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Yan S, Lu J, Li Y, Zhu H, Tian T, Qin Y, Zhu W. Large-scale functional network connectivity mediates the association between nigral neuromelanin hypopigmentation and motor impairment in Parkinson's disease. Brain Struct Funct 2024; 229:843-852. [PMID: 38347222 DOI: 10.1007/s00429-024-02761-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 01/09/2024] [Indexed: 04/10/2024]
Abstract
Neuromelanin hypopigmentation within substantia nigra pars compacta (SNc) reflects the loss of pigmented neurons, which in turn contributes to the dysfunction of the nigrostriatal and striato-cortical pathways in Parkinson's disease (PD). Our study aims to investigate the relationships between SN degeneration manifested by neuromelanin reduction, functional connectivity (FC) among large-scale brain networks, and motor impairment in PD. This study included 68 idiopathic PD patients and 32 age-, sex- and education level-matched healthy controls who underwent neuromelanin-sensitive magnetic resonance imaging (MRI), functional MRI, and motor assessments. SN integrity was measured using the subregional contrast-to-noise ratio calculated from neuromelanin-sensitive MRI. Resting-state FC maps were obtained based on the independent component analysis. Subsequently, we performed partial correlation and mediation analyses in SN degeneration, network disruption, and motor impairment for PD patients. We found significantly decreased neuromelanin within SN and widely altered inter-network FCs, mainly involved in the basal ganglia (BG), sensorimotor and frontoparietal networks in PD. In addition, decreased neuromelanin content was negatively correlated with the dorsal sensorimotor network (dSMN)-medial visual network connection (P = 0.012) and dSMN-BG connection (P = 0.004). Importantly, the effect of SN neuromelanin hypopigmentation on motor symptom severity in PD is partially mediated by the increased connectivity strength between BG and dSMN (indirect effect = - 1.358, 95% CI: - 2.997, - 0.147). Our results advanced our understanding of the interactions between neuromelanin hypopigmentation in SN and altered FCs of functional networks in PD and suggested the potential of multimodal metrics for early diagnosis and monitoring the response to therapies.
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Affiliation(s)
- Su Yan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, JiefangAvenue, Wuhan, 430030, China
| | - Jun Lu
- Department of CT & MRI, The First Affiliated Hospital, College of Medicine, Shihezi University, 107 North Second Road, Shihezi, China
| | - Yuanhao Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, JiefangAvenue, Wuhan, 430030, China
| | - Hongquan Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, JiefangAvenue, Wuhan, 430030, China
| | - Tian Tian
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, JiefangAvenue, Wuhan, 430030, China
| | - Yuanyuan Qin
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, JiefangAvenue, Wuhan, 430030, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, JiefangAvenue, Wuhan, 430030, China.
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2
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Theis H, Pavese N, Rektorová I, van Eimeren T. Imaging Biomarkers in Prodromal and Earliest Phases of Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2024:JPD230385. [PMID: 38339941 DOI: 10.3233/jpd-230385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2024]
Abstract
Assessing imaging biomarker in the prodromal and early phases of Parkinson's disease (PD) is of great importance to ensure an early and safe diagnosis. In the last decades, imaging modalities advanced and are now able to assess many different aspects of neurodegeneration in PD. MRI sequences can measure iron content or neuromelanin. Apart from SPECT imaging with Ioflupane, more specific PET tracers to assess degeneration of the dopaminergic system are available. Furthermore, metabolic PET patterns can be used to anticipate a phenoconversion from prodromal PD to manifest PD. In this regard, it is worth mentioning that PET imaging of inflammation will gain significance. Molecular imaging of neurotransmitters like serotonin, noradrenaline and acetylcholine shed more light on non-motor symptoms. Outside of the brain, molecular imaging of the heart and gut is used to measure PD-related degeneration of the autonomous nervous system. Moreover, optical coherence tomography can noninvasively detect degeneration of retinal fibers as a potential biomarker in PD. In this review, we describe these state-of-the-art imaging modalities in early and prodromal PD and point out in how far these techniques can and will be used in the future to pave the way towards a biomarker-based staging of PD.
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Affiliation(s)
- Hendrik Theis
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Multimodal Neuroimaging Group, Cologne, Germany
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany
| | - Nicola Pavese
- Aarhus University, Institute of Clinical Medicine, Department of Nuclear Medicine & PET, Aarhus N, Denmark
- Newcastle University, Translational and Clinical Research Institute, Newcastle upon Tyne, United Kingdom
| | - Irena Rektorová
- Masaryk University, Faculty of Medicine and St. Anne's University Hospital, International Clinical Research Center, ICRC, Brno, Czech Republic
- Masaryk University, Faculty of Medicine and St. Anne's University Hospital, First Department of Neurology, Brno, Czech Republic
- Masaryk University, Applied Neuroscience Research Group, Central European Institute of Technology - CEITEC, Brno, Czech Republic
| | - Thilo van Eimeren
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Multimodal Neuroimaging Group, Cologne, Germany
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany
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3
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Bitra VR, Challa SR, Adiukwu PC, Rapaka D. Tau trajectory in Alzheimer's disease: Evidence from the connectome-based computational models. Brain Res Bull 2023; 203:110777. [PMID: 37813312 DOI: 10.1016/j.brainresbull.2023.110777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 07/08/2023] [Accepted: 10/06/2023] [Indexed: 10/11/2023]
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder with an impairment of cognition and memory. Current research on connectomics have now related changes in the network organization in AD to the patterns of accumulation and spread of amyloid and tau, providing insights into the neurobiological mechanisms of the disease. In addition, network analysis and modeling focus on particular use of graphs to provide intuition into key organizational principles of brain structure, that stipulate how neural activity propagates along structural connections. The utility of connectome-based computational models aids in early predicting, tracking the progression of biomarker-directed AD neuropathology. In this article, we present a short review of tau trajectory, the connectome changes in tau pathology, and the dependent recent connectome-based computational modelling approaches for tau spreading, reproducing pragmatic findings, and developing significant novel tau targeted therapies.
