat Med 2024:10.1038/s41591-024-03118-z. [PMID: 38965435 DOI: 10.1038/s41591-024-03118-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 06/06/2024] [Indexed: 07/06/2024]
Abstract
Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care.
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Affiliation(s)
- Chonghua Xue
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Electrical & Computer Engineering, Boston University, Boston, MA, USA
| | - Sahana S Kowshik
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Faculty of Computing & Data Sciences, Boston University, Boston, MA, USA
| | - Diala Lteif
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Computer Science, Boston University, Boston, MA, USA
| | - Shreyas Puducheri
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Varuna H Jasodanand
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Olivia T Zhou
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Anika S Walia
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Osman B Guney
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Electrical & Computer Engineering, Boston University, Boston, MA, USA
| | - J Diana Zhang
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- School of Chemistry, University of New South Wales, Sydney, Australia
| | - Serena T Pham
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Artem Kaliaev
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - V Carlota Andreu-Arasa
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Brigid C Dwyer
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Chad W Farris
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Honglin Hao
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Sachin Kedar
- Departments of Neurology & Ophthalmology, Emory University School of Medicine, Atlanta, GA, USA
| | - Asim Z Mian
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Daniel L Murman
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, USA
| | - Sarah A O'Shea
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Aaron B Paul
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Saurabh Rohatgi
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Emmett A Sartor
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Bindu N Setty
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Juan E Small
- Department of Radiology, Lahey Hospital & Medical Center, Burlington, MA, USA
| | | | - Olga Taraschenko
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, USA
| | - Jing Yuan
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Yan Zhou
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Shuhan Zhu
- Department of Neurology, Brigham & Women's Hospital, Boston, MA, USA
| | - Cody Karjadi
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Ting Fang Alvin Ang
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Sarah A Bargal
- Department of Computer Science, Georgetown University, Washington, DC, USA
| | - Bryan A Plummer
- Department of Computer Science, Boston University, Boston, MA, USA
| | | | - Meysam Ahangaran
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Rhoda Au
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Boston University Alzheimer's Disease Research Center, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Vijaya B Kolachalama
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
- Faculty of Computing & Data Sciences, Boston University, Boston, MA, USA.
- Department of Computer Science, Boston University, Boston, MA, USA.
- Boston University Alzheimer's Disease Research Center, Boston, MA, USA.
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Carvalho de Abreu DC, Pieruccini-Faria F, Son S, Montero-Odasso M, Camicioli R. Is white matter hyperintensity burden associated with cognitive and motor impairment in patients with parkinson's disease? A systematic review and meta-analysis. Neurosci Biobehav Rev 2024; 161:105677. [PMID: 38636832 DOI: 10.1016/j.neubiorev.2024.105677] [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: 11/29/2022] [Revised: 02/08/2024] [Accepted: 04/12/2024] [Indexed: 04/20/2024]
Abstract
White matter damage quantified as white matter hyperintensities (WMH) may aggravate cognitive and motor impairments, but whether and how WMH burden impacts these problems in Parkinson's disease (PD) is not fully understood. This study aimed to examine the association between WMH and cognitive and motor performance in PD through a systematic review and meta-analysis. We compared the WMH burden across the cognitive spectrum (cognitively normal, mild cognitive impairment, dementia) in PD including controls. Motor signs were compared in PD with low/negative and high/positive WMH burden. We compared baseline WMH burden of PD who did and did not convert to MCI or dementia. MEDLINE and EMBASE databases were used to conduct the literature search resulting in 50 studies included for data extraction. Increased WMH burden was found in individuals with PD compared with individuals without PD (i.e. control) and across the cognitive spectrum in PD (i.e. PD, PD-MCI, PDD). Individuals with PD with high/positive WMH burden had worse global cognition, executive function, and attention. Similarly, PD with high/positive WMH presented worse motor signs compared with individuals presenting low/negative WMH burden. Only three longitudinal studies were retrieved from our search and they showed that PD who converted to MCI or dementia, did not have significantly higher WMH burden at baseline, although no data was provided on WMH burden changes during the follow up. We conclude, based on cross-sectional studies, that WMH burden appears to increase with PD worse cognitive and motor status in PD.
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Affiliation(s)
- Daniela Cristina Carvalho de Abreu
- Post-doctoral fellow at Gait and Brain Lab, University of Western Ontario, Canada, and Associated Professor of Physiotherapy Course, Department of Health Sciences, Rehabilitation and Functional Performance Program, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil.
| | - Frederico Pieruccini-Faria
- Deparment of Medicine, Schulich School of Medicine and Dentistry, The University of Western Ontario, Lawson Health Research Institute, St. Josephs Health Care, Parkwood Institute, Deputy Director of the Gait & Brain Lab, Canada
| | - Surim Son
- Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, University of Western Ontario, Statistician, Departments of Medicine, University of Western Ontario, Canada, Parkwood Institute, Lawson Health Research Institute, Canada
| | - Manuel Montero-Odasso
- Departments of Medicine, and Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, The University of Western Ontario, Canada Director of Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, Canada
| | - Richard Camicioli
- Department of Medicine, Division of Neurology, University of Alberta, Canada
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Xiao Y, Gui Y, Dai J, Zhao H, Rao Z, Luo D, Deng X, Xiao X. Mediation of White Matter Alterations in the Association Between Ventricular Dilation and Cognitive Decline in Hydrocephalus Patients: An MRI Study. J Magn Reson Imaging 2024. [PMID: 38767272 DOI: 10.1002/jmri.29452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 05/02/2024] [Accepted: 05/02/2024] [Indexed: 05/22/2024] Open
Abstract
BACKGROUND Cognitive impairment is commonly observed in hydrocephalus patients. Ventricular enlargement compresses brain parenchyma, especially the white matter (WM). PURPOSE To investigate whether the relationship between ventricular dilation and cognitive decline in hydrocephalus patients is mediated by WM alterations. STUDY TYPE Retrospective. POPULATION 51 communicating hydrocephalus patients (median age, 54 years), 50 obstructive hydrocephalus patients (median age, 49 years), and 53 control subjects (median age, 50 years). FIELD STRENGTH/SEQUENCE Diffusion tensors imaging, 3D T1 BRAVO, 3D FIESTA, CUBE T2, and FLAIR sequences at 3T. ASSESSMENT DTI parameters (skeletonized fractional anisotropy (FA), skeletonized mean diffusivity (MD), and peak width of skeletonized mean diffusivity p(PSMD)) were extracted using FSL software. Global, periventricular, and deep white matter hyperintensity (WMH) volumes, degree of ventricular enlargement (Evans index), and other conventional imaging markers (number of lacunes and perivascular spaces, intracranial and brain volume) were extracted using united imaging intelligence. Cognitive tests included Montreal cognitive assessment (MoCA), clock drawing test (CDT), and vocabulary fluency test (VFT). STATISTICAL TESTS Multivariable linear regression analysis, mediation analyses, and dominance analysis. P-value <0.05 was considered significant. RESULTS The degree of ventricular dilation, DTI parameters, and cognitive function scores were interrelated. The skeletonized FA values (β = -0.0917, 95% confidence interval (CI): -0.205, -0.024) and normalized global WMH volume (β = -0.0635, 95% CI: -0.13, -0.0005) together mediated 37.2% of the association between Evans index and MoCA. A comparable causal pathway was found for periventricular WMHs but not for deep WMHs. Dominance analysis indicated skeletonized FA values had a greater impact on cognition than WMH volume. The skeletonized FA values also mediated the association between Evans index and CDT (β = -0.0897, 95% CI: -0.165, -0.026) and VFT (β = -0.1589, 95% CI: -0.27, -0.083). CONCLUSION WM alterations were causal mediators between ventricular dilation and cognitive decline in hydrocephalus patients. EVIDENCE LEVEL 3. TECHNICAL EFFICACY Stage 3.
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Affiliation(s)
- Yawen Xiao
- Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Yifei Gui
- Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Jiankun Dai
- GE Healthcare, MR Research China, Beijing, China
| | - Heng Zhao
- Department of Radiology, First Affiliated Hospital of University of South China, Hengyang, China
| | - Zhongliang Rao
- Department of Radiology, The Third Hospital of Nanchang, Nanchang, China
| | - Dan Luo
- Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Xinru Deng
- Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Xinlan Xiao
- Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
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Doskas T, Vadikolias K, Ntoskas K, Vavougios GD, Tsiptsios D, Stamati P, Liampas I, Siokas V, Messinis L, Nasios G, Dardiotis E. Neurocognitive Impairment and Social Cognition in Parkinson's Disease Patients. Neurol Int 2024; 16:432-449. [PMID: 38668129 PMCID: PMC11054167 DOI: 10.3390/neurolint16020032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 04/06/2024] [Accepted: 04/11/2024] [Indexed: 04/29/2024] Open
Abstract
In addition to motor symptoms, neurocognitive impairment (NCI) affects patients with prodromal Parkinson's disease (PD). NCI in PD ranges from subjective cognitive complaints to dementia. The purpose of this review is to present the available evidence of NCI in PD and highlight the heterogeneity of NCI phenotypes as well as the range of factors that contribute to NCI onset and progression. A review of publications related to NCI in PD up to March 2023 was performed using PubMed/Medline. There is an interconnection between the neurocognitive and motor symptoms of the disease, suggesting a common underlying pathophysiology as well as an interconnection between NCI and non-motor symptoms, such as mood disorders, which may contribute to confounding NCI. Motor and non-motor symptom evaluation could be used prognostically for NCI onset and progression in combination with imaging, laboratory, and genetic data. Additionally, the implications of NCI on the social cognition of afflicted patients warrant its prompt management. The etiology of NCI onset and its progression in PD is multifactorial and its effects are equally grave as the motor effects. This review highlights the importance of the prompt identification of subjective cognitive complaints in PD patients and NCI management.
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Affiliation(s)
- Triantafyllos Doskas
- Department of Neurology, Athens Naval Hospital, 11521 Athens, Greece;
- Department of Neurology, General University Hospital of Alexandroupoli, 68100 Alexandroupoli, Greece; (K.V.); (D.T.)
| | - Konstantinos Vadikolias
- Department of Neurology, General University Hospital of Alexandroupoli, 68100 Alexandroupoli, Greece; (K.V.); (D.T.)
| | | | - George D. Vavougios
- Department of Neurology, Athens Naval Hospital, 11521 Athens, Greece;
- Department of Neurology, Faculty of Medicine, University of Cyprus, 1678 Lefkosia, Cyprus
- Department of Respiratory Medicine, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41500 Larissa, Greece
| | - Dimitrios Tsiptsios
- Department of Neurology, General University Hospital of Alexandroupoli, 68100 Alexandroupoli, Greece; (K.V.); (D.T.)
| | - Polyxeni Stamati
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (P.S.); (I.L.); (V.S.); (E.D.)
| | - Ioannis Liampas
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (P.S.); (I.L.); (V.S.); (E.D.)
| | - Vasileios Siokas
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (P.S.); (I.L.); (V.S.); (E.D.)
| | - Lambros Messinis
- School of Psychology, Laboratory of Neuropsychology and Behavioural Neuroscience, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
| | - Grigorios Nasios
- Department of Speech and Language Therapy, School of Health Sciences, University of Ioannina, 45500 Ioannina, Greece;
| | - Efthimios Dardiotis
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (P.S.); (I.L.); (V.S.); (E.D.)
