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Hanania JU, Reimers E, Bevington CWJ, Sossi V. PET-based brain molecular connectivity in neurodegenerative disease. Curr Opin Neurol 2024:00019052-990000000-00169. [PMID: 38813843 DOI: 10.1097/wco.0000000000001283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
PURPOSE OF REVIEW Molecular imaging has traditionally been used and interpreted primarily in the context of localized and relatively static neurochemical processes. New understanding of brain function and development of novel molecular imaging protocols and analysis methods highlights the relevance of molecular networks that co-exist and interact with functional and structural networks. Although the concept and evidence of disease-specific metabolic brain patterns has existed for some time, only recently has such an approach been applied in the neurotransmitter domain and in the context of multitracer and multimodal studies. This review briefly summarizes initial findings and highlights emerging applications enabled by this new approach. RECENT FINDINGS Connectivity based approaches applied to molecular and multimodal imaging have uncovered molecular networks with neurodegeneration-related alterations to metabolism and neurotransmission that uniquely relate to clinical findings; better disease stratification paradigms; an improved understanding of the relationships between neurochemical and functional networks and their related alterations, although the directionality of these relationships are still unresolved; and a new understanding of the molecular underpinning of disease-related alteration in resting-state brain activity. SUMMARY Connectivity approaches are poised to greatly enhance the information that can be extracted from molecular imaging. While currently mostly contributing to enhancing understanding of brain function, they are highly likely to contribute to the identification of specific biomarkers that will improve disease management and clinical care.
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Affiliation(s)
| | - Erik Reimers
- Department of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia, Canada
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Wei Y, Zhang C, Peng Y, Chen C, Han S, Wang W, Zhang Y, Lu H, Cheng J. MRI Assessment of Intrinsic Neural Timescale and Gray Matter Volume in Parkinson's Disease. J Magn Reson Imaging 2024; 59:987-995. [PMID: 37318377 DOI: 10.1002/jmri.28864] [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: 03/22/2023] [Revised: 05/28/2023] [Accepted: 05/30/2023] [Indexed: 06/16/2023] Open
Abstract
BACKGROUND Numerous studies have indicated altered temporal features of the brain function in Parkinson's disease (PD), and the autocorrelation magnitude of intrinsic neural signals, called intrinsic neural timescales, were often applied to estimate how long neural information stored in local brain areas. However, it is unclear whether PD patients at different disease stages exhibit abnormal timescales accompanied with abnormal gray matter volume (GMV). PURPOSE To assess the intrinsic timescale and GMV in PD. STUDY TYPE Prospective. POPULATION 74 idiopathic PD patients (44 early stage (PD-ES) and 30 late stage (PD-LS), as determined by the Hoehn and Yahr (HY) severity classification scale), and 73 healthy controls (HC). FIELD STRENGTH/SEQUENCE 3.0 T MRI scanner; magnetization prepared rapid acquisition gradient echo and echo planar imaging sequences. ASSESSMENT The timescales were estimated by using the autocorrelation magnitude of neural signals. Voxel-based morphometry was performed to calculate GMV in the whole brain. Severity of motor symptoms and cognitive impairments were assessed using the unified PD rating scale, the HY scale, the Montreal cognitive assessment, and the mini-mental state examination. STATISTICAL TEST Analysis of variance; two-sample t-test; Spearman rank correlation analysis; Mann-Whitney U test; Kruskal-Wallis' H test. A P value <0.05 was considered statistically significant. RESULTS The PD group had significantly abnormal intrinsic timescales in the sensorimotor, visual, and cognitive-related areas, which correlated with the symptom severity (ρ = -0.265, P = 0.022) and GMV (ρ = 0.254, P = 0.029). Compared to the HC group, the PD-ES group had significantly longer timescales in anterior cortical regions, whereas the PD-LS group had significantly shorter timescales in posterior cortical regions. CONCLUSION This study suggested that PD patients have abnormal timescales in multisystem and distinct patterns of timescales and GMV in cerebral cortex at different disease stages. This may provide new insights for the neural substrate of PD. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Chunyan Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yuanyuan Peng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Chen Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Hong Lu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
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Wang Y, Xiao Y, Xing Y, Yu M, Wang X, Ren J, Liu W, Zhong Y. Morphometric similarity differences in drug-naive Parkinson's disease correlate with transcriptomic signatures. CNS Neurosci Ther 2024; 30:e14680. [PMID: 38529533 PMCID: PMC10964038 DOI: 10.1111/cns.14680] [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: 10/30/2023] [Revised: 03/01/2024] [Accepted: 03/04/2024] [Indexed: 03/27/2024] Open
Abstract
BACKGROUND Differences in cortical morphology have been reported in individuals with Parkinson's disease (PD). However, the pathophysiological mechanism of transcriptomic vulnerability in local brain regions remains unclear. OBJECTIVE This study aimed to characterize the morphometric changes of brain regions in early drug-naive PD patients and uncover the brain-wide gene expression correlates. METHODS The morphometric similarity (MS) network analysis was used to quantify the interregional structural similarity from multiple magnetic resonance imaging anatomical indices measured in each brain region of 170 early drug-naive PD patients and 123 controls. Then, we applied partial least squares regression to determine the relationship between regional changes in MS and spatial transcriptional signatures from the Allen Human Brain Atlas dataset, and identified the specific genes related to MS differences in PD. We further investigated the biological processes by which the PD-related genes were enriched and the cellular characterization of these genes. RESULTS Our results showed that MS was mainly decreased in cingulate, frontal, and temporal cortical areas and increased in parietal and occipital cortical areas in early drug-naive PD patients. In addition, genes whose expression patterns were associated with regional MS changes in PD were involved in astrocytes, excitatory, and inhibitory neurons and were functionally enriched in neuron-specific biological processes related to trans-synaptic signaling and nervous system development. CONCLUSIONS These findings advance our understanding of the microscale genetic and cellular mechanisms driving macroscale morphological abnormalities in early drug-naive PD patients and provide potential targets for future therapeutic trials.
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Affiliation(s)
- Yajie Wang
- Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
- Department of NeurologyThe First People's Hospital of YanchengYanchengChina
| | - Yiwen Xiao
- School of PsychologyNanjing Normal UniversityNanjingChina
| | - Yi Xing
- Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Miao Yu
- Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Xiao Wang
- Department of RadiologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Jingru Ren
- Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Weiguo Liu
- Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Yuan Zhong
- School of PsychologyNanjing Normal UniversityNanjingChina
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Leung IHK, Strudwick MW. A systematic review of the challenges, emerging solutions and applications, and future directions of PET/MRI in Parkinson's disease. EJNMMI REPORTS 2024; 8:3. [PMID: 38748251 PMCID: PMC10962627 DOI: 10.1186/s41824-024-00194-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 12/26/2023] [Indexed: 05/19/2024]
Abstract
PET/MRI is a hybrid imaging modality that boasts the simultaneous acquisition of high-resolution anatomical data and metabolic information. Having these exceptional capabilities, it is often implicated in clinical research for diagnosing and grading, as well as tracking disease progression and response to interventions. Despite this, its low level of clinical widespread use is questioned. This is especially the case with Parkinson's disease (PD), the fastest progressively disabling and neurodegenerative cause of death. To optimise the clinical applicability of PET/MRI for diagnosing, differentiating, and tracking PD progression, the emerging novel uses, and current challenges must be identified. This systematic review aimed to present the specific challenges of PET/MRI use in PD. Further, this review aimed to highlight the possible resolution of these challenges, the emerging applications and future direction of PET/MRI use in PD. EBSCOHost (indexing CINAHL Plus, PsycINFO) Ovid (Medline, EMBASE) PubMed, Web of Science, and Scopus from 2006 (the year of first integrated PET/MRI hybrid system) to 30 September 2022 were used to search for relevant primary articles. A total of 933 studies were retrieved and following the screening procedure, 18 peer-reviewed articles were included in this review. This present study is of great clinical relevance and significance, as it informs the reasoning behind hindered widespread clinical use of PET/MRI for PD. Despite this, the emerging applications of image reconstruction developed by PET/MRI research data to the use of fully automated systems show promising and desirable utility. Furthermore, many of the current challenges and limitations can be resolved by using much larger-sampled and longitudinal studies. Meanwhile, the development of new fast-binding tracers that have specific affinity to PD pathological processes is warranted.
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Galvez V, Romero-Rebollar C, Estudillo-Guerra MA, Fernandez-Ruiz J. Resting-state networks and their relationship with MoCA performance in PD patients. Brain Imaging Behav 2024:10.1007/s11682-024-00860-3. [PMID: 38332386 DOI: 10.1007/s11682-024-00860-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/30/2024] [Indexed: 02/10/2024]
Abstract
Although mild cognitive impairment is a common non-motor symptom experienced by individuals with Parkinson's Disease, the changes in intrinsic resting-state networks associated with its onset in Parkinson's remain underexamined. To address the issue, our study sought to examine resting-state network alterations and their association with total performance in the Montreal Cognitive Assessment and its cognitive domains in Parkinson's by means of functional magnetic resonance imaging of 29 Parkinson's patients with normal cognition, 25 Parkinson's patients with mild cognitive impairment, and 13 healthy controls. To contrast the Parkinson's groups with each other and the controls, the images were used to estimate the Z-score coefficient between the regions of interest from the default mode network, the salience network and the central executive network. Our first finding was that default mode and salience network connectivity decreased significantly in Parkinson's patients regardless of their cognitive status. Additionally, default mode network nodes had a negative and salience network nodes a positive correlation with the global assessment in Parkinson's with normal cognition; this inverse relationship of both networks to total score was not found in the group with cognitive impairment. Finally, a positive correlation was found between executive scores and anterior and posterior cortical network connectivity and, in the group with cognitive impairment, between language scores and salience network connectivity. Our results suggest that specific resting-state networks of Parkinson's patients with cognitive impairment differ from those of Parkinson's patients with normal cognition, supporting the evidence that cognitive impairment in Parkinson's Disease displays a differentiated neurodegenerative pattern.
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Affiliation(s)
- Victor Galvez
- Laboratorio de Neurociencias Cognitivas y Desarrollo, Escuela de Psicología, Universidad Panamericana, Ciudad de México, México.
| | - César Romero-Rebollar
- Escuela de Pedagogía, Universidad Panamericana, Ciudad de México, México
- Universidad Tecnológica de México-UNITEC MÉXICO-Campus en línea, Ciudad de México, México
| | - M Anayali Estudillo-Guerra
- Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Juan Fernandez-Ruiz
- Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, México
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Ruppert-Junck MC, Kräling G, Greuel A, Tittgemeyer M, Timmermann L, Drzezga A, Eggers C, Pedrosa D. Random forest analysis of midbrain hypometabolism using [ 18F]-FDG PET identifies Parkinson's disease at the subject-level. Front Comput Neurosci 2024; 18:1328699. [PMID: 38384375 PMCID: PMC10879348 DOI: 10.3389/fncom.2024.1328699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 01/22/2024] [Indexed: 02/23/2024] Open
Abstract
Parkinson's disease (PD) is currently diagnosed largely on the basis of expert judgement with neuroimaging serving only as a supportive tool. In a recent study, we identified a hypometabolic midbrain cluster, which includes parts of the substantia nigra, as the best differentiating metabolic feature for PD-patients based on group comparison of [18F]-fluorodeoxyglucose ([18F]-FDG) PET scans. Longitudinal analyses confirmed progressive metabolic changes in this region and, an independent study showed great potential of nigral metabolism for diagnostic workup of parkinsonian syndromes. In this study, we applied a machine learning approach to evaluate midbrain metabolism measured by [18F]-FDG PET as a diagnostic marker for PD. In total, 51 mid-stage PD-patients and 16 healthy control subjects underwent high-resolution [18F]-FDG PET. Normalized tracer update values of the midbrain cluster identified by between-group comparison were extracted voxel-wise from individuals' scans. Extracted uptake values were subjected to a random forest feature classification algorithm. An adapted leave-one-out cross validation approach was applied for testing robustness of the model for differentiating between patients and controls. Performance of the model across all runs was evaluated by calculating sensitivity, specificity and model accuracy for the validation data set and the percentage of correctly categorized subjects for test data sets. The random forest feature classification of voxel-based uptake values from the midbrain cluster identified patients in the validation data set with an average sensitivity of 0.91 (Min: 0.82, Max: 0.94). For all 67 runs, in which each of the individuals was treated once as test data set, the test data set was correctly categorized by our model. The applied feature importance extraction consistently identified a subset of voxels within the midbrain cluster with highest importance across all runs which spatially converged with the left substantia nigra. Our data suggest midbrain metabolism measured by [18F]-FDG PET as a promising diagnostic imaging tool for PD. Given its close relationship to PD pathophysiology and very high discriminatory accuracy, this approach could help to objectify PD diagnosis and enable more accurate classification in relation to clinical trials, which could also be applicable to patients with prodromal disease.
