The influence of genetic factors on brain plasticity and recovery after neural injury

Pearson-Fuhrhop, Kristin M.; Burke, Erin; Cramer, Steven C.

doi:10.1097/wco.0b013e32835a360a

Cited by 35 publications

(21 citation statements)

References 62 publications

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“…23 Individuals' genetic profiles may also influence recovery. [24][25][26] While interest has centred on genes known to contribute to neuroplasticity, 27 there are a number of candidate biomarkers to consider as well as gene-gene interactions and epigenetics.…”

Section: Theme 2: Recovery Biomarkersmentioning

confidence: 99%

Moving rehabilitation research forward: Developing consensus statements for rehabilitation and recovery research

Bernhardt

Borschmann

Boyd

et al. 2016

International Journal of Stroke

136

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Stroke recovery is the next frontier in stroke medicine. While growth in rehabilitation and recovery research is exponential, a number of barriers hamper our ability to rapidly progress the field. Standardized terminology is absent in both animal and human research, methods are poorly described, recovery biomarkers are not well defined, and we lack consistent timeframes or measures to examine outcomes. Agreed methods and conventions for developing, monitoring, evaluating and reporting interventions directed at improving recovery are lacking, and current approaches are often not underpinned by biology. We urgently need to better understand the biology of recovery and its time course in both animals and humans to translate evidence from basic science into clinical trials. A new international partnership of stroke recovery and rehabilitation experts has committed to advancing the research agenda. In May 2016, the first Stroke Recovery and Rehabilitation Roundtable will be held, with the aim of achieving an agreed approach to the development, conduct and reporting of research. A range of methods will be used to achieve consensus in four priority areas: preclinical recovery research; biomarkers of recovery; intervention development, monitoring and reporting; and measurement in clinical trials. We hope to foster a global network of researchers committed to advancing this exciting field. Recovery from stroke is challenging for many survivors. They deserve effective treatments underpinned by our evolving understanding of brain recovery and human behaviour. Working together, we can develop game-changing interventions to improve recovery and quality of life in those living with stroke.

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Section: Theme 2: Recovery Biomarkersmentioning

confidence: 99%

Moving rehabilitation research forward: Developing consensus statements for rehabilitation and recovery research

Bernhardt

Borschmann

Boyd

et al. 2016

International Journal of Stroke

136

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“…Regenerative plasticity also varies with injury modality; regenerative responses to ablation and traumatic brain injury are more limited compared with ischemic injury (95, 183,186). There are numerous other contributors to variable regenerative responses, including injury severity (103), age (137,156), individual genetic differences (154), and common stroke comorbidities, such as diabetes (80, 176).…”

Section: Regenerative Responses To Strokementioning

confidence: 99%

Motor System Reorganization After Stroke: Stimulating and Training Toward Perfection

2015

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“…16,23,28,29 Some data in humans suggest that genetic variation, particularly in the genes for brain-derived neurotrophic factor (BDNF) and apolipoprotein E (ApoE), might also be related to variance in response to a restorative therapy, as polymorphisms for each have been associated with poorer poststroke outcome and reductions in some forms of cortical plasticity. [30][31][32] In addition, stroke subtype is important to many aspects of clinical decision making for patients with cerebrovascular disease 33,34 and has been suggested as important to recovery potential and improvements with restorative therapies in the chronic phase of stroke, 35 but this issue has received limited attention.…”

mentioning

confidence: 99%

Neural function, injury, and stroke subtype predict treatment gains after stroke

Quinlan

Dodakian

See

et al. 2014

Annals of Neurology

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189

186

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Objective To better understand the high variability in response seen when treating human subjects with restorative therapies post-stroke. Preclinical studies suggest that neural function, neural injury, and clinical status each influence treatment gains, therefore the current study hypothesized that a multivariate approach incorporating these three measures would have the greatest predictive value. Methods Patients 3-6 months post-stroke underwent a battery of assessments before receiving 3-weeks of standardized upper extremity robotic therapy. Candidate predictors included measures of brain injury (including to gray and white matter), neural function (cortical function and cortical connectivity), and clinical status (demographics/medical history, cognitive/mood, and impairment). Results Among all 29 patients, predictors of treatment gains identified measures of brain injury (smaller corticospinal tract (CST) injury), cortical function (greater ipsilesional motor cortex (M1) activation), and cortical connectivity (greater inter-hemispheric M1-M1 connectivity). Multivariate modeling found that best prediction was achieved using both CST injury and M1-M1 connectivity (r2=0.44, p=0.002), a result confirmed using Lasso regression. A threshold was defined whereby no subject with >63% CST injury achieved clinically significant gains. Results differed according to stroke subtype: gains in patients with lacunar stroke were exclusively predicted by a measure of intra-hemispheric connectivity. Interpretation Response to a restorative therapy after stroke is best predicted by a model that includes measures of both neural injury and function. Neuroimaging measures were the best predictors and may have an ascendant role in clinical decision-making for post-stroke rehabilitation, which remains largely reliant on behavioral assessments. Results differed across stroke subtypes, suggesting utility of lesion-specific strategies.

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The influence of genetic factors on brain plasticity and recovery after neural injury

Abstract: Understanding genetic variation gives clinicians a biological signal that could be used to predict who is most likely to recover from neural injury, to choose the optimal treatment for a patient, or to supplement rehabilitation therapy.

Cited by 35 publications

References 62 publications

Moving rehabilitation research forward: Developing consensus statements for rehabilitation and recovery research

Moving rehabilitation research forward: Developing consensus statements for rehabilitation and recovery research

Motor System Reorganization After Stroke: Stimulating and Training Toward Perfection

Neural function, injury, and stroke subtype predict treatment gains after stroke

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