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Eur J Nucl Med Mol Imaging. 2019 Jul 11. doi: 10.1007/s00259-019-04394-5. [Epub ahead of print]

Connectomics and molecular imaging in neurodegeneration.

Author information

1
Multimodal Neuroimaging Group, Department of Nuclear Medicine, University Hospital Cologne, Building 60, Kerpener Str. 62, 50937, Cologne, Germany. gerard.bischof@uk-koeln.de.
2
Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany. gerard.bischof@uk-koeln.de.
3
Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany.
4
German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.
5
Multimodal Neuroimaging Group, Department of Nuclear Medicine, University Hospital Cologne, Building 60, Kerpener Str. 62, 50937, Cologne, Germany.
6
Molecular Organization of the Brain, Institute of Neuroscience and Medicine (INM-2), Research Center Jülich, Jülich, Germany.
7
Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
8
Medical Research Council Cognition and Brain Sciences Unit, Cambridge, UK.
9
Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada.
10
Division of Brain, Imaging and Behaviour - Systems Neuroscience, University of Toronto, Toronto, Ontario, Canada.
11
Krembil Research Institute, UHN, University of Toronto, Toronto, Ontario, Canada.
12
Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.
13
Morton and Gloria Shulman Movement Disorder Unit & E.J. Safra Parkinson Disease Program, Neurology Division, Department of Medicine, Toronto Western Hospital, UHN, University of Toronto, Toronto, Ontario, Canada.
14
German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
15
Department of Neurology, University Hospital Cologne, Cologne, Germany.

Abstract

Our understanding on human neurodegenerative disease was previously limited to clinical data and inferences about the underlying pathology based on histopathological examination. Animal models and in vitro experiments have provided evidence for a cell-autonomous and a non-cell-autonomous mechanism for the accumulation of neuropathology. Combining modern neuroimaging tools to identify distinct neural networks (connectomics) with target-specific positron emission tomography (PET) tracers is an emerging and vibrant field of research with the potential to examine the contributions of cell-autonomous and non-cell-autonomous mechanisms to the spread of pathology. The evidence provided here suggests that both cell-autonomous and non-cell-autonomous processes relate to the observed in vivo characteristics of protein pathology and neurodegeneration across the disease spectrum. We propose a synergistic model of cell-autonomous and non-cell-autonomous accounts that integrates the most critical factors (i.e., protein strain, susceptible cell feature and connectome) contributing to the development of neuronal dysfunction and in turn produces the observed clinical phenotypes. We believe that a timely and longitudinal pursuit of such research programs will greatly advance our understanding of the complex mechanisms driving human neurodegenerative diseases.

KEYWORDS:

Functional Connectivity; Multimodal Imaging; Pathophysiological Spreading; Proteinpathology; Selective Vulnerability

PMID:
31292699
DOI:
10.1007/s00259-019-04394-5

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