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Affiliation(s)
- Veera Raghavulu Bitra
- School of Pharmacy, Faculty of Health Sciences, University of Botswana, P/Bag-0022, Gaborone, Botswana.
| | - Siva Reddy Challa
- Department of Cancer Biology and Pharmacology, University of Illinois College of Medicine, Peoria, IL 61614, USA; KVSR Siddartha College of Pharmaceutical Sciences, Vijayawada, Andhra Pradesh, India
| | - Paul C Adiukwu
- School of Pharmacy, Faculty of Health Sciences, University of Botswana, P/Bag-0022, Gaborone, Botswana
| | - Deepthi Rapaka
- Pharmacology Division, D.D.T. College of Medicine, Gaborone, Botswana.
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4
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Wang X, Wang T, Fan X, Zhang Z, Wang Y, Li Z. A Molecular Toolbox of Positron Emission Tomography Tracers for General Anesthesia Mechanism Research. J Med Chem 2023; 66:6463-6497. [PMID: 37145921 DOI: 10.1021/acs.jmedchem.2c01965] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
With appropriate radiotracers, positron emission tomography (PET) allows direct or indirect monitoring of the spatial and temporal distribution of anesthetics, neurotransmitters, and biomarkers, making it an indispensable tool for studying the general anesthesia mechanism. In this Perspective, PET tracers that have been recruited in general anesthesia research are introduced in the following order: 1) 11C/18F-labeled anesthetics, i.e., PET tracers made from inhaled and intravenous anesthetics; 2) PET tracers targeting anesthesia-related receptors, e.g., neurotransmitters and voltage-gated ion channels; and 3) PET tracers for studying anesthesia-related neurophysiological effects and neurotoxicity. The radiosynthesis, pharmacodynamics, and pharmacokinetics of the above PET tracers are mainly discussed to provide a practical molecular toolbox for radiochemists, anesthesiologists, and those who are interested in general anesthesia.
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Affiliation(s)
- Xiaoxiao Wang
- Center for Molecular Imaging and Translational Medicine, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, Fujian 361102, China
| | - Tao Wang
- Center for Molecular Imaging and Translational Medicine, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, Fujian 361102, China
| | - Xiaowei Fan
- Center for Molecular Imaging and Translational Medicine, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, Fujian 361102, China
| | - Zhao Zhang
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Yingwei Wang
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Zijing Li
- Center for Molecular Imaging and Translational Medicine, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, Fujian 361102, China
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5
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Mohanty R, Ferreira D, Nordberg A, Westman E. Associations between different tau-PET patterns and longitudinal atrophy in the Alzheimer's disease continuum: biological and methodological perspectives from disease heterogeneity. Alzheimers Res Ther 2023; 15:37. [PMID: 36814346 PMCID: PMC9945609 DOI: 10.1186/s13195-023-01173-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 01/18/2023] [Indexed: 02/24/2023]
Abstract
BACKGROUND Subtypes and patterns are defined using tau-PET (tau pathology) and structural MRI (atrophy) in Alzheimer's disease (AD). However, the relationship between tau pathology and atrophy across these subtypes/patterns remains unclear. Therefore, we investigated the biological association between baseline tau-PET patterns and longitudinal atrophy in the AD continuum; and the methodological characterization of heterogeneity as a continuous phenomenon over the conventional discrete subgrouping. METHODS In 366 individuals (amyloid-beta-positive cognitively normal, prodromal AD, AD dementia; amyloid-beta-negative cognitively normal), we examined the association between tau-PET patterns and longitudinal MRI. We modeled tau-PET patterns as a (a) continuous phenomenon with key dimensions: typicality and severity; and (b) discrete phenomenon by categorization into patterns: typical, limbic predominant, cortical predominant and minimal tau. Tau-PET patterns and associated longitudinal atrophy were contextualized within the Amyloid/Tau/Neurodegeneration (A/T/N) biomarker scheme. RESULTS Localization and longitudinal atrophy change vary differentially across different tau-PET patterns in the AD continuum. Atrophy, a downstream event, did not always follow a topography akin to the corresponding tau-PET pattern. Further, heterogeneity as a continuous phenomenon offered an alternative and useful characterization, sharing correspondence with the conventional subgrouping. Tau-PET patterns also show differential A/T/N profiles. CONCLUSIONS The site and rate of atrophy are different across the tau-PET patterns. Heterogeneity should be treated as a continuous, not discrete, phenomenon for greater sensitivity. Pattern-specific A/T/N profiles highlight differential multimodal interactions underlying heterogeneity. Therefore, tracking multimodal interactions among biomarkers longitudinally, modeling disease heterogeneity as a continuous phenomenon, and examining heterogeneity across the AD continuum could offer avenues for precision medicine.