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Xue C, Kowshik SS, Lteif D, Puducheri S, Jasodanand VH, Zhou OT, Walia AS, Guney OB, Zhang JD, Pham ST, Kaliaev A, Andreu-Arasa VC, Dwyer BC, Farris CW, Hao H, Kedar S, Mian AZ, Murman DL, O’Shea SA, Paul AB, Rohatgi S, Saint-Hilaire MH, Sartor EA, Setty BN, Small JE, Swaminathan A, Taraschenko O, Yuan J, Zhou Y, Zhu S, Karjadi C, Ang TFA, Bargal SA, Plummer BA, Poston KL, Ahangaran M, Au R, Kolachalama VB. AI-based differential diagnosis of dementia etiologies on multimodal data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.08.24302531. [PMID: 38585870 PMCID: PMC10996713 DOI: 10.1101/2024.02.08.24302531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an AI model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations, and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a micro-averaged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the micro-averaged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in various clinical settings and drug trials, with promising implications for person-level management.
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Affiliation(s)
- Chonghua Xue
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Electrical & Computer Engineering, Boston University, MA, USA
| | - Sahana S. Kowshik
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Faculty of Computing & Data Sciences, Boston University, MA, USA
| | - Diala Lteif
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Computer Science, Boston University, MA, USA
| | - Shreyas Puducheri
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Varuna H. Jasodanand
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Olivia T. Zhou
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Anika S. Walia
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Osman B. Guney
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Electrical & Computer Engineering, Boston University, MA, USA
| | - J. Diana Zhang
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- School of Chemistry, University of New South Wales, Sydney, Australia
| | - Serena T. Pham
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Artem Kaliaev
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - V. Carlota Andreu-Arasa
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Brigid C. Dwyer
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Chad W. Farris
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Honglin Hao
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Sachin Kedar
- Departments of Neurology & Ophthalmology, Emory University School of Medicine, Atlanta, GA, USA
| | - Asim Z. Mian
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Daniel L. Murman
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, USA
| | - Sarah A. O’Shea
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Aaron B. Paul
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Saurabh Rohatgi
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Emmett A. Sartor
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Bindu N. Setty
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Juan E. Small
- Department of Radiology, Lahey Hospital & Medical Center, Burlington, MA, USA
| | | | - Olga Taraschenko
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, USA
| | - Jing Yuan
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Yan Zhou
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Shuhan Zhu
- Department of Neurology, Brigham & Women’s Hospital, Boston, MA, USA
| | - Cody Karjadi
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Ting Fang Alvin Ang
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Sarah A. Bargal
- Department of Computer Science, Georgetown University, Washington DC, USA
| | | | | | - Meysam Ahangaran
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Rhoda Au
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Boston University Alzheimer’s Disease Research Center, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Vijaya B. Kolachalama
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Faculty of Computing & Data Sciences, Boston University, MA, USA
- Department of Computer Science, Boston University, MA, USA
- Boston University Alzheimer’s Disease Research Center, Boston, MA, USA
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6
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Takeshige-Amano H, Hatano T, Kamagata K, Andica C, Ogawa T, Shindo A, Uchida W, Sako W, Saiki S, Shimo Y, Oyama G, Umemura A, Ito M, Hori M, Aoki S, Hattori N. Free-water diffusion magnetic resonance imaging under selegiline treatment in Parkinson's disease. J Neurol Sci 2024; 457:122883. [PMID: 38246127 DOI: 10.1016/j.jns.2024.122883] [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: 10/15/2023] [Revised: 12/22/2023] [Accepted: 01/09/2024] [Indexed: 01/23/2024]
Abstract
INTRODUCTION Monoamine oxidase type B inhibitors, including selegiline, are established as anti-Parkinsonian Drugs. Inhibition of monoamine oxidase type B enzymes might suppress the inflammation because of inhibition to generate reactive oxygen species. However, its effect on brain microstructure remains unclear. The aim of this study is to elucidate white matter and substantia nigra (SN) microstructural differences between Patients with Parkinson's disease with and without selegiline treatment by two independently recruited cohorts. METHODS Diffusion tensor imaging and free water imaging indices of WM and SN were compared among 22/15 Patients with Parkinson's disease with selegiline (PDselegiline(+)), 33/23 Patients with Parkinson's disease without selegiline (PDselegiline(-)), and 25/20 controls, in the first/second cohorts. Two cohorts were analyzed with different MRI protocols. RESULTS Diffusion tensor imaging and free-water indices of major white matter tracts were significantly differed between the PDselegiline(-) and controls in both cohorts, although not between the PDselegiline(+) and controls except for restricted areas. Compared with the PDselegiline(+), free-water was significantly higher in the PDselegiline(-) in the inferior fronto-occipital fasciculus, superior longitudinal fasciculus, and superior and posterior corona radiata (first cohort) and the forceps major and splenium of the corpus callosum (second cohort). There were no significant differences in free-water of anterior or posterior substantia nigra between PDselegiline(+) and PDselegiline(-). CONCLUSIONS Selegiline treatment might reduce the white matter microstructural abnormalities detected by free-water imaging in Parkinson's disease.
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Affiliation(s)
- Haruka Takeshige-Amano
- Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Taku Hatano
- Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan.
| | - Koji Kamagata
- Department of Radiology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Christina Andica
- Department of Radiology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan; Faculty of Health Data Science, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Takashi Ogawa
- Department of Neurology, Faculty of Medicine, Juntendo University Urayasu Hospital, 2-1-1 Tomioka, Urayasu, Chiba 279-0021, Japan
| | - Atsuhiko Shindo
- Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Wataru Uchida
- Department of Radiology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Wataru Sako
- Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Shinji Saiki
- Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Yasushi Shimo
- Department of Neurology, Faculty of Medicine, Juntendo University Nerima Hospital, 3-1-10 Takanodai, Nerima-ku, Tokyo 177-8521, Japan
| | - Genko Oyama
- Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Atsushi Umemura
- Department of Neurosurgery, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Masanobu Ito
- Department of Psychiatry, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Masaaki Hori
- Department of Radiology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Shigeki Aoki
- Department of Radiology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Nobutaka Hattori
- Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan; Neurodegenerative Disorders Collaborative Laboratory, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan.
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Angelopoulou E, Bougea A, Hatzimanolis A, Stefanis L, Scarmeas N, Papageorgiou S. Mild Behavioral Impairment in Parkinson's Disease: An Updated Review on the Clinical, Genetic, Neuroanatomical, and Pathophysiological Aspects. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:115. [PMID: 38256375 PMCID: PMC10820007 DOI: 10.3390/medicina60010115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 12/30/2023] [Accepted: 01/05/2024] [Indexed: 01/24/2024]
Abstract
Neuropsychiatric symptoms (NPS), including depression, anxiety, apathy, visual hallucinations, and impulse control disorders, are very common during the course of Parkinson's disease (PD), occurring even at the prodromal and premotor stages. Mild behavioral impairment (MBI) represents a recently described neurobehavioral syndrome, characterized by the emergence of persistent and impactful NPS in later life, reflecting arisk of dementia. Accumulating evidence suggests that MBI is highly prevalent in non-demented patients with PD, also being associated with an advanced disease stage, more severe motor deficits, as well as global and multiple-domain cognitive impairment. Neuroimaging studies have revealed that MBI in patients with PD may be related todistinct patterns of brain atrophy, altered neuronal connectivity, and distribution of dopamine transporter (DAT) depletion, shedding more light on its pathophysiological background. Genetic studies in PD patients have also shown that specific single-nucleotide polymorphisms (SNPs) may be associated with MBI, paving the way for future research in this field. In this review, we summarize and critically discuss the emerging evidence on the frequency, associated clinical and genetic factors, as well as neuroanatomical and neurophysiological correlates of MBI in PD, aiming to elucidate the underlying pathophysiology and its potential role as an early "marker" of cognitive decline, particularly in this population. In addition, we aim to identify research gaps, and propose novel relative areas of interest that could aid in our better understanding of the relationship of this newly defined diagnostic entity with PD.
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Affiliation(s)
- Efthalia Angelopoulou
- Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.P.)
| | - Anastasia Bougea
- Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.P.)
| | - Alexandros Hatzimanolis
- Department of Psychiatry, Aiginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece;
| | - Leonidas Stefanis
- Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.P.)
| | - Nikolaos Scarmeas
- Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.P.)
- Department of Neurology, Columbia University, New York, NY 10032, USA
| | - Sokratis Papageorgiou
- Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.P.)
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Kobak Tur E, Ari BC. Mild cognitive impairment in patients with Parkinson´s disease and the analysis of associated factors. Neurol Res 2023; 45:1161-1168. [PMID: 37743634 DOI: 10.1080/01616412.2023.2258038] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 09/04/2023] [Indexed: 09/26/2023]
Abstract
OBJECTIVES This research targeted to understand the impact of clinical findings, non-motor symptoms, white matter hyperintensities (WMHs), and metabolic features on cognition in Parkinson's disease patients with mild cognitive impairment (PD-MCI). METHODS Sixty-one PD patients sundered into two groups: PD-MCI and normal cognition (PD-NC). We assessed cognition using Montreal Cognitive Assessment-TR (MoCA-TR) and Frontal Assessment Battery (FAB). We used the modified Hoehn&Yahr staging scale (mH&Y), Unified Parkinson's Disease Rating Scale (UPDRS), Freezing of Gait questionnaire, Beck Depression Inventory, Parkinson's disease sleep scale-2, Pittsburgh sleep quality index, Epworth sleepiness scale, and Non-motor symptoms questionnaire to evaluate all patients. We used the Fazekas scale to evaluate the WMHs and also investigated all laboratory parameters affecting cognitive functions. RESULTS Duration of disease, UPDRS-Motor part, age, disease stage, and daytime sleepiness were dramatically higher in the PD-MCI group than in PD-NC (p < 0.05). WMHs and homocysteine were higher in the PD-MCI group than in the controls (p = 0.016 and p < 0.001, respectively). There was a negative correlation between cognition and duration of disease, age, disease stage, UPDRS-Motor scale, daytime drowsiness, WMHs and homocysteine levels. Homocysteine was negatively related to visuospatial/executive functions (r=-0.303, p = 0.021). WMHs were correlated with global cognition (p =.000 r = .-542), language (p = .001, r = -.434), and delayed recall (p = .011, r = -.332). DISCUSSION Mild cognitive impairment is a widespread clinical situation of PD patients and often presents before the motor symptoms. Revealing curable causes that affect cognition before the development of PD-related dementia is crucial in controlling motor findings and reducing the burden of the caretakers.
