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Zheng L, Zhou C, Mao C, Xie C, You J, Cheng W, Liu C, Huang P, Guan X, Guo T, Wu J, Luo Y, Xu X, Zhang B, Zhang M, Wang L, Feng J. Contrastive machine learning reveals Parkinson's disease specific features associated with disease severity and progression. Commun Biol 2024; 7:954. [PMID: 39112797 PMCID: PMC11306336 DOI: 10.1038/s42003-024-06648-x] [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: 12/12/2023] [Accepted: 07/29/2024] [Indexed: 08/10/2024] Open
Abstract
Parkinson's disease (PD) exhibits heterogeneity in terms of symptoms and prognosis, likely due to diverse neuroanatomical alterations. This study employs a contrastive deep learning approach to analyze Magnetic Resonance Imaging (MRI) data from 932 PD patients and 366 controls, aiming to disentangle PD-specific neuroanatomical alterations. The results reveal that these neuroanatomical alterations in PD are correlated with individual differences in dopamine transporter binding deficit, neurodegeneration biomarkers, and clinical severity and progression. The correlation with clinical severity is verified in an external cohort. Notably, certain proteins in the cerebrospinal fluid are strongly associated with PD-specific features, particularly those involved in the immune function. The most notable neuroanatomical alterations are observed in both subcortical and temporal regions. Our findings provide deeper insights into the patterns of brain atrophy in PD and potential underlying molecular mechanisms, paving the way for earlier patient stratification and the development of treatments to slow down neurodegeneration.
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Affiliation(s)
- Liping Zheng
- Institute of Science and Technology for Brain-Inspired Intelligence, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Cheng Zhou
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chengjie Mao
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Chao Xie
- Institute of Science and Technology for Brain-Inspired Intelligence, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Jia You
- Institute of Science and Technology for Brain-Inspired Intelligence, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Chunfeng Liu
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaoujun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tao Guo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jingjing Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yajun Luo
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Baorong Zhang
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Linbo Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
- School of Data Science, Fudan University, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
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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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Ma W, Geng Y, Liu Y, Pan H, Wang Q, Zhang Y, Wang L. The mechanisms of white matter injury and immune system crosstalk in promoting the progression of Parkinson's disease: a narrative review. Front Aging Neurosci 2024; 16:1345918. [PMID: 38863783 PMCID: PMC11165104 DOI: 10.3389/fnagi.2024.1345918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 05/15/2024] [Indexed: 06/13/2024] Open
Abstract
Parkinson's disease (PD) is neurodegenerative disease in middle-aged and elderly people with some pathological mechanisms including immune disorder, neuroinflammation, white matter injury and abnormal aggregation of alpha-synuclein, etc. New research suggests that white matter injury may be important in the development of PD, but how inflammation, the immune system, and white matter damage interact to harm dopamine neurons is not yet understood. Therefore, it is particularly important to delve into the crosstalk between immune cells in the central and peripheral nervous system based on the study of white matter damage in PD. This crosstalk could not only exacerbate the pathological process of PD but may also reveal new therapeutic targets. By understanding how immune cells penetrate through the blood-brain barrier and activate inflammatory responses within the central nervous system, we can better grasp the impact of structural destruction of white matter in PD and explore how this process can be modulated to mitigate or combat disease progression. Microglia, astrocytes, oligodendrocytes and peripheral immune cells (especially T cells) play a central role in its pathological process where these immune cells produce and respond to pro-inflammatory cytokines such as tumor necrosis factor (TNF-α), interleukin-1β(IL-1β) and interleukin-6(IL-6), and white matter injury causes microglia to become pro-inflammatory and release inflammatory mediators, which attract more immune cells to the damaged area, increasing the inflammatory response. Moreover, white matter damage also causes dysfunction of blood-brain barrier, allows peripheral immune cells and inflammatory factors to invade the brain further, and enhances microglia activation forming a vicious circle that intensifies neuroinflammation. And these factors collectively promote the neuroinflammatory environment and neurodegeneration changes of PD. Overall, these findings not only deepen our understanding of the complexity of PD, but also provide new targets for the development of therapeutic strategies focused on inflammation and immune regulation mechanisms. In summary, this review provided the theoretical basis for clarifying the pathogenesis of PD, summarized the association between white matter damage and the immune cells in the central and peripheral nervous systems, and then emphasized their potential specific mechanisms of achieving crosstalk with further aggravating the pathological process of PD.
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Affiliation(s)
- Wen Ma
- Graduate School of Education, Shandong Sport University, Jinan, Shandong, China
| | - Yifan Geng
- Xuzhou Clinical School, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Youhan Liu
- Graduate School of Education, Shandong Sport University, Jinan, Shandong, China
| | - Huixin Pan
- Graduate School of Education, Shandong Sport University, Jinan, Shandong, China
| | - Qinglu Wang
- Graduate School of Education, Shandong Sport University, Jinan, Shandong, China
| | - Yaohua Zhang
- Key Laboratory of Biomedical Engineering & Technology of Shandong High School, Qilu Medical University, Zibo, China
| | - Liping Wang
- Graduate School of Education, Shandong Sport University, Jinan, Shandong, China
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Karalija N, Papenberg G, Johansson J, Wåhlin A, Salami A, Andersson M, Axelsson J, Kuznetsov D, Riklund K, Lövdén M, Lindenberger U, Bäckman L, Nyberg L. Longitudinal support for the correlative triad among aging, dopamine D2-like receptor loss, and memory decline. Neurobiol Aging 2024; 136:125-132. [PMID: 38359585 DOI: 10.1016/j.neurobiolaging.2024.02.001] [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: 05/04/2023] [Revised: 01/25/2024] [Accepted: 02/01/2024] [Indexed: 02/17/2024]
Abstract
Dopamine decline is suggested to underlie aging-related cognitive decline, but longitudinal examinations of this link are currently missing. We analyzed 5-year longitudinal data for a sample of healthy, older adults (baseline: n = 181, age: 64-68 years; 5-year follow-up: n = 129) who underwent positron emission tomography with 11C-raclopride to assess dopamine D2-like receptor (DRD2) availability, magnetic resonance imaging to evaluate structural brain measures, and cognitive tests. Health, lifestyle, and genetic data were also collected. A data-driven approach (k-means cluster analysis) identified groups that differed maximally in DRD2 decline rates in age-sensitive brain regions. One group (n = 47) had DRD2 decline exclusively in the caudate and no cognitive decline. A second group (n = 72) had more wide-ranged DRD2 decline in putamen and nucleus accumbens and also in extrastriatal regions. The latter group showed significant 5-year working memory decline that correlated with putamen DRD2 decline, along with higher dementia and cardiovascular risk and a faster biological pace of aging. Taken together, for individuals with more extensive DRD2 decline, dopamine decline is associated with memory decline in aging.
