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BDNF Val66Met Polymorphism Is Related to Motor System Function After Stroke

Dae Yul Kim, Erin B. Quinlan, Robert Gramer, Steven C. Cramer
DOI: 10.2522/ptj.20150135 Published 1 April 2016
Dae Yul Kim
D.Y. Kim, MD, Department of Rehabilitation, University of Ulsan, Ulsan, Korea.
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Erin B. Quinlan
E.B. Quinlan, PhD, Department of Neurology, University of California at Irvine, Irvine, California.
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Robert Gramer
R. Gramer, BA, Department of Neurology, University of California at Irvine.
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Steven C. Cramer
S.C. Cramer, MD, MMSc, Department of Neurology, University of California at Irvine, Hewitt Hall, Room 1331, Mail Code 1385, Irvine, CA 92697 (USA).
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Figure.

Brain activation in each genotype group, contrasting paretic hand movement with rest. During movement of the paretic hand, larger brain activation (measured using a significance threshold of P<.001, which is approximately Z>3 in the figure) was seen among (A) the 26 patients with stroke who lacked the brain-derived neurotrophic factor (BDNF) val66met polymorphism compared with (B) the 16 patients with stroke who had the polymorphism. This finding was particularly true in the primary sensorimotor cortex contralateral to the moving hand (indicated by yellow arrows), which, in each case, was the ipsilesional primary sensorimotor cortex. The color bar at bottom indicates significance of activation.

Tables

Table 3.
Table 3.

Regional Brain Activation During Paretic Hand Movement According to Brain-Derived Neurotrophic Factor (BDNF) Val66Met Polymorphism Statusa

  • ↵a Values are mean±standard error of the mean.

Table 1.
Table 1.

Allele and Genotype Frequencies for Brain-Derived Neurotrophic Factor (BDNF) Val66Met Polymorphism in 3 Countriesa

  • ↵a Data are from a meta-analysis by Shimizu et al,16 who found these ethnic differences across the 3 countries to be significant.

Table 2.
Table 2.

Participant Characteristics in Relation to Brain-Derived Neurotrophic Factor Val66Met Polymorphisma

  • ↵a Values are mean±standard error of the mean, except for the National Institutes of Health Stroke Scale, for which values are median (interquartile range). Scores on the arm motor Fugl-Meyer scale (FM) reflect moderate-to-severe arm motor deficits (maximum score=66; higher is better). Scores on the Nottingham Sensory Assessment reflect overall mild sensory deficits (maximum score=17; higher is better). Scores on the Geriatric Depression Scale reflect overall mild depression symptoms (higher is worse; scores >10 generally consistent with depression). M=male, F=female, Y=yes, N=no, L=left, R=right.

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Vol 96 Issue 4 Table of Contents
Physical Therapy: 96 (4)

Issue highlights

  • Confidence and Fear of Falling Avoidance Behavior in Older Adults
  • Reliability of the ECHOWS Tool
  • Functional Gait Assessment in Older Adults
  • Community-Based Exercise for People With Stroke
  • Knee Osteoarthritis and Promoting Exercise Adherence
  • Test Comparisons in Predicting Falls in Parkinson Disease
  • Scapular Position Using the Protractor Method
  • Physical Activity and Physical Fitness in Autism
  • Disability and Active Video Gaming
  • BNDF Genotype and Brain Function After Stroke
  • Electrodiagnostic Evaluation and Individuals With Volumetric Muscle Injury
  • Regenerative Rehabilitation and Advanced Technologies in Physical Therapy
  • Physical Therapists and Mechanotherapy
  • Translating Genomic Advances to Physical Therapist Practice
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BDNF Val66Met Polymorphism Is Related to Motor System Function After Stroke
Dae Yul Kim, Erin B. Quinlan, Robert Gramer, Steven C. Cramer
Physical Therapy Apr 2016, 96 (4) 533-539; DOI: 10.2522/ptj.20150135

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BDNF Val66Met Polymorphism Is Related to Motor System Function After Stroke
Dae Yul Kim, Erin B. Quinlan, Robert Gramer, Steven C. Cramer
Physical Therapy Apr 2016, 96 (4) 533-539; DOI: 10.2522/ptj.20150135
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Subjects

  • Geriatrics
    • Stroke (Geriatrics)
  • Special Series and Special Issues
    • Special Series on Regenerative Rehabilitation and Genomics
  • Neurology/Neuromuscular System
    • Stroke (Neurology)
    • Motor Control and Motor Learning

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