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PLoS Curr. 2011 Oct 4;3:RRN1268.

Longitudinal Change in Gait and Motor Function in Pre-manifest Huntington's Disease.

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  • 1Program in Physical Therapy, Department of Rehabilitation and Regenerative Medicine and Sergievsky Center, Columbia University College of Physicians and Surgeons. New York, NY. USA; Motor Performance Lab, Dept. of Neurology, Columbia University, New York; Department of Neurology, G.H. Sergievsky Center at the Columbia University College of Physicians and Surgeons, New York, NY and Department of Neurology, Psychiatry, Sergievsky Center, and the Taub Institute for the Aging Brain, Columbia University College of Physicians and Surgeons.


The purpose of this study was to examine longitudinal change in gait and motor function in pre-manifest Huntington's disease (HD).We examined ten pre-manifest subjects at baseline, one and five years. Quantitative gait data were collected with an electronic mat (GAITRiteĀ®). We analyzed measures related to speed (velocity, step length, cadence), asymmetry (step length difference), dynamic balance (percent time in double support, support base) and variability in stride length and swing time. Motor function was assessed with the motor component of the Unified Huntington's Disease Rating Scale.Gait velocity decreased (p=0.001), whereas step length difference (p=0.006), stride length variability (p=0.0001) and swing time variability increased (p=0.0001) from baseline to year five. Step length difference (p<0.05) and swing time variability (p<0.05) increased marginally in one year from baseline. UHDRS Total motor score increased over five years (p=0.003), though the increase in one year was not significant (p=0.053). Of the individual motor domain scores (eye, hand movements, gait and balance, chorea) only dystonia worsened over five years (p=0.02). Total motor score (r2= 0.49, p<0.001) and swing time variability (r2= 0.22, p<0.009) were correlated with estimated years to diagnosis.Our results present the longest longitudinal follow up of gait in pre-manifest HD thus far. Despite the small sample size, quantitative gait analysis was able to detect changes in gait speed, symmetry and variability. Swing time variability was particularly important because it increased in one year from baseline and was correlated with estimated time to diagnosis. Our results highlight the importance of predictive outcomes such as gait variability using quantitative analysis.

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