Genetic and Neurophysiological Biomarkers of Neuroplasticity Inform Post-Stroke Language Recovery

Background There is high variability in post-stroke aphasia severity and predicting recovery remains imprecise. Standard prognostics do not include neurophysiological indicators or genetic biomarkers of neuroplasticity, which may be critical sources of variability. Objective To evaluate whether a common polymorphism (Val(66)Met) in the gene for brain-derived neurotrophic factor (BDNF) contributes to variability in post-stroke aphasia, and to assess whether BDNF polymorphism interacts with neurophysiological indicators of neuroplasticity (cortical excitability and stimulation-induced neuroplasticity) to improve estimates of aphasia severity. Methods Saliva samples and motor-evoked potentials (MEPs) were collected from participants with chronic aphasia subsequent to left-hemisphere stroke. MEPs were collected prior to continuous theta burst stimulation (cTBS; index for cortical excitability) and 10 minutes following cTBS (index for stimulation-induced neuroplasticity) to the right primary motor cortex. Analyses assessed the extent to which BDNF polymorphism interacted with cortical excitability and stimulation-induced neuroplasticity to predict aphasia severity beyond established predictors. Results Val(66)Val carriers showed less aphasia severity than Val(66)Met carriers, after controlling for lesion volume and time post-stroke. Furthermore, Val(66)Val carriers showed expected effects of age on aphasia severity, and positive associations between severity and both cortical excitability and stimulation-induced neuroplasticity. In contrast, Val(66)Met carriers showed weaker effects of age and negative associations between cortical excitability, stimulation-induced neuroplasticity and aphasia severity. Conclusions Neurophysiological indicators and genetic biomarkers of neuroplasticity improved aphasia severity predictions. Furthermore, BDNF polymorphism interacted with cortical excitability and stimulation-induced neuroplasticity to improve predictions. These findings provide novel insights into mechanisms of variability in stroke recovery and may improve aphasia prognostics.