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Affiliation(s)
- Nina Karalija
- Department of Medical and Translational Biology, Umeå University, Umeå S-90187, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90187, Sweden.
| | - Goran Papenberg
- Aging Research Center, Karolinska Institutet & Stockholm University, Stockholm S-17165, Sweden
| | - Jarkko Johansson
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90187, Sweden; Department of Diagnostics and Intervention, Diagnostic Radiology, Umeå University, Umeå S-90187, Sweden
| | - Anders Wåhlin
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90187, Sweden; Department of Diagnostics and Intervention, Radiation Physics, Umeå University, Umeå S-90187, Sweden; Department of Applied Physics and Electronics, Umeå University, Umeå S-90187, Sweden
| | - Alireza Salami
- Department of Medical and Translational Biology, Umeå University, Umeå S-90187, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90187, Sweden; Aging Research Center, Karolinska Institutet & Stockholm University, Stockholm S-17165, Sweden; Wallenberg Center for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Micael Andersson
- Department of Medical and Translational Biology, Umeå University, Umeå S-90187, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90187, Sweden
| | - Jan Axelsson
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90187, Sweden; Department of Diagnostics and Intervention, Radiation Physics, Umeå University, Umeå S-90187, Sweden
| | - Dmitry Kuznetsov
- Faculty of Sociology, University of Bielefeld, Bielefeld, Germany
| | - Katrine Riklund
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90187, Sweden; Department of Diagnostics and Intervention, Diagnostic Radiology, Umeå University, Umeå S-90187, Sweden
| | - Martin Lövdén
- Department of Psychology, University of Gothenburg, Göteborg S-41314, Sweden
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin D-14195, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, UK
| | - Lars Bäckman
- Aging Research Center, Karolinska Institutet & Stockholm University, Stockholm S-17165, Sweden
| | - Lars Nyberg
- Department of Medical and Translational Biology, Umeå University, Umeå S-90187, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90187, Sweden; Department of Diagnostics and Intervention, Diagnostic Radiology, Umeå University, Umeå S-90187, Sweden
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Buchman AS, Yu L, Oveisgharan S, Zammit AR, Wang T, Shulman JM, VanderHorst V, Nag S, Bennett DA. Parkinson's Disease and Other Alzheimer's Disease and Related Dementia Pathologies and the Progression of Parkinsonism in Older Adults. J Alzheimers Dis 2024; 100:S197-S209. [PMID: 39121125 DOI: 10.3233/jad-240593] [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] [Indexed: 08/11/2024]
Abstract
Background The interrelationship of parkinsonism, Parkinson's disease (PD) and other Alzheimer's disease (AD) and Alzheimer's disease and related dementias (ADRD) pathologies is unclear. Objective We examined the progression of parkinsonian signs in adults with and without parkinsonism, and their underlying brain pathologies. Methods Annual parkinsonian signs were based on a modified Unified Parkinson's Disease Rating Scale. We used linear mixed effects models to compare the progression of parkinsonian signs in 3 groups categorized based on all available clinical evaluations: Group1 (never parkinsonism or clinical PD), Group2 (ever parkinsonism, but never clinical PD), Group3 (ever clinical PD). In decedents, we examined the progression of parkinsonian signs with PD and eight other AD/ADRD pathologies. Results During average follow-up of 8 years, parkinsonian signs on average increased by 7.3% SD/year (N = 3,807). The progression of parkinsonian signs was slowest in Group1 (never parkinsonism or clinical PD), intermediate in Group2, and fastest in Group3. In decedents (n = 1,717) pathologic PD and cerebrovascular (CVD) pathologies were associated with a faster rate of progressive parkinsonian signs (all p values <0.05). However, pathologic PD was rare in adults without clinical PD (Group1, 5%; Group2, 7% versus Group3, 55%). Yet, 70% of adults in Group2 without pathologic PD showed one or more CVD pathologies. In Group2, adults with pathologic PD showed faster progression of parkinsonian signs compared with those without evidence of pathologic PD and their rate of progression was indistinguishable from adults with clinical PD. Conclusions Parkinsonism in old age is more commonly related to cerebrovascular pathologies relative to pathologic PD and only a minority manifest prodromal PD.