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Affiliation(s)
- Marina C. Ruppert-Junck
- Department of Neurology, Philipps-University of Marburg, Marburg, Germany
- Clinic for Neurology, University Hospital Gießen and Marburg GmbH, Marburg, Germany
- Center for Mind, Brain and Behavior, Philipps-University of Marburg and Justus-Liebig University Gießen, Marburg, Germany
| | - Gunter Kräling
- Clinic for Neurology, University Hospital Gießen and Marburg GmbH, Marburg, Germany
| | - Andrea Greuel
- Department of Psychiatry, Psychotherapy and Psychosomatics, Vivantes Hospital Neukölln, Berlin, Germany
| | - Marc Tittgemeyer
- Max Planck Institute for Metabolism Research, Cologne, Germany
- Cluster of Excellence in Cellular Stress and Aging Associated Disease (CECAD), Cologne, Germany
| | - Lars Timmermann
- Department of Neurology, Philipps-University of Marburg, Marburg, Germany
- Clinic for Neurology, University Hospital Gießen and Marburg GmbH, Marburg, Germany
- Center for Mind, Brain and Behavior, Philipps-University of Marburg and Justus-Liebig University Gießen, Marburg, Germany
| | - Alexander Drzezga
- Cluster of Excellence in Cellular Stress and Aging Associated Disease (CECAD), Cologne, Germany
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-2), Research Center Jülich, Jülich, Germany
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Carsten Eggers
- Department of Neurology, Philipps-University of Marburg, Marburg, Germany
- Department of Neurology, Knappschaftskrankenhaus Bottrop, Bottrop, Germany
| | - David Pedrosa
- Department of Neurology, Philipps-University of Marburg, Marburg, Germany
- Clinic for Neurology, University Hospital Gießen and Marburg GmbH, Marburg, Germany
- Center for Mind, Brain and Behavior, Philipps-University of Marburg and Justus-Liebig University Gießen, Marburg, Germany
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Laugisch O, Ruppert-Jungck MC, Auschill TM, Eick S, Sculean A, Heumann C, Timmermann L, Pedrosa DJ, Eggers C, Arweiler NB. Glucose-6-Phosphatase-Dehydrogenase activity as modulative association between Parkinson's disease and periodontitis. Front Cell Infect Microbiol 2024; 14:1298546. [PMID: 38404290 PMCID: PMC10885135 DOI: 10.3389/fcimb.2024.1298546] [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: 09/21/2023] [Accepted: 01/12/2024] [Indexed: 02/27/2024] Open
Abstract
The association between periodontitis (PD) and Parkinson's disease (PK) is discussed due to the inflammatory component of neurodegenerative processes. PK severity and affected areas were determined using the following neuropsychological tests: Unified Parkinson's Disease Rating Score (UPDRS) and Hoehn and Yahr; non-motoric symptoms by Non-Motor Symptoms Scale (NMSS), and cognitive involvement by Mini-Mental State Examination (MMSE). Neuroinflammation and the resulting Glucose-6-Phosphatase-Dehydrogenase (G6PD) dysfunction are part of the pathophysiology of PK. This study aimed to evaluate these associations in periodontal inflammation. Clinical data and saliva-, serum-, and RNA-biobank samples of 50 well-characterized diametric patients with PK and five age- and sex-matched neurologically healthy participants were analyzed for G6PD function, periodontal pathogens (Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Prevotella intermedia, Campylobacter rectus, Fusobacterium nucleatum, and Filifactor alocis), monocyte chemoattractant protein (MCP) 1, and interleukin (IL) 1-beta. Regression analysis was used to identify associations between clinical and behavioral data, and t-tests were used to compare health and disease. Compared with PK, no pathogens and lower inflammatory markers (p < 0.001) were detectible in healthy saliva and serum, PK-severity/UPDRS interrelated with the occurrence of Prevotella intermedia in serum as well as IL1-beta levels in serum and saliva (p = 0.006, 0.019, 0.034), Hoehn and Yahr correlated with Porphyromonas gingivalis, Prevotella intermedia, RNA IL1-beta regulation, serum, and saliva IL1-beta levels, with p-values of 0.038, 0.011, 0.008, <0.001, and 0.010, while MMSE was associated with Aggregatibacter actinomycetemcomitans, Fusobacterium nucleatum, serum MCP 1 levels, RNA IL1-beta regulation and G6PD serum activity (p = 0.036, 0.003, 0.045, <0.001, and 0.021). Cognitive and motor skills seem to be important as representative tests are associated with periodontal pathogens and oral/general inflammation, wherein G6PD-saliva dysfunction might be involved. Clinical trial registration https://www.bfarm.de/DE/Das-BfArM/Aufgaben/Deutsches-Register-Klinischer-Studien/_node.html, identifier DRKS00005388.
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Affiliation(s)
- Oliver Laugisch
- Department of Periodontology and Peri-Implant Diseases, Universitätsklinikum Giessen und Marburg (UKGM), Philipps University, Marburg, Germany
| | - Marina C. Ruppert-Jungck
- Department of Neurology, University Hospital Giessen and Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Universities of Giessen and Marburg, Marburg, Germany
| | - Thorsten M. Auschill
- Department of Periodontology and Peri-Implant Diseases, Universitätsklinikum Giessen und Marburg (UKGM), Philipps University, Marburg, Germany
| | - Sigrun Eick
- Department of Periodontology, School of Dental Medicine, University of Bern, Bern, Switzerland
| | - Anton Sculean
- Department of Periodontology, School of Dental Medicine, University of Bern, Bern, Switzerland
| | - Christian Heumann
- Department of Statistics, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Lars Timmermann
- Department of Neurology, University Hospital Giessen and Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Universities of Giessen and Marburg, Marburg, Germany
| | - David J. Pedrosa
- Department of Neurology, University Hospital Giessen and Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Universities of Giessen and Marburg, Marburg, Germany
| | - Carsten Eggers
- Department of Neurology, University Hospital Giessen and Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Universities of Giessen and Marburg, Marburg, Germany
- Department of Neurology, Knappschaftskrankenhaus Bottrop, Bottrop, Germany
| | - Nicole B. Arweiler
- Department of Periodontology and Peri-Implant Diseases, Universitätsklinikum Giessen und Marburg (UKGM), Philipps University, Marburg, Germany
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Maggi G, Giacobbe C, Vitale C, Amboni M, Obeso I, Santangelo G. Theory of mind in mild cognitive impairment and Parkinson's disease: The role of memory impairment. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2024; 24:156-170. [PMID: 38049608 PMCID: PMC10827829 DOI: 10.3758/s13415-023-01142-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/14/2023] [Indexed: 12/06/2023]
Abstract
BACKGROUND Social cognition is impaired in Parkinson's disease (PD). Whether social cognitive impairment (iSC) is a by-product of the underlying cognitive deficits in PD or a process independent of cognitive status is unknown. To this end, the present study was designed to investigate the weight of specific cognitive deficits in social cognition, considering different mild cognitive impairment subtypes of PD (PD-MCI). METHODS Fifty-eight PD patients underwent a neuropsychological battery assessing executive functions, memory, language, and visuospatial domains, together with social cognitive tests focused on theory of mind (ToM). Patients were divided into subgroups according to their clinical cognitive status: amnestic PD-MCI (PD-aMCI, n = 18), non-amnestic PD-MCI (PD-naMCI, n = 16), and cognitively unimpaired (PD-CU, n = 24). Composite scores for cognitive and social domains were computed to perform mediation analyses. RESULTS Memory and language impairments mediated the effect of executive functioning in social cognitive deficits in PD patients. Dividing by MCI subgroups, iSC occurred more frequently in PD-aMCI (77.8%) than in PD-naMCI (18.8%) and PD-CU (8.3%). Moreover, PD-aMCI performed worse than PD-CU in all social cognitive measures, whereas PD-naMCI performed worse than PD-CU in only one subtype of the affective and cognitive ToM tests. CONCLUSIONS Our findings suggest that ToM impairment in PD can be explained by memory dysfunction that mediates executive control. ToM downsides in the amnesic forms of PD-MCI may suggest that subtle changes in social cognition could partly explain future transitions into dementia. Hence, the evaluation of social cognition in PD is critical to characterize a possible behavioral marker of cognitive decline.
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Affiliation(s)
- Gianpaolo Maggi
- Department of Psychology, University of Campania "Luigi Vanvitelli," Viale Ellittico, 31, 81100, Caserta, Italy.
| | - Chiara Giacobbe
- Department of Psychology, University of Campania "Luigi Vanvitelli," Viale Ellittico, 31, 81100, Caserta, Italy
| | - Carmine Vitale
- Institute of Diagnosis and Health, IDC-Hermitage Capodimonte, Naples, Italy
- Department of Motor Sciences and Wellness, University "Parthenope, Naples, Italy
| | - Marianna Amboni
- Institute of Diagnosis and Health, IDC-Hermitage Capodimonte, Naples, Italy
- Department of Medicine, Surgery and Dentistry, University of Salerno, Salerno, Italy
| | - Ignacio Obeso
- HM Hospitales - Centro Integral de Neurociencias AC HM CINAC, Hospital Universitario HM Puerta del Sur, HM Hospitales, Avda. Carlos V, 70. 28938, Móstoles, Madrid, Spain.
- Department of Psychobiology and Methods on Behavioural Sciences, Complutense University of Madrid, Madrid, Spain.
| | - Gabriella Santangelo
- Department of Psychology, University of Campania "Luigi Vanvitelli," Viale Ellittico, 31, 81100, Caserta, Italy.
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Wang Y, Gao Y, Zhao M, Hu X, Wang J, Han Y, Wang Q, Fu X, Dai Z, Ren F, Li M, Gao F. Abnormal white and gray matter functional connectivity is associated with cognitive dysfunction in presbycusis. Cereb Cortex 2024; 34:bhad495. [PMID: 38112670 DOI: 10.1093/cercor/bhad495] [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: 09/02/2023] [Revised: 11/24/2023] [Accepted: 11/27/2023] [Indexed: 12/21/2023] Open
Abstract
Presbycusis is characterized by high-frequency hearing loss and is closely associated with cognitive decline. Previous studies have observed functional reorganization of gray matter in presbycusis, but the information transmission between gray matter and white matter remains ill-defined. Using resting-state functional magnetic resonance imaging, we investigated differences in functional connectivity (GM-GM, WM-WM, and GM-WM) between 60 patients with presbycusis and 57 healthy controls. Subsequently, we examined the correlation between these connectivity differences with high-frequency hearing loss as well as cognitive impairment. Our results revealed significant alterations in functional connectivity involving the body of the corpus callosum, posterior limbs of the internal capsule, retrolenticular region of the internal capsule, and the gray matter regions in presbycusis. Notably, disrupted functional connectivity was observed between the body of the corpus callosum and ventral anterior cingulate cortex in presbycusis, which was associated with impaired attention. Additionally, enhanced functional connectivity was found in presbycusis between the internal capsule and the ventral auditory processing stream, which was related to impaired cognition in multiple domains. These two patterns of altered functional connectivity between gray matter and white matter may involve both bottom-up and top-down regulation of cognitive function. These findings provide novel insights into understanding cognitive compensation and resource redistribution mechanisms in presbycusis.