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Affiliation(s)
- Esma Kobak Tur
- Department of Neurology, University of Health Sciences, Istanbul, Turkey
| | - Buse Cagla Ari
- Department of Neurology, Bahcesehir University Medical Faculty, Istanbul, Turkey
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Ma X, Li S, Liu F, Du Y, Chen H, Su W. Glycated hemoglobin A1c, cerebral small vessel disease burden, and disease severity in Parkinson's disease. Ann Clin Transl Neurol 2023; 10:2276-2284. [PMID: 37750198 PMCID: PMC10723236 DOI: 10.1002/acn3.51913] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 09/12/2023] [Accepted: 09/16/2023] [Indexed: 09/27/2023] Open
Abstract
OBJECTIVE Our study aimed to investigate the glucose levels in PD and controls. We also examine whether glucose control is associated with PD severity regardless of diabetic status, and test whether the correlation is mediated by cerebral small vessel disease (CSVD) burden. METHODS A total of 100 patients with idiopathic PD and 100 age- and sex-matched controls who underwent brain magnetic resonance imaging (MRI) were enrolled in this study. We collected the clinical data and blood parameters, including fasting blood glucose (FBG), glycated hemoglobin A1c (HbA1c), and blood lipid. Patients with PD were divided into early (n = 61) and advanced (n = 39) subgroups, based on Hoehn and Yahr (H&Y) stages. Differences between the PD and controls, PD with and without diabetes, and between two PD subgroups were compared. CSVD markers were assessed, including lacunes, white matter hyperintensities, enlarged perivascular spaces, and cerebral microbleeds. Multivariable logistic regressions were used to test the association between HbA1c and H&Y stages. Interaction between HbA1c and CSVD burden in relation to H&Y stages was also analyzed. RESULTS PD group exhibited higher HbA1c (p < 0.001), lower high-density lipoprotein cholesterol (p < 0.001) and triglyceride (p = 0.049) than controls. Advanced PD patients showed higher HbA1c than early PD group (p = 0.022). Increasing HbA1c (OR = 1.54, 95% CI 1.03-2.32, p = 0.036) along with longer disease duration (OR = 1.14, 95% CI 1.01-1.27, p = 0.028) and higher UPDRS III score (OR = 1.07, 95% CI 1.02-1.11, p = 0.002) increased the risk of belonging to the higher H&Y stage. However, interaction between HbA1c and CSVD burden in relation to H&Y stages was not significant. INTERPRETATION HbA1c is independently associated with H&Y stages in PD, and this correlation may not be mediated by CSVD burden.
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Affiliation(s)
- Xinxin Ma
- Department of NeurologyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical SciencesNo. 1 Da HuaRoad, DongDanBeijing100730P.R. China
| | - Shuhua Li
- Department of NeurologyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical SciencesNo. 1 Da HuaRoad, DongDanBeijing100730P.R. China
| | - Fengzhi Liu
- Department of NeurologyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical SciencesNo. 1 Da HuaRoad, DongDanBeijing100730P.R. China
| | - Yu Du
- Department of NeurologyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical SciencesNo. 1 Da HuaRoad, DongDanBeijing100730P.R. China
| | - Haibo Chen
- Department of NeurologyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical SciencesNo. 1 Da HuaRoad, DongDanBeijing100730P.R. China
| | - Wen Su
- Department of NeurologyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical SciencesNo. 1 Da HuaRoad, DongDanBeijing100730P.R. China
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Reekes TH, Higginson CI, Sigvardt KA, King DS, Levine D, Wheelock VL, Disbrow EA. Sex differences in Parkinson disease-associated episodic memory and processing speed deficits. J Int Neuropsychol Soc 2023; 29:813-820. [PMID: 36971238 DOI: 10.1017/s1355617723000097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
OBJECTIVES This study aims to address a gap in the data on cognitive sex differences in persons living with Parkinson disease (PD). There is some evidence that cognitive dysfunction is more severe in male PD, however data on episodic memory and processing speed is incomplete. METHODS One hundred and sixty-seven individuals with a diagnosis of PD were included in this study. Fifty-six of those individuals identified as female. The California Verbal Learning Test 1st edition and the Wechsler Memory Scale 3rd edition were used to evaluate verbal and visuospatial episodic memory and the Wechsler Adult Intelligence Scale 3rd edition was used to evaluate processing speed. Multivariate analysis of covariance was used to identify sex-specific differences across groups. RESULTS Our results show that males with PD performed significantly worse than females in verbal and visuospatial recall as well as a trend for the processing speed task of coding. CONCLUSIONS Our finding of superior performance among females with PD in verbal episodic memory is consistent with reports in both healthy and PD individuals; however, females outperforming males in measures of visuospatial episodic memory is unique to PD. Cognitive deficits preferentially affecting males appear to be associated with frontal lobe-related function. Therefore, males may represent a disease subgroup more susceptible to disease mechanisms affecting frontal lobe deterioration and cognitive disturbances in PD.
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Affiliation(s)
- Tyler H Reekes
- Department of Pharmacology, Toxicology, and Neuroscience, Louisiana State University Health Sciences Center, Shreveport, LA, USA
- LSU Health Shreveport Center for Brain Health, Shreveport, LA, USA
| | | | - Karen A Sigvardt
- Department of Neurology, University of California Davis, Davis, CA, USA
| | - David S King
- Clinical Functional Neuroscience Department, Kaiser Permanente Northern California, Sacramento, CA, USA
| | - Dawn Levine
- Clinical Functional Neuroscience Department, Kaiser Permanente Northern California, Sacramento, CA, USA
| | - Vicki L Wheelock
- Department of Neurology, University of California Davis, Davis, CA, USA
- Clinical Functional Neuroscience Department, Kaiser Permanente Northern California, Sacramento, CA, USA
| | - Elizabeth A Disbrow
- Department of Pharmacology, Toxicology, and Neuroscience, Louisiana State University Health Sciences Center, Shreveport, LA, USA
- LSU Health Shreveport Center for Brain Health, Shreveport, LA, USA
- Department of Neurology, Louisiana State University Health Sciences Center, Shreveport, LA, USA
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Esmaili M, Farhud DD, Poushaneh K, Baghdassarians A, Ashayeri H. Executive Functions and Public Health: A Narrative Review. IRANIAN JOURNAL OF PUBLIC HEALTH 2023; 52:1589-1599. [PMID: 37744538 PMCID: PMC10512143 DOI: 10.18502/ijph.v52i8.13398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 04/10/2023] [Indexed: 09/26/2023]
Abstract
Executive functions (EFs) skills are necessary for regulating the thoughts, emotions, and actions which are associated with many aspects of daily functioning. Executive dysfunction (EDFs) is present in a wide range of mental disorders. New study indicates that EFs may predict health behavior and make it easier to engage in a variety of healthy activities. In this narrative review, EFs and public health are briefly discussed. In general, 133 articles met the inclusion criteria (published 2018-2023) which were reviewed. EFs affect the mental and physical health. Besides individual problems, people with mental problems have heavy costs to society. Mental health cannot be considered separately from general health. Consequently, preventive and therapeutic approaches to mental health should be considered not only at the level of the whole society, but also at the global level.
