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Jiang L, Zhuo J, Furman A, Fishman PS, Gullapalli R. Cerebellar functional connectivity change is associated with motor and neuropsychological function in early stage drug-naïve patients with Parkinson's disease. Front Neurosci 2023; 17:1113889. [PMID: 37425003 PMCID: PMC10324581 DOI: 10.3389/fnins.2023.1113889] [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: 12/01/2022] [Accepted: 06/05/2023] [Indexed: 07/11/2023] Open
Abstract
Introduction Parkinson's Disease (PD) is a progressive neurodegenerative disorder affecting both motor and cognitive function. Previous neuroimaging studies have reported altered functional connectivity (FC) in distributed functional networks. However, most neuroimaging studies focused on patients at an advanced stage and with antiparkinsonian medication. This study aims to conduct a cross-sectional study on cerebellar FC changes in early-stage drug-naïve PD patients and its association with motor and cognitive function. Methods Twenty-nine early-stage drug-naïve PD patients and 20 healthy controls (HCs) with resting-state fMRI data and motor UPDRS and neuropsychological cognitive data were extracted from the Parkinson's Progression Markers Initiative (PPMI) archives. We used seed-based resting-state fMRI (rs-fMRI) FC analysis and the cerebellar seeds were defined based on the hierarchical parcellation of the cerebellum (AAL atlas) and its topological function mapping (motor cerebellum and non-motor cerebellum). Results The early stage drug-naïve PD patients had significant differences in cerebellar FC when compared with HCs. Our findings include: (1) Increased intra-cerebellar FC within motor cerebellum, (2) increase motor cerebellar FC in inferior temporal gyrus and lateral occipital gyrus within ventral visual pathway and decreased motor-cerebellar FC in cuneus and dorsal posterior precuneus within dorsal visual pathway, (3) increased non-motor cerebellar FC in attention, language, and visual cortical networks, (4) increased vermal FC in somatomotor cortical network, and (5) decreased non-motor and vermal FC within brainstem, thalamus and hippocampus. Enhanced FC within motor cerebellum is positively associated with the MDS-UPDRS motor score and enhanced non-motor FC and vermal FC is negatively associated with cognitive function test scores of SDM and SFT. Conclusion These findings provide support for the involvement of cerebellum at an early stage and prior to clinical presentation of non-motor features of the disease in PD patients.
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Affiliation(s)
- Li Jiang
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Center for Advanced Imaging Research (CAIR), University of Maryland School of Medicine, Baltimore, MD, United States
| | - Jiachen Zhuo
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Center for Advanced Imaging Research (CAIR), University of Maryland School of Medicine, Baltimore, MD, United States
| | - Andrew Furman
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Center for Advanced Imaging Research (CAIR), University of Maryland School of Medicine, Baltimore, MD, United States
| | - Paul S. Fishman
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Rao Gullapalli
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Center for Advanced Imaging Research (CAIR), University of Maryland School of Medicine, Baltimore, MD, United States
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Droby A, Nosatzki S, Edry Y, Thaler A, Giladi N, Mirelman A, Maidan I. The interplay between structural and functional connectivity in early stage Parkinson's disease patients. J Neurol Sci 2022; 442:120452. [PMID: 36265263 DOI: 10.1016/j.jns.2022.120452] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 08/21/2022] [Accepted: 10/04/2022] [Indexed: 10/31/2022]
Abstract
The mechanisms underlying cognitive disturbances in Parkinson's disease (PD) are poorly understood but likely to depend on the ongoing degenerative processes affecting structural and functional connectivity (FC). This pilot study examined patterns of FC alterations during a cognitive task using EEG and structural characteristics of white matter (WM) pathways connecting these activated regions in early-stage PD. Eleven PD patients and nine healthy controls (HCs) underwent EEG recording during an auditory oddball task and MRI scans. Source localization was performed and Gaussian mixture model was fitted to identify brain regions with high power during task performance. These areas served as seed regions for connectivity analysis. FC among these regions was assessed by measures of magnitude squared coherence (MSC), and phase-locking value (PLV), while structural connectivity was evaluated using fiber tracking based on diffusion tensor imaging (DTI). The paracentral lobule (PL), superior parietal lobule (SPL), superior and middle frontal gyrus (SMFG), parahippocampal gyrus, superior and middle temporal gyri (STG, MTG) demonstrated increased activation during task performance. Compared to HCs, PD showed lower FC between SMFG and PL and between SMFG and SPL in MSC (p = 0.012 and p = 0.036 respectively). No significant differences between the groups were observed in PLV and the measured DTI metrics along WM tracts. These findings demonstrate that in early PD, cognitive performance changes might be attributed to FC alterations, suggesting that FC is affected early on in the degenerative process, whereas structural damage is more prominent in advanced stages as a result of the disease burden accumulation.