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Affiliation(s)
- Aron S Buchman
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Shahram Oveisgharan
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Andrea R Zammit
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Tianhao Wang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Joshua M Shulman
- Department of Neurology and Center for Alzheimer's and Neurodegenerative Diseases, Baylor College of Medicine and Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | | | - Sukrit Nag
- Department of Pathology (Neuropathology), Rush University Medical Center, Chicago, IL, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
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Zhang Y, Ya D, Yang J, Jiang Y, Li X, Wang J, Tian N, Deng J, Yang B, Li Q, Liao R. EAAT3 impedes oligodendrocyte remyelination in chronic cerebral hypoperfusion-induced white matter injury. CNS Neurosci Ther 2024; 30:e14487. [PMID: 37803915 PMCID: PMC10805396 DOI: 10.1111/cns.14487] [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: 06/26/2023] [Revised: 09/20/2023] [Accepted: 09/22/2023] [Indexed: 10/08/2023] Open
Abstract
BACKGROUND Chronic cerebral hypoperfusion-induced demyelination causes progressive white matter injury, although the pathogenic pathways are unknown. METHODS The Single Cell Portal and PanglaoDB databases were used to analyze single-cell RNA sequencing experiments to determine the pattern of EAAT3 expression in CNS cells. Immunofluorescence (IF) was used to detect EAAT3 expression in oligodendrocytes and oligodendrocyte progenitor cells (OPCs). EAAT3 levels in mouse brains were measured using a western blot at various phases of development, as well as in traumatic brain injury (TBI) and intracerebral hemorrhage (ICH) mouse models. The mouse bilateral carotid artery stenosis (BCAS) model was used to create white matter injury. IF, Luxol Fast Blue staining, and electron microscopy were used to investigate the effect of remyelination. 5-Ethynyl-2-Deoxy Uridine staining, transwell chamber assays, and IF were used to examine the effects of OPCs' proliferation, migration, and differentiation in vivo and in vitro. The novel object recognition test, the Y-maze test, the rotarod test, and the grid walking test were used to examine the impact of behavioral modifications. RESULTS A considerable amount of EAAT3 was expressed in OPCs and mature oligodendrocytes, according to single-cell RNA sequencing data. During multiple critical phases of mouse brain development, there were no substantial changes in EAAT3 levels in the hippocampus, cerebral cortex, or white matter. Furthermore, neither the TBI nor ICH models significantly affected the levels of EAAT3 in the aforementioned brain areas. The chronic white matter injury caused by BCAS, on the other hand, resulted in a strikingly high level of EAAT3 expression in the oligodendroglia and white matter. Correspondingly, blocking EAAT3 assisted in the recovery of cognitive and motor impairment as well as the restoration of cerebral blood flow following BCAS. Furthermore, EAAT3 suppression was connected to improved OPCs' survival and proliferation in vivo as well as faster OPCs' proliferation, migration, and differentiation in vitro. Furthermore, this study revealed that the mTOR pathway is implicated in EAAT3-mediated remyelination. CONCLUSIONS Our findings provide the first evidence that abnormally high levels of oligodendroglial EAAT3 in chronic cerebral hypoperfusion impair OPCs' pro-remyelination actions, hence impeding white matter repair and functional recovery. EAAT3 inhibitors could be useful in the treatment of ischemia demyelination.
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Affiliation(s)
- Yingmei Zhang
- Laboratory of NeuroscienceAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
- Department of NeurologyAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
| | - Dongshan Ya
- Laboratory of NeuroscienceAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
- Department of NeurologyAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
| | - Jiaxin Yang
- Laboratory of NeuroscienceAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
- Department of NeurologyAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
| | - Yanlin Jiang
- Department of PharmacologyAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
| | - Xiaoxia Li
- Laboratory of NeuroscienceAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
- Department of NeurologyAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
| | - Jiawen Wang
- Laboratory of NeuroscienceAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
- Guangxi Clinical Research Center for Neurological DiseasesAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
| | - Ning Tian
- Laboratory of NeuroscienceAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
- Guangxi Clinical Research Center for Neurological DiseasesAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
| | - Jungang Deng
- Department of PharmacologyAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
| | - Bin Yang
- Guangxi Clinical Research Center for Neurological DiseasesAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
| | - Qinghua Li
- Laboratory of NeuroscienceAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
- Department of NeurologyAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
- Guangxi Clinical Research Center for Neurological DiseasesAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
| | - Rujia Liao
- Laboratory of NeuroscienceAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
- Department of NeurologyAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
- Guangxi Clinical Research Center for Neurological DiseasesAffiliated Hospital of Guilin Medical University, Guilin Medical UniversityGuilinChina
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Cai M, Jacob MA, Marques J, Norris DG, Duering M, Esselink RAJ, Zhang Y, de Leeuw FE, Tuladhar AM. Structural Network Efficiency Predicts Conversion to Incident Parkinsonism in Patients With Cerebral Small Vessel Disease. J Gerontol A Biol Sci Med Sci 2024; 79:glad182. [PMID: 37527837 PMCID: PMC10733213 DOI: 10.1093/gerona/glad182] [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: 03/31/2023] [Indexed: 08/03/2023] Open
Abstract
BACKGROUND To investigate whether structural network disconnectivity is associated with parkinsonian signs and their progression, as well as with an increased risk of incident parkinsonism. METHODS In a prospective cohort (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort study) consisting of 293 participants with small vessel disease (SVD), we assessed parkinsonian signs and incident parkinsonism over an 8-year follow-up. In addition, we reconstructed the white matter network followed by graph-theoretical analyses to compute the network metrics. Conventional magnetic resonance imaging markers for SVD were assessed. RESULTS We included 293 patients free of parkinsonism at baseline (2011), with a mean age 68.8 (standard deviation [SD] 8.4) years, and 130 (44.4%) were men. Nineteen participants (6.5%) developed parkinsonism during a median (SD) follow-up time of 8.3 years. Compared with participants without parkinsonism, those with all-cause parkinsonism had higher Unified Parkinson's Disease Rating scale (UPDRS) scores and lower global efficiency at baseline. Baseline global efficiency was associated with UPDRS motor scores in 2011 (β = -0.047, p < .001) and 2015 (β = -0.84, p < .001), as well as with the changes in UPDRS scores during the 4-year follow-up (β = -0.63, p = .004). In addition, at the regional level, we identified an inter-hemispheric disconnected network associated with an increased UPDRS motor score. Besides, lower global efficiency was associated with an increased risk of all-cause and vascular parkinsonism independent of SVD markers. CONCLUSIONS Our findings suggest that global network efficiency is associated with a gradual decline in motor performance, ultimately leading to incident parkinsonism in the elderly with SVD. Global network efficiency may have the added value to serve as a useful marker to capture changes in motor signs.