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Affiliation(s)
- Yao Wang
- School of Life Sciences, Tiangong University, Tianjin 300387, China
- Tianjin Key Laboratory of Optoelectronic Detection Technology and System, Tiangong University, Tianjin 300387, China
| | - Yuting Gao
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Min Zhao
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Xin Hu
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Jing Wang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Yu Han
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Qinghui Wang
- Department of Radiology, Shandong Provincial Hospital, Shandong University, Jinan 250021, Shandong, China
| | - Xinxing Fu
- Beijing Institute of Otolaryngology, Otolaryngology-Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing 100069, China
| | - Zongrui Dai
- Department of Biostatistics, University of Michigan Ann Arbor, Ann Arbor, MI 48109, United States
| | - Funxin Ren
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Muwei Li
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Fei Gao
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
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Cai YH, Huang X. Abnormal functional connectivity strength in age-related macular degeneration patients: a fMRI study. Neuroreport 2023; 34:845-852. [PMID: 37942735 DOI: 10.1097/wnr.0000000000001962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
OBJECTIVE Age-related macular degeneration (AMD) is a serious blinding eye disease. Previous neuroimaging studies reported that AMD were accompanied by abnormalities of the brain. However, whether AMD patients were associated with functional connectivity strength (FCS) or not remains unknown. In our study, the purpose of the study was to assess FCS changes in AMD patients. METHODS In our study, 20 AMD patients and 20 healthy controls (HCs), matched closely by sex, age, and educational level were underwent MRI scanning. FCS method and seed-based functional connectivity (FC) method were applied to investigate the functional network changes between two groups. Moreover, support vector machine (SVM) method was applied to assess the FCS maps as a feature to classification of AMD diseases. RESULTS Our study reported that AMD patients showed decreased FCS values in the bilateral calcarine, left supplementary motor area, left superior parietal lobule and left paracentral lobule (ParaL) relative to the HC group. Meanwhile, our study found that the AMD patients showed abnormal FC within visual network, sensorimotor network and default mode network. Moreover, the SVM method showed that FCS maps as machine learning features shows good classification efficiency (area under curve = 0.82) in the study. CONCLUSION Our study demonstrated that AMD patients showed abnormal FCS with the visual network, sensorimotor network and default mode network, which might reflect the impaired vision, cognition and motor function in AMD patients. In addition, FCS indicator can be used as an effective biological marker to assist the clinical diagnosis of AMD.
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Affiliation(s)
- Yue-Hong Cai
- Department of Ophthalmology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
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11
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Huang X, He Q, Ruan X, Li Y, Kuang Z, Wang M, Guo R, Bu S, Wang Z, Yu S, Chen A, Wei X. Structural connectivity from DTI to predict mild cognitive impairment in de novo Parkinson's disease. Neuroimage Clin 2023; 41:103548. [PMID: 38061176 PMCID: PMC10755095 DOI: 10.1016/j.nicl.2023.103548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 01/01/2024]
Abstract
BACKGROUND Early detection of Parkinson's disease (PD) patients at high risk for mild cognitive impairment (MCI) can help with timely intervention. White matter structural connectivity is considered an early and sensitive indicator of neurodegenerative disease. OBJECTIVES To investigate whether baseline white matter structural connectivity features from diffusion tensor imaging (DTI) of de novo PD patients can help predict PD-MCI conversion at an individual level using machine learning methods. METHODS We included 90 de novo PD patients who underwent DTI and 3D T1-weighted imaging. Elastic net-based feature consensus ranking (ENFCR) was used with 1000 random training sets to select clinical and structural connectivity features. Linear discrimination analysis (LDA), support vector machine (SVM), K-nearest neighbor (KNN) and naïve Bayes (NB) classifiers were trained based on features selected more than 500 times. The area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN) and specificity (SPE) were used to evaluate model performance. RESULTS A total of 57 PD patients were classified as PD-MCI nonconverters, and 33 PD patients were classified as PD-MCI converters. The models trained with clinical data showed moderate performance (AUC range: 0.62-0.68; ACC range: 0.63-0.77; SEN range: 0.45-0.66; SPE range: 0.64-0.84). Models trained with structural connectivity (AUC range, 0.81-0.84; ACC range, 0.75-0.86; SEN range, 0.77-0.91; SPE range, 0.71-0.88) performed similar to models that were trained with both clinical and structural connectivity data (AUC range, 0.81-0.85; ACC range, 0.74-0.85; SEN range, 0.79-0.91; SPE range, 0.70-0.89). CONCLUSIONS Baseline white matter structural connectivity from DTI is helpful in predicting future MCI conversion in de novo PD patients.
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Affiliation(s)
- Xiaofei Huang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Qing He
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Xiuhang Ruan
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Yuting Li
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China; Affiliated Dongguan Hospital, Southern Medical University (Dongguan People's Hospital), Guangdong, China
| | - Zhanyu Kuang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Mengfan Wang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Riyu Guo
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Shuwen Bu
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Zhaoxiu Wang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Shaode Yu
- School of Information and Communication Engineering, Communication University of China, Beijing, China.
| | - Amei Chen
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China.
| | - Xinhua Wei
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China.
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12
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da Silva Castanheira J, Wiesman AI, Hansen JY, Misic B, Baillet S. The neurophysiological brain-fingerprint of Parkinson's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.03.23285441. [PMID: 36798232 PMCID: PMC9934726 DOI: 10.1101/2023.02.03.23285441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
In this study, we investigate the clinical potential of brain-fingerprints derived from electrophysiological brain activity for diagnostics and progression monitoring of Parkinson's disease (PD). We obtained brain-fingerprints from PD patients and age-matched healthy controls using short, task-free magnetoencephalographic recordings. The rhythmic components of the individual brain-fingerprint distinguished between patients and healthy participants with approximately 90% accuracy. The most prominent cortical features of the Parkinson's brain-fingerprint mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also show that Parkinson's disease stages can be decoded directly from cortical neurophysiological activity. Additionally, our study reveals that the cortical topography of the Parkinson's brain-fingerprint aligns with that of neurotransmitter systems affected by the disease's pathophysiology. We further demonstrate that the arrhythmic components of cortical activity are more variable over short periods of time in patients with Parkinson's disease than in healthy controls, making individual differentiation between patients based on these features more challenging and explaining previous negative published results. Overall, we outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and clinical staging of Parkinson's disease. For this reason, the proposed definition of a rhythmic brain-fingerprint of Parkinson's disease may contribute to novel, refined approaches to patient stratification and to the improved identification and testing of therapeutic neurostimulation targets.
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Affiliation(s)
| | - Alex I. Wiesman
- Montreal Neurological Institute, McGill University, Montreal QC, Canada
| | - Justine Y. Hansen
- Montreal Neurological Institute, McGill University, Montreal QC, Canada
| | - Bratislav Misic
- Montreal Neurological Institute, McGill University, Montreal QC, Canada
| | - Sylvain Baillet
- Montreal Neurological Institute, McGill University, Montreal QC, Canada
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Li J, Tan C, Zhang L, Cai S, Shen Q, Liu Q, Wang M, Song C, Zhou F, Yuan J, Liu Y, Lan B, Liao H. Neural functional network of early Parkinson's disease based on independent component analysis. Cereb Cortex 2023; 33:11025-11035. [PMID: 37746803 DOI: 10.1093/cercor/bhad342] [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: 07/02/2023] [Revised: 08/08/2023] [Indexed: 09/26/2023] Open
Abstract
This work explored neural network changes in early Parkinson's disease: Resting-state functional magnetic resonance imaging was used to investigate functional alterations in different stages of Parkinson's disease (PD). Ninety-five PD patients (50 early/mild and 45 early/moderate) and 37 healthy controls (HCs) were included. Independent component analysis revealed significant differences in intra-network connectivity, specifically in the default mode network (DMN) and right frontoparietal network (RFPN), in both PD groups compared to HCs. Inter-network connectivity analysis showed reduced connectivity between the executive control network (ECN) and DMN, as well as ECN-left frontoparietal network (LFPN), in early/mild PD. Early/moderate PD exhibited decreased connectivity in ECN-LFPN, ECN-RFPN, ECN-DMN, and DMN-auditory network, along with increased connectivity in LFPN-cerebellar network. Correlations were found between ECN-DMN and ECN-LFPN connections with UPDRS-III scores in early/mild PD. These findings suggest that PD progression involves dysfunction in multiple intra- and inter-networks, particularly implicating the ECN, and a wider range of abnormal functional networks may mark the progression of the disease.
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Affiliation(s)
- Junli Li
- Department of Medical Imaging, Huizhou Central People's Hospital, Eling North Road, Huicheng District, Huizhou, Guangdong 516001, China
| | - Changlian Tan
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Lin Zhang
- Department of Radiology, Chengdu Fifth People's Hospital, Mashi Street, Wenjiang District, Chengdu, Sichuan 611130, China
| | - Sainan Cai
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Qin Shen
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Qinru Liu
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Min Wang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - ChenDie Song
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Fan Zhou
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Jiaying Yuan
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Yujing Liu
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Bowen Lan
- Department of Medical Imaging, Huizhou Central People's Hospital, Eling North Road, Huicheng District, Huizhou, Guangdong 516001, China
| | - Haiyan Liao
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
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Zarghami TS. A new causal centrality measure reveals the prominent role of subcortical structures in the causal architecture of the extended default mode network. Brain Struct Funct 2023; 228:1917-1941. [PMID: 37658184 DOI: 10.1007/s00429-023-02697-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 08/09/2023] [Indexed: 09/03/2023]
Abstract
Network representation has been an incredibly useful concept for understanding the behavior of complex systems in social sciences, biology, neuroscience, and beyond. Network science is mathematically founded on graph theory, where nodal importance is gauged using measures of centrality. Notably, recent work suggests that the topological centrality of a node should not be over-interpreted as its dynamical or causal importance in the network. Hence, identifying the influential nodes in dynamic causal models (DCM) remains an open question. This paper introduces causal centrality for DCM, a dynamics-sensitive and causally-founded centrality measure based on the notion of intervention in graphical models. Operationally, this measure simplifies to an identifiable expression using Bayesian model reduction. As a proof of concept, the average DCM of the extended default mode network (eDMN) was computed in 74 healthy subjects. Next, causal centralities of different regions were computed for this causal graph, and compared against several graph-theoretical centralities. The results showed that the subcortical structures of the eDMN were more causally central than the cortical regions, even though the graph-theoretical centralities unanimously favored the latter. Importantly, model comparison revealed that only the pattern of causal centrality was causally relevant. These results are consistent with the crucial role of the subcortical structures in the neuromodulatory systems of the brain, and highlight their contribution to the organization of large-scale networks. Potential applications of causal centrality-to study causal models of other neurotypical and pathological functional networks-are discussed, and some future lines of research are outlined.
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Affiliation(s)
- Tahereh S Zarghami
- Bio-Electric Department, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
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15
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Zang Z, Zhang X, Song T, Li J, Nie B, Mei S, Hu Z, Zhang Y, Lu J. Association between gene expression and functional-metabolic architecture in Parkinson's disease. Hum Brain Mapp 2023; 44:5387-5401. [PMID: 37605831 PMCID: PMC10543112 DOI: 10.1002/hbm.26443] [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: 04/20/2023] [Revised: 06/02/2023] [Accepted: 07/23/2023] [Indexed: 08/23/2023] Open
Abstract
Gene expression plays a critical role in the pathogenesis of Parkinson's disease (PD). How gene expression profiles are correlated with functional-metabolic architecture remains obscure. We enrolled 34 PD patients and 25 age-and-sex-matched healthy controls for simultaneous 18 F-FDG-PET/functional MRI scanning during resting state. We investigated the functional gradients and the ratio of standard uptake value. Principal component analysis was used to further combine the functional gradients and glucose metabolism into functional-metabolic architecture. Using partial least squares (PLS) regression, we introduced the transcriptomic data from the Allen Institute of Brain Sciences to identify gene expression patterns underlying the affected functional-metabolic architecture in PD. Between-group comparisons revealed significantly higher gradient variation in the visual, somatomotor, dorsal attention, frontoparietal, default mode, and subcortical network (pFDR < .048) in PD. Increased FDG-uptake was found in the somatomotor and ventral attention network while decreased FDG-uptake was found in the visual network (pFDR < .008). Spatial correlation analysis showed consistently affected patterns of functional gradients and metabolism (p = 2.47 × 10-8 ). PLS analysis and gene ontological analyses further revealed that genes were mainly enriched for metabolic, catabolic, cellular response to ions, and regulation of DNA transcription and RNA biosynthesis. In conclusion, our study provided genetic pathological mechanism to explain imaging-defined brain functional-metabolic architecture of PD.