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Affiliation(s)
- Rosaleena Mohanty
- Division of Clinical Geriatrics, Center for Alzheimer Research. Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Blickagången 16, 14152, Huddinge, Sweden.
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research. Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Blickagången 16, 14152, Huddinge, Sweden
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research. Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Blickagången 16, 14152, Huddinge, Sweden
- Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research. Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Blickagången 16, 14152, Huddinge, Sweden
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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6
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Hoenig MC, Drzezga A. Clear-headed into old age: Resilience and resistance against brain aging-A PET imaging perspective. J Neurochem 2023; 164:325-345. [PMID: 35226362 DOI: 10.1111/jnc.15598] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 02/18/2022] [Accepted: 02/22/2022] [Indexed: 11/28/2022]
Abstract
With the advances in modern medicine and the adaptation towards healthier lifestyles, the average life expectancy has doubled since the 1930s, with individuals born in the millennium years now carrying an estimated life expectancy of around 100 years. And even though many individuals around the globe manage to age successfully, the prevalence of aging-associated neurodegenerative diseases such as sporadic Alzheimer's disease has never been as high as nowadays. The prevalence of Alzheimer's disease is anticipated to triple by 2050, increasing the societal and economic burden tremendously. Despite all efforts, there is still no available treatment defeating the accelerated aging process as seen in this disease. Yet, given the advances in neuroimaging techniques that are discussed in the current Review article, such as in positron emission tomography (PET) or magnetic resonance imaging (MRI), pivotal insights into the heterogenous effects of aging-associated processes and the contribution of distinct lifestyle and risk factors already have and are still being gathered. In particular, the concepts of resilience (i.e. coping with brain pathology) and resistance (i.e. avoiding brain pathology) have more recently been discussed as they relate to mechanisms that are associated with the prolongation and/or even stop of the progressive brain aging process. Better understanding of the underlying mechanisms of resilience and resistance may one day, hopefully, support the identification of defeating mechanism against accelerating aging.
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Affiliation(s)
- Merle C Hoenig
- Research Center Juelich, Institute for Neuroscience and Medicine II, Molecular Organization of the Brain, Juelich, Germany.,Department of Nuclear Medicine, Faculty of Medicine, University Hospital Cologne, Cologne, Germany
| | - Alexander Drzezga
- Research Center Juelich, Institute for Neuroscience and Medicine II, Molecular Organization of the Brain, Juelich, Germany.,Department of Nuclear Medicine, Faculty of Medicine, University Hospital Cologne, Cologne, Germany.,German Center for Neurodegenerative Diseases, Bonn/Cologne, Germany
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7
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Cheirdaris DG. Graph Theory-Based Approach in Brain Connectivity Modeling and Alzheimer's Disease Detection. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1424:49-58. [PMID: 37486478 DOI: 10.1007/978-3-031-31982-2_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
There is strong evidence that the pathological findings of Alzheimer's disease (AD), consisting of accumulated amyloid plaques and neurofibrillary tangles, could spread around the brain through synapses and neural connections of neighboring brain sections. Graph theory is a helpful tool in depicting the complex human brain divided into various regions of interest (ROIs) and the connections among them. Thus, applying graph theory-based models in the study of brain connectivity comes natural in the study of AD propagation mechanisms. Moreover, graph theory-based computational approaches have been lately applied in order to boost data-driven analysis, extract model measures and robustness-effectiveness indexes, and provide insights on casual interactions between regions of interest (ROI), as imposed by the models' architecture.
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Affiliation(s)
- Dionysios G Cheirdaris
- Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Corfu, Greece.
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8
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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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9
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Steidel K, Ruppert MC, Greuel A, Tahmasian M, Maier F, Hammes J, van Eimeren T, Timmermann L, Tittgemeyer M, Drzezga A, Pedrosa DJ, Eggers C. Longitudinal trimodal imaging of midbrain-associated network degeneration in Parkinson's disease. NPJ Parkinsons Dis 2022; 8:79. [PMID: 35732679 PMCID: PMC9218128 DOI: 10.1038/s41531-022-00341-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 05/24/2022] [Indexed: 11/20/2022] Open
Abstract
The prevailing network perspective of Parkinson’s disease (PD) emerges not least from the ascending neuropathology traceable in histological studies. However, whether longitudinal in vivo correlates of network degeneration in PD can be observed remains unresolved. Here, we applied a trimodal imaging protocol combining 18F-fluorodeoxyglucose (FDG)- and 18F-fluoro-L-Dopa- (FDOPA)-PET with resting-state functional MRI to assess longitudinal changes in midbrain metabolism, striatal dopamine depletion and striatocortical dysconnectivity in 17 well-characterized PD patients. Whole-brain (un)paired-t-tests with focus on midbrain or striatum were performed between visits and in relation to 14 healthy controls (HC) in PET modalities. Resulting clusters of FDOPA-PET comparisons provided volumes for seed-based functional connectivity (FC) analyses between visits and in relation to HC. FDG metabolism in the left midbrain decreased compared to baseline along with caudatal FDOPA-uptake. This caudate cluster exhibited a longitudinal FC decrease to sensorimotor and frontal areas. Compared to healthy subjects, dopamine-depleted putamina indicated stronger decline in striatocortical FC at follow-up with respect to baseline. Increasing nigrostriatal deficits and striatocortical decoupling were associated with deterioration in motor scores between visits in repeated-measures correlations. In summary, our results demonstrate the feasibility of in-vivo tracking of progressive network degeneration using a multimodal imaging approach. Specifically, our data suggest advancing striatal and widespread striatocortical dysfunction via an anterior-posterior gradient originating from a hypometabolic midbrain cluster within a well-characterized and only mild to moderately affected PD cohort during a relatively short period.