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Affiliation(s)
- Mengfei Cai
- Department of Neurology, Guangdong Cardiovascular Institute, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Mina A Jacob
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - José Marques
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - David G Norris
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Marco Duering
- Medical Image Analysis Center (MIAC AG) and qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Rianne A J Esselink
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Yuhu Zhang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People’s Republic of China
| | - Frank-Erik de Leeuw
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Anil M Tuladhar
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
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Gan J, Shi Z, Liu S, Li X, Liu Y, Zhu H, Shen L, Zhang G, Lu H, Gang B, Chen Z, Ji Y. White matter hyperintensities in cognitive impairment with Lewy body disease: a multicentre study. Eur J Neurol 2023; 30:3711-3721. [PMID: 37500565 DOI: 10.1111/ene.16002] [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: 05/16/2023] [Revised: 07/13/2023] [Accepted: 07/19/2023] [Indexed: 07/29/2023]
Abstract
BACKGROUND AND PURPOSE White matter hyperintensities (WMHs) are associated with cognitive deficits and worse clinical outcomes in dementia, but rare studies have been carried out of cognitive impairment in Lewy body disease (CI-LB) patients. The objective was to investigate the associations between WMHs and clinical manifestations in patients with CI-LB. METHODS In this retrospective multicentre cohort study, 929 patients (486 with dementia with Lewy bodies [DLB], 262 with Parkinson's disease dementia [PDD], 74 with mild cognitive impairment [MCI] with Lewy bodies [MCI-LB] and 107 with Parkinson's disease with MCI [PD-MCI]) were analysed from 22 memory clinics between January 2018 and June 2022. Demographic and clinical data were collected by reviewing medical records. WMHs were semi-quantified according to the Fazekas method. Associations between WMHs and clinical manifestations were investigated by multivariate linear or logistic regression models. RESULTS Dementia with Lewy bodies patients had the highest Fazekas scores compared with PDD, MCI-LB and PD-MCI. Multivariable regressions showed the Fazekas score was positively associated with the scores of Unified Parkinson's Disease Rating Scale Part III (p = 0.001), Hoehn-Yahn stage (p = 0.004) and total Neuropsychiatric Inventory (p = 0.001) in MCI-LB and PD-MCI patients. In patients with DLB and PDD, Fazekas scores were associated with the absence of rapid eye movement sleep behaviour disorder (p = 0.041) and scores of Unified Parkinson's Disease Rating Scale Part III (p < 0.001), Hoehn-Yahn stage (p < 0.001) and the Montreal Cognitive Assessment (p = 0.014). CONCLUSION White matter hyperintensity burden of DLB was higher than for PDD, MCI-LB and PD-MCI. The greater WMH burden was significantly associated with poorer cognitive performance, worse motor function and more severe neuropsychiatric symptoms in CI-LB.
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Affiliation(s)
- Jinghuan Gan
- Department of Neurology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhihong Shi
- Department of Neurology, Tianjin Key Laboratory of Cerebrovascular and of Neurodegenerative Diseases, Tianjin Dementia Institute, Tianjin Huanhu Hospital, Tianjin, China
| | - Shuai Liu
- Department of Neurology, Tianjin Key Laboratory of Cerebrovascular and of Neurodegenerative Diseases, Tianjin Dementia Institute, Tianjin Huanhu Hospital, Tianjin, China
| | - Xudong Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Centre for Neurological Diseases, Beijing, China
| | - Yiming Liu
- Department of Neurology, Qilu Hospital, Shandong University, Shandong, China
| | - Hongcan Zhu
- Department of Neurology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lu Shen
- Department of Neurology, Xiangya Hospital, Central South University, Hunan, China
| | - Guili Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Centre for Neurological Diseases, Beijing, China
| | - Hao Lu
- Department of Radiology, Tianjin Huanhu Hospital, Tianjin, China
| | - Baozhi Gang
- Department of Neurology, First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Zhichao Chen
- Department of Neurology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Yong Ji
- Department of Neurology, Tianjin Key Laboratory of Cerebrovascular and of Neurodegenerative Diseases, Tianjin Dementia Institute, Tianjin Huanhu Hospital, Tianjin, China
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Blackhurst BM, Funk KE. Molecular and Cellular Mechanisms Underlying Neurologic Manifestations of Mosquito-Borne Flavivirus Infections. Viruses 2023; 15:2200. [PMID: 38005878 PMCID: PMC10674799 DOI: 10.3390/v15112200] [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: 09/30/2023] [Revised: 10/21/2023] [Accepted: 10/25/2023] [Indexed: 11/26/2023] Open
Abstract
Flaviviruses are a family of enveloped viruses with a positive-sense RNA genome, transmitted by arthropod vectors. These viruses are known for their broad cellular tropism leading to infection of multiple body systems, which can include the central nervous system. Neurologic effects of flavivirus infection can arise during both acute and post-acute infectious periods; however, the molecular and cellular mechanisms underlying post-acute sequelae are not fully understood. Here, we review recent studies that have examined molecular and cellular mechanisms that may contribute to neurologic sequelae following infection with the West Nile virus, Japanese encephalitis virus, Zika virus, dengue virus, and St. Louis encephalitis virus. Neuronal death, either from direct infection or due to the resultant inflammatory response, is a common mechanism by which flavivirus infection can lead to neurologic impairment. Other types of cellular damage, such as oxidative stress and DNA damage, appear to be more specific to certain viruses. This article aims to highlight mechanisms of cellular damage that are common across several flavivirus members and mechanisms that are more unique to specific members. Our goal is to inspire further research to improve understanding of this area in the hope of identifying treatment options for flavivirus-associated neurologic changes.