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Affiliation(s)
- Amgad Droby
- Laboratory of Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Department of Neurology, Sackler School of Medicine, Tel Aviv University, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
| | - Shai Nosatzki
- Laboratory of Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Israel
| | - Yariv Edry
- Laboratory of Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Israel
| | - Avner Thaler
- Laboratory of Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Department of Neurology, Sackler School of Medicine, Tel Aviv University, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Nir Giladi
- Laboratory of Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Department of Neurology, Sackler School of Medicine, Tel Aviv University, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Anat Mirelman
- Laboratory of Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Department of Neurology, Sackler School of Medicine, Tel Aviv University, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Inbal Maidan
- Laboratory of Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Department of Neurology, Sackler School of Medicine, Tel Aviv University, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
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Bahrami M, Simpson SL, Burdette JH, Lyday RG, Quandt SA, Chen H, Arcury TA, Laurienti PJ. Altered Default Mode Network Associated with Pesticide Exposure in Latinx Children from Rural Farmworker Families. Neuroimage 2022; 256:119179. [PMID: 35429626 PMCID: PMC9251855 DOI: 10.1016/j.neuroimage.2022.119179] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 03/03/2022] [Accepted: 04/03/2022] [Indexed: 01/21/2023] Open
Abstract
Pesticide exposure has been associated with adverse cognitive and neurological effects. However, neuroimaging studies aimed at examining the impacts of pesticide exposure on brain networks underlying abnormal neurodevelopment in children remain limited. It has been demonstrated that pesticide exposure in children is associated with disrupted brain anatomy in regions that make up the default mode network (DMN), a subnetwork engaged across a diverse set of cognitive processes, particularly higher-order cognitive tasks. This study tested the hypothesis that functional brain network connectivity/topology in Latinx children from rural farmworker families (FW children) would differ from urban Latinx children from non-farmworker families (NFW children). We also tested the hypothesis that probable historic childhood exposure to pesticides among FW children would be associated with network connectivity/topology in a manner that parallels differences between FW and NFW children. We used brain networks from functional magnetic resonance imaging (fMRI) data from 78 children and a mixed-effects regression framework to test our hypotheses. We found that network topology was differently associated with the connection probability between FW and NFW children in the DMN. Our results also indicated that, among 48 FW children, historic reports of exposure to pesticides from prenatal to 96 months old were significantly associated with DMN topology, as hypothesized. Although the cause of the differences in brain networks between FW and NFW children cannot be determined using a cross-sectional study design, the observed associations between network connectivity/topology and historic exposure reports in FW children provide compelling evidence for a contribution of pesticide exposure on altering the DMN network organization in this vulnerable population. Although longitudinal follow-up of the children is necessary to further elucidate the cause and reveal the ultimate neurological implications, these findings raise serious concerns about the potential adverse health consequences from developmental neurotoxicity associated with pesticide exposure in this vulnerable population.