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Affiliation(s)
- Zhenxiang Zang
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
| | - Xiaolong Zhang
- Department of Physiology, College of Basic Medical SciencesArmy Medical UniversityChongqingChina
| | - Tianbin Song
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
| | - Jiping Li
- Beijing Institute of Functional NeurosurgeryXuanwu Hospital, Capital Medical UniversityBeijingChina
| | - Binbin Nie
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy PhysicsChinese Academy of SciencesBeijingChina
| | - Shanshan Mei
- Department of NeurologyXuanwu Hospital, Capital Medical UniversityBeijingChina
| | - Zhi'an Hu
- Department of Physiology, College of Basic Medical SciencesArmy Medical UniversityChongqingChina
| | - Yuqing Zhang
- Beijing Institute of Functional NeurosurgeryXuanwu Hospital, Capital Medical UniversityBeijingChina
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
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16
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Yu Z, Pang H, Yu H, Wu Z, Ding Z, Fan G. Segmental disturbance of white matter microstructure in predicting mild cognitive impairment in idiopathic Parkinson's disease: An individualized study based on automated fiber quantification tractography. Parkinsonism Relat Disord 2023; 115:105802. [PMID: 37734997 DOI: 10.1016/j.parkreldis.2023.105802] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Revised: 08/01/2023] [Accepted: 08/05/2023] [Indexed: 09/23/2023]
Abstract
PURPOSE The neurobiological mechanisms and an early identification of MCI in idiopathic Parkinson's disease (IPD) remain unclear. To investigate the abnormalities of types of white matter (WM) fiber tracts segmentally and establish reliable indicator in IPD-MCI. METHODS Forty IPD with normal cognition (IPD-NCI), thirty IPD-MCI, and thirty healthy controls were included. Automated fiber quantification was applied to extract the fractional anisotropy (FA) and mean diffusivity (MD) values at 100 locations along the major fibers. Partial correlation was performed between diffusion values and cognitive performance. Furthermore, machine learning analyses were conducted to determine the imaging biomarker of MCI. Permutation tests were performed to evaluate the pointwise differences under the FWE correction. RESULTS IPD-MCI had similar but more severe and widespread WM degeneration in the association, projection, and commissural fibers compared with IPD-NCI. Meanwhile, IPD-MCI showed distinct degeneration pattern in the association fibers. The FA of the anterior segment of right inferior fronto-occipital fasciculus (IFOF) was positively correlated with MoCA (P < 0.05) and executive function (P < 0.05). The MD of the middle and posterior segment of left superior longitudinal fasciculus (SLF) was negatively correlated with MoCA P < 0.05), executive (P < 0.05), visuospatial function (P < 0.05). Furthermore, the AUC of support vector machine model was 0.80 in the validation dataset. The FA of anterior segment of right IFOF contribute the most. CONCLUSION This study demonstrated that regional tract-specific microstructural degeneration, especially the association fibers, can be used to predict MCI in IPD. Especially, the right IFOF may be a significant imaging biomarker in predicting IPD with MCI.
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Affiliation(s)
- Ziyang Yu
- School of Medicine, Xiamen University, Xiamen, Fujian Province, China; Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China.
| | - Huize Pang
- Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China.
| | - Hongmei Yu
- Department of Neurology, First Affiliated Hospital of China Medical University, Shenyang, China.
| | - Ziqian Wu
- School of Medicine, Xiamen University, Xiamen, Fujian Province, China.
| | - Zhi Ding
- School of Medicine, Xiamen University, Xiamen, Fujian Province, China.
| | - Guoguang Fan
- Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China.
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Barbero JA, Unadkat P, Choi YY, Eidelberg D. Functional Brain Networks to Evaluate Treatment Responses in Parkinson's Disease. Neurotherapeutics 2023; 20:1653-1668. [PMID: 37684533 PMCID: PMC10684458 DOI: 10.1007/s13311-023-01433-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/24/2023] [Indexed: 09/10/2023] Open
Abstract
Network analysis of functional brain scans acquired with [18F]-fluorodeoxyglucose positron emission tomography (FDG PET, to map cerebral glucose metabolism), or resting-state functional magnetic resonance imaging (rs-fMRI, to map blood oxygen level-dependent brain activity) has increasingly been used to identify and validate reproducible circuit abnormalities associated with neurodegenerative disorders such as Parkinson's disease (PD). In addition to serving as imaging markers of the underlying disease process, these networks can be used singly or in combination as an adjunct to clinical diagnosis and as a screening tool for therapeutics trials. Disease networks can also be used to measure rates of progression in natural history studies and to assess treatment responses in individual subjects. Recent imaging studies in PD subjects scanned before and after treatment have revealed therapeutic effects beyond the modulation of established disease networks. Rather, other mechanisms of action may be at play, such as the induction of novel functional brain networks directly by treatment. To date, specific treatment-induced networks have been described in association with novel interventions for PD such as subthalamic adeno-associated virus glutamic acid decarboxylase (AAV2-GAD) gene therapy, as well as sham surgery or oral placebo under blinded conditions. Indeed, changes in the expression of these networks with treatment have been found to correlate consistently with clinical outcome. In aggregate, these attributes suggest a role for functional brain networks as biomarkers in future clinical trials.
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Affiliation(s)
- János A Barbero
- Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11549, USA
| | - Prashin Unadkat
- Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11549, USA
- Elmezzi Graduate School of Molecular Medicine, Manhasset, NY, 11030, USA
| | - Yoon Young Choi
- Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA
| | - David Eidelberg
- Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA.
- Molecular Medicine and Neurology, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11549, USA.
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Lin J, Kang X, Lu H, Zhang D, Bian X, Zhou J, Hu J, Zhang D, Sepulcre J, Pan L, Lou X. Magnetic Resonance-Guided Focused Ultrasound Thalamotomy Rebalances Atypical Functional Hierarchy in Patients with Essential Tremor. Neurotherapeutics 2023; 20:1755-1766. [PMID: 37843768 PMCID: PMC10684443 DOI: 10.1007/s13311-023-01442-9] [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] [Accepted: 09/12/2023] [Indexed: 10/17/2023] Open
Abstract
Magnetic resonance-guided focused ultrasound (MRgFUS) has brought thalamotomy back to the frontline for essential tremor (ET). As functional organization of human brain strictly follows hierarchical principles which are frequently deficient in neurological diseases, whether additional damage from MRgFUS thalamotomy induces further disruptions of ET functional scaffolds are still controversial. This study was to examine the alteration features of brain functional frameworks following MRgFUS thalamotomy in patients with ET. We retrospectively obtained preoperative (ETpre) and postoperative 6-month (ET6m) data of 30 ET patients underwent MRgFUS thalamotomy from 2018 to 2020. Their archived functional MR images were used to functional gradient comparison. Both supervised pattern learning and stepwise linear regression were conducted to associate gradient features to tremor symptoms with additional neuropathophysiological analysis. MRgFUS thalamotomy relieved 78.19% of hand tremor symptoms and induced vast global framework alteration (ET6m vs. ETpre: Cohen d = - 0.80, P < 0.001). Multiple robust alterations were identified especially in posterior cingulate cortex ([Formula: see text] ET6m vs. [Formula: see text] ETpre: Cohen d = 0.87, P = 0.048). Compared with matched health controls (HCs), its gradient distances to primary communities were significantly increased in [Formula: see text] ETpre patients with anomalous stepwise connectivity (P < 0.05 in ETpre vs. HCs), which were restored after MRgFUS thalamotomy. Both global and regional gradient features could be used for tremor symptom prediction and were linked to neuropathophysiological features of Parkinson disease and oxidative phosphorylation. MRgFUS thalamotomy not only suppress tremor symptoms but also rebalances atypical functional hierarchical architecture of ET patients.
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Affiliation(s)
- Jiaji Lin
- Department of Radiology, Chinese PLA General Hospital/Medical School of Chinese PLA, No.28 Fuxing Road, Beijing, 100853, China
| | - Xiaopeng Kang
- School of Artificial Intelligence, University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100876, China
| | - Haoxuan Lu
- Department of Radiology, Chinese PLA General Hospital/Medical School of Chinese PLA, No.28 Fuxing Road, Beijing, 100853, China
| | - Dekang Zhang
- Department of Radiology, Chinese PLA General Hospital/Medical School of Chinese PLA, No.28 Fuxing Road, Beijing, 100853, China
| | - Xianbing Bian
- Department of Radiology, Chinese PLA General Hospital/Medical School of Chinese PLA, No.28 Fuxing Road, Beijing, 100853, China
| | - Jiayou Zhou
- Department of Neurosurgery, Chinese PLA General Hospital/Medical School of Chinese PLA, No.28 Fuxing Road, Beijing, 100853, China
| | - Jianxing Hu
- Department of Radiology, Chinese PLA General Hospital/Medical School of Chinese PLA, No.28 Fuxing Road, Beijing, 100853, China
| | - Dong Zhang
- Department of Radiology, Chinese PLA General Hospital/Medical School of Chinese PLA, No.28 Fuxing Road, Beijing, 100853, China
| | - Jorge Sepulcre
- Gordon Center for Medical Imaging, Harvard Medical School, No.55 Fruit Street, Boston, 02114, USA
| | - Longsheng Pan
- Department of Neurosurgery, Chinese PLA General Hospital/Medical School of Chinese PLA, No.28 Fuxing Road, Beijing, 100853, China.
| | - Xin Lou
- Department of Radiology, Chinese PLA General Hospital/Medical School of Chinese PLA, No.28 Fuxing Road, Beijing, 100853, China.
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Di Tella S, De Marco M, Baglio F, Silveri MC, Venneri A. Resting-state functional connectivity is modulated by cognitive reserve in early Parkinson's disease. Front Psychol 2023; 14:1207988. [PMID: 37691780 PMCID: PMC10485267 DOI: 10.3389/fpsyg.2023.1207988] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 07/28/2023] [Indexed: 09/12/2023] Open
Abstract
Background Fronto-striatal disconnection is thought to be at the basis of dysexecutive symptoms in patients with Parkinson's disease (PD). Multiple reserve-related processes may offer resilience against functional decline. Among these, cognitive reserve (CR) refers to the adaptability of cognitive processes. Objective To test the hypothesis that functional connectivity of pathways associated with executive dysfunction in PD is modulated by CR. Methods Twenty-six PD patients and 24 controls underwent resting-state functional magnetic resonance imaging. Functional connectivity was explored with independent component analysis and seed-based approaches. The following networks were selected from the outcome of the independent component analysis: default-mode (DMN), left and right fronto-parietal (l/rFPN), salience (SalN), sensorimotor (SMN), and occipital visual (OVN). Seed regions were selected in the substantia nigra and in the dorsolateral and ventromedial prefrontal cortex for the assessment of seed-based functional connectivity maps. Educational and occupational attainments were used as CR proxies. Results Compared with their counterparts with high CR, PD individuals with low CR had reduced posterior DMN functional connectivity in the anterior cingulate and basal ganglia, and bilaterally reduced connectivity in fronto-parietal regions within the networks defined by the dorsolateral and ventrolateral prefrontal seeds. Hyper-connectivity was detected within medial prefrontal regions when comparing low-CR PD with low-CR controls. Conclusion CR may exert a modulatory effect on functional connectivity in basal ganglia and executive-attentional fronto-parietal networks. In PD patients with low CR, attentional control networks seem to be downregulated, whereas higher recruitment of medial frontal regions suggests compensation via an upregulation mechanism. This upregulation might contribute to maintaining efficient cognitive functioning when posterior cortical function is progressively reduced.