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Affiliation(s)
- Mina Esmaili
- Department of Psychology, Faculty of Psychology and Educational Sciences, Central Tehran Branch, Islamic Azad University Tehran, Iran
| | - Dariush D. Farhud
- School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
- Department of Basic Sciences, Iranian Academy of Medical Sciences, Tehran, Iran
| | - Kambiz Poushaneh
- Department of Psychology, Faculty of Psychology and Educational Sciences, Central Tehran Branch, Islamic Azad University Tehran, Iran
| | - Anita Baghdassarians
- Department of Psychology, Faculty of Psychology and Educational Sciences, Central Tehran Branch, Islamic Azad University Tehran, Iran
| | - Hassan Ashayeri
- Department of Basic Sciences, Faculty of Rehabilitation Sciences, Tehran University of Medical Sciences, Tehran, Iran
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12
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Ryman SG, Shaff N, Dodd A, Nitschke S, Wertz C, Julio K, Suarez Cedeno G, Deligtisch A, Erhardt E, Lin H, Vakhtin A, Poston KL, Tarawneh R, Pirio Richardson S, Mayer A. Reduced and Delayed Cerebrovascular Reactivity in Patients with Parkinson's Disease. Mov Disord 2023; 38:1262-1272. [PMID: 37157056 PMCID: PMC10524339 DOI: 10.1002/mds.29429] [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: 02/03/2023] [Accepted: 04/17/2023] [Indexed: 05/10/2023] Open
Abstract
BACKGROUND Cerebrovascular dysfunction in Parkinson's disease (PD) is heterogeneous and may contribute to disease pathophysiology or progression. There is a need to understand the mechanisms by which cerebrovascular dysfunction is altered in participants with PD. OBJECTIVES The objective of this study is to test the hypothesis that participants with PD exhibit a significant reduction in the ability of the cerebral vessels to dilate in response to vasoactive challenges relative to healthy controls (HC). METHODS The current study uses a vasodilatory challenge while participants undergo functional magnetic resonance imaging to quantify the amplitude and delay of cerebrovascular reactivity in participants with PD relative to age and sex-matched HC. An analysis of covariance was used to evaluate differences in cerebrovascular reactivity amplitude and latency between PD participants and HC. RESULTS A significant main effect of group was observed for whole-brain cerebrovascular reactivity amplitude (F(1, 28) = 4.38, p = 0.046, Hedge's g = 0.73) and latency (F(1, 28) = 16.35, p < 0.001, Hedge's g = 1.42). Participants with PD exhibited reduced whole-brain amplitude and increased latencies in cerebrovascular reactivity relative to HC. The evaluation of regional effects indicates that the largest effects were observed in the cuneus, precuneus, and parietal regions. CONCLUSIONS PD participants exhibited reduced and delayed cerebrovascular reactivity. This dysfunction may play an important role in chronic hypoxia, neuroinflammation, and protein aggregation, mechanisms that could lead to disease progression. Cerebrovascular reactivity may serve as an important biomarker and target for future interventions. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Sephira G Ryman
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, New Mexico, USA
- Nene and Jamie Koch Comprehensive Movement Disorder Center, Department of Neurology, University of New Mexico, Albuquerque, New Mexico, USA
| | - Nicholas Shaff
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, New Mexico, USA
| | - Andrew Dodd
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, New Mexico, USA
| | - Stephanie Nitschke
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, New Mexico, USA
| | - Christopher Wertz
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, New Mexico, USA
| | - Kayla Julio
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, New Mexico, USA
| | - Gerson Suarez Cedeno
- Nene and Jamie Koch Comprehensive Movement Disorder Center, Department of Neurology, University of New Mexico, Albuquerque, New Mexico, USA
| | - Amanda Deligtisch
- Nene and Jamie Koch Comprehensive Movement Disorder Center, Department of Neurology, University of New Mexico, Albuquerque, New Mexico, USA
| | - Erik Erhardt
- Department of Mathematics and Statistics, University of New Mexico, Albuquerque, New Mexico, USA
| | - Henry Lin
- Department of Medicine, University of New Mexico, Albuquerque, New Mexico, USA
- Neurology|Medicine, New Mexico VA Health Care System, Albuquerque, New Mexico, USA
| | - Andrei Vakhtin
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, New Mexico, USA
| | - Kathleen L Poston
- Movement Disorders Division in the Department of Neurology and Neurological Sciences, Stanford University, Stanford, California, USA
| | - Rawan Tarawneh
- Memory and Aging Center, Department of Neurology, University of New Mexico, Albuquerque, New Mexico, USA
| | - Sarah Pirio Richardson
- Nene and Jamie Koch Comprehensive Movement Disorder Center, Department of Neurology, University of New Mexico, Albuquerque, New Mexico, USA
- Neurology|Medicine, New Mexico VA Health Care System, Albuquerque, New Mexico, USA
| | - Andrew Mayer
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, New Mexico, USA
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13
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Hernadi G, Perlaki G, Kovacs M, Pinter D, Orsi G, Janszky J, Kovacs N. White matter hyperintensities associated with impulse control disorders in Parkinson's Disease. Sci Rep 2023; 13:10594. [PMID: 37391475 PMCID: PMC10313834 DOI: 10.1038/s41598-023-37054-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 06/15/2023] [Indexed: 07/02/2023] Open
Abstract
Impulse control disorders (ICDs) in Parkinson's disease (PD) are increasingly recognized as clinically significant non-motor features that potentially impair the quality of life. White matter hyperintensities (WMHs), detected by magnetic resonance imaging, are frequently observed in PD and can be associated with both motor- and certain non-motor symptoms. Given the limited number of non-motor features studied in this context, our aim was to reveal the potential association between the severity of WMHs and ICDs in PD. Fluid-attenuated inversion recovery magnetic resonance images were retrospectively evaluated in 70 patients with PD (48 males; 59.3 ± 10.1 years). The severity of WMHs was assessed by Fazekas scores and by the volume and number of supratentorial WMHs. ICDs were evaluated using the modified Minnesota Impulsive Disorders Interview. Significant interaction between age and the severity of WMHs was present for ICDs. In our younger patients (< 60.5 years), severity of WMHs was positively associated with ICDs (p = 0.004, p = 0.021, p < 0.001 and p < 0.001, respectively for periventricular white matter and total Fazekas scores and the volume and number of WMHs). Our study supports the hypothesis that WMHs of presumed vascular origin may contribute to ICDs in PD. Future prospective studies are needed to assess the prognostic relevance of this finding.
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Affiliation(s)
| | - Gabor Perlaki
- Pecs Diagnostic Centre, Pecs, Hungary
- ELKH-PTE Clinical Neuroscience MR Research Group, Pecs, Hungary
- Department of Neurology, Medical School, University of Pecs, Pecs, Hungary
- Department of Neurosurgery, Medical School, University of Pecs, Pecs, Hungary
| | - Marton Kovacs
- Department of Neurology, Medical School, University of Pecs, Pecs, Hungary.
| | - David Pinter
- ELKH-PTE Clinical Neuroscience MR Research Group, Pecs, Hungary
- Department of Neurology, Medical School, University of Pecs, Pecs, Hungary
| | - Gergely Orsi
- Pecs Diagnostic Centre, Pecs, Hungary
- ELKH-PTE Clinical Neuroscience MR Research Group, Pecs, Hungary
- Department of Neurology, Medical School, University of Pecs, Pecs, Hungary
- Department of Neurosurgery, Medical School, University of Pecs, Pecs, Hungary
| | - Jozsef Janszky
- ELKH-PTE Clinical Neuroscience MR Research Group, Pecs, Hungary
- Department of Neurology, Medical School, University of Pecs, Pecs, Hungary
| | - Norbert Kovacs
- ELKH-PTE Clinical Neuroscience MR Research Group, Pecs, Hungary
- Department of Neurology, Medical School, University of Pecs, Pecs, Hungary
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14
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Dogariu OA, Dogariu I, Vasile CM, Berceanu MC, Raicea VC, Albu CV, Gheonea IA. Diagnosis and treatment of Watershed strokes: a narrative review. J Med Life 2023; 16:842-850. [PMID: 37675172 PMCID: PMC10478671 DOI: 10.25122/jml-2023-0127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Accepted: 05/25/2023] [Indexed: 09/08/2023] Open
Abstract
Watershed strokes have been described previously as ischemic strokes located in vulnerable border zones between brain tissue supplied by the anterior, posterior, and middle cerebral arteries in the distal junction between two non-anastomotic arterial territories. Ischemic strokes in border zones are well-recognized entities and well-described in terms of imaging features, but the pathophysiological mechanism of brain injury production is not fully defined. Border zone ischemia is caused by cerebral hypoperfusion through decreased cerebral blood flow and arterial embolism in unstable atheroma plaque. It is often difficult to say which mechanisms are fully responsible for producing cerebral ischemic lesions. This review aimed to highlight the imaging aspect of watershed strokes and to correlate the clinical characteristics of this type of stroke with the diagnostic algorithm for optimal therapeutic management. Neurologists should promptly recognize this type of stroke and investigate its etiology in the shortest possible time.
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Affiliation(s)
- Oana Andreea Dogariu
- University of Medicine and Pharmacy, Craiova, Romania
- Department of Neurology, Emergency County Hospital, Targu-Jiu, Romania
| | - Ioan Dogariu
- Department of Neurology, Emergency County Hospital, Targu-Jiu, Romania
| | - Corina Maria Vasile
- Department of Pediatric and Adult Congenital Cardiology, University of Bordeaux, Bordeaux, France
| | - Mihaela Corina Berceanu
- University of Medicine and Pharmacy, Craiova, Romania
- Department of Cardiology, County Hospital, Craiova, Romania
| | - Victor Cornel Raicea
- University of Medicine and Pharmacy, Craiova, Romania
- Department of Cardiology, County Hospital, Craiova, Romania
| | - Carmen Valeria Albu
- University of Medicine and Pharmacy, Craiova, Romania
- Department of Neurology, Neuropsychiatry Hospital, Craiova, Romania
| | - Ioana Andreea Gheonea
- University of Medicine and Pharmacy, Craiova, Romania
- Department of Radiology, Emergency County Hospital, Craiova, Romania
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15
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Chen K, Jin Z, Fang J, Qi L, Liu C, Wang R, Su Y, Yan H, Liu A, Xi J, Wen Q, Fang B. The impact of cerebral small vessel disease burden and its imaging markers on gait, postural control, and cognition in Parkinson's disease. Neurol Sci 2023; 44:1223-1233. [PMID: 36547777 DOI: 10.1007/s10072-022-06563-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022]
Abstract
OBJECTIVE This study aimed to investigate how cerebral small vessel disease (CSVD) burden and its imaging markers are related to alterations in different gait parameters in Parkinson's disease (PD) and whether they affect attention, information processing speed, and executive function when global mental status is relatively intact. METHODS Sixty-five PD patients were divided into the low CSVD burden group (n = 43) and the high CSVD burden group (n = 22). All patients underwent brain magnetic resonance imaging scans, clinical scale evaluations, and neuropsychological tests, as well as quantitative evaluation of gait and postural control. Multivariable linear regression models were conducted to investigate associations between CSVD burden and PD symptoms. RESULTS Between-group analysis showed that the high CSVD group had worse attention, executive dysfunction, information processing speed, gait, balance, and postural control than the low CSVD group. Regression analysis revealed that greater CSVD burden was associated with poor attention, impaired executive function, and slow gait speed; white matter hyperintensity was associated with slow gait speed, decreased cadence, increased stride time, and increased stance phase time; the presence of lacune was associated only with poor attention and impaired executive function; enlarged perivascular space in the basal ganglia was associated with gait speed. CONCLUSIONS CSVD burden may worsen gait, postural control, attention, and executive function in patients with PD, and different imaging markers play different roles. Early management of vascular risks and treatment of vascular diseases provide an alternate way to mitigate some motor and cognitive dysfunction in PD.
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Affiliation(s)
- Keke Chen
- Capital Medical University, Beijing, China
| | - Zhaohui Jin
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Jinping Fang
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Lin Qi
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Cui Liu
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Ruidan Wang
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Yuan Su
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Hongjiao Yan
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Aixian Liu
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Jianing Xi
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Qiping Wen
- Radiology Department, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China.
| | - Boyan Fang
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China.
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16
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Shekari E, Nozari N. A narrative review of the anatomy and function of the white matter tracts in language production and comprehension. Front Hum Neurosci 2023; 17:1139292. [PMID: 37051488 PMCID: PMC10083342 DOI: 10.3389/fnhum.2023.1139292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 02/24/2023] [Indexed: 03/28/2023] Open
Abstract
Much is known about the role of cortical areas in language processing. The shift towards network approaches in recent years has highlighted the importance of uncovering the role of white matter in connecting these areas. However, despite a large body of research, many of these tracts’ functions are not well-understood. We present a comprehensive review of the empirical evidence on the role of eight major tracts that are hypothesized to be involved in language processing (inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, extreme capsule, middle longitudinal fasciculus, superior longitudinal fasciculus, arcuate fasciculus, and frontal aslant tract). For each tract, we hypothesize its role based on the function of the cortical regions it connects. We then evaluate these hypotheses with data from three sources: studies in neurotypical individuals, neuropsychological data, and intraoperative stimulation studies. Finally, we summarize the conclusions supported by the data and highlight the areas needing further investigation.