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Affiliation(s)
- Kenan Steidel
- Department of Neurology, University Hospital of Marburg, Marburg, Germany.
| | - Marina C Ruppert
- Department of Neurology, University Hospital of Marburg, Marburg, Germany.,Center for Mind, Brain and Behavior-CMBB, Universities Marburg and Gießen, Marburg, Germany
| | - Andrea Greuel
- Department of Neurology, University Hospital of Marburg, 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 University Hospital Cologne, Cologne, Germany
| | - Thilo van Eimeren
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Medical Faculty 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-Cologne, Germany
| | - Lars Timmermann
- Department of Neurology, University Hospital of Marburg, Marburg, Germany.,Center for Mind, Brain and Behavior-CMBB, Universities 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 University Hospital Cologne, Cologne, Germany.,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
| | - David J Pedrosa
- Department of Neurology, University Hospital of Marburg, Marburg, Germany.,Center for Mind, Brain and Behavior-CMBB, Universities Marburg and Gießen, Marburg, Germany
| | - Carsten Eggers
- Department of Neurology, University Hospital of Marburg, Marburg, Germany.,Department of Neurology, Knappschaftskrankenhaus Bottrop, Bottrop, Germany
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10
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Sun Z, Meikle S, Calamante F. CONN-NLM: A Novel CONNectome-Based Non-local Means Filter for PET-MRI Denoising. Front Neurosci 2022; 16:824431. [PMID: 35712456 PMCID: PMC9197079 DOI: 10.3389/fnins.2022.824431] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 04/22/2022] [Indexed: 11/13/2022] Open
Abstract
Background Advancements in hybrid positron emission tomography-magnetic resonance (PET-MR) systems allow for combining the advantages of each modality. Integrating information from MRI and PET can be valuable for diagnosing and treating neurological disorders. However, combining diffusion MRI (dMRI) and PET data, which provide highly complementary information, has rarely been exploited in image post-processing. dMRI has the ability to investigate the white matter pathways of the brain through fibre tractography, which enables comprehensive mapping of the brain connection networks (the "connectome"). Novel methods are required to combine information present in the connectome and PET to increase the full potential of PET-MRI. Methods We developed a CONNectome-based Non-Local Means (CONN-NLM) filter to exploit synergies between dMRI-derived structural connectivity and PET intensity information to denoise PET images. PET-MR data are parcelled into a number of regions based on a brain atlas, and the inter-regional structural connectivity is calculated based on dMRI fibre-tracking. The CONN-NLM filter is then implemented as a post-reconstruction filter by combining the nonlocal means filter and a connectivity-based cortical smoothing. The effect of this approach is to weight voxels with similar PET intensity and highly connected voxels higher when computing the weighted-average to perform more informative denoising. The proposed method was first evaluated using a novel computer phantom framework to simulate realistic hybrid PET-MR images with different lesion scenarios. CONN-NLM was further assessed with clinical dMRI and tau PET examples. Results The results showed that CONN-NLM has the capacity to improve the overall PET image quality by reducing noise while preserving lesion contrasts, and it outperformed a range of filters that did not use dMRI information. The simulations demonstrate that CONN-NLM can handle various lesion contrasts consistently, as well as lesions with different levels of inter-connectivity. Conclusion CONN-NLM has unique advantages of providing more informative and accurate PET smoothing by adding complementary structural connectivity information from dMRI, representing a new avenue to exploit synergies between MRI and PET.