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Affiliation(s)
| | - Kristen E. Funk
- Department of Biological Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
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10
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Agrawal S, Leurgans SE, Nag S, Oveisgharan S, Barnes LL, Bennett DA, Buchman AS, Schneider JA. Effects of Cerebrovascular and Lewy Body Pathology on Parkinsonian Signs in Community-Dwelling Older Adults. Neurology 2023; 101:e754-e763. [PMID: 37438127 PMCID: PMC10437019 DOI: 10.1212/wnl.0000000000207497] [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: 08/26/2022] [Accepted: 04/21/2023] [Indexed: 07/14/2023] Open
Abstract
BACKGROUND AND OBJECTIVES The roles of Lewy body (LB) and separately of cerebrovascular disease (CVD) pathologies in the severity of parkinsonian signs are well recognized in old age. We investigated whether the 2 pathologies act synergistically to further potentiate the severity of parkinsonism beyond their separate effects. METHODS We used postmortem data of decedents from 3 longitudinal community-based studies of aging who underwent annual clinical evaluation to assess parkinsonian signs using 26 items of the motor portion of a modified Unified Parkinson Disease Rating Scale. A summary score was developed from each item score to construct a global parkinsonian score, with a higher score indicating more severe parkinsonism. A detailed neuropathologic evaluation was performed to identify LB, Alzheimer disease pathology, nigral neuronal loss, atherosclerosis, macroscopic infarcts, and other CVD pathologies (arteriolosclerosis, cerebral amyloid angiopathy, and microscopic infarcts). A series of regression models with terms for LB, CVD pathology, and the interaction of LB with CVD pathologies was fit for global parkinsonism proximate to death and for individual parkinsonian signs scores including, parkinsonian gait, rigidity, tremor, and bradykinesia. RESULTS In 1,753 participants (mean age at death = 89 years; 68% women), LB was observed in 26% of participants, and CVD pathologies were present in more than two-thirds of participants. LB and 3 CVD pathologies (atherosclerosis, arteriolosclerosis, and macroscopic infarcts) were each independently associated with the severity of global parkinsonism proximate to death (LB: β = 0.318, SE = 0.08, p < 0.001; atherosclerosis: β = 0.373, SE = 0.079, p < 0.001; arteriolosclerosis: β = 0.253, SE = 0.078, p = 0.001; macroscopic infarcts: β = 0.333, SE = 0.077, p < 0.001). A linear regression model adjusted for demographics, CVD, and neurodegenerative pathologies showed interaction between LB and macroscopic infarcts (β = 0.463, SE = 0.168, p = 0.006), with LBs being associated with worse global parkinsonism when macroinfarcts are present. Similar interactions were found for atherosclerosis and LBs (β = 0.371, SE = 0.173, p = 0.032) and for parkinsonian gait as the outcome (macroscopic infarcts: β = 0.662, SE = 0.239, p = 0.005; atherosclerosis: β = 0.509, SE = 0.246, p = 0.038). Findings were not affected when the 66 participants with a clinical diagnosis of Parkinson disease were excluded. By contrast, there were no interactions between LB and other CVD pathologies or between atherosclerosis and macroscopic infarcts for global parkinsonism proximate to death. DISCUSSION These findings suggest that atherosclerosis and macroscopic infarcts interact with LB pathology to increase the severity of parkinsonism beyond their additive effects in older persons.
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Affiliation(s)
- Sonal Agrawal
- From the Rush Alzheimer's Disease Center (S.A., S.E.L., S.N., S.O., L.L.B., D.A.B., A.S.B., J.A.S.); Departments of Pathology (S.A., S.N., J.A.S.), Neurological Sciences (S.E.L., S.O., L.L.B., D.A.B., A.S.B., J.A.S.) and Behavioral Sciences (L.L.B.), Rush University Medical Center, Chicago, IL.
| | - Sue E Leurgans
- From the Rush Alzheimer's Disease Center (S.A., S.E.L., S.N., S.O., L.L.B., D.A.B., A.S.B., J.A.S.); Departments of Pathology (S.A., S.N., J.A.S.), Neurological Sciences (S.E.L., S.O., L.L.B., D.A.B., A.S.B., J.A.S.) and Behavioral Sciences (L.L.B.), Rush University Medical Center, Chicago, IL
| | - Sukriti Nag
- From the Rush Alzheimer's Disease Center (S.A., S.E.L., S.N., S.O., L.L.B., D.A.B., A.S.B., J.A.S.); Departments of Pathology (S.A., S.N., J.A.S.), Neurological Sciences (S.E.L., S.O., L.L.B., D.A.B., A.S.B., J.A.S.) and Behavioral Sciences (L.L.B.), Rush University Medical Center, Chicago, IL
| | - Shahram Oveisgharan
- From the Rush Alzheimer's Disease Center (S.A., S.E.L., S.N., S.O., L.L.B., D.A.B., A.S.B., J.A.S.); Departments of Pathology (S.A., S.N., J.A.S.), Neurological Sciences (S.E.L., S.O., L.L.B., D.A.B., A.S.B., J.A.S.) and Behavioral Sciences (L.L.B.), Rush University Medical Center, Chicago, IL
| | - Lisa L Barnes
- From the Rush Alzheimer's Disease Center (S.A., S.E.L., S.N., S.O., L.L.B., D.A.B., A.S.B., J.A.S.); Departments of Pathology (S.A., S.N., J.A.S.), Neurological Sciences (S.E.L., S.O., L.L.B., D.A.B., A.S.B., J.A.S.) and Behavioral Sciences (L.L.B.), Rush University Medical Center, Chicago, IL
| | - David A Bennett
- From the Rush Alzheimer's Disease Center (S.A., S.E.L., S.N., S.O., L.L.B., D.A.B., A.S.B., J.A.S.); Departments of Pathology (S.A., S.N., J.A.S.), Neurological Sciences (S.E.L., S.O., L.L.B., D.A.B., A.S.B., J.A.S.) and Behavioral Sciences (L.L.B.), Rush University Medical Center, Chicago, IL
| | - Aron S Buchman
- From the Rush Alzheimer's Disease Center (S.A., S.E.L., S.N., S.O., L.L.B., D.A.B., A.S.B., J.A.S.); Departments of Pathology (S.A., S.N., J.A.S.), Neurological Sciences (S.E.L., S.O., L.L.B., D.A.B., A.S.B., J.A.S.) and Behavioral Sciences (L.L.B.), Rush University Medical Center, Chicago, IL
| | - Julie A Schneider
- From the Rush Alzheimer's Disease Center (S.A., S.E.L., S.N., S.O., L.L.B., D.A.B., A.S.B., J.A.S.); Departments of Pathology (S.A., S.N., J.A.S.), Neurological Sciences (S.E.L., S.O., L.L.B., D.A.B., A.S.B., J.A.S.) and Behavioral Sciences (L.L.B.), Rush University Medical Center, Chicago, IL
