Brain damage due to stroke or traumatic brain injury (TBI), both leading causes of serious long-term disability, often leads to the development of epilepsy. Patients who develop post-injury epilepsy tend to have poor functional outcomes. Emerging evidence highlights a potential role for blood-brain barrier (BBB) dysfunction in the development of post-injury epilepsy. However, common mechanisms underlying the pathological hyperexcitability are largely unknown. Here, we show that comparative transcriptome analyses predict remodeling of extracellular matrix (ECM) as a common response to different types of injuries. ECM-related transcriptional changes were induced by the serum protein albumin via TGFβ signaling in primary astrocytes. In accordance with transcriptional responses, we found persistent degradation of protective ECM structures called perineuronal nets (PNNs) around fast-spiking inhibitory interneurons, in a rat model of TBI as well as in brains of human epileptic patients. Exposure of a naïve brain to albumin was sufficient to induce the transcriptional and translational upregulation of molecules related to ECM remodeling and the persistent breakdown of PNNs around fast-spiking inhibitory interneurons, which was contingent on TGFβ signaling activation. Our findings provide insights on how albumin extravasation that occurs upon BBB dysfunction in various brain injuries can predispose neural circuitry to the development of chronic inhibition deficits.

Postinjury epilepsy (PIE) is a devastating sequela of various brain insults. While recent studies offer novel insights into the mechanisms underlying epileptogenesis and discover potential preventive treatments, the lack of PIE biomarkers hinders the clinical implementation of such treatments. Here we explored the biomarker potential of different electrographic features in five models of PIE. Electrocorticographic or intrahippocampal recordings of epileptogenesis (from the insult to the first spontaneous seizure) from two laboratories were analyzed in three mouse and two rat PIE models. Time, frequency, and fractal and nonlinear properties of the signals were examined, in addition to the daily rate of epileptiform spikes, the relative power of five frequency bands (theta, alpha, beta, low gamma, and high gamma) and the dynamics of these features over time. During the latent pre-seizure period, epileptiform spikes were more frequent in epileptic compared with nonepileptic rodents; however, this feature showed limited predictive power due to high inter- and intra-animal variability. While nondynamic rhythmic representation failed to predict epilepsy, the dynamics of the theta band were found to predict PIE with a sensitivity and specificity of >90%. Moreover, theta dynamics were found to be inversely correlated with the latency period (and thus predict the onset of seizures) and with the power change of the high-gamma rhythm. In addition, changes in theta band power during epileptogenesis were associated with altered locomotor activity and distorted circadian rhythm. These results suggest that changes in theta band during the epileptogenic period may serve as a diagnostic biomarker for epileptogenesis, able to predict the future onset of spontaneous seizures.SIGNIFICANCE STATEMENTPostinjury epilepsy is an unpreventable and devastating disorder that develops following brain injuries, such as traumatic brain injury and stroke, and is often associated with neuropsychiatric comorbidities. As PIE affects as many as 20% of brain-injured patients, reliable biomarkers are imperative before any preclinical therapeutics can find clinical translation. We demonstrate the capacity to predict the epileptic outcome in five different models of PIE, highlighting theta rhythm dynamics as a promising biomarker for epilepsy. Our findings prompt the exploration of theta dynamics (using repeated electroencephalographic recordings) as an epilepsy biomarker in brain injury patients.

Peri-infarct opening of the blood–brain barrier may be associated with spreading depolarizations, seizures, and epileptogenesis as well as cognitive dysfunction. We aimed to investigate the mechanisms underlying neural network pathophysiology in the blood–brain barrier-dysfunctional hippocampus. Photothrombotic stroke within the rat neocortex was associated with increased intracranial pressure, vasogenic edema, and peri-ischemic blood–brain barrier dysfunction that included the ipsilateral hippocampus. Intrahippocampal recordings revealed electrographic seizures within the first week in two-thirds of animals, accompanied by a reduction in gamma and increase in theta frequency bands. Synaptic interactions were studied in parasagittal hippocampal slices at 24 h and seven days post-stroke. Field potential recordings in CA1 and CA3 uncovered multiple population spikes, epileptiform episodes, and spreading depolarizations at 24 h. Input–output analysis revealed that fEPSP-spike coupling was significantly enhanced at seven days. In addition, CA1 feedback and feedforward inhibition were diminished. Slices generating epileptiform activity at seven days revealed impaired bidirectional long-term plasticity following high and low-frequency stimulation protocols. Microarray and PCR data confirmed changes in expression of astrocyte-related genes and suggested downregulation in expression of GABA_A-receptor subunits. We conclude that blood-brain barrier dysfunction in the peri-infarct hippocampus is associated with early disinhibition, hyperexcitability, and abnormal synaptic plasticity.