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Affiliation(s)
- Zhuopin Sun
- School of Biomedical Engineering, The University of Sydney, Sydney, NSW, Australia
| | - Steven Meikle
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Fernando Calamante
- School of Biomedical Engineering, The University of Sydney, Sydney, NSW, Australia.,Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia.,Sydney Imaging, The University of Sydney, Sydney, NSW, Australia
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11
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Filippi M, Balestrino R, Basaia S, Agosta F. Neuroimaging in Glucocerebrosidase-Associated Parkinsonism: A Systematic Review. Mov Disord 2022; 37:1375-1393. [PMID: 35521899 PMCID: PMC9546404 DOI: 10.1002/mds.29047] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/14/2022] [Accepted: 04/18/2022] [Indexed: 12/11/2022] Open
Abstract
Background Mutations in the GBA gene cause Gaucher's disease (GD) and constitute the most frequent genetic risk factor for idiopathic Parkinson's disease (iPD). Nonmanifesting carriers of GBA mutations/variants (GBA‐NMC) constitute a potential PD preclinical population, whereas PD patients carrying some GBA mutations/variants (GBA‐PD) have a higher risk of a more aggressive disease course. Different neuroimaging techniques are emerging as potential biomarkers in PD and have been used to study GBA‐associated parkinsonism. Objective The aim is to critically review studies applying neuroimaging to GBA‐associated parkinsonism. Methods Literature search was performed using PubMed and EMBASE databases (last search February 7, 2022). Studies reporting neuroimaging findings in GBA‐PD, GD with and without parkinsonism, and GBA‐NMC were included. Results Thirty‐five studies were included. In longitudinal studies, GBA‐PD patients show a more aggressive disease than iPD at both structural magnetic resonance imaging and 123‐fluoropropylcarbomethoxyiodophenylnortropane single‐photon emission computed tomography. Fluorodeoxyglucose‐positron emission tomography and brain perfusion studies reported a greater cortical involvement in GBA‐PD compared to iPD. Overall, contrasting evidence is available regarding GBA‐NMC for imaging and clinical findings, although subtle differences have been reported compared with healthy controls with no mutations. Conclusions Although results must be interpreted with caution due to limitations of the studies, in line with previous clinical observations, GBA‐PD showed a more aggressive disease progression in neuroimaging longitudinal studies compared to iPD. Cognitive impairment, a “clinical signature” of GBA‐PD, seems to find its neuroimaging correlate in the greater cortical burden displayed by these patients as compared to iPD. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
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Affiliation(s)
- Massimo Filippi
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Roberta Balestrino
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Agosta
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
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12
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de Flores R, Das SR, Xie L, Wisse LEM, Lyu X, Shah P, Yushkevich PA, Wolk DA. Medial Temporal Lobe Networks in Alzheimer's Disease: Structural and Molecular Vulnerabilities. J Neurosci 2022; 42:2131-2141. [PMID: 35086906 PMCID: PMC8916768 DOI: 10.1523/jneurosci.0949-21.2021] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 11/30/2021] [Accepted: 12/04/2021] [Indexed: 11/21/2022] Open
Abstract
The medial temporal lobe (MTL) is connected to the rest of the brain through two main networks: the anterior-temporal (AT) and the posterior-medial (PM) systems. Given the crucial role of the MTL and networks in the physiopathology of Alzheimer's disease (AD), the present study aimed at (1) investigating whether MTL atrophy propagates specifically within the AT and PM networks, and (2) evaluating the vulnerability of these networks to AD proteinopathies. To do that, we used neuroimaging data acquired in human male and female in three distinct cohorts: (1) resting-state functional MRI (rs-fMRI) from the aging brain cohort (ABC) to define the AT and PM networks (n = 68); (2) longitudinal structural MRI from Alzheimer's disease neuroimaging initiative (ADNI)GO/2 to highlight structural covariance patterns (n = 349); and (3) positron emission tomography (PET) data from ADNI3 to evaluate the networks' vulnerability to amyloid and tau (n = 186). Our results suggest that the atrophy of distinct MTL subregions propagates within the AT and PM networks in a dissociable manner. Brodmann area (BA)35 structurally covaried within the AT network while the parahippocampal cortex (PHC) covaried within the PM network. In addition, these networks are differentially associated with relative tau and amyloid burden, with higher tau levels in AT than in PM and higher amyloid levels in PM than in AT. Our results also suggest differences in the relative burden of tau species. The current results provide further support for the notion that two distinct MTL networks display differential alterations in the context of AD. These findings have important implications for disease spread and the cognitive manifestations of AD.SIGNIFICANCE STATEMENT The current study provides further support for the notion that two distinct medial temporal lobe (MTL) networks, i.e., anterior-temporal (AT) and the posterior-medial (PM), display differential alterations in the context of Alzheimer's disease (AD). Importantly, neurodegeneration appears to occur within these networks in a dissociable manner marked by their covariance patterns. In addition, the AT and PM networks are also differentially associated with relative tau and amyloid burden, and perhaps differences in the relative burden of tau species [e.g., neurofibriliary tangles (NFTs) vs tau in neuritic plaques]. These findings, in the context of a growing literature consistent with the present results, have important implications for disease spread and the cognitive manifestations of AD in light of the differential cognitive processes ascribed to them.
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Affiliation(s)
- Robin de Flores
- Department of Neurology, University of Pennsylvania, Philadelphia 19104, Pennsylvania
- Université de Caen Normandie, Institut National de la Santé et de la Recherche Médicale Unité Mixte de Recherche Scientifique (UMRS) Unité 1237, Caen 14000, France
| | - Sandhitsu R Das
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - Long Xie
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia 19104, Pennsylvania
- Department of Radiology, University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - Laura E M Wisse
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia 19104, Pennsylvania
- Department of Diagnostic Radiology, Lund University, Lund 22185, Sweden
| | - Xueying Lyu
- Department of Bioengineering, University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - Preya Shah
- Department of Bioengineering, University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - Paul A Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia 19104, Pennsylvania
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13
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Basaia S, Agosta F, Diez I, Bueichekú E, d'Oleire Uquillas F, Delgado-Alvarado M, Caballero-Gaudes C, Rodriguez-Oroz M, Stojkovic T, Kostic VS, Filippi M, Sepulcre J. Neurogenetic traits outline vulnerability to cortical disruption in Parkinson's disease. Neuroimage Clin 2022; 33:102941. [PMID: 35091253 PMCID: PMC8800137 DOI: 10.1016/j.nicl.2022.102941] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 12/03/2021] [Accepted: 01/10/2022] [Indexed: 01/18/2023]
Abstract
The genetic traits that underlie vulnerability to neuronal damage across specific brain circuits in Parkinson's disease (PD) remain to be elucidated. In this study, we characterized the brain topological intersection between propagating connectivity networks in controls and PD participants and gene expression patterns across the human cortex - such as the SNCA gene. We observed that brain connectivity originated from PD-related pathology epicenters in the brainstem recapitulated the anatomical distribution of alpha-synuclein histopathology in postmortem data. We also discovered that the gene set most related to cortical propagation patterns of PD-related pathology was primarily involved in microtubule cellular components. Thus, this study sheds light on new avenues for enhancing detection of PD neuronal vulnerability via an evaluation of in vivo connectivity trajectories across the human brain and successful integration of neuroimaging-genetic strategies.