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Affiliation(s)
- Ehsan Shekari
- Department of Neuroscience, Iran University of Medical Sciences, Tehran, Iran
| | - Nazbanou Nozari
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA, United States
- Center for the Neural Basis of Cognition (CNBC), Pittsburgh, PA, United States
- *Correspondence: Nazbanou Nozari
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17
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Abdelnour C, Poston KL. Cognitive Impairment in Neurodegenerative Movement Disorders. Semin Neurol 2023; 43:81-94. [PMID: 36940727 DOI: 10.1055/s-0043-1764204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/22/2023]
Abstract
Patients with neurodegenerative movement disorders can develop cognitive impairment during the disease. Cognitive symptoms have been associated with decreased quality of life, higher caregiver burden, and earlier institutionalization, and are therefore critical for physicians to understand and address. The evaluation of cognitive performance of patients with neurodegenerative movement disorders is important for providing adequate diagnosis, management, prognosis, and support patients and their caregivers. In this review, we discuss the features of the cognitive impairment profile of commonly encountered movement disorders: Parkinson's disease, dementia with Lewy bodies, multiple system atrophy, progressive supranuclear palsy, corticobasal syndrome, and Huntington's disease. In addition, we provide neurologists with practical guidance and evaluation tools for the assessment and management of these challenging patients.
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Affiliation(s)
- Carla Abdelnour
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Kathleen L Poston
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, California
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18
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Zhu Y, Du R, He Z, Pang X, Yu W, Huang X. Assessing the association between white matter lesions and Parkinson's disease. Neurol Sci 2023; 44:897-903. [PMID: 36350453 DOI: 10.1007/s10072-022-06494-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 11/02/2022] [Indexed: 11/10/2022]
Abstract
BACKGROUND The association between white matter (WM) lesions and Parkinson's disease (PD) was not fully established. We therefore applied Mendelian randomization (MR) analyses to identify the causal effect between white matter lesions and PD. METHODS We performed a bidirectional two-sample Mendelian randomization (MR) study to investigate the association between three WM phenotypes-white matter hyperintensities (WMH, N = 18,381), fractional anisotropy (FA, N = 17,673), and mean diffusivity (MD, N = 17,467)-with PD (N = 482,730) using summary statistics from genome-wide association studies (GWAS). The inverse variance weighted (IVW), weighted median, MR-Egger, and MR-PRESSO methods were used to evaluate the causal estimate. RESULTS Significant evidence was suggested that higher MD was associated with a higher PD risk (OR = 1.049, 95% CI = 1.018-1.081, p = 0.022) when the outlier was removed using MR-PRESSO method. Moreover, genetically predicted PD was associated with a lower WMH load (IVW β = - 0.047, 95% CI = - 0.085 to - 0.009, p = 0.016) and a higher FA (β = 0.185, 95% CI = 0.021-0.349, p = 0.027). No evidence of pleiotropy was found using MR-Egger intercept. CONCLUSION Our findings provided genetic support that white matter microstructural integrity lesions might increase the risk of PD. However, genetically predicted PD was potentially associated with a lower load of white matter lesions.
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Affiliation(s)
- Yahui Zhu
- Medical School of Chinese PLA, Beijing, China.,Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Rongrong Du
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China.,College of Medicine, Nankai University, Tianjin, China
| | - Zhengqing He
- Medical School of Chinese PLA, Beijing, China.,Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Xinyuan Pang
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China.,College of Medicine, Nankai University, Tianjin, China
| | - Wenxiu Yu
- Medical School of Chinese PLA, Beijing, China.,Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Xusheng Huang
- Medical School of Chinese PLA, Beijing, China. .,Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China.
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19
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Chen K, Jin Z, Fang J, Qi L, Liu C, Wang R, Su Y, Yan H, Liu A, Xi J, Fang B. Lacunes may worsen cognition but not motor function in Parkinson's disease. Brain Behav 2023; 13:e2880. [PMID: 36586096 PMCID: PMC9927847 DOI: 10.1002/brb3.2880] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 11/28/2022] [Accepted: 12/18/2022] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND As one of the imaging markers of cerebral small vessel disease, lacunes has received little attention. The objective of this study was to investigate the associations of lacunes, cognition and motor function in patients with Parkinson's disease (PD) and whether these associations are independent of other imaging markers. METHODS Patients were consecutively included from April 2019 to July 2022 in Beijing Rehabilitation Hospital. All patients underwent brain magnetic resonance imaging scans, clinical scale evaluations, and neuropsychological tests, as well as quantitative evaluation of postural control. To eliminate the possible factors contributing to cognition and motor dysfunction in patients with PD, in particular white matter hyperintensities and enlarged perivascular space in the basal ganglia, multivariate linear regression models were constructed to sort out the effect of lacunes. RESULTS Ninety-four patients were included in this study, 56 without lacunes and 38 with lacunes. Patients with lacunes showed shorter disease duration, slower gait speed and spent more time on Trail-Making Test part A (TMT-A) than those without lacunes. The number of lacunes were positively correlated with the time to complete the TMT-A and negatively related to gait speed. Multivariate linear regression models showed that the presence of lacunes was associated with longer TMT-A time after adjusting for potential confounders. CONCLUSIONS Lacunes were independently associated with worse visual scanning, attention, and processing speed in patients with PD. In addition, lacunes may accelerate the course of PD. Early treatment of vascular disease provides an alternate way to mitigate some motor and cognitive dysfunction in patients with PD.
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Affiliation(s)
- Keke Chen
- School of Beijing Rehabilitation Medicine, Capital Medical University, Beijing, China
| | - Zhaohui Jin
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Jinping Fang
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Lin Qi
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Cui Liu
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Ruidan Wang
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Yuan Su
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Hongjiao Yan
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Aixian Liu
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Jianing Xi
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Boyan Fang
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
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20
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Zhang Z, Li S, Wang S. Application of Periventricular White Matter Hyperintensities Combined with Homocysteine into Predicting Mild Cognitive Impairment in Parkinson's Disease. Int J Gen Med 2023; 16:785-792. [PMID: 36879618 PMCID: PMC9985451 DOI: 10.2147/ijgm.s399307] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 02/21/2023] [Indexed: 03/05/2023] Open
Abstract
Purpose To verify the associations between white matter hyperintensities (WMHs), plasma homocysteine (Hcy) levels, and mild cognitive impairment (MCI) in Parkinson's disease (PD) patients and evaluate the predictive value of combination of WMHs and plasma Hcy levels for MCI. Patients and methods In this study, 387 patients with PD were divided into MCI group and non-MCI group. Their cognition was evaluated with a comprehensive neuropsychological evaluation including 10 tests. Five cognitive domains, including the memory, attention/working memory, visuospatial, executive and language domains, were evaluated using two tests for each domain. MCI was determined when at least two tests demonstrated abnormal results, either one impaired test in two different cognitive domains or two impaired tests in a single cognitive domain. Multivariate analysis was performed to determine risk factors for MCI in PD patients. The receiver operating characteristic (ROC) curve was employed to assess the predictive values, and the Z test was employed to compare the area under curve (AUC). Results MCI was identified in 195 PD patients with an incidence of 50.4%. Multivariate analysis results showed that PWMHs (OR: 5.162, 95% CI: 2.318~9.527), Hcy levels (OR: 1.189, 95% CI: 1.071~1.405) and MDS-UPDRS part III score (OR: 1.173, 95% CI: 1.062~1.394) were independently correlated with MCI in PD patients after adjusting for confounders. ROC curves showed that the AUCs of PWMHs, Hcy levels and their combination were 0.701 (SE: 0.026, 95% CI: 0.647~0.752), 0.688 (SE: 0.027, 95% CI: 0.635~0.742) and 0.879 (SE: 0.018, 95% CI: 0.844~0.915), respectively. Z test showed that the AUC of combination prediction was significantly higher than those of individual predictions (0.879 vs 0.701, Z=5.629, P<0.001; 0.879 vs 0.688, Z=5.886, P<0.001). Conclusion The combination of WMHs and plasma Hcy levels could be applied in the prediction of MCI in PD patients.
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Affiliation(s)
- Zuowen Zhang
- Department of Neurology, Chongqing University Jiangjin Hospital, Chongqing, People's Republic of China
| | - Shishuang Li
- Department of Neurology, Chongqing University Jiangjin Hospital, Chongqing, People's Republic of China
| | - Shumei Wang
- College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, People's Republic of China
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21
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Sinani O, Dadouli K, Ntellas P, Kapsalaki EZ, Vlychou M, Raptis DG, Marogianni C, Markou K, Dardiotis E, Xiromerisiou G. Association between white matter lesions and Parkinson's disease: an impact on Postural/Gait difficulty phenotype and cognitive performance. Neurol Res 2022; 44:1122-1131. [PMID: 35994524 DOI: 10.1080/01616412.2022.2112378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND White matter hyperintensities (WMHs) may be observed on Magnetic Resonance Imaging (MRI) in patients with Parkinson disease with or without vascular risk factors. Whether WMHs may influence motor and non-motor aspects of Parkinson disease is a subject of debate. The aim of this study is to evaluate the impact of WMH severity on various aspects of Parkinson disease in combination to the estimation of the impact of cerebrovascular risk factors. MATERIALS AND METHODS We included a cohort of patients with Parkinson's disease who underwent MRI examination. The Fazekas visual rating scale was used to assess the severity and location of WMHs, and patient clinical characteristics were correlated with MRI data. RESULTS All vascular risk factors were associated with higher Fazekas score in both periventricular and deep white matter. Periventricular white matter hyperintensities (PWMHs) and deep white matter hyperintensities (DWMHs) were associated with lower scores in the ACE-R cognitive assessment scale (p < 0.001). Furthermore, PWMHs and DWMHs severity was associated with higher UPDRS motor score (p < 0.001), while the Postural Instability Gait Difficulty (PIGD) phenotype was correlated with higher burden of WMHs. CONCLUSIONS Comorbid WMHs may contribute to multi-dimension dysfunction in patients with Parkinson disease and consequently the management of vascular risk factors may be crucial to maintain motor and non-motor functions in PD.
