Genetic Variation and Neuroplasticity: Role in Rehabilitation After Stroke. (July 2017)

• Record Type: Journal Article
• Authors: Stewart, Jill Campbell; Cramer, Steven C.
• Is Part Of: Journal of neurologic physical therapy. Volume 41(2017)Supplement 3
• Publication Date: 2017-07
• Subjects: motor learning -- polymorphism -- predictive models -- recovery; Nervous system -- Diseases -- Physical therapy -- Periodicals; Nervous system -- Diseases -- Treatment -- Periodicals; 616.80462
• DOI: 10.1097/NPT.0000000000000180
• Languages: English
• ISSNs: 1557-0576

Abstract

Abstract : Background and Purpose: In many neurologic diagnoses, significant interindividual variability exists in the outcomes of rehabilitation. One factor that may impact response to rehabilitation interventions is genetic variation. Genetic variation refers to the presence of differences in the DNA sequence among individuals in a population. Genetic polymorphisms are variations that occur relatively commonly and, while not disease-causing, can impact the function of biological systems. The purpose of this article is to describe genetic polymorphisms that may impact neuroplasticity, motor learning, and recovery after stroke. Summary of Key Points: Genetic polymorphisms for brain-derived neurotrophic factor (BDNF), dopamine, and apolipoprotein E have been shown to impact neuroplasticity and motor learning. Rehabilitation interventions that rely on the molecular and cellular pathways of these factors may be impacted by the presence of the polymorphism. For example, it has been hypothesized that individuals with the BDNF polymorphism may show a decreased response to neuroplasticity-based interventions, decreased rate of learning, and overall less recovery after stroke. However, research to date has been limited and additional work is needed to fully understand the role of genetic variation in learning and recovery. Recommendations for Clinical Practice: Genetic polymorphisms should be considered as possible predictors or covariates in studies that investigate neuroplasticity, motor learning, or motor recovery after stroke. Future predictive models of stroke recovery will likely include a combination of genetic factors and other traditional factors (eg, age, lesion type, corticospinal tract integrity) to determine an individual's expected response to a specific rehabilitation intervention.