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Affiliation(s)
- Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - Ibai Diez
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Elisenda Bueichekú
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Federico d'Oleire Uquillas
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Manuel Delgado-Alvarado
- Neurology Department, Sierrallana Hospital, Torrelavega, Spain; IDIVAL, Valdecilla Biomedical Research Institute, Santander, Spain; Biomedical Research Networking Center for Mental Health (CIBERSAM), Madrid, Spain
| | | | - MariCruz Rodriguez-Oroz
- Neurology Department, Clínica Universidad de Navarra, Neuroscience Unit, CIMA Universidad de Navarra, Spain
| | - Tanja Stojkovic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Vladimir S Kostic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - Jorge Sepulcre
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
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14
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Weller A, Bischof GN, Schlüter P, Richter N, Dronse J, Onur O, Neumaier B, Kukolja J, Langen KJ, Fink G, Kunoth A, Shao Y, van Eimeren T, Drzezga A. Finding New Communities: A Principle of Neuronal Network Reorganization in Alzheimer's Disease. Brain Connect 2021; 11:225-238. [PMID: 33356820 DOI: 10.1089/brain.2020.0889] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background: Graph-theoretical analyses have been previously used to investigate changes in the functional connectome in patients with Alzheimer's disease (AD). However, these analyses generally assume static organizational principles, thereby neglecting a fundamental reconfiguration of functional connections in the face of neurodegeneration. Methods: Here, we focus on differences in the community structure of the functional connectome in young and old individuals and patients with AD. Patients with AD, moreover, underwent molecular imaging positron emission tomography by using [18F]AV1451 to measure tau burden, a major hallmark of AD. Results: Although the overall organizational principles of the community structure of the human functional connectome were preserved even in advanced healthy aging, they were considerably changed in AD. We discovered that the communities in AD are re-organized, with nodes changing their allegiance to communities, thus resulting in an overall less efficient re-organized community structure. We further discovered that nodes with a tendency to leave the communities displayed a relatively higher tau pathology burden. Discussion: Together, this study suggests that local tau pathology in AD is associated to fundamental changes in basic organizational principles of the human connectome. Our results shed new light on previous findings obtained by using the graph theory in AD and imply a general principle of the brain in response to neurodegeneration.
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Affiliation(s)
- Anna Weller
- Division of Mathematics, Department of Mathematics and Computer Science, University of Cologne, Cologne, Germany
| | - Gérard N Bischof
- Department of Nuclear Medicine, Multimodal Neuroimaging Group, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany.,Research Center Juelich, Institute of Neuroscience and Medicine (INM-3), Cognitive Neuroscience, Juelich, Germany
| | - Philipp Schlüter
- Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
| | - Nils Richter
- Research Center Juelich, Institute of Neuroscience and Medicine (INM-3), Cognitive Neuroscience, Juelich, Germany.,Department of Neurology, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany
| | - Julian Dronse
- Department of Neurology, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany
| | - Oezguer Onur
- Research Center Juelich, Institute of Neuroscience and Medicine (INM-3), Cognitive Neuroscience, Juelich, Germany.,Department of Neurology, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany
| | - Bernd Neumaier
- Research Center Juelich, Institute of Neuroscience and Medicine (INM-3), Radiochemistry, Juelich, Germany
| | - Juraj Kukolja
- Department of Neurology, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany.,Department of Neurology and clinical Neurophysiology, Helios University Hospital Wuppertal, Wuppertal, Germany.,Faculty of Health, Witten/Herdecke University, Witten, Germany
| | - Karl-Josef Langen
- Research Center Juelich, Institute of Neuroscience and Medicine (INM-4), Medical Imaging Physics, Juelich, Germany
| | - Gereon Fink
- Research Center Juelich, Institute of Neuroscience and Medicine (INM-3), Cognitive Neuroscience, Juelich, Germany.,Department of Neurology, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany
| | - Angela Kunoth
- Division of Mathematics, Department of Mathematics and Computer Science, University of Cologne, Cologne, Germany
| | - Yaping Shao
- Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
| | - Thilo van Eimeren
- Department of Nuclear Medicine, Multimodal Neuroimaging Group, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany.,Department of Neurology, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Alexander Drzezga
- Department of Nuclear Medicine, Multimodal Neuroimaging Group, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Research Center Juelich, Institute of Neuroscience and Medicine (INM-2), Molecular Organization of the Brain, Juelich, Germany
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15
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Kocagoncu E, Quinn A, Firouzian A, Cooper E, Greve A, Gunn R, Green G, Woolrich MW, Henson RN, Lovestone S, Rowe JB. Tau pathology in early Alzheimer's disease is linked to selective disruptions in neurophysiological network dynamics. Neurobiol Aging 2020; 92:141-152. [PMID: 32280029 PMCID: PMC7269692 DOI: 10.1016/j.neurobiolaging.2020.03.009] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 02/03/2020] [Accepted: 03/10/2020] [Indexed: 11/29/2022]
Abstract
Understanding the role of Tau protein aggregation in the pathogenesis of Alzheimer's disease is critical for the development of new Tau-based therapeutic strategies to slow or prevent dementia. We tested the hypothesis that Tau pathology is associated with functional organization of widespread neurophysiological networks. We used electro-magnetoencephalography with [18F]AV-1451 PET scanning to quantify Tau-dependent network changes. Using a graph theoretical approach to brain connectivity, we quantified nodal measures of functional segregation, centrality, and the efficiency of information transfer and tested them against levels of [18F]AV-1451. Higher Tau burden in early Alzheimer's disease was associated with a shift away from the optimal small-world organization and a more fragmented network in the beta and gamma bands, whereby parieto-occipital areas were disconnected from the anterior parts of the network. Similarly, higher Tau burden was associated with decreases in both local and global efficiency, especially in the gamma band. The results support the translational development of neurophysiological "signatures" of Alzheimer's disease, to understand disease mechanisms in humans and facilitate experimental medicine studies.
