Altered brain structural topological properties in Parkinson's disease with levodopa-induced dyskinesias

Wang, Lina; Wang, Min; Si, Qianqian; Yuan, Yongsheng; Ma, Kewei; Gan, Caiting; Zhang, Kezhong

doi:10.1016/j.parkreldis.2019.09.022

Cited by 12 publications

(19 citation statements)

References 29 publications

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“…This finding suggest that overall information flow is defective in PD. Similar results have been observed in network topology analysis based on MRI data [ 35 ] and correlate with cognitive [ 36 ] and motor symptoms [ 37 ]. These observations confirm the reliability of GC computation based on EEG source analysis reconstruction; they may pave the way for a more widespread use of EEG data, which are part of clinical practice and low-cost, for this kind of analysis.…”

Section: Discussionsupporting

confidence: 85%

Reduced Effective Connectivity in the Motor Cortex in Parkinson’s Disease

et al. 2021

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Fast rhythms excess is a hallmark of Parkinson’s Disease (PD). To implement innovative, non-pharmacological, neurostimulation interventions to restore cortical-cortical interactions, we need to understand the neurophysiological mechanisms underlying these phenomena. Here, we investigated effective connectivity on source-level resting-state electroencephalography (EEG) signals in 15 PD participants and 10 healthy controls. First, we fitted multivariate auto-regressive models to the EEG source waveforms. Second, we estimated causal connections using Granger Causality, which provide information on connections’ strength and directionality. Lastly, we sought significant differences connectivity patterns between the two populations characterizing the network graph features—i.e., global efficiency and node strength. Causal brain networks in PD show overall poorer and weaker connections compared to controls quantified as a reduction of global efficiency. Motor areas appear almost isolated, with a strongly impoverished information flow particularly from parietal and occipital cortices. This striking isolation of motor areas may reflect an impaired sensory-motor integration in PD. The identification of defective nodes/edges in PD network may be a biomarker of disease and a potential target for future interventional trials.

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Section: Discussionsupporting

confidence: 85%

Reduced Effective Connectivity in the Motor Cortex in Parkinson’s Disease

et al. 2021

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“…pathogenic characteristic of PD prior to neuronal death [11], DTI analysis of WM may play a role in uncovering the early pathological process in PD. Along with predisposing clinical factors for the development of LID, imaging studies have found LID-relevant structural changes, such as a thickened inferior frontal gyrus [10] and an over-optimized fronto-striato-thalamic structural network [45]. Since most previous imaging studies were conducted after the onset of LID, it is uncertain whether these changes may reflect the underlying predisposing conditions leading to the development of LID.…”

Section: Introductionmentioning

confidence: 99%

White matter connectivity networks predict levodopa-induced dyskinesia in Parkinson’s disease

et al. 2021

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Background Although levodopa-induced dyskinesia-relevant white matter change has been evaluated, it is uncertain whether these changes may reflect the underlying predisposing conditions leading to the development of levodopa-induced dyskinesia. Objective To elucidate the role of white matter connectivity networks in the development of levodopa-induced dyskinesia in drug-naïve Parkinson's disease. Methods We recruited 30 patients who developed levodopa-induced dyskinesia within 5 years from MRI acquisition (vulnerable-group), 47 patients who had not developed levodopa-induced dyskinesia within 5 years (resistant-group), and 28 controls. We performed comparative analyses of whole-brain white matter integrity and connectivity using tract-based spatial and network-and degree-based statistics. We evaluated the predictability of levodopa-induced dyskinesia development and relationship with its latency, using the average connectivity strength as a predictor in Cox-and linear-regression, respectively. Results Mean-diffusivity was lower mainly at the left frontal region in the vulnerable-group compared to the resistant-group. Network-based statistics identified a subnetwork consisting of the bilateral fronto-striato-pallido-thalamic and lateral parietal regions (subnetwork A) and degree-based statistics identified four subnetworks (hub-subnetwork) consisting of edges centered on the left superior frontal gyrus, left putamen, left insular, or left precentral gyrus, where the vulnerable-group had stronger connectivity compared to the resistant-group. Stronger connectivity within the subnetwork A and hub-subnetwork centered on the left superior frontal gyrus was a predictor of levodopa-induced dyskinesia development independent of known risk factors and had an inverse relationship with its latency. Conclusions Our data suggest that white matter connectivity subnetworks within corticostriatal regions play a pivotal role in the development of levodopa-induced dyskinesia.