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Affiliation(s)
- Sonia Di Tella
- Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy
- IRCCS, Fondazione Don Carlo Gnocchi Onlus, Milan, Italy
| | - Matteo De Marco
- Department of Life Sciences, Brunel University London, Uxbridge, United Kingdom
| | | | | | - Annalena Venneri
- Department of Life Sciences, Brunel University London, Uxbridge, United Kingdom
- Department of Medicine and Surgery, University of Parma, Parma, Italy
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Yassine S, Gschwandtner U, Auffret M, Duprez J, Verin M, Fuhr P, Hassan M. Identification of Parkinson's Disease Subtypes from Resting-State Electroencephalography. Mov Disord 2023; 38:1451-1460. [PMID: 37310340 DOI: 10.1002/mds.29451] [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: 01/13/2023] [Revised: 04/11/2023] [Accepted: 05/05/2023] [Indexed: 06/14/2023] Open
Abstract
BACKGROUND Parkinson's disease (PD) patients present with a heterogeneous clinical phenotype, including motor, cognitive, sleep, and affective disruptions. However, this heterogeneity is often either ignored or assessed using only clinical assessments. OBJECTIVES We aimed to identify different PD sub-phenotypes in a longitudinal follow-up analysis and their electrophysiological profile based on resting-state electroencephalography (RS-EEG) and to assess their clinical significance over the course of the disease. METHODS Using electrophysiological features obtained from RS-EEG recordings and data-driven methods (similarity network fusion and source-space spectral analysis), we have performed a clustering analysis to identify disease sub-phenotypes and we examined whether their different patterns of disruption are predictive of disease outcome. RESULTS We showed that PD patients (n = 44) can be sub-grouped into three phenotypes with distinct electrophysiological profiles. These clusters are characterized by different levels of disruptions in the somatomotor network (Δ and β band), the frontotemporal network (α2 band) and the default mode network (α1 band), which consistently correlate with clinical profiles and disease courses. These clusters are classified into either moderate (only-motor) or mild-to-severe (diffuse) disease. We showed that EEG features can predict cognitive evolution of PD patients from baseline, when the cognitive clinical scores were overlapped. CONCLUSIONS The identification of novel PD subtypes based on electrical brain activity signatures may provide a more accurate prognosis in individual patients in clinical practice and help to stratify subgroups in clinical trials. Innovative profiling in PD can also support new therapeutic strategies that are brain-based and designed to modulate brain activity disruption. © 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)
- Sahar Yassine
- LTSI - INSERM U1099, University of Rennes, Rennes, France
- NeuroKyma, Rennes, France
- Behavior and Basal Ganglia, CIC1414, CIC-IT, CHU Rennes, Rennes, France
| | - Ute Gschwandtner
- Department of Neurology, Hospitals of the University of Basel, Basel, Switzerland
| | - Manon Auffret
- LTSI - INSERM U1099, University of Rennes, Rennes, France
- Behavior and Basal Ganglia, CIC1414, CIC-IT, CHU Rennes, Rennes, France
- Institut des Neurosciences Cliniques de Rennes (INCR), Rennes, France
- France Développement Electronique, Monswiller, France
| | - Joan Duprez
- LTSI - INSERM U1099, University of Rennes, Rennes, France
| | - Marc Verin
- LTSI - INSERM U1099, University of Rennes, Rennes, France
- Behavior and Basal Ganglia, CIC1414, CIC-IT, CHU Rennes, Rennes, France
- Institut des Neurosciences Cliniques de Rennes (INCR), Rennes, France
- Movement Disorders Unit, Neurology Department, Pontchaillou University Hospital, Rennes, France
| | - Peter Fuhr
- Department of Neurology, Hospitals of the University of Basel, Basel, Switzerland
| | - Mahmoud Hassan
- Behavior and Basal Ganglia, CIC1414, CIC-IT, CHU Rennes, Rennes, France
- School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
- MINDIG, Rennes, France
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21
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Mertiens S, Sure M, Schnitzler A, Florin E. Alterations of PAC-based resting state networks in Parkinson's disease are partially alleviated by levodopa medication. Front Syst Neurosci 2023; 17:1219334. [PMID: 37588811 PMCID: PMC10427244 DOI: 10.3389/fnsys.2023.1219334] [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: 05/08/2023] [Accepted: 07/10/2023] [Indexed: 08/18/2023] Open
Abstract
Introduction Parkinson's disease (PD) is a neurodegenerative disorder affecting the whole brain, leading to several motor and non-motor symptoms. In the past, it has been shown that PD alters resting state networks (RSN) in the brain. These networks are usually derived from fMRI BOLD signals. This study investigated RSN changes in PD patients based on maximum phase-amplitude coupling (PAC) throughout the cortex. We also tested the hypothesis that levodopa medication shifts network activity back toward a healthy state. Methods We recorded 23 PD patients and 24 healthy age-matched participants for 30 min at rest with magnetoencephalography (MEG). PD patients were measured once in the dopaminergic medication ON and once in the medication OFF state. A T1-MRI brain scan was acquired from each participant for source reconstruction. After correcting the data for artifacts and performing source reconstruction using a linearly constrained minimum variance beamformer, we extracted visual, sensorimotor (SMN), and frontal RSNs based on PAC. Results We found significant changes in all networks between healthy participants and PD patients in the medication OFF state. Levodopa had a significant effect on the SMN but not on the other networks. There was no significant change in the optimal PAC coupling frequencies between healthy participants and PD patients. Discussion Our results suggest that RSNs, based on PAC in different parts of the cortex, are altered in PD patients. Furthermore, levodopa significantly affects the SMN, reflecting the clinical alleviation of motor symptoms and leading to a network normalization compared to healthy controls.
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Affiliation(s)
- Sean Mertiens
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Matthias Sure
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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22
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Zhang Q, Lin Z, He Y, Jiang J, Hu D. Mendelian Randomization Analysis Reveals No Causal Relationship Between Plasma α-Synuclein and Parkinson's Disease. Mol Neurobiol 2023; 60:2268-2276. [PMID: 36640248 DOI: 10.1007/s12035-023-03206-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 12/29/2022] [Indexed: 01/15/2023]
Abstract
So far, the studies exploring plasma α-synuclein as a biomarker of Parkinson's disease (PD) have provided contradictory results. Here, we first employed the Mendelian randomization (MR) approach to elucidate their potential causal relationship. Five genetic instrumental variables of plasma α-synuclein were acquired from two publicly available datasets. Three independent genome-wide association studies of PD were used as outcome cohorts (PD cohorts 1, 2, and 3). Two-sample MR analyses were conducted using inverse-variance weighted (IVW), MR-Egger, weighted median, simple mode, and leave-one-out methods. Though the IVW approach demonstrated positive plasma α-synuclein effect on the PD risk in three outcome cohorts (OR = 1.134, 1.164, and 1.189, respectively), the P values were all larger than 0.05. The conclusions were robust under complementary sensitivity analyses. Our results did not support the causal relationship between plasma α-synuclein and PD.
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Affiliation(s)
- Qi Zhang
- The Department of Neurology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
| | - Zenan Lin
- Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China
| | - Yan He
- The Molecular Neuropharmacology Laboratory and the Eye-Brain Research Center, The State Key Laboratory of Ophthalmology, Optometry and Vision Science, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Junhong Jiang
- Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China.
| | - Di Hu
- Children's Hospital of Fudan University, No.399 Wanyuan Road, Shanghai, 201102, China.
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23
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Li N, Ma W, Ren F, Li X, Li F, Zong W, Wu L, Dai Z, Hui SCN, Edden RAE, Li M, Gao F. Neurochemical and functional reorganization of the cognitive-ear link underlies cognitive impairment in presbycusis. Neuroimage 2023; 268:119861. [PMID: 36610677 PMCID: PMC10026366 DOI: 10.1016/j.neuroimage.2023.119861] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 12/11/2022] [Accepted: 01/03/2023] [Indexed: 01/06/2023] Open
Abstract
Recent studies suggest that the interaction between presbycusis and cognitive impairment may be partially explained by the cognitive-ear link. However, the underlying neurophysiological mechanisms remain largely unknown. In this study, we combined magnetic resonance spectroscopy (MRS) and resting-state functional magnetic resonance imaging (fMRI) to investigate auditory gamma-aminobutyric acid (GABA) and glutamate (Glu) levels, intra- and inter-network functional connectivity, and their relationships with auditory and cognitive function in 51 presbycusis patients and 51 well-matched healthy controls. Our results confirmed reorganization of the cognitive-ear link in presbycusis, including decreased auditory GABA and Glu levels and aberrant functional connectivity involving auditory networks (AN) and cognitive-related networks, which were associated with reduced speech perception or cognitive impairment. Moreover, mediation analyses revealed that decreased auditory GABA levels and dysconnectivity between the AN and default mode network (DMN) mediated the association between hearing loss and impaired information processing speed in presbycusis. These findings highlight the importance of AN-DMN dysconnectivity in cognitive-ear link reorganization leading to cognitive impairment, and hearing loss may drive reorganization via decreased auditory GABA levels. Modulation of GABA neurotransmission may lead to new treatment strategies for cognitive impairment in presbycusis patients.
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Affiliation(s)
- Ning Li
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Wen Ma
- Department of Otolaryngology, the Central Hospital of Jinan City, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Fuxin Ren
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China; Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Xiao Li
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China; Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Fuyan Li
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China; Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Wei Zong
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China; Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Lili Wu
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Zongrui Dai
- Westa College, Southwest University, Chongqing, China
| | - Steve C N Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Muwei Li
- Vanderbilt University Institute of Imaging Science, Nashville, TN, USA
| | - Fei Gao
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
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24
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Wang J, Sun L, Chen L, Sun J, Xie Y, Tian D, Gao L, Zhang D, Xia M, Wu T. Common and distinct roles of amygdala subregional functional connectivity in non-motor symptoms of Parkinson's disease. NPJ Parkinsons Dis 2023; 9:28. [PMID: 36806219 PMCID: PMC9938150 DOI: 10.1038/s41531-023-00469-1] [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: 07/26/2022] [Accepted: 02/02/2023] [Indexed: 02/19/2023] Open
Abstract
Neuroimaging studies suggest a pivotal role of amygdala dysfunction in non-motor symptoms (NMS) of Parkinson's disease (PD). However, the relationship between amygdala subregions (the centromedial (CMA), basolateral (BLA) and superficial amygdala (SFA)) and NMS has not been delineated. We used resting-state functional MRI to examine the PD-related alterations in functional connectivity for amygdala subregions. The left three subregions and right BLA exhibited between-group differences, and were commonly hypo-connected with the frontal, temporal, insular cortex, and putamen in PD. Each subregion displayed distinct hypoconnectivity with the limbic systems. Partial least-squares analysis revealed distinct amygdala subregional involvement in diverse NMS. Hypo-connectivity of all four subregions was associated with emotion, pain, olfaction, and cognition. Hypo-connectivity of the left SFA was associated with sleepiness. Our findings highlight the hypofunction of the amygdala subregions in PD and their preliminary associations with NMS, providing new insights into the pathogenesis of NMS.