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Affiliation(s)
- Ece Kocagoncu
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Andrew Quinn
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK,Department of Psychiatry, University of Oxford, Oxford, UK
| | | | - Elisa Cooper
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Andrea Greve
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Roger Gunn
- Invicro LLC, London, UK,Department of Medicine, Imperial College London, London, UK,Department of Engineering Science, University of Oxford, Oxford, UK
| | - Gary Green
- Department of Psychology, University of York, York, UK
| | - Mark W. Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK,Department of Psychiatry, University of Oxford, Oxford, UK
| | - Richard N. Henson
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK,Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | | | - James B. Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
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16
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Ruppert MC, Greuel A, Tahmasian M, Schwartz F, Stürmer S, Maier F, Hammes J, Tittgemeyer M, Timmermann L, van Eimeren T, Drzezga A, Eggers C. Network degeneration in Parkinson’s disease: multimodal imaging of nigro-striato-cortical dysfunction. Brain 2020; 143:944-959. [DOI: 10.1093/brain/awaa019] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 11/21/2019] [Accepted: 12/11/2019] [Indexed: 11/14/2022] Open
Abstract
Abstract
The spreading hypothesis of neurodegeneration assumes an expansion of neural pathologies along existing neural pathways. Multimodal neuroimaging studies have demonstrated distinct topographic patterns of cerebral pathologies in neurodegeneration. For Parkinson’s disease the hypothesis so far rests largely on histopathological evidence of α-synuclein spreading in a characteristic pattern and progressive nigrostriatal dopamine depletion. Functional consequences of nigrostriatal dysfunction on cortical activity remain to be elucidated. Our goal was to investigate multimodal imaging correlates of degenerative processes in Parkinson’s disease by assessing dopamine depletion and its potential effect on striatocortical connectivity networks and cortical metabolism in relation to parkinsonian symptoms. We combined 18F-DOPA-PET, 18F-fluorodeoxyglucose (FDG)-PET and resting state functional MRI to multimodally characterize network alterations in Parkinson’s disease. Forty-two patients with mild-to-moderate stage Parkinson’s disease and 14 age-matched healthy control subjects underwent a multimodal imaging protocol and comprehensive clinical examination. A voxel-wise group comparison of 18F-DOPA uptake identified the exact location and extent of putaminal dopamine depletion in patients. Resulting clusters were defined as seeds for a seed-to-voxel functional connectivity analysis. 18F-FDG metabolism was compared between groups at a whole-brain level and uptake values were extracted from regions with reduced putaminal connectivity. To unravel associations between dopaminergic activity, striatocortical connectivity, glucose metabolism and symptom severity, correlations between normalized uptake values, seed-to-cluster β-values and clinical parameters were tested while controlling for age and dopaminergic medication. Aside from cortical hypometabolism, 18F-FDG-PET data for the first time revealed a hypometabolic midbrain cluster in patients with Parkinson’s disease that comprised caudal parts of the bilateral substantia nigra pars compacta. Putaminal dopamine synthesis capacity was significantly reduced in the bilateral posterior putamen and correlated with ipsilateral nigral 18F-FDG uptake. Resting state functional MRI data indicated significantly reduced functional connectivity between the dopamine depleted putaminal seed and cortical areas primarily belonging to the sensorimotor network in patients with Parkinson’s disease. In the inferior parietal cortex, hypoconnectivity in patients was significantly correlated with lower metabolism (left P = 0.021, right P = 0.018). Of note, unilateral network alterations quantified with different modalities corresponded with contralateral motor impairments. In conclusion, our results support the hypothesis that degeneration of nigrostriatal fibres functionally impairs distinct striatocortical connections, disturbing the efficient interplay between motor processing areas and impairing motor control in patients with Parkinson’s disease. The present study is the first to reveal trimodal evidence for network-dependent degeneration in Parkinson’s disease by outlining the impact of functional nigrostriatal pathway impairment on striatocortical functional connectivity networks and cortical metabolism.