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“…Numerous studies have shown the importance of the cortico-striatal pathway in LID pathogenesis. Imaging studies have shown an association between the prefrontal cortex (including the inferior frontal cortex) and/or the SMA, which are involved in motor programming and inhibition, and LID using photon emission computed tomography, functional MRI, and voxel-based morphometry [6][7][8]. Furthermore, connectivity between the frontal lobe and striatum during LID was found in a local field potential study [36] and functional MRI studies [7,8].…”

Section: Reduced Effects In the Ifof Uf And Ec May Be Important Features Of Lid Pathophysiologymentioning

confidence: 97%

“…Imaging studies have shown an association between the prefrontal cortex (including the inferior frontal cortex) and/or the SMA, which are involved in motor programming and inhibition, and LID using photon emission computed tomography, functional MRI, and voxel-based morphometry [6][7][8]. Furthermore, connectivity between the frontal lobe and striatum during LID was found in a local field potential study [36] and functional MRI studies [7,8]. In the present study, we found reduced effects in the EC, IFOF, and UF in PD-LID patients and axonal loss or reduced neurite density in PD-nLID patients, which also supports the importance of cortico-striatal projections in LID pathogenesis.…”

Section: Reduced Effects In the Ifof Uf And Ec May Be Important Features Of Lid Pathophysiologymentioning

confidence: 99%

“…The pathogenetic mechanisms of LID might be related to synaptic plasticity [4] and are greater in younger subjects [5]. Previous microstructural studies have reported striatal dendritic or dendritic spine alterations and electrophysiological changes related to the cortico-striatal-thalamic loop in LID models [4], and imaging studies have reported changes associated with LID in the frontal cortex and striatum [6][7][8]. Given these changes, white matter structures serving as pathways connecting the cortex and basal ganglia may also be involved in LID pathophysiology.…”

Section: Introductionmentioning

confidence: 99%

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White matter alterations in Parkinson's disease with levodopa-induced dyskinesia

Ogawa

Hatano

Kamagata

et al. 2021

Parkinsonism & Related Disorders

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Levodopa-induced dyskinesia is a complication of levodopa therapy and negatively impacts the quality of life of patients. We aimed to elucidate white matter alterations in Parkinson's disease with levodopainduced dyskinesia using advanced diffusion magnetic resonance imaging techniques. Methods: The enrolled subjects included 26 clinically confirmed Parkinson's disease patients without levodopainduced dyskinesia, 25 Parkinson's disease patients with levodopa-induced dyskinesia, and 23 healthy controls. Subjects were imaged using a 3-T magnetic resonance scanner. Diffusion tensor imaging, diffusion kurtosis imaging, and neurite orientation dispersion and density imaging findings were compared between groups with a group-wise whole brain approach and a region-of-interest analysis for each white matter tract. Additionally, logistic regression analysis was used to calculate odds ratios for levodopa-induced dyskinesia. Results: Group-wise tract-based spatial statistical analysis revealed significant white matter differences in isotropic diffusion, complexity, or heterogeneity, and neurite density between healthy controls and Parkinson's disease patients without levodopa-induced dyskinesia and between patients with and without levodopa-induced dyskinesia. Region-of-interest analysis revealed similar alterations using a group-wise whole-brain approach in the external capsule, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus. These tracts had an odds ratio of approximately 2.3 for the presence of levodopa-induced dyskinesia. Conclusions: Our findings suggest that Parkinson's disease with levodopa-induced dyskinesia produces less white matter microstructural disruption, especially in temporal lobe fibers, than Parkinson's disease without levodopainduced dyskinesia. These fibers has a more than 2-fold odds ratio for the presence of levodopa-induced dyskinesia and might be associated with the pathogenesis of the sequela.

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Altered brain structural topological properties in Parkinson's disease with levodopa-induced dyskinesias

Cited by 12 publications

References 29 publications

Reduced Effective Connectivity in the Motor Cortex in Parkinson’s Disease

Reduced Effective Connectivity in the Motor Cortex in Parkinson’s Disease

White matter connectivity networks predict levodopa-induced dyskinesia in Parkinson’s disease

White matter alterations in Parkinson's disease with levodopa-induced dyskinesia

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