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Gait-related metabolic covariance networks at rest in Parkinson’s disease

Lookup NU author(s): Dr Hilmar SigurdssonORCiD, Professor Alison Yarnall, Dr Brook Galna, Dr Susan Lord, Dr Lisa AlcockORCiD, Dr Rachael LawsonORCiD, Dr Sean Colloby, Dr Michael FirbankORCiD, Professor John-Paul TaylorORCiD, Professor Nicola PaveseORCiD, Professor David BrooksORCiD, Professor John O'Brien, Professor David Burn, Professor Lynn RochesterORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Background: Gait impairments are characteristic motor manifestations and significant predictors of poor quality of life in Parkinson's disease. Neuroimaging biomarkers for gait impairments in Parkinson’s could facilitate effective interventions to improve these symptoms and are highly warranted. Objective: To identify neural networks of discrete gait impairments in Parkinson’s. Methods: Fifty-five early Parkinson’s participants and 20 age-matched healthy volunteers underwent quantitative gait assessment deriving 12 discrete spatiotemporal gait characteristics and [18F]-2-fluoro-2-deoxyglucose-PET 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 Parkinson’s. Results: In Parkinson’s, 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 cortex, insula, sensorimotor cortex, supplementary motor area, ventrolateral thalamus, cerebellum and fusiform gyrus. 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 and occipital cortices, basal ganglia, insula, hippocampus, red nucleus and medio-dorsal thalamus. Expression of both networks were significantly elevated in Parkinson’s participants relative to controls and were not related to levodopa dosage or total Parkinson’s 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 Parkinson’s and facilitate development of therapeutic strategies for these disabling symptoms.

Publication metadata

Author(s): Sigurdsson HP, Yarnall AJ, Galna B, Lord S, Alcock L, Lawson RA, Colloby SJ, Firbank MJ, Taylor JP, Pavese N, Brooks DJ, O'Brien JT, Burn DJ, Rochester L

Publication type: Article

Publication status: Published

Journal: Movement Disorders

Year: 2022

Volume: 37

Issue: 6

Pages: 1222-1234

Print publication date: 01/06/2022

Online publication date: 14/03/2022

Acceptance date: 10/02/2022

Date deposited: 10/02/2022

ISSN (print): 0885-3185

ISSN (electronic): 1531-8257

Publisher: John Wiley & Sons, Inc.


DOI: 10.1002/mds.28977


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Funder referenceFunder name
J-0802Parkinson`s UK (formerly Parkinson`s Disease Society)
Lockhart Parkinson's Disease Research Fund
Newcastle Biomedical Research Centre