Structural connectivity and brain network analyses in Parkinson's disease: A cross-sectional and longitudinal study
IntroductionParkinson's disease (PD) is an idiopathic disease of the central nervous system characterized by both motor and non-motor symptoms. It is the second most common neurodegenerative disease. Magnetic resonance imaging (MRI) can reveal underlying brain changes associated with PD.Objecti...
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| Format: | Article |
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Frontiers Media S.A.
2023-03-01
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| Series: | Frontiers in Neurology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2023.1137780/full |
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| author | Maurizio Bergamino Elizabeth G. Keeling Elizabeth G. Keeling Nicola J. Ray Antonella Macerollo Antonella Macerollo Monty Silverdale Ashley M. Stokes |
| author_facet | Maurizio Bergamino Elizabeth G. Keeling Elizabeth G. Keeling Nicola J. Ray Antonella Macerollo Antonella Macerollo Monty Silverdale Ashley M. Stokes |
| author_sort | Maurizio Bergamino |
| collection | DOAJ |
| description | IntroductionParkinson's disease (PD) is an idiopathic disease of the central nervous system characterized by both motor and non-motor symptoms. It is the second most common neurodegenerative disease. Magnetic resonance imaging (MRI) can reveal underlying brain changes associated with PD.ObjectiveIn this study, structural connectivity and white matter networks were analyzed by diffusion MRI and graph theory in a cohort of patients with PD and a cohort of healthy controls (HC) obtained from the Parkinson's Progression Markers Initiative (PPMI) database in a cross-sectional analysis. Furthermore, we investigated longitudinal changes in the PD cohort over 36 months.ResultCompared with the control group, participants with PD showed lower structural connectivity in several brain areas, including the corpus callosum, fornix, and uncinate fasciculus, which were also confirmed by a large effect-size. Additionally, altered connectivity between baseline and after 36 months was found in different network paths inside the white matter with a medium effect-size. Network analysis showed trends toward lower network density in PD compared with HC at baseline and after 36 months, though not significant after correction. Significant differences were observed in nodal degree and strength in several nodes.ConclusionIn conclusion, altered structural and network metrics in several brain regions, such as corpus callosum, fornix, and cingulum were found in PD, compared to HC. We also report altered connectivity in the PD group after 36 months, reflecting the impact of both PD pathology and aging processes. These results indicate that structural and network metrics might yield insight into network reorganization that occurs in PD. |
| first_indexed | 2024-04-09T22:14:03Z |
| format | Article |
| id | doaj.art-797334f90c9549c8b5d7c199911b7abc |
| institution | Directory Open Access Journal |
| issn | 1664-2295 |
| language | English |
| last_indexed | 2024-04-09T22:14:03Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neurology |
| spelling | doaj.art-797334f90c9549c8b5d7c199911b7abc2023-03-23T05:35:04ZengFrontiers Media S.A.Frontiers in Neurology1664-22952023-03-011410.3389/fneur.2023.11377801137780Structural connectivity and brain network analyses in Parkinson's disease: A cross-sectional and longitudinal studyMaurizio Bergamino0Elizabeth G. Keeling1Elizabeth G. Keeling2Nicola J. Ray3Antonella Macerollo4Antonella Macerollo5Monty Silverdale6Ashley M. Stokes7Barrow Neuroimaging Innovation Center, Barrow Neurological Institute, Phoenix, AZ, United StatesBarrow Neuroimaging Innovation Center, Barrow Neurological Institute, Phoenix, AZ, United StatesSchool of Life Sciences, Arizona State University, Tempe, AZ, United StatesHealth, Psychology and Communities Research Centre, Department of Psychology, Manchester Metropolitan University, Manchester, United KingdomNeurology Department, The Walton Centre NHS Foundation Trust, Liverpool, United KingdomInstitute of Systems, Molecular and Integrative Biology, School of Life Sciences, University of Liverpool, Liverpool, United KingdomManchester Centre for Clinical Neurosciences, University of Manchester, Manchester, United KingdomBarrow Neuroimaging Innovation Center, Barrow Neurological Institute, Phoenix, AZ, United StatesIntroductionParkinson's disease (PD) is an idiopathic disease of the central nervous system characterized by both motor and non-motor symptoms. It is the second most common neurodegenerative disease. Magnetic resonance imaging (MRI) can reveal underlying brain changes associated with PD.ObjectiveIn this study, structural connectivity and white matter networks were analyzed by diffusion MRI and graph theory in a cohort of patients with PD and a cohort of healthy controls (HC) obtained from the Parkinson's Progression Markers Initiative (PPMI) database in a cross-sectional analysis. Furthermore, we investigated longitudinal changes in the PD cohort over 36 months.ResultCompared with the control group, participants with PD showed lower structural connectivity in several brain areas, including the corpus callosum, fornix, and uncinate fasciculus, which were also confirmed by a large effect-size. Additionally, altered connectivity between baseline and after 36 months was found in different network paths inside the white matter with a medium effect-size. Network analysis showed trends toward lower network density in PD compared with HC at baseline and after 36 months, though not significant after correction. Significant differences were observed in nodal degree and strength in several nodes.ConclusionIn conclusion, altered structural and network metrics in several brain regions, such as corpus callosum, fornix, and cingulum were found in PD, compared to HC. We also report altered connectivity in the PD group after 36 months, reflecting the impact of both PD pathology and aging processes. These results indicate that structural and network metrics might yield insight into network reorganization that occurs in PD.https://www.frontiersin.org/articles/10.3389/fneur.2023.1137780/fullParkinson's diseaseParkinson's Progression Markers Initiativestructural connectivitydiffusion magnetic resonance imagingnetwork analysis |
| spellingShingle | Maurizio Bergamino Elizabeth G. Keeling Elizabeth G. Keeling Nicola J. Ray Antonella Macerollo Antonella Macerollo Monty Silverdale Ashley M. Stokes Structural connectivity and brain network analyses in Parkinson's disease: A cross-sectional and longitudinal study Frontiers in Neurology Parkinson's disease Parkinson's Progression Markers Initiative structural connectivity diffusion magnetic resonance imaging network analysis |
| title | Structural connectivity and brain network analyses in Parkinson's disease: A cross-sectional and longitudinal study |
| title_full | Structural connectivity and brain network analyses in Parkinson's disease: A cross-sectional and longitudinal study |
| title_fullStr | Structural connectivity and brain network analyses in Parkinson's disease: A cross-sectional and longitudinal study |
| title_full_unstemmed | Structural connectivity and brain network analyses in Parkinson's disease: A cross-sectional and longitudinal study |
| title_short | Structural connectivity and brain network analyses in Parkinson's disease: A cross-sectional and longitudinal study |
| title_sort | structural connectivity and brain network analyses in parkinson s disease a cross sectional and longitudinal study |
| topic | Parkinson's disease Parkinson's Progression Markers Initiative structural connectivity diffusion magnetic resonance imaging network analysis |
| url | https://www.frontiersin.org/articles/10.3389/fneur.2023.1137780/full |
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