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Affiliation(s)
- Olga Sinani
- Faculty of Medicine, University of Thessaly, Larisa, Greece
| | - Katerina Dadouli
- Laboratory of Hygiene and Epidemiology, Faculty of Medicine, University of Thessaly, Larisa, Greece
| | - Panagiotis Ntellas
- Department of Medical Oncology, University Hospital of Ioannina, Ioannina, Greece
| | - Eftychia Z Kapsalaki
- Department of Diagnostic Radiology, Faculty of Medicine, University of Thessaly, Larisa, Greece
| | - Marianna Vlychou
- Department of Diagnostic Radiology, Faculty of Medicine, University of Thessaly, Larisa, Greece
| | - Dimitrios G Raptis
- Respiratory Medicine Department, Faculty of Medicine, University of Thessaly, Larisa, Greece
| | | | - Katerina Markou
- Department of Neurology, University Hospital of Larisa, Larisa, Greece
| | | | - Georgia Xiromerisiou
- Department of Neurology, University Hospital of Larisa, Larisa, Greece.,Faculty of Medicine, School of Health Sciences, University of Thessaly, Volos, Greece
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22
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Röhrig L, Sperber C, Bonilha L, Rorden C, Karnath HO. Right hemispheric white matter hyperintensities improve the prediction of spatial neglect severity in acute stroke. Neuroimage Clin 2022; 36:103265. [PMID: 36451368 PMCID: PMC9723300 DOI: 10.1016/j.nicl.2022.103265] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 10/12/2022] [Accepted: 11/08/2022] [Indexed: 11/13/2022]
Abstract
White matter hyperintensities (WMH) are frequently observed in brain scans of elderly people. They are associated with an increased risk of stroke, cognitive decline, and dementia. However, it is unknown yet if measures of WMH provide information that improve the understanding of poststroke outcome compared to only state-of-the-art stereotaxic structural lesion data. We implemented high-dimensional machine learning models, based on support vector regression, to predict the severity of spatial neglect in 103 acute right hemispheric stroke patients. We found that (1) the additional information of right hemispheric or bilateral voxel-based topographic WMH extent indeed yielded a significant improvement in predicting acute neglect severity (compared to the voxel-based stroke lesion map alone). (2) Periventricular WMH appeared more relevant for prediction than deep subcortical WMH. (3) Among different measures of WMH, voxel-based maps as measures of topographic extent allowed more accurate predictions compared to the use of traditional ordinally assessed visual rating scales (Fazekas-scale, Cardiovascular Health Study-scale). In summary, topographic WMH appear to be a valuable clinical imaging biomarker for predicting the severity of cognitive deficits and bears great potential for rehabilitation guidance of acute stroke patients.
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Affiliation(s)
- Lisa Röhrig
- Division of Neuropsychology, Center of Neurology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen 72076, Germany
| | - Christoph Sperber
- Division of Neuropsychology, Center of Neurology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen 72076, Germany
| | - Leonardo Bonilha
- Department of Neurology, Emory University, Atlanta, GA 30322, USA
| | - Christopher Rorden
- Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
| | - Hans-Otto Karnath
- Division of Neuropsychology, Center of Neurology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen 72076, Germany; Department of Psychology, University of South Carolina, Columbia, SC 29208, USA.
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23
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Kent DM, Leung LY, Puttock EJ, Wang AY, Luetmer PH, Kallmes DF, Nelson J, Fu S, Zheng C, Vickery EM, Liu H, Noyce AJ, Chen W. Development of Parkinson Disease and Its Relationship with Incidentally Discovered White Matter Disease and Covert Brain Infarction in a Real-World Cohort. Ann Neurol 2022; 92:620-630. [PMID: 35866711 PMCID: PMC9489676 DOI: 10.1002/ana.26458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 07/18/2022] [Accepted: 07/20/2022] [Indexed: 11/08/2022]
Abstract
OBJECTIVE This study aimed to examine the relationship between covert cerebrovascular disease, comprised of covert brain infarction and white matter disease, discovered incidentally in routine care, and subsequent Parkinson disease. METHODS Patients were ≥50 years and received neuroimaging for non-stroke indications in the Kaiser Permanente Southern California system from 2009 to 2019. Natural language processing identified incidentally discovered covert brain infarction and white matter disease and classified white matter disease severity. The Parkinson disease outcome was defined as 2 ICD diagnosis codes. RESULTS 230,062 patients were included (median follow-up 3.72 years). A total of 1,941 Parkinson disease cases were identified (median time-to-event 2.35 years). Natural language processing identified covert cerebrovascular disease in 70,592 (30.7%) patients, 10,622 (4.6%) with covert brain infarction and 65,814 (28.6%) with white matter disease. After adjustment for known risk factors, white matter disease was associated with Parkinson disease (hazard ratio 1.67 [95%CI, 1.44, 1.93] for patients <70 years and 1.33 [1.18, 1.50] for those ≥70 years). Greater severity of white matter disease was associated with increased incidence of Parkinson disease(/1,000 person-years), from 1.52 (1.43, 1.61) in patients without white matter disease to 4.90 (3.86, 6.13) in those with severe disease. Findings were robust when more specific definitions of Parkinson disease were used. Covert brain infarction was not associated with Parkinson disease (adjusted hazard ratio = 1.05 [0.88, 1.24]). INTERPRETATION Incidentally discovered white matter disease was associated with subsequent Parkinson disease, an association strengthened with younger age and increased white matter disease severity. Incidentally discovered covert brain infarction did not appear to be associated with subsequent Parkinson disease. ANN NEUROL 2022;92:620-630.
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Affiliation(s)
- David M. Kent
- Predictive Analytics and Comparative Effectiveness Center,
Tufts Medical Center, Boston, MA, USA
| | - Lester Y. Leung
- Department of Neurology, Tufts Medical Center, Boston, MA,
USA
| | - Eric J. Puttock
- Department of Research and Evaluation, Kaiser Permanente
Southern California, Pasadena, CA, USA
| | - Andy Y. Wang
- Predictive Analytics and Comparative Effectiveness Center,
Tufts Medical Center, Boston, MA, USA
| | | | | | - Jason Nelson
- Predictive Analytics and Comparative Effectiveness Center,
Tufts Medical Center, Boston, MA, USA
| | - Sunyang Fu
- Department of AI and Informatics, Mayo Clinic, Rochester,
MN, USA
| | - Chengyi Zheng
- Department of Research and Evaluation, Kaiser Permanente
Southern California, Pasadena, CA, USA
| | - Ellen M. Vickery
- Predictive Analytics and Comparative Effectiveness Center,
Tufts Medical Center, Boston, MA, USA
| | - Hongfang Liu
- Department of AI and Informatics, Mayo Clinic, Rochester,
MN, USA
| | - Alastair J. Noyce
- Preventive Neurology Unit, Wolfson Institute of Population
Health, Queen Mary University of London, UK
- Department of Clinical and Movement Neuroscience, UCL
Institute of Neurology, London, UK
| | - Wansu Chen
- Department of Research and Evaluation, Kaiser Permanente
Southern California, Pasadena, CA, USA
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24
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Lipsmeier F, Taylor KI, Postuma RB, Volkova-Volkmar E, Kilchenmann T, Mollenhauer B, Bamdadian A, Popp WL, Cheng WY, Zhang YP, Wolf D, Schjodt-Eriksen J, Boulay A, Svoboda H, Zago W, Pagano G, Lindemann M. Reliability and validity of the Roche PD Mobile Application for remote monitoring of early Parkinson's disease. Sci Rep 2022; 12:12081. [PMID: 35840753 PMCID: PMC9287320 DOI: 10.1038/s41598-022-15874-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 06/30/2022] [Indexed: 11/19/2022] Open
Abstract
Digital health technologies enable remote and therefore frequent measurement of motor signs, potentially providing reliable and valid estimates of motor sign severity and progression in Parkinson’s disease (PD). The Roche PD Mobile Application v2 was developed to measure bradykinesia, bradyphrenia and speech, tremor, gait and balance. It comprises 10 smartphone active tests (with ½ tests administered daily), as well as daily passive monitoring via a smartphone and smartwatch. It was studied in 316 early-stage PD participants who performed daily active tests at home then carried a smartphone and wore a smartwatch throughout the day for passive monitoring (study NCT03100149). Here, we report baseline data. Adherence was excellent (96.29%). All pre-specified sensor features exhibited good-to-excellent test–retest reliability (median intraclass correlation coefficient = 0.9), and correlated with corresponding Movement Disorder Society–Unified Parkinson's Disease Rating Scale items (rho: 0.12–0.71). These findings demonstrate the preliminary reliability and validity of remote at-home quantification of motor sign severity with the Roche PD Mobile Application v2 in individuals with early PD.
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Affiliation(s)
- Florian Lipsmeier
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Kirsten I Taylor
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Ronald B Postuma
- Department of Neurology, McGill University, Montreal General Hospital, Montreal, QC, Canada
| | - Ekaterina Volkova-Volkmar
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Timothy Kilchenmann
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Brit Mollenhauer
- Paracelsus-Elena-Klinik, Kassel, Germany.,Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
| | - Atieh Bamdadian
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Werner L Popp
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Wei-Yi Cheng
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Yan-Ping Zhang
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Detlef Wolf
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Jens Schjodt-Eriksen
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Anne Boulay
- Idorsia Pharmaceuticals Ltd, Allschwil, Switzerland
| | - Hanno Svoboda
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Wagner Zago
- Prothena Biosciences Inc, South San Francisco, CA, USA
| | - Gennaro Pagano
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Michael Lindemann
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
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25
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罗 冬, 李 国, 齐 伟, 陈 丹. [Association of sudden sensorineural hearing loss and its prognosis with the brain white matter hyperintensity]. LIN CHUANG ER BI YAN HOU TOU JING WAI KE ZA ZHI = JOURNAL OF CLINICAL OTORHINOLARYNGOLOGY, HEAD, AND NECK SURGERY 2022; 36:523-527. [PMID: 35822380 PMCID: PMC10128380 DOI: 10.13201/j.issn.2096-7993.2022.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Indexed: 06/15/2023]
Abstract
Objective:To explore the relationship between white matter hyperintensity(WMH) and sudden sensorineural hearing loss(SSHL) and evaluate the influence of WMH on the prognosis of SSHL. Methods:Fifty hospitalized unilateral SSHL patients and 50 age and gender matched routine physical examination individuals without SSHL history from June 2019 to June 2020 were included for a case-control study. All included subjects underwent 3.0 Tesla cranial magnetic resonance examination, and the Fazekas scale was applied to evaluate periventricular white matter hyperintense(PVWMH) and deep white matter hyperintense(DWMH). Fazekas score and distribution proportions of Fazekas score was compared between SSHL and control. Ordered logistic regression was used to study the relationship between prognosis of SSHL and WMH. Results:The Fazekas score of WMH in SSHL group was significantly higher than that of control group(PVWMH: P=0.004, DWMH: P=0.010); There was a significant difference in the distribution proportions of Fazekas scores between SSHL and control(PVWMH: P=0.036, DWMH: P=0.047); The results of ordered logistic regression showed that patients without WMH(Fazekas=0) is an independent predictor of good prognosis in SSHL(P=0.025, OR=12.779). Conclusion:The prevalence of WMH in SSHL patients was higher than that of control. SSHL patients without WMH has a better prognosis than those with WMH.
