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Gait-Related Metabolic Covariance Networks at Rest in Parkinson's Disease

Title: Gait-Related Metabolic Covariance Networks at Rest in Parkinson's Disease
Authors: Sigurdsson, Hilmar P; Yarnall, Alison J; Galna, Brook; Lord, Sue; Alcock, Lisa; Lawson, Rachael A; Colloby, Sean J; Firbank, Michael J; Taylor, John-Paul; Pavese, Nicola; Brooks, David J; O'Brien, John T; Burn, David J; Rochester, Lynn
Source: Sigurdsson, H P, Yarnall, A J, Galna, B, Lord, S, Alcock, L, Lawson, R A, Colloby, S J, Firbank, M J, Taylor, J-P, Pavese, N, Brooks, D J, O'Brien, J T, Burn, D J & Rochester, L 2022, 'Gait-Related Metabolic Covariance Networks at Rest in Parkinson's Disease', Movement Disorders, vol. 37, no. 6, pp. 1222-1234. https://doi.org/10.1002/mds.28977
Publication Year: 2022
Collection: Aarhus University: Research
Subject Terms: PET; Parkinson's disease; [ F]-2-fluoro-2-deoxyglucose; gait; multivariate covariance networks
Description: Background: Gait impairments are characteristic motor manifestations and significant predictors of poor quality of life in Parkinson's disease (PD). Neuroimaging biomarkers for gait impairments in PD could facilitate effective interventions to improve these symptoms and are highly warranted. Objective: The aim of this study was to identify neural networks of discrete gait impairments in PD. Methods: Fifty-five participants with early-stage PD and 20 age-matched healthy volunteers underwent quantitative gait assessment deriving 12 discrete spatiotemporal gait characteristics and [ 18 F]-2-fluoro-2-deoxyglucose-positron emission tomography measuring resting cerebral glucose metabolism. A multivariate spatial covariance approach was used to identify metabolic brain networks that were related to discrete gait characteristics in PD. Results: In PD, we identified two metabolic gait-related covariance networks. The first correlated with mean step velocity and mean step length (pace gait network), which involved relatively increased and decreased metabolism in frontal cortices, including the dorsolateral prefrontal and orbital frontal, insula, supplementary motor area, ventrolateral thalamus, cerebellum, and cuneus. The second correlated with swing time variability and step time variability (temporal variability gait network), which included relatively increased and decreased metabolism in sensorimotor, superior parietal cortex, basal ganglia, insula, hippocampus, red nucleus, and mediodorsal thalamus. Expression of both networks was significantly elevated in participants with PD relative to healthy volunteers and were not related to levodopa dosage or motor severity. Conclusions: We have identified two novel gait-related brain networks of altered glucose metabolism at rest. These gait networks could serve as a potential neuroimaging biomarker of gait impairments in PD and facilitate development of therapeutic strategies for these disabling symptoms.
Document Type: article in journal/newspaper
Language: English
ISSN: 0885-3185; 1531-8257
Relation: info:eu-repo/semantics/altIdentifier/pmid/35285068; info:eu-repo/semantics/altIdentifier/wos/000768453000001; info:eu-repo/semantics/altIdentifier/pissn/0885-3185; info:eu-repo/semantics/altIdentifier/eissn/1531-8257
DOI: 10.1002/mds.28977
Availability: https://pure.au.dk/portal/en/publications/7bb2fa3a-77b7-4da9-a26f-c6f1aee8ed67; https://doi.org/10.1002/mds.28977; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9314598/pdf/MDS-37-1222.pdf
Rights: info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.F8BBD605
Database: BASE