Category: Parkinson's Disease: Neuroimaging
Objective: To identify Parkinson’s disease [PD] specific patterns in the brain using a multi-modal neuroimaging design and use these to predict gait decline.
Background: Gait impairment in PD is common, occurs early and progressively worsens with disease severity [1]. Early, identifiable markers of neural activity predicting decline in posture and gait control in PD remain relatively unexplored.
Method: 101 PD patients (32 females, MAGE 67±11y) recruited at time of diagnosis and 52 matched controls (20 females, MAGE 67±9y) had [18F] fluorodeoxyglucose Positron Emission Tomography [FDG-PET] measuring resting cerebral glucose metabolism (CMRGlc), resting-state fMRI imaging and gait assessments at baseline as part of the ICICLE-PD and ICICLE-gait studies [2]. 16 spatiotemporal gait characteristics were acquired using a pressure-sensitive mat (GAITrite) at 3 timepoints (Baseline, 18 and 36 months). We computed the fractional amplitude of low-frequency fluctuations [fALFF] as a marker of regional spontaneous neural oscillations in the brain. PD-specific signatures in the brain were quantified using a multivariate spatial covariance pattern [SCP] approach for both CMRGlc and fALFF. This method identifies spatially distributed networks in the brain that best discriminate between groups.
Results: FDG-SCP, but not fALFF-SCP, discriminated the two groups. The Subject Scaling Factor [SSF] scores – i.e. how much each subject expressed the SCP – was significantly greater in PD (p<0.0001). Regions showing a significant (|Z>1.64|) FDG binding increase in PD included areas in frontal, limbic, sensorimotor and vestibular cortices, basal ganglia nuclei and motor area of the cerebellum. Regions of decreased FDG binding in PD included visual and posterior parietal cortices. The SSF and gait characteristics at all 3 timepoints were entered into a linear mixed effects model with age and sex as covariates. Increase in step time (β=1.03, t=2.14, p=0.03), step length (β=0.001, t=2.26, p=0.02) and swing time variability (β=1.16, t=2.07, p=0.04) were significantly predicted by the baseline FDG-SCP pattern.
Conclusion: This study demonstrated altered FDG-binding in PD relative to normal ageing. Brain regions critical for gait control and spatial navigation showed altered CMRGlc. Our findings demonstrate the potential of baseline CMRGlc as a neural marker to predict decline in gait and postural control in early PD.
References: [1] Galna, B., Lord, S., Burn, D. J., and Rochester, L. (2014). Progression of gait dysfunction in incident Parkinson’s disease: Impact of medication and phenotype. Movement Disorders.30(3), 359-367. [2] Yarnall, A. J., Breen, D. P., Duncan, G. W., Khoo, T.K., Coleman, S.Y., et. al. (2014). Characterizing mild cognitive impairment in incident Parkinson disease: the ICICLE-PD study. Neurology, 82(4), 308-316.
To cite this abstract in AMA style:
H. Sigurdsson, A. Yarnall, B. Galna, S. Lord, L. Alcock, R. Morris, R. Lawson, S. Colloby, M. Firbank, N. Pavese, D. Brooks, J. O'brien, D. Burn, L. Rochester. Identifying neural signatures of Parkinson’s disease that predict decline in gait and postural control [abstract]. Mov Disord. 2020; 35 (suppl 1). https://www.mdsabstracts.org/abstract/identifying-neural-signatures-of-parkinsons-disease-that-predict-decline-in-gait-and-postural-control/. Accessed November 22, 2024.« Back to MDS Virtual Congress 2020
MDS Abstracts - https://www.mdsabstracts.org/abstract/identifying-neural-signatures-of-parkinsons-disease-that-predict-decline-in-gait-and-postural-control/