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Affiliation(s)
- Marina C Ruppert
- Department of Neurology, University Hospital of Marburg, Germany
- Center for Mind, Brain and Behavior - CMBB, Universities Marburg and Gießen, Germany
| | - Andrea Greuel
- Department of Neurology, University Hospital of Marburg, Germany
| | - Masoud Tahmasian
- Institue of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Frank Schwartz
- Department of Neurology, Hospital of the Brothers of Mercy, Trier, Germany
| | - Sophie Stürmer
- Max Planck Institute for Metabolism Research, Cologne, Germany
- Department of Neurology, Medical Faculty and University Hospital Cologne, University Hospital Cologne, 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
| | - 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, University Hospital of Marburg, Germany
- Center for Mind, Brain and Behavior - CMBB, Universities Marburg and Gießen, Germany
| | - Thilo van Eimeren
- Department of Neurology, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Germany
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Germany
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, Germany
- German Center for Neurodegenerative Diseases (DZNE), 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), Germany
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-2), Research Center Jülich, 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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17
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Pereira JB, Harrison TM, La Joie R, Baker SL, Jagust WJ. Spatial patterns of tau deposition are associated with amyloid, ApoE, sex, and cognitive decline in older adults. Eur J Nucl Med Mol Imaging 2020; 47:2155-2164. [PMID: 31915896 PMCID: PMC7338820 DOI: 10.1007/s00259-019-04669-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2019] [Accepted: 12/23/2019] [Indexed: 12/22/2022]
Abstract
Purpose The abnormal deposition of tau begins before the onset of clinical symptoms and seems to target specific brain networks. The aim of this study is to identify the spatial patterns of tau deposition in cognitively normal older adults and assess whether they are related to amyloid-β (Aβ), APOE, sex, and longitudinal cognitive decline. Methods We included 114 older adults with cross-sectional flortaucipir (FTP) and Pittsburgh Compound-B PET in addition to longitudinal cognitive testing. A voxel-wise independent component analysis was applied to FTP images to identify the spatial patterns of tau deposition. We then assessed whether tau within these patterns differed by Aβ status, APOE genotype, and sex. Linear mixed effects models were built to test whether tau in each component predicted cognitive decline. Finally, we ordered the spatial components based on the frequency of high tau deposition to model tau spread. Results We found 10 biologically plausible tau patterns in the whole sample. There was greater tau in medial temporal, occipital, and orbitofrontal components in Aβ-positive compared with Aβ-negative individuals; in the parahippocampal component in ε3ε3 compared with ε2ε3 carriers; and in temporo-parietal and anterior frontal components in women compared with men. Higher tau in temporal and frontal components predicted longitudinal cognitive decline in memory and executive functions, respectively. Tau deposition was most frequently observed in medial temporal and ventral cortical areas, followed by lateral and primary areas. Conclusions These findings suggest that the spatial patterns of tau in asymptomatic individuals are clinically meaningful and are associated with Aβ, APOE ε2ε3, sex and cognitive decline. These patterns could be used to predict the regional spread of tau and perform in vivo tau staging in older adults. Electronic supplementary material The online version of this article (10.1007/s00259-019-04669-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Joana B Pereira
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden. .,Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.
| | - Theresa M Harrison
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, University of California, Oakland, CA, USA
| | - Suzanne L Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA.,Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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18
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Abstract
Parkinson's disease (PD) is a chronic, debilitating neurodegenerative disorder characterized clinically by a variety of progressive motor and nonmotor symptoms. Currently, there is a dearth of diagnostic tools available to predict, diagnose or mitigate disease risk or progression, leading to a challenging dilemma within the healthcare management system. The search for a reliable biomarker for PD that reflects underlying pathology is a high priority in PD research. Currently, there is no reliable single biomarker predictive of risk for motor and cognitive decline, and there have been few longitudinal studies of temporal progression. A combination of multiple biomarkers might facilitate earlier diagnosis and more accurate prognosis in PD. In this review, we focus on the recent developments of serial biomarkers for PD from a variety of clinical, biochemical, genetic and neuroimaging perspectives.
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Affiliation(s)
- Anastasia Bougea
- Neurochemistry Laboratory, 1st Department of Neurology and Movement Disorders, Medical School, Aeginition Hospital, National and Kapodistrian University of Athens, Athens, Greece; Neuroscience Laboratory, Center for Basic Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
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19
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Jiang JB, Cao Y, An NY, Yang Q, Cui LB. Magnetic Resonance Imaging-Based Connectomics in First-Episode Schizophrenia: From Preclinical Study to Clinical Translation. Front Psychiatry 2020; 11:565056. [PMID: 33061921 PMCID: PMC7518111 DOI: 10.3389/fpsyt.2020.565056] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 08/24/2020] [Indexed: 01/11/2023] Open
Affiliation(s)
- Jin-Bo Jiang
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Yang Cao
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Ning-Yu An
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Qun Yang
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Long-Biao Cui
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China.,Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
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20
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van Eimeren T, Drzezga A. From molecules to system failure: translational frontiers of multimodal imaging in neurodegenerative diseases. Eur J Nucl Med Mol Imaging 2019; 46:2816-2818. [PMID: 31667539 DOI: 10.1007/s00259-019-04562-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2019] [Accepted: 09/27/2019] [Indexed: 11/26/2022]
Affiliation(s)
- Thilo van Eimeren
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, University of Cologne, Cologne, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany.
- Department of Neurology, University of Cologne, Cologne, Germany.
| | - Alexander Drzezga
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, University of Cologne, Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany
- Molecular Organization of the Brain, Institute of Neuroscience and Medicine (INM-2), Research Center Jülich, Jülich, Germany
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