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Wang L, Zhou C, Zhang W, Zhang M, Cheng W, Feng J. Association of Cortical and Subcortical Microstructure With Clinical Progression and Fluid Biomarkers in Patients With Parkinson Disease. Neurology 2023; 101:e300-e310. [PMID: 37202161 PMCID: PMC10382272 DOI: 10.1212/wnl.0000000000207408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 03/28/2023] [Indexed: 05/20/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Mean diffusivity (MD) of diffusion MRI (dMRI) has been used to measure cortical and subcortical microstructural properties. This study investigated relationships of cortical and subcortical MD, clinical progression, and fluid biomarkers in Parkinson disease (PD). METHODS This longitudinal study using data from the Parkinson's Progression Markers Initiative was collected from April 2011 to July 2022. Clinical symptoms were assessed with Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (UPDRS) and Montreal Cognitive Assessment (MoCA) scores. Clinical assessments were followed up to 5 years. Linear mixed-effects (LME) models were performed to examine associations of MD and the annual rate of changes in clinical scores. Partial correlation analysis was conducted to examine the associations of MD and fluid biomarker levels. RESULTS A total of 174 patients with PD (age 61.9 ± 9.7 years, 63% male) with baseline dMRI and at least 2 years of clinical follow-up were included. Results of LME models revealed a significant association between MD values, predominantly in subcortical regions, temporal lobe, occipital lobe, and frontal lobe, and annual rate of changes in clinical scores (UPDRS-Part-I, standardized β > 2.35; UPDRS-Part-II, standardized β > 2.34; postural instability and gait disorder score, standardized β > 2.47; MoCA, standardized β < -2.42; all p < 0.05, false discovery rate [FDR] corrected). In addition, MD was associated with the levels of neurofilament light chain in serum (r > 0.22) and α-synuclein (right putamen r = 0.31), β-amyloid 1-42 (left hippocampus r = -0.30), phosphorylated tau at 181 threonine position (r > 0.26), and total tau (r > 0.23) in CSF at baseline (all p < 0.05, FDR corrected). Furthermore, the β coefficients derived from MD and annual rate of changes in the clinical score recapitulated the spatial distribution of dopamine (DAT, D1, and D2), glutamate (mGluR5 and NMDA), serotonin (5-HT1a and 5-HT2a), cannabinoid (CB1), and γ-amino butyric acid A receptor neurotransmitter receptors/transporters (p < 0.05, FDR corrected) derived from PET scans in the brain of healthy volunteers. DISCUSSION In this cohort study, cortical and subcortical MD values at baseline were associated with clinical progression and baseline fluid biomarkers, suggesting that microstructural properties could be useful for stratification of patients with fast clinical progression.
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Affiliation(s)
- Linbo Wang
- From the Institute of Science and Technology for Brain-Inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; MOE Frontiers Center for Brain Science (L.W., W.Z., W.C., J.F.), Fudan University; Zhangjiang Fudan International Innovation Center (L.W., W.Z., W.C., J.F.), Shanghai; Department of Radiology (C.Z., M.Z.), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C.), Zhejiang Normal University, Jinhua, China; and Department of Computer Science (J.F.), University of Warwick, Coventry, United Kingdom
| | - Cheng Zhou
- From the Institute of Science and Technology for Brain-Inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; MOE Frontiers Center for Brain Science (L.W., W.Z., W.C., J.F.), Fudan University; Zhangjiang Fudan International Innovation Center (L.W., W.Z., W.C., J.F.), Shanghai; Department of Radiology (C.Z., M.Z.), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C.), Zhejiang Normal University, Jinhua, China; and Department of Computer Science (J.F.), University of Warwick, Coventry, United Kingdom
| | - Wei Zhang
- From the Institute of Science and Technology for Brain-Inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; MOE Frontiers Center for Brain Science (L.W., W.Z., W.C., J.F.), Fudan University; Zhangjiang Fudan International Innovation Center (L.W., W.Z., W.C., J.F.), Shanghai; Department of Radiology (C.Z., M.Z.), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C.), Zhejiang Normal University, Jinhua, China; and Department of Computer Science (J.F.), University of Warwick, Coventry, United Kingdom
| | - Minming Zhang
- From the Institute of Science and Technology for Brain-Inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; MOE Frontiers Center for Brain Science (L.W., W.Z., W.C., J.F.), Fudan University; Zhangjiang Fudan International Innovation Center (L.W., W.Z., W.C., J.F.), Shanghai; Department of Radiology (C.Z., M.Z.), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C.), Zhejiang Normal University, Jinhua, China; and Department of Computer Science (J.F.), University of Warwick, Coventry, United Kingdom
| | - Wei Cheng
- From the Institute of Science and Technology for Brain-Inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; MOE Frontiers Center for Brain Science (L.W., W.Z., W.C., J.F.), Fudan University; Zhangjiang Fudan International Innovation Center (L.W., W.Z., W.C., J.F.), Shanghai; Department of Radiology (C.Z., M.Z.), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C.), Zhejiang Normal University, Jinhua, China; and Department of Computer Science (J.F.), University of Warwick, Coventry, United Kingdom
| | - Jianfeng Feng
- From the Institute of Science and Technology for Brain-Inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; MOE Frontiers Center for Brain Science (L.W., W.Z., W.C., J.F.), Fudan University; Zhangjiang Fudan International Innovation Center (L.W., W.Z., W.C., J.F.), Shanghai; Department of Radiology (C.Z., M.Z.), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C.), Zhejiang Normal University, Jinhua, China; and Department of Computer Science (J.F.), University of Warwick, Coventry, United Kingdom.