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Affiliation(s)
- Junling Wang
- grid.24696.3f0000 0004 0369 153XCenter for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Lianglong Sun
- grid.20513.350000 0004 1789 9964State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100091 China ,grid.20513.350000 0004 1789 9964Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100091 China ,grid.20513.350000 0004 1789 9964IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100091 China
| | - Lili Chen
- grid.24696.3f0000 0004 0369 153XCenter for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Junyan Sun
- grid.24696.3f0000 0004 0369 153XCenter for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Yapei Xie
- grid.20513.350000 0004 1789 9964State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100091 China ,grid.20513.350000 0004 1789 9964Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100091 China ,grid.20513.350000 0004 1789 9964IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100091 China
| | - Dezheng Tian
- grid.20513.350000 0004 1789 9964State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100091 China ,grid.20513.350000 0004 1789 9964Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100091 China ,grid.20513.350000 0004 1789 9964IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100091 China
| | - Linlin Gao
- grid.417031.00000 0004 1799 2675Department of General Medicine, Tianjin Union Medical Center, Tianjin, 300122 China
| | - Dongling Zhang
- grid.24696.3f0000 0004 0369 153XCenter for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100091, China. .,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100091, China. .,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100091, China.
| | - Tao Wu
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
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25
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Perovnik M, Rus T, Schindlbeck KA, Eidelberg D. Functional brain networks in the evaluation of patients with neurodegenerative disorders. Nat Rev Neurol 2023; 19:73-90. [PMID: 36539533 DOI: 10.1038/s41582-022-00753-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/21/2022] [Indexed: 12/24/2022]
Abstract
Network analytical tools are increasingly being applied to brain imaging maps of resting metabolic activity (PET) or blood oxygenation-dependent signals (functional MRI) to characterize the abnormal neural circuitry that underlies brain diseases. This approach is particularly valuable for the study of neurodegenerative disorders, which are characterized by stereotyped spread of pathology along discrete neural pathways. Identification and validation of disease-specific brain networks facilitate the quantitative assessment of pathway changes over time and during the course of treatment. Network abnormalities can often be identified before symptom onset and can be used to track disease progression even in the preclinical period. Likewise, network activity can be modulated by treatment and might therefore be used as a marker of efficacy in clinical trials. Finally, early differential diagnosis can be achieved by simultaneously measuring the activity levels of multiple disease networks in an individual patient's scans. Although these techniques were originally developed for PET, over the past several years analogous methods have been introduced for functional MRI, a more accessible non-invasive imaging modality. This advance is expected to broaden the application of network tools to large and diverse patient populations.
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Affiliation(s)
- Matej Perovnik
- Department of Neurology, University Medical Center Ljubljana, Ljubljana, Slovenia.,Medical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | - Tomaž Rus
- Department of Neurology, University Medical Center Ljubljana, Ljubljana, Slovenia.,Medical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | | | - David Eidelberg
- Center for Neurosciences, The Feinstein Institutes for Medical Research, Manhasset, NY, USA.
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26
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Zang Z, Song T, Li J, Nie B, Mei S, Zhang Y, Lu J. Severity-dependent functional connectome and the association with glucose metabolism in the sensorimotor cortex of Parkinson's disease. Front Neurosci 2023; 17:1104886. [PMID: 36793540 PMCID: PMC9922997 DOI: 10.3389/fnins.2023.1104886] [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: 11/22/2022] [Accepted: 01/16/2023] [Indexed: 01/31/2023] Open
Abstract
Functional MRI studies have achieved promising outcomes in revealing abnormal functional connectivity in Parkinson's disease (PD). The primary sensorimotor area (PSMA) received a large amount of attention because it closely correlates with motor deficits. While functional connectivity represents signaling between PSMA and other brain regions, the metabolic mechanism behind PSMA connectivity has rarely been well established. By introducing hybrid PET/MRI scanning, the current study enrolled 33 advanced PD patients during medication-off condition and 25 age-and-sex-matched healthy controls (HCs), aiming to not only identify the abnormal functional connectome pattern of the PSMA, but also to simultaneously investigate how PSMA functional connectome correlates with glucose metabolism. We calculated degree centrality (DC) and the ratio of standard uptake value (SUVr) using resting state fMRI and 18F-FDG-PET data. A two-sample t-test revealed significantly decreased PSMA DC (PFWE < 0.014) in PD patients. The PSMA DC also correlated negatively with H-Y stage (P = 0.031). We found a widespread reduction of H-Y stage associated (P-values < 0.041) functional connectivity between PSMA and the visual network, attention network, somatomotor network, limbic network, frontoparietal network as well as the default mode network. The PSMA DC correlated positively with FDG-uptake in the HCs (P = 0.039) but not in the PD patients (P > 0.44). In summary, we identified disease severity-dependent PSMA functional connectome which in addition uncoupled with glucose metabolism in PD patients. The current study highlighted the critical role of simultaneous PET/fMRI in revealing the functional-metabolic mechanism in the PSMA of PD patients.
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Affiliation(s)
- Zhenxiang Zang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Tianbin Song
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Jiping Li
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Binbin Nie
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
| | - Shanshan Mei
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yuqing Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China,*Correspondence: Jie Lu ✉
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27
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Waldthaler J, Sperlich A, König A, Stüssel C, Bremmer F, Timmermann L, Pedrosa D. High (130 Hz)- and mid (60 Hz)-frequency deep brain stimulation in the subthalamic nucleus differentially modulate response inhibition: A preliminary combined EEG and eye tracking study. Neuroimage Clin 2023; 37:103314. [PMID: 36630863 PMCID: PMC9841351 DOI: 10.1016/j.nicl.2023.103314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 12/23/2022] [Accepted: 01/02/2023] [Indexed: 01/06/2023]
Abstract
While deep brain stimulation (DBS) in the subthalamic nucleus (STN) improves motor functions in Parkinson's disease (PD), it may also increase impulsivity by interfering with the inhibition of reflexive responses. The aim of this study was to investigate if varying the pulse frequency of STN-DBS has a modulating effect on response inhibition and its neural correlates. For this purpose, 14 persons with PD repeated an antisaccade task in three stimulation settings (DBS off, high-frequency DBS (130 Hz), mid-frequency DBS (60 Hz)) in a randomized order, while eye movements and brain activity via high-density EEG were recorded. On a behavioral level, 130 Hz DBS stimulation had no effect on response inhibition measured as antisaccade error rate, while 60 Hz DBS induced a slight but significant reduction of directional errors compared with the DBS-off state and 130 Hz DBS. Further, stimulation with both frequencies decreased the onset latency of correct antisaccades, while increasing the latency of directional errors. Time-frequency domain analysis of the EEG data revealed that 60 Hz DBS was associated with an increase in preparatory theta power over a midfrontal region of interest compared with the off-DBS state which is generally regarded as a marker of increased cognitive control. While no significant differences in brain activity over mid- and lateral prefrontal regions of interest emerged between the 60 Hz and 130 Hz conditions, both stimulation frequencies were associated with a stronger midfrontal beta desynchronization during the mental preparation for correct antisaccades compared with DBS off-state which is discussed in the context of potentially enhanced proactive recruitment of the oculomotor network. Our preliminary findings suggest that mid-frequency STN-DBS may provide beneficial effects on response inhibition, while both 130 Hz- and 60 Hz STN-DBS may promote voluntary actions at the expense of slower reflexive responses.
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Affiliation(s)
- Josefine Waldthaler
- Department of Neurology, University Hospital Giessen and Marburg, Marburg, Germany; Department of Neurology, Philipps-University Marburg, Marburg, Germany; Center for Mind, Brain, and Behavior (CMBB), Philipps-University Marburg and Justus-Liebig-University, Giessen, Germany.
| | - Alexander Sperlich
- Department of Neurology, University Hospital Giessen and Marburg, Marburg, Germany; Department of Neurology, Philipps-University Marburg, Marburg, Germany
| | - Aylin König
- Department of Neurophysics, Philipps-University Marburg, Marburg, Germany
| | - Charlotte Stüssel
- Department of Neurology, University Hospital Giessen and Marburg, Marburg, Germany; Department of Neurology, Philipps-University Marburg, Marburg, Germany
| | - Frank Bremmer
- Center for Mind, Brain, and Behavior (CMBB), Philipps-University Marburg and Justus-Liebig-University, Giessen, Germany; Department of Neurophysics, Philipps-University Marburg, Marburg, Germany
| | - Lars Timmermann
- Department of Neurology, University Hospital Giessen and Marburg, Marburg, Germany; Department of Neurology, Philipps-University Marburg, Marburg, Germany; Center for Mind, Brain, and Behavior (CMBB), Philipps-University Marburg and Justus-Liebig-University, Giessen, Germany
| | - David Pedrosa
- Department of Neurology, University Hospital Giessen and Marburg, Marburg, Germany; Department of Neurology, Philipps-University Marburg, Marburg, Germany; Center for Mind, Brain, and Behavior (CMBB), Philipps-University Marburg and Justus-Liebig-University, Giessen, Germany
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28
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Resting-state network connectivity changes in drug-naive Parkinson's disease patients with probable REM sleep behavior disorder. J Neural Transm (Vienna) 2023; 130:43-51. [PMID: 36474090 DOI: 10.1007/s00702-022-02565-7] [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: 08/08/2022] [Accepted: 11/01/2022] [Indexed: 12/12/2022]
Abstract
Epidemiological studies have shown that Parkinson's disease (PD) patients with probable REM sleep behavior disorder (pRBD) present an increased risk of worse cognitive progression over the disease course. The aim of this study was to investigate, using resting-state functional MRI (RS-fMRI), the functional connectivity (FC) changes associated with the presence of pRBD in a cohort of newly diagnosed, drug-naive and cognitively unimpaired PD patients compared to healthy controls (HC). Fifty-six drug-naïve patients (25 PD-pRBD+ and 31 PD-pRBD-) and 23 HC underwent both RS-fMRI and clinical assessment. Single-subject and group-level independent component analysis was used to analyze intra- and inter-network FC differences within the major large-scale neurocognitive networks, namely the default mode (DMN), frontoparietal (FPN), salience (SN) and executive-control (ECN) networks. Widespread FC changes were found within the most relevant neurocognitive networks in PD patients compared to HC. Moreover, PD-pRBD+ patients showed abnormal intrinsic FC within the DMN, ECN and SN compared to PD-pRBD-. Finally, PD-pRBD+ patients showed functional decoupling between left and right FPN. In the present study, we revealed that FC changes within the most relevant neurocognitive networks are already detectable in early drug-naïve PD patients, even in the absence of clinical overt cognitive impairment. These changes are even more evident in PD patients with RBD, potentially leading to profound impairment in cognitive processing and cognitive/behavioral integration, as well as to fronto-striatal maladaptive compensatory mechanisms.
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29
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Wang Y, Ning H, Ren J, Pan C, Yu M, Xue C, Wang X, Zhou G, Chen Y, Liu W. Integrated Clinical Features with Plasma and Multi-modal Neuroimaging Biomarkers to Diagnose Mild Cognitive Impairment in Early Drug-Naive Parkinson's Disease. ACS Chem Neurosci 2022; 13:3523-3533. [PMID: 36417458 DOI: 10.1021/acschemneuro.2c00565] [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: 11/24/2022] Open
Abstract
The pathogenesis of cognitive impairment in Parkinson's disease (PD) patients remains unclear, and there is no ideal diagnostic tool available at present. We assessed integrated clinical features with plasma and multi-modal neuroimaging biomarkers to identify mild cognitive impairment (MCI) in early drug-naive PD patients. 49 early drug-naive PD patients, including 26 with MCI (PD-MCI) and 23 with normal cognition (PD-NC), and 20 controls were recruited. Plasma markers [α-synuclein, beta-amyloid 1-40 (Aβ40), beta-amyloid 1-42 (Aβ42), and phosphorylated Tau 181 (p-Tau181) levels], functional connectivity (FC) of the default mode network, and cortical thickness (CTh) were evaluated to identify PD-MCI. The PD-MCI group had significantly higher plasma p-Tau181 levels and p-Tau181/Aβ42 ratio and lower Aβ42/Aβ40 ratio compared to the PD-NC group. Compared to PD-NC, the PD-MCI group showed increased FC between left posterior cingulate cortex (pCC) and the left parahippocampal gyrus (PHG), and between the right hippocampal formation and the left anterior cingulate and paracingulate gyri, and the right middle temporal gyrus. Additionally, the PD-MCI group had thinner cortex thickness in the right lateral occipital and frontal pole compared to the PD-NC group. The final model combining clinical characteristics and several variables (age, sex, plasma p-Tau181 level, Aβ42/Aβ40 ratio, the right lateral occipital CTh, and the FC value between the left pCC and left PHG) had the highest diagnostic accuracy for PD-MCI (AUC = 0.987, 95% CI 0.903-1.000; p = 0.001 compared to age and sex alone). The combination of clinical features, plasma biomarkers, and multi-modal neuroimaging biomarkers can identify early cognitive decline in PD patients.
