Pilocarpine-induced status epilepticus (SE), which results in temporal lobe epilepsy (TLE) in rodents, activates the JAK/STAT pathway. In the current study, we evaluate whether brief exposure to a selective inhibitor of the JAK/STAT pathway (WP1066) early after the onset of SE effects the severity of SE or reduces later spontaneous seizure frequency via inhibition of STAT3-regulated gene transcription. Rats that received systemic WP1066 or vehicle at the onset of SE were continuously video-EEG monitored during SE and for one month to assess seizure frequency over time. Protein and/or mRNA levels for pSTAT3, and STAT3-regulated genes including: ICER, Gabra1, c-myc, mcl-1, cyclin D1, and bcl-xl were evaluated in WP1066 and vehicle-treated rats during stages of epileptogenesis to determine the acute effects of WP1066 administration on SE and chronic epilepsy. WP1066 (two 50 mg/kg doses) administered within the first hour after onset of SE results in transient inhibition of pSTAT3 and long-term reduction in spontaneous seizure frequency WP1066 alters the severity of chronic epilepsy without affecting SE or cell death. Early WP1066 administration reduces known downstream targets of STAT3 transcription 24 hours after SE including cyclin D1 and mcl-1 levels, known for their roles in cell-cycle progression and cell survival, respectively. These findings uncover a potential effect of the JAK/STAT pathway after brain injury that is physiologically important and may provide a new therapeutic target that can be harnessed for the prevention of epilepsy development and/or progression.

Background Brain-derived neurotrophic factor (BDNF) is a major signaling molecule that the brain uses to control a vast network of intracellular cascades fundamental to properties of learning and memory, and cognition. While much is known about BDNF signaling in the healthy nervous system where it controls the mitogen activated protein kinase (MAPK) and cyclic-AMP pathways, less is known about its role in multiple brain disorders where it contributes to the dysregulated neuroplasticity seen in epilepsy and traumatic brain injury (TBI). We previously found that neurons respond to prolonged BDNF exposure (both in vivo (in models of epilepsy and TBI) and in vitro (in BDNF treated primary neuronal cultures)) by activating the Janus Kinase/Signal Transducer and Activator of Transcription (JAK/STAT) signaling pathway. This pathway is best known for its association with inflammatory cytokines in non-neuronal cells. Results Here, using deep RNA-sequencing of neurons exposed to BDNF in the presence and absence of well characterized JAK/STAT inhibitors, and without non-neuronal cells, we determine the BDNF transcriptome that is specifically regulated by agents that inhibit JAK/STAT signaling. Surprisingly, the BDNF-induced JAK/STAT transcriptome contains ion channels and neurotransmitter receptors coming from all the major classes expressed in the brain, along with key modulators of synaptic plasticity, neurogenesis, and axonal remodeling. Analysis of this dataset has revealed a unique non-canonical mechanism of JAK/STATs in neurons as differential gene expression mediated by STAT3 is not solely dependent upon phosphorylation at residue 705 and may involve a BDNF-induced interaction of STAT3 with Heterochromatin Protein 1 alpha (HP1α). Conclusions These findings suggest that the neuronal BDNF-induced JAK/STAT pathway involves more than STAT3 phosphorylation at 705, providing the first evidence for a non-canonical mechanism that may involve HP1α. Our analysis reveals that JAK/STAT signaling regulates many of the genes associated with epilepsy syndromes where BDNF levels are markedly elevated. Uncovering the mechanism of this novel form of BDNF signaling in the brain may provide a new direction for epilepsy therapeutics and open a window into the complex mechanisms of STAT3 transcriptional regulation in neurological disease. Electronic supplementary material The online version of this article (10.1186/s12864-019-6033-2) contains supplementary material, which is available to authorized users.

While the exact role of β1 subunit-containing GABA-A receptors (GABARs) in brain function is not well understood, altered expression of the β1 subunit gene (GABRB1) is associated with neurological and neuropsychiatric disorders. In particular, down-regulation of β1 subunit levels is observed in brains of patients with epilepsy, autism, bipolar disorder and schizophrenia. A pathophysiological feature of these disease states is imbalance in energy metabolism and mitochondrial dysfunction. The transcription factor, nuclear respiratory factor 1 (NRF-1), has been shown to be a key mediator of genes involved in oxidative phosphorylation and mitochondrial biogenesis. Using a variety of molecular approaches (including mobility shift, promoter/reporter assays, and overexpression of dominant negative NRF-1), we now report that NRF-1 regulates transcription of GABRB1 and that its core promoter contains a conserved canonical NRF-1 element responsible for sequence specific binding and transcriptional activation. Our identification of GABRB1 as a new target for NRF-1 in neurons suggests that genes coding for inhibitory neurotransmission may be coupled to cellular metabolism. This is especially meaningful as binding of NRF-1 to its element is sensitive to the kind of epigenetic changes that occur in multiple disorders associated with altered brain inhibition.

Summary Objective Temporal lobe epilepsy (TLE) is frequently medically intractable and often progressive. Compromised inhibitory neurotransmission due to altered GABAA receptor α4 (GABARα4) subunit expression has been emphasized as a potential contributor to the initial development of epilepsy following a brain insult (primary epileptogenesis), but the regulation of GABARα4 during chronic epilepsy, specifically, how expression is altered following spontaneous seizures, is less well understood. Methods Continuous video-EEG recordings from rats with pilocarpine-induced TLE were used to capture epileptic animals within 3 hours of a spontaneous seizure (SS) or greater than 24 hours after the last SS to determine whether recent occurrence of a seizure was associated with altered levels of GABARα4 subunit expression. We further evaluated whether this GABARα4 subunit plasticity is regulated by signaling mechanisms active in primary epileptogenesis, specifically, increases in brain-derived neurotrophic factor (BDNF) and early growth response factor 3 (Egr3). Results Elevated levels of GABARα4 subunit mRNA and protein were observed following spontaneous seizures, and were associated with higher levels of BDNF and Egr3 mRNA Significance These data suggest that spontaneous, recurrent seizures that define chronic epilepsy may influence changes in GABARα4 subunit expression, and that signaling pathways known to regulate GABARα4 expression after SE may also be activated after spontaneous seizures in chronically epileptic animals.

Background Characterization of prediagnostic Parkinson’s Disease (PD) and early prediction of subsequent development are critical for preventive interventions, risk stratification and understanding of disease pathology. This study aims to characterize the role of the prediagnostic period in PD and, using selected features from this period as novel interception points, construct a prediction model to accelerate the diagnosis in a real-world setting. Methods We constructed two sets of machine learning models: a retrospective approach highlighting exposures up to 5 years prior to PD diagnosis, and an alternative model that prospectively predicted future PD diagnosis from all individuals at their first diagnosis of a gait or tremor disorder, these being features that appeared to represent the initiation of a differential diagnostic window. Results We found many novel features captured by the retrospective models; however, the high accuracy was primarily driven from surrogate diagnoses for PD, such as gait and tremor disorders, suggesting the presence of a distinctive differential diagnostic period when the clinician already suspected PD. The model utilizing a gait/tremor diagnosis as the interception point, achieved a validation AUC of 0.874 with potential time compression to a future PD diagnosis of more than 300 days. Comparisons of predictive diagnoses between the prospective and prediagnostic cohorts suggest the presence of distinctive trajectories of PD progression based on comorbidity profiles. Conclusions Overall, our machine learning approach allows for both guiding clinical decisions such as the initiation of neuroprotective interventions and importantly, the possibility of earlier diagnosis for clinical trials for disease modifying therapies.