Background: There is high variability in poststroke aphasia severity, and predicting language recovery remains imprecise. Standard prognostic measures do not include neurophysiological indicators or genetic biomarkers of neuroplasticity, which may be critical sources of variability.
Objective: To evaluate whether a common polymorphism (Val66Met) in the gene for brain derived neurotrophic factor (BDNF; a gene related to neuroplasticity) contributes to variability in poststroke language recovery, and to assess whether BDNF polymorphism interacts with neurophysiological indicators of neuroplasticity (cortical excitability and stimulation induced plasticity in response to continuous theta burst stimulation [cTBS]) to improve estimates of aphasia severity.
Methods: Saliva samples and motor evoked potentials (MEPs) were collected from participants with chronic aphasia subsequent to a left hemisphere ischemic stroke. MEPs were collected prior to cTBS (index for cortical excitability) and 10 minutes following cTBS (index for stimulation induced neuroplasticity) to the left 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: Val66Val carriers showed less aphasia severity than Met allele carriers, after controlling for lesion volume and time poststroke. Furthermore, Val66Val carriers showed expected responses of strong effects of age on aphasia severity, and positive associations between both cortical excitability and stimulation induced neuroplasticity and severity. In contrast, Met allele carriers showed weaker effects of age and unexpected negative associations between cortical excitability, stimulation induced neuroplasticity and aphasia severity.
Conclusions: Neurophysiological indicators and genetic biomarkers of neuroplasticity improved ability to predict poststroke aphasia severity. Furthermore, BDNF polymorphism interacted with cortical excitability and stimulation-induced neuroplasticity to predict aphasia recovery. These findings provide novel insights into mechanisms of variability in stroke recovery and may improve aphasia prognostics.