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Affiliation(s)
- Yajie Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Houxu Ning
- Department of Chinese Medicine, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Jingru Ren
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Chenxi Pan
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Miao Yu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Chen Xue
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Xiao Wang
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Gaiyan Zhou
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Yubing Chen
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Weiguo Liu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
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30
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Ay U, Gürvit İH. Alterations in Large-Scale Intrinsic Connectivity Networks in the Parkinson's Disease-Associated Cognitive Impairment Continuum: A Systematic Review. Noro Psikiyatr Ars 2022; 59:S57-S66. [PMID: 36578982 PMCID: PMC9767132 DOI: 10.29399/npa.28209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 06/08/2022] [Indexed: 12/31/2022] Open
Abstract
Introduction Cognitive impairment is common in the course of Parkinson's disease (PD) and displays a continuum from subjective cognitive impairment to dementia. Illuminating the pathophysiological processes associated with the continuum may help create follow-up and new treatment approaches. In this context, large-scale intrinsic connectivity networks are widely investigated to elucidate the neural processes underlying PD and are promising as non-invasive biomarkers. This systematic review aims to examine the alterations in large-scale intrinsic connectivity networks in the continuum of PD-associated cognitive impairment. Method ScienceDirect, Web of Science, and PubMed databases were searched with the specified keywords. The studies obtained as a result of this review were investigated by the PRISMA criteria, which were taken as a basis for the systematic review and writing of meta-analyses. Results A total of 974 studies were obtained from three databases. Twenty studies were included in the systematic review based on predetermined eligibility criteria. Among the large-scale connectivity networks examined in these studies, it was found that sensory-motor networks decreased their connectivity in the continuum of PD-associated cognitive impairment, and there were conflicting results in terms of cognitive networks. Conclusion Well-designed longitudinal studies are needed to clarify the alterations in the intrinsic connectivity networks in the PD cognitive impairment continuum. In these studies, it is necessary to define the cognitive disorder groups well, to control the connectivity changes that may occur due to dopaminergic treatment, and to evaluate Parkinson's patients with subjective cognitive impairment and dementia within the continuum.
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Affiliation(s)
- Ulaş Ay
- Neuroimaging Unit, Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, Istanbul, Turkey,Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey,Graduate School of Health Sciences, Istanbul University, Istanbul, Turkey,Correspondence Address: Ulaş Ay, İstanbul Üniversitesi, Hulusi Behçet Yaşam Bilimleri Araştırma Laboratuvarı, Nörogörüntüleme Birimi, Turgut Özal Millet Cd, 34093, Fatih, İstanbul, Turkey • E-mail:
| | - İ. Hakan Gürvit
- Department of Neurology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
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31
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Wang J, Sun J, Gao L, Zhang D, Chen L, Wu T. Common and unique dysconnectivity profiles of dorsal and median raphe in Parkinson's disease. Hum Brain Mapp 2022; 44:1070-1078. [PMID: 36334274 PMCID: PMC9875924 DOI: 10.1002/hbm.26139] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 10/11/2022] [Accepted: 10/23/2022] [Indexed: 11/07/2022] Open
Abstract
The serotonergic (5-HT) system, which undergoes degeneration in Parkinson's disease (PD), is involved in the pathogenesis of motor and nonmotor symptoms. The dorsal raphe (DR) and median raphe (MR) nuclei are the main source of 5-HT neurons, however, brain connectivity changes in these two nuclei have not been delineated in PD. Here we used resting-state fMRI (rs-fMRI) to characterize functional connectivity profiles of DR and MR and further examine the associations between dysconnectivity of raphe nuclei and clinical phenotypes of PD. We found that DR and MR commonly hypo-connected with the sensorimotor, temporal, and occipital cortex, limbic system, left thalamus, putamen, and cerebellum in PD. DR had unique decreased connectivity with the bilateral prefrontal and cingulate cortices, while MR had lower connectivity with the pons. Moreover, reduced connectivity of DR correlated with depression, drowsiness, and anxiety, whereas dysconnectivity of MR correlated with depression, cognitive deficits, sleep disturbances, and pain. Our findings highlight the complex roles of raphe nuclei in motor and nonmotor symptoms, providing novel insights into the neurophysiological mechanisms underlying pathogenesis of PD.
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Affiliation(s)
- Junling Wang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Junyan Sun
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Linlin Gao
- Department of General MedicineTianjin Union Medical CenterTianjinChina
| | - Dongling Zhang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Lili Chen
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Tao Wu
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
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32
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Shang S, Ye J, Wu J, Zhang H, Dou W, Krishnan Muthaiah VP, Tian Y, Zhang Y, Chen YC, Yin X. Early disturbance of dynamic synchronization and neurovascular coupling in cognitively normal Parkinson's disease. J Cereb Blood Flow Metab 2022; 42:1719-1731. [PMID: 35473430 PMCID: PMC9441726 DOI: 10.1177/0271678x221098503] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Pathological process in Parkinson's disease (PD) is accompanied with functional and metabolic alterations. The time-varying properties of functional coherence and their coupling to regional perfusion are still rarely elucidated. To investigate early disruption of dynamic regional homogeneity (dReho) and neurovascular coupling in cognitively normal PD patients, dynamic neuronal synchronization and regional perfusion were measured using dReho and cerebral blood flow (CBF), respectively. Neurovascular coupling was assessed by CBF-ReHo correlation coefficient and CBF/ReHo ratio. Multivariate pattern analysis was conducted for the differentiating ability of each feature. Relative to healthy controls (HC) subjects, PD patients demonstrated increased dReho in middle temporal gyrus (MTG), rectus gyrus, middle occipital gyrus, and precuneus, whereas reduced dReho in putamen and supplementary motor area (SMA); while higher CBF/dReho ratio was located in putamen, SMA, paracentral lobule, and postcentral gyrus, whereas lower CBF/dReho ratio in superior temporal gyrus, MTG, precuneus, and angular gyrus (AG). Global and regional CBF-Reho decoupling were both observed in PD groups. The CBF/Reho ratio features achieved more powerful classification performance than other features. From the view of dynamic neural synchronization and neurovascular coupling, this study reinforced the insights into neural basis underlying PD and the potential role in the disease diagnosis and differentiation.
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Affiliation(s)
- Song'an Shang
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Jing Ye
- Department of Radiology, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Jingtao Wu
- Department of Radiology, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Hongying Zhang
- Department of Radiology, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Weiqiang Dou
- MR Research China, GE Healthcare, Beijing, China
| | | | - Youyong Tian
- Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Yingdong Zhang
- Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Yu-Chen Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Xindao Yin
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
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Prange S, Theis H, Banwinkler M, van Eimeren T. Molecular Imaging in Parkinsonian Disorders—What’s New and Hot? Brain Sci 2022; 12:brainsci12091146. [PMID: 36138882 PMCID: PMC9496752 DOI: 10.3390/brainsci12091146] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/23/2022] [Accepted: 08/24/2022] [Indexed: 12/02/2022] Open
Abstract
Highlights Abstract Neurodegenerative parkinsonian disorders are characterized by a great diversity of clinical symptoms and underlying neuropathology, yet differential diagnosis during lifetime remains probabilistic. Molecular imaging is a powerful method to detect pathological changes in vivo on a cellular and molecular level with high specificity. Thereby, molecular imaging enables to investigate functional changes and pathological hallmarks in neurodegenerative disorders, thus allowing to better differentiate between different forms of degenerative parkinsonism, improve the accuracy of the clinical diagnosis and disentangle the pathophysiology of disease-related symptoms. The past decade led to significant progress in the field of molecular imaging, including the development of multiple new and promising radioactive tracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) as well as novel analytical methods. Here, we review the most recent advances in molecular imaging for the diagnosis, prognosis, and mechanistic understanding of parkinsonian disorders. First, advances in imaging of neurotransmission abnormalities, metabolism, synaptic density, inflammation, and pathological protein aggregation are reviewed, highlighting our renewed understanding regarding the multiplicity of neurodegenerative processes involved in parkinsonian disorders. Consequently, we review the role of molecular imaging in the context of disease-modifying interventions to follow neurodegeneration, ensure stratification, and target engagement in clinical trials.
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Affiliation(s)
- Stéphane Prange
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- Institut des Sciences Cognitives Marc Jeannerod, CNRS, UMR 5229, Université de Lyon, 69675 Bron, France
- Correspondence: (S.P.); (T.v.E.); Tel.: +49-221-47882843 (T.v.E.)
| | - Hendrik Theis
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- Department of Neurology, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
| | - Magdalena Banwinkler
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
| | - Thilo van Eimeren
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- Department of Neurology, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- Correspondence: (S.P.); (T.v.E.); Tel.: +49-221-47882843 (T.v.E.)
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Chen L, Huang T, Ma D, Chen YC. Altered Default Mode Network Functional Connectivity in Parkinson’s Disease: A Resting-State Functional Magnetic Resonance Imaging Study. Front Neurosci 2022; 16:905121. [PMID: 35720728 PMCID: PMC9204219 DOI: 10.3389/fnins.2022.905121] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 05/10/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeWhether the intrinsic functional connectivity pattern of the default mode network (DMN) is involved in the progression of cognitive decline in Parkinson’s disease (PD) remains unclear. This study aimed to investigate the intrinsic functional connectivity (FC) pattern of the DMN anchored on the posterior cingulate cortex (PCC) in patients with PD by resting-state functional magnetic resonance imaging (fMRI).MethodsFifty patients with PD and 50 healthy controls (HCs) were included for resting-state fMRI scanning. A seed-based FC method was used to reveal FC patterns in the DMN with region of interest (ROI) in the PCC. Relationships between FC patterns and disease severity (UPDRS-III) were detected.ResultsCompared with the HCs, the patients with PD showed increased FC between the PCC and the right precuneus, left cuneus, and right angular gyrus. In the PD group, the increased FC values in the right precuneus were significantly and positively correlated with motor severity as assessed with UPDRS-III scores (rho = 0.337, p = 0.02).ConclusionOur result highlights that the patients with PD showed increased FC between the PCC and the right precuneus, left cuneus, and right angular gyrus in the DMN. The altered connectivity pattern in the DMN may play a crucial role in the neurophysiological mechanism of cognitive decline in patients with PD. These findings might provide new insights into neural mechanisms of cognitive decline in PD.
