Multimodal view on resting-state brain activity in Parkinson’s disease: examining the relation between functional resting-state networks and metabolic network activity

Research focusing on the pathophysiology of neurodegenerative disorders has undergone a fundamental shift towards a network perspective in the last decades. Besides regional aggregation of misfolded proteins and changes in cellular metabolism, accompanying changes of synaptic activity evolve and evo...

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Bibliographic Details
Main Author: Ruppert-Junck, Marina Christine
Contributors: Pedrosa, David (PD Dr.) (Thesis advisor)
Format: Doctoral Thesis
Published: Philipps-Universität Marburg 2023
Online Access:PDF Full Text
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Summary:Research focusing on the pathophysiology of neurodegenerative disorders has undergone a fundamental shift towards a network perspective in the last decades. Besides regional aggregation of misfolded proteins and changes in cellular metabolism, accompanying changes of synaptic activity evolve and evoke dysregulation within neural circuits including remote brain regions. Modern theories of neurodegeneration propose a stereotypic pattern of these cerebral pathologies, which partly are in vivo accessible by multimodal neuroimaging techniques. The most often used indirect measurement of functional network integrity is resting-state functional magnetic resonance imaging, which depends on a complex interplay of hemodynamics, blood volume, and blood flow. Less is known about a potential metabolic component underlying resting-state networks in healthy brains and changes thereof in neurodegeneration and the influence of different transmitter systems. The current work therefore sought to investigate the association between functional resting-state networks and metabolic network activity and focused on metabolic consequences of nigrostriatal and striatocortical dysfunction in Parkinson’s disease. In the current work, a multimodal data set of the TP10 KFO219 cohort was analyzed regarding 1) the impact of nigrostriatal dopamine depletion on resting-state networks and 2) the relation between changes in functional connectivity and metabolic network activity. The first study addressed the subset of the KFO219 TP10 cohort who completed the trimodal imaging protocol (42 patients vs. 14 controls). Dopamine deficiency in Parkinson’s patients was examined by voxel-wise comparison of 6-[18F]fluoro-L-Dopa positron emission tomography scans. Resulting clusters served as seeds for restingstate functional connectivity maps that were compared between both groups by voxelwise t-tests. Metabolic activity was extracted from 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography scans for respective cortical clusters with striatocortical dysconnectivity and the relation to functional connectivity values was analyzed. In a separate study, functional and metabolic resting-state networks were obtained by performing spatial independent component analyses in a subset of the same cohort who underwent 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography and functional magnetic resonance imaging (56 vs 16) and completed neuropsychological testing. Multimodally obtained regions of interest in the default mode network were defined and metabolic activity as well as metabolic connectivity compared to functional connectivity differences between patients without or with mild cognitive impairment and healthy controls. Moreover, a third study was initiated in the context of the present work with the aim of establishing a dynamic 2-[18F]fluoro-2-deoxy-D-glucose positronemission tomography acquisition with a constant infusion protocol for examining interregional metabolic connectivity on single subject level and enable comparable analysis of hemodynamic and metabolic fluctuations in Parkinson’s disease. In the first study, a significant association between striatocortical functional connectivity changes of the data-driven defined dopamine depleted posterior putamen and metabolic activity of the cortical target area in the inferior parietal cortex was found in Parkinson’s disease. Interestingly, striatocortical connectivity of the inferior parietal cortex was associated with motor and cognitive impairment. In a second study, the multivariate approach revealed a moderate spatial convergence for the posterior default mode network in functional and metabolic data. For all multimodally obtained default mode network regions, a significant trend towards an increment of metabolic deficits from healthy controls via unimpaired patients to patients with mild cognitive impairment was identified. In addition, posterior default mode network regions with the strongest metabolic deficits and gradual decline in comparison to controls, also showed the strongest increases in both metabolic and functional connectivity compared to controls. The verification of the applicability of a constant infusion dynamic 2-[18F]fluoro-2-deoxy- D-glucose positron emission tomography protocol in Parkinson’s disease patients was started in a self-initiated study, which finished the acquisition phase with 10 participants per group by the time the current work was submitted. Together the first two studies highlight the added value of multimodal imaging in investigating human brain function and the pathophysiology of neurodegenerative disorders, in particular their great potential for identifying links between individual pathologies. The second study partly continued, and answered questions raised in response to the first study, which hinted at an involvement of default mode network regions in cognitive symptoms of Parkinson’s disease and a relation between functional network degeneration and metabolic activity. The current work shows exemplary the complementarity of both measures of brain network activity and their individual significance for cognitive symptoms in Parkinson’s disease. The presented work highlights how multimodal resting-state studies can provide new insights into the (patho-)physiological network organization of brain activity by confirming insights obtained by one modality and deepen our understanding of disease processes. The selfinitiated study further laid the ground for multimodal characterization of metabolic and hemodynamic network changes on single-subject level and the evaluation of dynamic positron emission tomography-based connectivity as metabolic network marker for Parkinson’s disease.