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12
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Shu L, Zhong K, Chen N, Gu W, Shang W, Liang J, Ren J, Hong H. Predicting the severity of white matter lesions among patients with cerebrovascular risk factors based on retinal images and clinical laboratory data: a deep learning study. Front Neurol 2023; 14:1168836. [PMID: 37492851 PMCID: PMC10363667 DOI: 10.3389/fneur.2023.1168836] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 06/20/2023] [Indexed: 07/27/2023] Open
Abstract
Background and purpose As one common feature of cerebral small vascular disease (cSVD), white matter lesions (WMLs) could lead to reduction in brain function. Using a convenient, cheap, and non-intrusive method to detect WMLs could substantially benefit to patient management in the community screening, especially in the settings of availability or contraindication of magnetic resonance imaging (MRI). Therefore, this study aimed to develop a useful model to incorporate clinical laboratory data and retinal images using deep learning models to predict the severity of WMLs. Methods Two hundred fifty-nine patients with any kind of neurological diseases were enrolled in our study. Demographic data, retinal images, MRI, and laboratory data were collected for the patients. The patients were assigned to the absent/mild and moderate-severe WMLs groups according to Fazekas scoring system. Retinal images were acquired by fundus photography. A ResNet deep learning framework was used to analyze the retinal images. A clinical-laboratory signature was generated from laboratory data. Two prediction models, a combined model including demographic data, the clinical-laboratory signature, and the retinal images and a clinical model including only demographic data and the clinical-laboratory signature, were developed to predict the severity of WMLs. Results Approximately one-quarter of the patients (25.6%) had moderate-severe WMLs. The left and right retinal images predicted moderate-severe WMLs with area under the curves (AUCs) of 0.73 and 0.94. The clinical-laboratory signature predicted moderate-severe WMLs with an AUC of 0.73. The combined model showed good performance in predicting moderate-severe WMLs with an AUC of 0.95, while the clinical model predicted moderate-severe WMLs with an AUC of 0.78. Conclusion Combined with retinal images from conventional fundus photography and clinical laboratory data are reliable and convenient approach to predict the severity of WMLs and are helpful for the management and follow-up of WMLs patients.
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Affiliation(s)
- Liming Shu
- Department of Neurology, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
- Department of Neurology, Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Kaiyi Zhong
- Department of Neurology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Nanya Chen
- School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China
| | - Wenxin Gu
- School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China
| | - Wenjing Shang
- Department of Neurology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jiahui Liang
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, Guangzhou, China
- Guangdong Key Laboratory of Non-human Primate Research, Guangdong-Hongkong-Macau Institute of CNS Regeneration, Jinan University, Guangzhou, China
| | - Jiangtao Ren
- School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China
| | - Hua Hong
- Department of Neurology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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13
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Chen Z, Wu B, Li G, Zhou L, Zhang L, Liu J. Age and sex differentially shape brain networks in Parkinson's disease. CNS Neurosci Ther 2023. [PMID: 36890620 DOI: 10.1111/cns.14149] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 02/18/2023] [Accepted: 02/20/2023] [Indexed: 03/10/2023] Open
Abstract
AIMS Age and sex are important individual factors modifying the clinical symptoms of patients with Parkinson's disease (PD). Our goal is to evaluate the effects of age and sex on brain networks and clinical manifestations of PD patients. METHODS Parkinson's disease participants (n = 198) receiving functional magnetic resonance imaging from Parkinson's Progression Markers Initiative database were investigated. Participants were classified into lower quartile group (age rank: 0%~25%), interquartile group (age rank: 26%~75%), and upper quartile group (age rank: 76%~100%) according to their age quartiles to examine how age shapes brain network topology. The differences of brain network topological properties between male and female participants were also investigated. RESULTS Parkinson's disease patients in the upper quartile age group exhibited disrupted network topology of white matter networks and impaired integrity of white matter fibers compared to lower quartile age group. In contrast, sex preferentially shaped the small-world topology of gray matter covariance network. Differential network metrics mediated the effects of age and sex on cognitive function of PD patients. CONCLUSION Age and sex have diverse effects on brain structural networks and cognitive function of PD patients, highlighting their roles in the clinical management of PD.
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Affiliation(s)
- Zhichun Chen
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Department of Neurology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Bin Wu
- Department of Neurology, Xuchang Central Hospital affiliated with Henan University of Science and Technology, Henan, China
| | - Guanglu Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Liche Zhou
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lina Zhang
- Department of Biostatistics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Liu
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Jacob MA, Cai M, Bergkamp M, Darweesh SKL, Gelissen LMY, Marques J, Norris DG, Duering M, Esselink RAJ, Tuladhar AM, de Leeuw FE. Cerebral Small Vessel Disease Progression Increases Risk of Incident Parkinsonism. Ann Neurol 2023; 93:1130-1141. [PMID: 36762437 DOI: 10.1002/ana.26615] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 02/05/2023] [Accepted: 02/08/2023] [Indexed: 02/11/2023]
Abstract
OBJECTIVE Cerebral small vessel disease (SVD) is associated with motor impairments and parkinsonian signs cross-sectionally, however, there are little longitudinal data on whether SVD increases risk of incident parkinsonism itself. We investigated the relation between baseline SVD severity as well as SVD progression, and incident parkinsonism over a follow-up of 14 years. METHODS This study included 503 participants with SVD, and without parkinsonism at baseline, from the RUN DMC prospective cohort study. Baseline inclusion was performed in 2006 and follow-up took place in 2011, 2015, and 2020, including magnetic resonance imaging (MRI) and motor assessments. Parkinsonism was diagnosed according to the UK Brain Bank criteria, and stratified into vascular parkinsonism (VaP) and idiopathic Parkinson's disease (IPD). Linear mixed-effect models were constructed to estimate individual rate changes of MRI-characteristics. RESULTS Follow-up for incident parkinsonism was near-complete (99%). In total, 51 (10.2%) participants developed parkinsonism (33 VaP, 17 IPD, and 1 progressive supranuclear palsy). Patients with incident VaP had higher SVD burden compared with patients with IPD. Higher baseline white matter hyperintensities (hazard ratio [HR] = 1.46 per 1-SD increase, 95% confidence interval [CI] = 1.21-1.78), peak width of skeletonized mean diffusivity (HR = 1.66 per 1-SD increase, 95% CI = 1.34-2.05), and presence of lacunes (HR = 1.84, 95% CI = 0.99-3.42) were associated with increased risk of all-cause parkinsonism. Incident lacunes were associated with incident VaP (HR = 4.64, 95% CI = 1.32-16.32). INTERPRETATION Both baseline SVD severity and SVD progression are independently associated with long-term parkinsonism. Our findings indicate a causal role of SVD in parkinsonism. Future studies are needed to examine the underlying pathophysiology of this relation. ANN NEUROL 2023.