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Affiliation(s)
- Mohsen Bahrami
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, USA.
| | - Sean L Simpson
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jonathan H Burdette
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Robert G Lyday
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Sara A Quandt
- Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Haiying Chen
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Thomas A Arcury
- Department of Family and Community Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Paul J Laurienti
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, USA
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Zhou C, Guo T, Bai X, Wu J, Gao T, Guan X, Liu X, Gu L, Huang P, Xuan M, Gu Q, Xu X, Zhang B, Zhang M. Locus coeruleus degeneration is associated with disorganized functional topology in Parkinson's disease. Neuroimage Clin 2022; 32:102873. [PMID: 34749290 PMCID: PMC8578042 DOI: 10.1016/j.nicl.2021.102873] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 09/07/2021] [Accepted: 10/30/2021] [Indexed: 10/26/2022]
Abstract
Degeneration of the locus coeruleus (LC) is recognized as a critical hallmark of Parkinson's disease (PD). Recent studies have reported that noradrenaline produced from the LC has critical effects on brain functional organization. However, it is unknown if LC degeneration in PD contributes to cognitive/motor manifestations through modulating brain functional organization. This study enrolled 94 PD patients and 68 healthy controls, and LC integrity was measured using the contrast-to-noise ratio of the LC (CNRLC) calculated from T1-weighted magnetic resonance imaging. We used graph-theory-based network analysis to characterize brain functional organization. The relationships among LC degeneration, network disruption, and cognitive/motor manifestations in PD were assessed. Whether network disruption was a mediator between LC degeneration and cognitive/motor impairments was assessed further. In addition, an independent PD subgroup (n = 35) having functional magnetic resonance scanning before and after levodopa administration was enrolled to evaluate whether LC degeneration-related network deficiencies were independent of dopamine deficiency. We demonstrated that PD patients have significant LC degeneration compared to healthy controls. CNRLC was positively correlated with Montreal Cognitive Assessment score and the nodal efficiency (NE) of several cognitive-related regions. Lower NE of the superior temporal gyrus was a mediator between LC degeneration and cognitive impairment in PD. However, levodopa treatment could not normalize the reduced NE of the superior temporal gyrus (mediator). In conclusion, we provided evidence for the relationship between LC degeneration and extensive network disruption in PD, and highlight the role of network disorganization in LC degeneration-related cognitive impairment.
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Affiliation(s)
- Cheng Zhou
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Tao Guo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Xueqin Bai
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - JingJing Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Ting Gao
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Xiaocao Liu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Luyan Gu
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Min Xuan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Quanquan Gu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Baorong Zhang
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
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Wang Z, Liu Y, Ruan X, Li Y, Li E, Zhang G, Li M, Wei X. Aberrant Amplitude of Low-Frequency Fluctuations in Different Frequency Bands in Patients With Parkinson's Disease. Front Aging Neurosci 2020; 12:576682. [PMID: 33343329 PMCID: PMC7744880 DOI: 10.3389/fnagi.2020.576682] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Accepted: 10/26/2020] [Indexed: 12/16/2022] Open
Abstract
Previous studies reported abnormal spontaneous neural activity in Parkinson's disease (PD) patients using resting-state functional magnetic resonance imaging (R-fMRI). However, the frequency-dependent neural activity in PD is largely unknown. Here, 35 PD patients and 35 age- and education-matched healthy controls (HCs) underwent R-fMRI scanning to investigate abnormal spontaneous neural activity of PD using the amplitude of low-frequency fluctuation (ALFF) approach within the conventional band (typical band: 0.01-0.08 Hz) and specific frequency bands (slow-5: 0.010-0.027 Hz and slow-4: 0.027-0.073 Hz). Compared with HCs, PD patients exhibited increased ALFF in the parieto-temporo-occipital regions, such as the bilateral inferior temporal gyrus/fusiform gyrus (ITG/FG) and left angular gyrus/posterior middle temporal gyrus (AG/pMTG), and displayed decreased ALFF in the left cerebellum, right precuneus, and left postcentral gyrus/supramarginal gyrus (PostC/SMG) in the typical band. PD patients showed greater increased ALFF in the left caudate/putamen, left anterior cingulate cortex/medial superior frontal gyrus (ACC/mSFG), left middle cingulate cortex (MCC), right ITG, and left hippocampus, along with greater decreased ALFF in the left pallidum in the slow-5 band, whereas greater increased ALFF in the left ITG/FG/hippocampus accompanied by greater decreased ALFF in the precentral gyrus/PostC was found in the slow-4 band (uncorrected). Additionally, the left caudate/putamen was positively correlated with levodopa equivalent daily dose (LEDD), Hoehn and Yahr (HY) stage, and disease duration. Our results suggest that PD is related to widespread abnormal brain activities and that the abnormalities of ALFF in PD are associated with specific frequency bands. Future studies should take frequency band effects into account when examining spontaneous neural activity in PD.