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Affiliation(s)
- Lu Chen
- Department of Radiology, Nanjing Integrated Traditional Chinese and Western Medicine Hospital Affiliated With Nanjing University of Chinese Medicine, Nanjing, China
| | - Ting Huang
- Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Di Ma
- College of Information Science and Technology, Nanjing Forestry University, Nanjing, China
| | - Yu-Chen Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- *Correspondence: Yu-Chen Chen,
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35
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Clinical evaluation and resting state fMRI analysis of virtual reality based training in Parkinson’s disease through a randomized controlled trial. Sci Rep 2022; 12:8024. [PMID: 35577874 PMCID: PMC9110743 DOI: 10.1038/s41598-022-12061-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 05/04/2022] [Indexed: 12/04/2022] Open
Abstract
There are few studies investigating the short-term effects of Virtual Reality based Exergaming (EG) on motor and cognition simultaneously and pursue the brain functional activity changes after these interventions in patients with Parkinson’s Disease (PD). The purpose of this study was to investigate the synergistic therapeutic effects of Virtual Reality based EG on motor and cognitive symptoms in PD and its possible effects on neuroplasticity. Eligible patients with the diagnosis of PD were randomly assigned to one of the two study groups: (1) an experimental EG group, (2) an active control Exercise Therapy (ET) group. All patients participated in a 4-week exercise program consisting of 12 treatment sessions. Every session lasted 60 min. Participants underwent a motor evaluation, extensive neuropsychological assessment battery and rs-fMRI before and after the interventions. Thirty patients fulfilled the inclusion criteria and were randomly assigned to the EG and ET groups. After the dropouts, 23 patients completed the assessments and interventions (11 in EG, 13 in ET). Within group analysis showed significant improvements in both groups. Between group comparisons considering the interaction of group × time effect, showed superiority of EG in terms of general cognition, delayed visual recall memory and Boston Naming Test. These results were consistent in the within-group and between-group analysis. Finally, rs-fMRI analysis showed increased activity in the precuneus region in the time × group interaction in the favor of EG group. EG can be an effective alternative in terms of motor and cognitive outcomes in patients with PD. Compared to ET, EG may affect brain functional connectivity and can have beneficial effects on patients’ cognitive functions and motor symptoms. Whenever possible, using EG and ET in combination, may have the better effects on patients daily living and patients can benefit from the advantages of both interventions.
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36
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Abstract
Cognitive impairment affects up to 80% of patients with Parkinson's disease (PD) and is associated with poor quality of life. PD cognitive dysfunction includes poor working memory, impairments in executive function and difficulty in set-shifting. The pathophysiology underlying cognitive impairment in PD is still poorly understood, but there is evidence to support involvements of the cholinergic, dopaminergic, and noradrenergic systems. Only rivastigmine, an acetyl- and butyrylcholinesterase inhibitor, is efficacious for the treatment of PD dementia, which limits management of cognitive impairment in PD. Whereas the role of the serotonergic system in PD cognition is less understood, through its interactions with other neurotransmitters systems, namely, the cholinergic system, it may be implicated in cognitive processes. In this chapter, we provide an overview of the pharmacological, clinical and pathological evidence that implicates the serotonergic system in mediating cognition in PD.
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37
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Fan Y, Han J, Zhao L, Wu C, Wu P, Huang Z, Hao X, Ji Y, Chen D, Zhu M. Experimental Models of Cognitive Impairment for Use in Parkinson's Disease Research: The Distance Between Reality and Ideal. Front Aging Neurosci 2021; 13:745438. [PMID: 34912207 PMCID: PMC8667076 DOI: 10.3389/fnagi.2021.745438] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 11/01/2021] [Indexed: 12/14/2022] Open
Abstract
Parkinson’s disease (PD) is the second most common neurodegenerative disease. Cognitive impairment is one of the key non-motor symptoms of PD, affecting both mortality and quality of life. However, there are few experimental studies on the pathology and treatments of PD with mild cognitive impairment (PD-MCI) and PD dementia (PDD) due to the lack of representative models. To identify new strategies for developing representative models, we systematically summarized previous studies on PD-MCI and PDD and compared differences between existing models and diseases. Our initial search identified 5432 articles, of which 738 were duplicates. A total of 227 articles met our inclusion criteria and were included in the analysis. Models fell into three categories based on model design: neurotoxin-induced, transgenic, and combined. Although the neurotoxin-induced experimental model was the most common type that was used during every time period, transgenic and combined experimental models have gained significant recent attention. Unfortunately, there remains a big gap between ideal and actual experimental models. While each model has its own disadvantages, there have been tremendous advances in the development of PD models of cognitive impairment, and almost every model can verify a hypothesis about PD-MCI or PDD. Finally, our proposed strategies for developing novel models are as follows: a set of plans that integrate symptoms, biochemistry, neuroimaging, and other objective indicators to judge and identify that the novel model plays a key role in new strategies for developing representative models; novel models should simulate different clinical features of PD-MCI or PDD; inducible α-Syn overexpression and SH-SY5Y-A53T cellular models are good candidate models of PD-MCI or PDD.
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Affiliation(s)
- Yaohua Fan
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Jiajun Han
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Lijun Zhao
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Chunxiao Wu
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China.,Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Peipei Wu
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Zifeng Huang
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Xiaoqian Hao
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - YiChun Ji
- Shenzhen Bao'an Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Dongfeng Chen
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Meiling Zhu
- Guangzhou University of Chinese Medicine, Guangzhou, China
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Steidel K, Ruppert MC, Palaghia I, Greuel A, Tahmasian M, Maier F, Hammes J, van Eimeren T, Timmermann L, Tittgemeyer M, Drzezga A, Pedrosa D, Eggers C. Dopaminergic pathways and resting-state functional connectivity in Parkinson's disease with freezing of gait. Neuroimage Clin 2021; 32:102899. [PMID: 34911202 PMCID: PMC8645514 DOI: 10.1016/j.nicl.2021.102899] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 11/23/2021] [Accepted: 11/24/2021] [Indexed: 11/15/2022]
Abstract
Freezing of gait is a common phenomenon of advanced Parkinson's disease. Besides locomotor function per se, a role of cognitive deficits has been suggested. Limited evidence of associated dopaminergic deficits points to caudatal denervation. Further, altered functional connectivity within resting-state networks with importance for cognitive functions has been described in freezers. A potential pathophysiological link between both imaging findings has not yet been addressed. The current study sought to investigate the association between dopaminergic pathway dysintegrity and functional dysconnectivity in relation to FOG severity and cognitive performance in a well-characterized PD cohort undergoing high-resolution 6-[18F]fluoro-L-Dopa PET and functional MRI. The freezing of gait questionnaire was applied to categorize patients (n = 59) into freezers and non-freezers. A voxel-wise group comparison of 6-[18F]fluoro-L-Dopa PET scans with focus on striatum was performed between both well-matched and neuropsychologically characterized patient groups. Seed-to-voxel resting-state functional connectivity maps of the resulting dopamine depleted structures and dopaminergic midbrain regions were created and compared between both groups. For a direct between-group comparison of dopaminergic pathway integrity, a molecular connectivity approach was conducted on 6-[18F]fluoro-L-Dopa scans. With respect to striatal regions, freezers showed significant dopaminergic deficits in the left caudate nucleus, which exhibited altered functional connectivity with regions of the visual network. Regarding midbrain structures, the bilateral ventral tegmental area showed altered functional coupling to regions of the default mode network. An explorative examination of the integrity of dopaminergic pathways by molecular connectivity analysis revealed freezing-associated impairments in mesolimbic and mesocortical pathways. This study represents the first characterization of a link between dopaminergic pathway dysintegrity and altered functional connectivity in Parkinson's disease with freezing of gait and hints at a specific involvement of striatocortical and mesocorticolimbic pathways in freezers.
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Affiliation(s)
- Kenan Steidel
- Department of Neurology, University Hospital of Marburg, Germany.
| | - Marina C Ruppert
- Department of Neurology, University Hospital of Marburg, Germany; Center for Mind, Brain and Behavior - CMBB, Universities Marburg and Gießen, Germany
| | - Irina Palaghia
- Department of Neurology, University Hospital of Marburg, Germany
| | - Andrea Greuel
- Department of Neurology, University Hospital of Marburg, Germany
| | - Masoud Tahmasian
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Franziska Maier
- Department of Psychiatry, University Hospital Cologne, Medical Faculty, Cologne, Germany
| | - Jochen Hammes
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Germany
| | - Thilo van Eimeren
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Germany; Department of Neurology, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Germany; German Center for Neurodegenerative Diseases (DZNE), Bonn- Cologne, Germany
| | - Lars Timmermann
- Department of Neurology, University Hospital of Marburg, Germany; Center for Mind, Brain and Behavior - CMBB, Universities Marburg and Gießen, Germany
| | - Marc Tittgemeyer
- Max Planck Institute for Metabolism Research, Cologne, Germany; Cluster of Excellence in Cellular Stress and Aging Associated Disease (CECAD), Cologne, Germany
| | - Alexander Drzezga
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Germany; German Center for Neurodegenerative Diseases (DZNE), Bonn- Cologne, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-2), Research Center Jülich, Germany
| | - David Pedrosa
- Department of Neurology, University Hospital of Marburg, Germany; Center for Mind, Brain and Behavior - CMBB, Universities Marburg and Gießen, Germany
| | - Carsten Eggers
- Department of Neurology, University Hospital of Marburg, Germany; Center for Mind, Brain and Behavior - CMBB, Universities Marburg and Gießen, Germany
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39
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Ruppert MC, Greuel A, Freigang J, Tahmasian M, Maier F, Hammes J, van Eimeren T, Timmermann L, Tittgemeyer M, Drzezga A, Eggers C. The default mode network and cognition in Parkinson's disease: A multimodal resting-state network approach. Hum Brain Mapp 2021; 42:2623-2641. [PMID: 33638213 PMCID: PMC8090788 DOI: 10.1002/hbm.25393] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 02/12/2021] [Accepted: 02/17/2021] [Indexed: 12/12/2022] Open
Abstract
Involvement of the default mode network (DMN) in cognitive symptoms of Parkinson's disease (PD) has been reported by resting-state functional MRI (rsfMRI) studies. However, the relation to metabolic measures obtained by [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) is largely unknown. We applied multimodal resting-state network analysis to clarify the association between intrinsic metabolic and functional connectivity abnormalities within the DMN and their significance for cognitive symptoms in PD. PD patients were classified into normal cognition (n = 36) and mild cognitive impairment (MCI; n = 12). The DMN was identified by applying an independent component analysis to FDG-PET and rsfMRI data of a matched subset (16 controls and 16 PD patients) of the total cohort. Besides metabolic activity, metabolic and functional connectivity within the DMN were compared between the patients' groups and healthy controls (n = 16). Glucose metabolism was significantly reduced in all DMN nodes in both patient groups compared to controls, with the lowest uptake in PD-MCI (p < .05). Increased metabolic and functional connectivity along fronto-parietal connections was identified in PD-MCI patients compared to controls and unimpaired patients. Functional connectivity negatively correlated with cognitive composite z-scores in patients (r = -.43, p = .005). The current study clarifies the commonalities of metabolic and hemodynamic measures of brain network activity and their individual significance for cognitive symptoms in PD, highlighting the added value of multimodal resting-state network approaches for identifying prospective biomarkers.
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Affiliation(s)
- Marina C Ruppert
- Department of Neurology, University Hospital of Marburg, Marburg, Germany.,Center for Mind, Brain, and Behavior-CMBB, Universities of Marburg and Gießen, Marburg, Germany
| | - Andrea Greuel
- Department of Neurology, University Hospital of Marburg, Marburg, Germany
| | - Julia Freigang
- Department of Neurology, University Hospital of Marburg, Marburg, Germany.,Center for Mind, Brain, and Behavior-CMBB, Universities of Marburg and Gießen, Marburg, Germany
| | - Masoud Tahmasian
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Franziska Maier
- Medical Faculty, Department of Psychiatry, University Hospital Cologne, Cologne, Germany
| | - Jochen Hammes
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Cologne, Germany
| | - Thilo van Eimeren
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Cologne, Germany.,Department of Neurology, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Cologne, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Lars Timmermann
- Department of Neurology, University Hospital of Marburg, Marburg, Germany.,Center for Mind, Brain, and Behavior-CMBB, Universities of Marburg and Gießen, Marburg, Germany
| | - Marc Tittgemeyer
- Max Planck Institute for Metabolism Research, Cologne, Germany.,Cluster of Excellence in Cellular Stress and Aging Associated Disease (CECAD), Cologne, Germany
| | - Alexander Drzezga
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Cologne, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-2), Jülich, Germany
| | - Carsten Eggers
- Department of Neurology, University Hospital of Marburg, Marburg, Germany.,Center for Mind, Brain, and Behavior-CMBB, Universities of Marburg and Gießen, Marburg, Germany
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