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Affiliation(s)
- 冬 罗
- 宝鸡市中心医院神经内科(陕西宝鸡,721008)Department of Neurology, Baoji Municipal Central Hospital, Baoji, 721008, China
| | - 国梁 李
- 宝鸡市中心医院神经内科(陕西宝鸡,721008)Department of Neurology, Baoji Municipal Central Hospital, Baoji, 721008, China
| | - 伟平 齐
- 宝鸡市中心医院耳鼻咽喉头颈外科Department of Otolaryngology Head and Neck Surgery, Baoji Municipal Central Hospital
| | - 丹 陈
- 宝鸡市中心医院耳鼻咽喉头颈外科Department of Otolaryngology Head and Neck Surgery, Baoji Municipal Central Hospital
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26
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Qiu S, Miller MI, Joshi PS, Lee JC, Xue C, Ni Y, Wang Y, De Anda-Duran I, Hwang PH, Cramer JA, Dwyer BC, Hao H, Kaku MC, Kedar S, Lee PH, Mian AZ, Murman DL, O'Shea S, Paul AB, Saint-Hilaire MH, Alton Sartor E, Saxena AR, Shih LC, Small JE, Smith MJ, Swaminathan A, Takahashi CE, Taraschenko O, You H, Yuan J, Zhou Y, Zhu S, Alosco ML, Mez J, Stein TD, Poston KL, Au R, Kolachalama VB. Multimodal deep learning for Alzheimer's disease dementia assessment. Nat Commun 2022; 13:3404. [PMID: 35725739 PMCID: PMC9209452 DOI: 10.1038/s41467-022-31037-5] [Citation(s) in RCA: 59] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Accepted: 05/06/2022] [Indexed: 02/02/2023] Open
Abstract
Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we report a deep learning framework that accomplishes multiple diagnostic steps in successive fashion to identify persons with normal cognition (NC), mild cognitive impairment (MCI), AD, and non-AD dementias (nADD). We demonstrate a range of models capable of accepting flexible combinations of routinely collected clinical information, including demographics, medical history, neuropsychological testing, neuroimaging, and functional assessments. We then show that these frameworks compare favorably with the diagnostic accuracy of practicing neurologists and neuroradiologists. Lastly, we apply interpretability methods in computer vision to show that disease-specific patterns detected by our models track distinct patterns of degenerative changes throughout the brain and correspond closely with the presence of neuropathological lesions on autopsy. Our work demonstrates methodologies for validating computational predictions with established standards of medical diagnosis.
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Grants
- R01 AG054076 NIA NIH HHS
- R01 AG016495 NIA NIH HHS
- U19 AG065156 NIA NIH HHS
- P30 AG066515 NIA NIH HHS
- RF1 AG062109 NIA NIH HHS
- RF1 AG072654 NIA NIH HHS
- R01 NS115114 NINDS NIH HHS
- R01 HL159620 NHLBI NIH HHS
- R56 AG062109 NIA NIH HHS
- P30 AG013846 NIA NIH HHS
- R21 CA253498 NCI NIH HHS
- K23 NS075097 NINDS NIH HHS
- U19 AG068753 NIA NIH HHS
- P30 AG066546 NIA NIH HHS
- R01 AG033040 NIA NIH HHS
- The Karen Toffler Charitable Trust, the Michael J. Fox Foundation, the Lewy Body Dementia Association, the Alzheimer’s Drug Discovery Foundation, the American Heart Association (20SFRN35460031), and the National Institutes of Health (R01-HL159620, R21-CA253498, RF1-AG062109, RF1-AG072654, U19-AG065156, P30-AG066515, R01-NS115114, K23-NS075097, U19-AG068753 and P30-AG013846).
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Affiliation(s)
- Shangran Qiu
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Physics, College of Arts & Sciences, Boston University, Boston, MA, USA
| | - Matthew I Miller
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Prajakta S Joshi
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
- Department of General Dentistry, Boston University School of Dental Medicine, Boston, MA, USA
- The Framingham Heart Study, Boston University School of Medicine, Boston, MA, USA
| | - Joyce C Lee
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Chonghua Xue
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Yunruo Ni
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Yuwei Wang
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Ileana De Anda-Duran
- School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Phillip H Hwang
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Justin A Cramer
- Department of Radiology, College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
| | - Brigid C Dwyer
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Honglin Hao
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Michelle C Kaku
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Sachin Kedar
- Department of Neurological Sciences, College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
- Department Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department Ophthalmology, Emory University School of Medicine, Atlanta, GA, USA
| | - Peter H Lee
- Department of Radiology, Lahey Hospital & Medical Center, Burlington, MA, USA
| | - Asim Z Mian
- Department of Radiology, Boston University School of Medicine, Boston, MA, USA
| | - Daniel L Murman
- Department of Neurological Sciences, College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
| | - Sarah O'Shea
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Aaron B Paul
- Department of Radiology, Lahey Hospital & Medical Center, Burlington, MA, USA
| | | | - E Alton Sartor
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Aneeta R Saxena
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Ludy C Shih
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Juan E Small
- Department of Radiology, Lahey Hospital & Medical Center, Burlington, MA, USA
| | - Maximilian J Smith
- Department of Radiology, Lahey Hospital & Medical Center, Burlington, MA, USA
| | - Arun Swaminathan
- Department of Neurological Sciences, College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
| | | | - Olga Taraschenko
- Department of Neurological Sciences, College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
| | - Hui You
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Jing Yuan
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Yan Zhou
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Shuhan Zhu
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Michael L Alosco
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Boston University Alzheimer's Disease Research Center, Boston, MA, USA
| | - Jesse Mez
- The Framingham Heart Study, Boston University School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Boston University Alzheimer's Disease Research Center, Boston, MA, USA
| | - Thor D Stein
- Boston University Alzheimer's Disease Research Center, Boston, MA, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA
- Boston VA Healthcare System, Boston, MA, USA
- Bedford VA Healthcare System, Bedford, MA, USA
| | | | - Rhoda Au
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
- The Framingham Heart Study, Boston University School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Boston University Alzheimer's Disease Research Center, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Vijaya B Kolachalama
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
- Boston University Alzheimer's Disease Research Center, Boston, MA, USA.
- Department of Computer Science, Boston University, Boston, MA, USA.
- Faculty of Computing & Data Sciences, Boston University, Boston, MA, USA.
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27
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Montaser-Kouhsari L, Young CB, Poston KL. Neuroimaging approaches to cognition in Parkinson's disease. PROGRESS IN BRAIN RESEARCH 2022; 269:257-286. [PMID: 35248197 DOI: 10.1016/bs.pbr.2022.01.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
While direct visualization of Lewy body accumulation within the brain is not yet possible in living Parkinson's disease patients, brain imaging studies offer insights into how the buildup of Lewy body pathology impacts different regions of the brain. Unlike biological biomarkers and purely behavioral research, these brain imaging studies therefore offer a unique opportunity to relate brain localization to cognitive function and dysfunction in living patients. Magnetic resonance imaging studies can reveal physical changes in brain structure as they relate to different cognitive domains and task specific impairments. Functional imaging studies use a combination of task and resting state magnetic resonance imaging, as well as positron emission tomography and single photon emission computed tomography, and can be used to determine changes in blood flow, neuronal activation and neurochemical changes in the brain associated with PD cognition and cognitive impairments. Other unique advantages to brain imaging studies are the ability to monitor changes in brain structure and function longitudinally as patients progress and the ability to study changes in brain function when patients are exposed to different pharmacological manipulations. This is particularly true when assessing the effects of dopaminergic replacement therapy on cognitive function in Parkinson's disease patients. Together, this chapter will describe imaging studies that have helped identify structural and functional brain changes associated with cognition, cognitive impairment, and dementia in Parkinson's disease.
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Affiliation(s)
- Leila Montaser-Kouhsari
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, United States
| | - Christina B Young
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, United States
| | - Kathleen L Poston
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, United States; Department of Neurosurgery, Stanford University, Stanford, CA, United States.
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28
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Hijazi Z, Yassi N, O'Brien JT, Watson R. The influence of cerebrovascular disease in dementia with Lewy bodies and Parkinson's disease dementia. Eur J Neurol 2021; 29:1254-1265. [PMID: 34923713 DOI: 10.1111/ene.15211] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 12/08/2021] [Indexed: 11/28/2022]
Abstract
INTRODUCTION Lewy body dementia (LBD), including dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD), is a common form of neurodegenerative dementia. The frequency and influence of comorbid cerebrovascular disease is not understood but has potentially important clinical management implications. METHODS A systematic literature search was conducted (Medline and Embase) for studies including participants with DLB and/or PDD assessing cerebrovascular lesions (imaging and pathological studies). They included white matter changes, cerebral amyloid angiopathy (CAA), cerebral microbleeds (CMB), macroscopic infarcts, micro-infarcts and intracerebral haemorrhage. RESULTS Of 4411 articles, 63 studies were included. Cerebrovascular lesions commonly studied included white matter changes (41 studies) and CMB (18 studies). There was an increased severity of white matter changes on magnetic resonance imaging (visualized as white matter hyperintensities, WMH), but not neuropathology, in LBD compared to PD without dementia and age-matched controls. CMB prevalence in DLB was highly variable but broadly similar to Alzheimer's disease (AD) (0-48%), with a lobar predominance. No relationship was found between large cortical or small subcortical infarcts or intracerebral haemorrhage and presence of LBD. CONCLUSION The underlying mechanisms of WMH in LBD require further exploration, as their increased severity in LBD was not supported by neuropathological examination of white matter. CMB in LBD had a similar prevalence as AD. There is a need for larger studies assessing the influence of cerebrovascular lesions on clinical symptoms, disease progression and outcomes.
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Affiliation(s)
- Zina Hijazi
- Monash University School of Rural Health, Bendigo Hospital, Bendigo, VIC, Australia.,Department of Medicine, Bendigo Hospital, Bendigo, VIC, Australia
| | - Nawaf Yassi
- Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia.,Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.,Department of Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville, Australia
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge, Level E4, Box 189, Cambridge, CB2 0QC, UK
| | - Rosie Watson
- Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia.,Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
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Liu H, Deng B, Xie F, Yang X, Xie Z, Chen Y, Yang Z, Huang X, Zhu S, Wang Q. The influence of white matter hyperintensity on cognitive impairment in Parkinson's disease. Ann Clin Transl Neurol 2021; 8:1917-1934. [PMID: 34310081 PMCID: PMC8419402 DOI: 10.1002/acn3.51429] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/05/2021] [Accepted: 07/02/2021] [Indexed: 01/11/2023] Open
Abstract
The aim of this meta‐analysis was to review systematically and to identify the relationship between the severity and location of white matter hyperintensities (WMHs) and the degree of cognitive decline in patients with Parkinson’s disease (PD). We searched the PubMed, EMBASE, Web of Science, Ovid, and Cochrane Library databases for clinical trials of the severity and location of WMHs on the degree of cognitive impairment in PD through October 2020. We conducted the survey to compare the association of WMH burden in patients with PD with mild cognitive impairment (PD‐MCI) versus those with normal cognition (PD‐NC) and in patients with PD with dementia (PDD) versus those with PD without dementia (PD‐ND). Nine studies with PD‐MCI versus PD‐NC and 10 studies with PDD versus PD‐ND comparisons were included. The WMH burden in PD‐MCI patients was significantly different compared to that in PD‐NC patients (standard mean difference, SMD = 0.39, 95% CI: 0.12 to 0.66, p = 0.005), while there was no correlation shown in the age‐matched subgroup of the comparison. In addition, PDD patients had a significantly higher burden of WMHs (SMD = 0.8, 95% CI: 0.44 to 1.71, p < 0.0001), especially deep white matter hyperintensities (SMD = 0.54, 95% CI: 0.36 to 0.73, p < 0.00001) and periventricular hyperintensities (SMD = 0.70, 95% CI: 0.36 to 1.04, p < 0.0001), than PD‐NC patients, regardless of the adjustment of age. WMHs might be imaging markers for cognitive impairment in PDD but not in PD‐MCI, regardless of age, vascular risk factors, or race. Further prospective studies are needed to validate the conclusions.