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Affiliation(s)
- Zhaoxiu Wang
- Department of Radiology, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Yanjun Liu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- Padova Neuroscience Center (PNC), University of Padova, Padua, Italy
| | - Xiuhang Ruan
- Department of Radiology, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Yuting Li
- Department of Radiology, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - E. Li
- Department of Radiology, Guangzhou First People’s Hospital, Guangzhou Medical University, Guangzhou, China
| | - Guoqin Zhang
- Department of Radiology, Guangzhou First People’s Hospital, Guangzhou Medical University, Guangzhou, China
| | - Mengyan Li
- Department of Neurology, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Xinhua Wei
- Department of Radiology, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, China
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Galdi P, Fratello M, Trojsi F, Russo A, Tedeschi G, Tagliaferri R, Esposito F. Stochastic Rank Aggregation for the Identification of Functional Neuromarkers. Neuroinformatics 2019; 17:479-496. [PMID: 30604083 DOI: 10.1007/s12021-018-9412-y] [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: 11/28/2022]
Abstract
The main challenge in analysing functional magnetic resonance imaging (fMRI) data from extended samples of subject (N > 100) is to extract as much relevant information as possible from big amounts of noisy data. When studying neurodegenerative diseases with resting-state fMRI, one of the objectives is to determine regions with abnormal background activity with respect to a healthy brain and this is often attained with comparative statistical models applied to single voxels or brain parcels within one or several functional networks. In this work, we propose a novel approach based on clustering and stochastic rank aggregation to identify parcels that exhibit a coherent behaviour in groups of subjects affected by the same disorder and apply it to default-mode network independent component maps from resting-state fMRI data sets. Brain voxels are partitioned into parcels through k-means clustering, then solutions are enhanced by means of consensus techniques. For each subject, clusters are ranked according to their median value and a stochastic rank aggregation method, TopKLists, is applied to combine the individual rankings within each class of subjects. For comparison, the same approach was tested on an anatomical parcellation. We found parcels for which the rankings were different among control subjects and subjects affected by Parkinson's disease and amyotrophic lateral sclerosis and found evidence in literature for the relevance of top ranked regions in default-mode brain activity. The proposed framework represents a valid method for the identification of functional neuromarkers from resting-state fMRI data, and it might therefore constitute a step forward in the development of fully automated data-driven techniques to support early diagnoses of neurodegenerative diseases.
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Affiliation(s)
- Paola Galdi
- NeuRoNe Lab, Department of Management and Innovation Systems, University of Salerno, Fisciano, Salerno, Italy
| | - Michele Fratello
- Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Francesca Trojsi
- Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Antonio Russo
- Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Gioacchino Tedeschi
- Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Roberto Tagliaferri
- NeuRoNe Lab, Department of Management and Innovation Systems, University of Salerno, Fisciano, Salerno, Italy
| | - Fabrizio Esposito
- Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Via S. Allende, 84081, Baronissi, Salerno, Italy.
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