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Affiliation(s)
- Mina A Jacob
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mengfei Cai
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands.,Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Mayra Bergkamp
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Sirwan K L Darweesh
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Liza M Y Gelissen
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - José Marques
- Center for Cognitive Neuroimaging, Cognition and Behaviour, Nijmegen, The Netherlands
| | - David G Norris
- Center for Cognitive Neuroimaging, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Marco Duering
- Medical Image Analysis Center (MIAC AG) and qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Rianne A J Esselink
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Anil M Tuladhar
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
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15
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Oveisgharan S, Kim N, Agrawal S, Yu L, Leurgans S, Kapasi A, Arfanakis K, Bennett DA, Schneider JA, Buchman AS. Brain and spinal cord arteriolosclerosis and its associations with cerebrovascular disease risk factors in community-dwelling older adults. Acta Neuropathol 2023; 145:219-233. [PMID: 36469116 PMCID: PMC10183107 DOI: 10.1007/s00401-022-02527-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 11/30/2022] [Accepted: 11/30/2022] [Indexed: 12/12/2022]
Abstract
Arteriolosclerosis is common in older brains and related to cognitive and motor impairment. We compared the severity of arteriolosclerosis and its associations with cerebrovascular disease risk factors (CVD-RFs) in multiple locations in the brain and spinal cord. Participants (n = 390) were recruited in the context of a longitudinal community-based clinical-pathological study, the Rush Memory and Aging Project. CVD-RFs were assessed annually for an average of 8.7 (SD = 4.3) years before death. The annual assessments included systolic (SBP) and diastolic (DBP) blood pressure, diabetes mellitus (DM), low- and high-density lipoprotein cholesterol, triglyceride, body mass index, and smoking. Postmortem pathological assessments included assessment of arteriolosclerosis severity using the same rating scale in three brain locations (basal ganglia, frontal, and parietal white matter regions) and four spinal cord levels (cervical, thoracic, lumbar and sacral levels). A single measure was used to summarize the severity of spinal arteriolosclerosis assessments at the four levels due to their high correlations. Average age at death was 91.5 (SD = 6.2) years, and 73% were women. Half showed arteriolosclerosis in frontal white matter and spinal cord followed by parietal white matter (38%) and basal ganglia (27%). The severity of arteriolosclerosis in all three brain locations showed mild-to-moderate correlations. By contrast, spinal arteriolosclerosis was associated with brain arteriolosclerosis only in frontal white matter. Higher DBP was associated with more severe arteriolosclerosis in all three brain locations. DM was associated with more severe arteriolosclerosis only in frontal white matter. Controlling for DBP, higher SBP was inversely associated with arteriolosclerosis in parietal white matter. Blood cholesterol and triglyceride, high body mass index, or smoking were not related to the severity of arteriolosclerosis in any brain region. None of the CVD-RFs were associated with the severity of spinal arteriolosclerosis. These data indicate that severity of arteriolosclerosis and its associations with CVD-RFs may vary in different CNS locations.
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Affiliation(s)
- Shahram Oveisgharan
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison, Suite 1000, Chicago, IL, USA.
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA.
| | - Namhee Kim
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison, Suite 1000, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Sonal Agrawal
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison, Suite 1000, Chicago, IL, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Chicago, IL, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison, Suite 1000, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Sue Leurgans
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison, Suite 1000, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Alifiya Kapasi
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison, Suite 1000, Chicago, IL, USA
- Department of Pathology, Rush University Medical Center, Chicago, IL, USA
| | - Konstantinos Arfanakis
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison, Suite 1000, Chicago, IL, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Chicago, IL, USA
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison, Suite 1000, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Julie A Schneider
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison, Suite 1000, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
- Department of Pathology, Rush University Medical Center, Chicago, IL, USA
| | - Aron S Buchman
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison, Suite 1000, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
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16
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Huang P, Zhang M. Magnetic Resonance Imaging Studies of Neurodegenerative Disease: From Methods to Translational Research. Neurosci Bull 2023; 39:99-112. [PMID: 35771383 PMCID: PMC9849544 DOI: 10.1007/s12264-022-00905-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 05/07/2022] [Indexed: 01/22/2023] Open
Abstract
Neurodegenerative diseases (NDs) have become a significant threat to an aging human society. Numerous studies have been conducted in the past decades to clarify their pathologic mechanisms and search for reliable biomarkers. Magnetic resonance imaging (MRI) is a powerful tool for investigating structural and functional brain alterations in NDs. With the advantages of being non-invasive and non-radioactive, it has been frequently used in both animal research and large-scale clinical investigations. MRI may serve as a bridge connecting micro- and macro-level analysis and promoting bench-to-bed translational research. Nevertheless, due to the abundance and complexity of MRI techniques, exploiting their potential is not always straightforward. This review aims to briefly introduce research progress in clinical imaging studies and discuss possible strategies for applying MRI in translational ND research.
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Affiliation(s)
- Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009 China
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17
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Error in Figure. JAMA Neurol 2022; 79:531. [PMID: 35311952 DOI: 10.1001/jamaneurol.2022.0536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
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