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Affiliation(s)
- Hailing Liu
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China.,Department of Neurology, Maoming People's Hospital, Maoming, Guangdong, China
| | - Bin Deng
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Fen Xie
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Xiaohua Yang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Zhenchao Xie
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Yonghua Chen
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Zhi Yang
- Department of Neurology, Maoming People's Hospital, Maoming, Guangdong, China
| | - Xiyan Huang
- Department of Rehabilitation, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Shuzhen Zhu
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
| | - Qing Wang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China
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30
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Ma X, Li S, Li C, Wang R, Chen M, Chen H, Su W. Total Cerebral Small Vessel Score Association With Hoehn and Yahr Stage in Parkinson's Disease. Front Aging Neurosci 2021; 13:682776. [PMID: 34122053 PMCID: PMC8192831 DOI: 10.3389/fnagi.2021.682776] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 04/26/2021] [Indexed: 11/13/2022] Open
Abstract
Background: This study aimed to evaluate the total cerebral small vessel disease (CSVD) score in patients with Parkinson’s disease (PD) at different stages and related factors. Methods: A 100 and seven patients with idiopathic PD and 62 normal controls (NCs) who underwent brain magnetic resonance imaging (MRI) were enrolled. PD patients were divided into two groups: early PD [(Hoehn and Yahr (H&Y) 1–1.5, n = 36)] and advanced PD (H&Y 2–4, n = 71) groups. We calculated the total CSVD score for each participant based on lacunes, high-grade white matter hyperintensities (WMH), enlarged perivascular spaces (EPVS), and cerebral microbleeds (CMBs). Differences in total CSVD score between the PD and NCs and between the two subgroups were compared. In addition, a multivariate logistic regression analysis was conducted to investigate the association between CSVD markers and clinical variables in PD. Results: Lacunes were found in 9.3% of patients with PD, periventricular WMH (PVWMH) in 89.7%, deep WMH (DWMH) in 81.3%, EPVS in 85%, and CMBs in 2.8%. Compared with NCs, patients with PD showed higher PVWMH and DWMH scores. Advanced PD patients exhibited greater PVWMH (P = 0.041), DWMH (P = 0.046), and total CSVD score (P = 0.044) than the early PD group. After adjusting for multiple variables, higher H&Y stage was independently correlated with increased total CSVD score (OR = 2.667, 95% CI 1.154–2.266) and PVWMH score (OR = 2.237, 95% CI 1.084–1.696). Conclusions: CSVD may play a critical role in patients with PD. The total CSVD score is a potential neuroimaging marker for monitoring the progression of PD.
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Affiliation(s)
- Xinxin Ma
- Department of Neurology, Parkinson's Disease and Extra Pyramidal Disease Diagnosis and Treatment Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Shuhua Li
- Department of Neurology, Parkinson's Disease and Extra Pyramidal Disease Diagnosis and Treatment Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Chunmei Li
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Rui Wang
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Haibo Chen
- Department of Neurology, Parkinson's Disease and Extra Pyramidal Disease Diagnosis and Treatment Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Wen Su
- Department of Neurology, Parkinson's Disease and Extra Pyramidal Disease Diagnosis and Treatment Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
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31
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Pierzchlińska A, Kwaśniak-Butowska M, Sławek J, Droździk M, Białecka M. Arterial Blood Pressure Variability and Other Vascular Factors Contribution to the Cognitive Decline in Parkinson's Disease. Molecules 2021; 26:molecules26061523. [PMID: 33802165 PMCID: PMC8001922 DOI: 10.3390/molecules26061523] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 03/08/2021] [Accepted: 03/09/2021] [Indexed: 11/24/2022] Open
Abstract
Dementia is one of the most disabling non-motor symptoms in Parkinson’s disease (PD). Unlike in Alzheimer’s disease, the vascular pathology in PD is less documented. Due to the uncertain role of commonly investigated metabolic or vascular factors, e.g., hypertension or diabetes, other factors corresponding to PD dementia have been proposed. Associated dysautonomia and dopaminergic treatment seem to have an impact on diurnal blood pressure (BP) variability, which may presumably contribute to white matter hyperintensities (WMH) development and cognitive decline. We aim to review possible vascular and metabolic factors: Renin-angiotensin-aldosterone system, vascular endothelial growth factor (VEGF), hyperhomocysteinemia (HHcy), as well as the dopaminergic treatment, in the etiopathogenesis of PD dementia. Additionally, we focus on the role of polymorphisms within the genes for catechol-O-methyltransferase (COMT), apolipoprotein E (APOE), vascular endothelial growth factor (VEGF), and for renin-angiotensin-aldosterone system components, and their contribution to cognitive decline in PD. Determining vascular risk factors and their contribution to the cognitive impairment in PD may result in screening, as well as preventive measures.
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Affiliation(s)
- Anna Pierzchlińska
- Department of Pharmacokinetics and Therapeutic Drug Monitoring, Pomeranian Medical University, Aleja Powstańców Wlkp 72, 70-111 Szczecin, Poland;
- Correspondence: (A.P.); (M.D.)
| | - Magdalena Kwaśniak-Butowska
- Division of Neurological and Psychiatric Nursing, Medical University of Gdansk, Aleja Jana Pawła II 50, 80-462 Gdansk, Poland; (M.K.-B.); (J.S.)
- Department of Neurology, St Adalbert Hospital, Aleja Jana Pawła II 50, 80-462 Gdansk, Poland
| | - Jarosław Sławek
- Division of Neurological and Psychiatric Nursing, Medical University of Gdansk, Aleja Jana Pawła II 50, 80-462 Gdansk, Poland; (M.K.-B.); (J.S.)
- Department of Neurology, St Adalbert Hospital, Aleja Jana Pawła II 50, 80-462 Gdansk, Poland
| | - Marek Droździk
- Department of Experimental and Clinical Pharmacology, Pomeranian Medical University, Aleja Powstańców Wlkp 72, 70-111 Szczecin, Poland
- Correspondence: (A.P.); (M.D.)
| | - Monika Białecka
- Department of Pharmacokinetics and Therapeutic Drug Monitoring, Pomeranian Medical University, Aleja Powstańców Wlkp 72, 70-111 Szczecin, Poland;
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32
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Yang Q, Nanivadekar S, Taylor PA, Dou Z, Lungu CI, Horovitz SG. Executive function network's white matter alterations relate to Parkinson's disease motor phenotype. Neurosci Lett 2021; 741:135486. [PMID: 33161103 PMCID: PMC7750296 DOI: 10.1016/j.neulet.2020.135486] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Revised: 10/28/2020] [Accepted: 10/31/2020] [Indexed: 11/25/2022]
Abstract
Parkinson's disease (PD) patients with postural instability and gait disorder phenotype (PIGD) are at high risk of cognitive deficits compared to those with tremor dominant phenotype (TD). Alterations of white matter (WM) integrity can occur in patients with normal cognitive functions (PD-N). However, the alterations of WM integrity related to cognitive functions in PD-N, especially in these two motor phenotypes, remain unclear. Diffusion tensor imaging (DTI) is a non-invasive neuroimaging method to evaluate WM properties and by applying DTI tractography, one can identify WM tracts connecting functional regions. Here, we 1) compared the executive function (EF) in PIGD phenotype with normal cognitive functions (PIGD-N) and TD phenotype with normal cognitive functions (TD-N) phenotypes; 2) used DTI tractography to evaluated differences in WM alterations between these two phenotypes within a task-based functional network; and 3) examined the WM integrity alterations related to EF in a whole brain network for PD-N patients regardless of phenotypes. Thirty-four idiopathic PD-N patients were classified into two groups based on phenotypes: TD-N and PIGD-N, using an algorithm based on UPDRS part III. Neuropsychological tests were used to evaluate patients' EF, including the Trail making test part A and B, the Stroop color naming, the Stroop word naming, the Stroop color-word interference task, as well as the FAS verbal fluency task and the animal category fluency tasks. DTI measures were calculated among WM regions associated with the verbal fluency network defined from previous task fMRI studies and compared between PIGD-N and TD-N groups. In addition, the relationship of DTI measures and verbal fluency scores were evaluated for our full cohort of PD-N patients within the whole brain network. These values were also correlated with the scores of the FAS verbal fluency task. Only the FAS verbal fluency test showed significant group differences, having lower scores in PIGD-N when compared to TD-N phenotype (p < 0.05). Compared to the TD-N, PIGD-N group exhibited significantly higher MD and RD in the tracts connecting the left superior temporal gyrus and left insula, and those connecting the right pars opercularis and right insula. Moreover, compared to TD-N, PIGD-N group had significantly higher RD in the tracts connecting right pars opercularis and right pars triangularis, and the tracts connecting right inferior temporal gyrus and right middle temporal gyrus. For the entire PD-N cohort, FAS verbal fluency scores positively correlated with MD in the superior longitudinal fasciculus (SLF). This study confirmed that PIGD-N phenotype has more deficits in verbal fluency task than TD-N phenotype. Additionally, our findings suggest: (1) PIGD-N shows more microstructural changes related to FAS verbal fluency task when compared to TD-N phenotype; (2) SLF plays an important role in FAS verbal fluency task in PD-N patients regardless of motor phenotypes.
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Affiliation(s)
- Qinglu Yang
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States; The Third Affiliated Hospital of Sun Yat-sen University, Rehabilitation Department, Guangzhou, PR China
| | - Shruti Nanivadekar
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Paul A Taylor
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Zulin Dou
- The Third Affiliated Hospital of Sun Yat-sen University, Rehabilitation Department, Guangzhou, PR China
| | - Codrin I Lungu
- Parkinson Disease Clinic, OCD, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Silvina G Horovitz
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States.
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