Glutamate receptor-mediated excitotoxicity is a common pathogenic process in many neurological conditions including epilepsy. Prolonged seizures induce elevations in extracellular glutamate that contribute to excitotoxic damage, which in turn can trigger chronic neuroinflammatory reactions, leading to secondary damage to the brain. Blocking key inflammatory pathways could prevent such secondary brain injury following the initial excitotoxic insults. Prostaglandin E2 (PGE 2 ) has emerged as an important mediator of neuroinflammation-associated injury, in large part via activating its EP2 receptor subtype. Herein, we investigated the effects of EP2 receptor inhibition on excitotoxicity-associated neuronal inflammation and injury in vivo. Utilizing a bioavailable and brain-permeant compound, TG6-10-1, we found that pharmacological inhibition of EP2 receptor after a one-hour episode of kainate-induced status epilepticus (SE) in mice reduced seizure-promoted functional deficits, cytokine induction, reactive gliosis, blood-brain barrier impairment, and hippocampal damage. Our preclinical findings endorse the feasibility of blocking PGE 2 /EP2 signaling as an adjunctive strategy to treat prolonged seizures. The promising benefits from EP2 receptor inhibition should also be relevant to other neurological conditions in which excitotoxicity-associated secondary damage to the brain represents a pathogenic event.

The focus of the Area I Benchmarks is on understanding the etiologies of the epilepsies and related conditions. The greatest advances in the past 3 years have been made in our understanding of the genetic and immune causes of epilepsy. Novel gene and autoimmune discoveries have been facilitated by technologic advances and by large collaborative efforts to combine patients and streamline experimental studies. The underlying mechanisms of seizures as they present in the different epilepsy syndromes continue to be a main focus of funded studies. Many studies have examined the bidirectional relationship between epilepsy and psychiatric comorbidity; effects of seizures on both behavior and cognition in animal models; and the illness-related and psychosocial variables associated with the psychiatric, cognitive, linguistic, and social comorbidities of epilepsy. Yet, advances in “identifying the underlying mechanisms, interacting mechanisms, and consequences of the first condition (epilepsy) of these comorbidities” have been slow to emerge. We identify key advances and discuss the factors that have promoted or hindered progress in achieving these goals, and we consider the research that should be conducted to move the field forward.

The Epilepsy Benchmark goals in Area III focus on making progress in understanding and controlling seizures and related conditions as well as on developing biomarkers and new therapies that will reduce seizures and improve outcomes for individuals with epilepsy. Area III emphasizes a need to better understand the ways in which seizures start, propagate, and terminate and whether those network processes are common or unique in different forms of epilepsy. The application of that knowledge to improved seizure prediction and detection will also play a role in improving patient outcomes. Animal models of treatment-resistant epilepsy that are aligned with etiologies and clinical features of human epilepsies are especially encouraged as necessary tools to understand mechanisms and test potential therapies. Antiseizure therapies that target (either alone or in combination) novel or multiple seizure mechanisms are prioritized in this section of the Benchmarks. Area III goals also highlight validation of biomarkers of treatment response and safety risk, effective self-management, and patient-centered outcome measures as important areas of emphasis for the next five to ten years.

In April 2013, the National Institute of Neurological Disorders and Stroke (NINDS) hosted “Curing the Epilepsies 2013: Pathways Forward,” the third in a series of Curing the Epilepsies conferences held in partnership with epilepsy advocacy and professional organizations to assess progress in epilepsy research and help set a research agenda for future years. As an important outcome, these conferences have led to the development of the Benchmarks for Epilepsy Research, which reflect priorities for research toward clinically meaningful advances in understanding and treating the epilepsies.

Area IV Benchmarks focus on mechanistic understanding and prevention of epilepsy-related consequences. As such, these Benchmarks cover “epilepsy beyond the seizures,” areas related to the neurodevelopment, mental health comorbidities, intellectual functioning, and general health of individuals with epilepsy, the short- and long-term effects of antiseizure treatments, and risks for epilepsy-related mortality. This area also covers unique issues of special populations with seizures, such as pregnant women, children, the elderly, and people with nonepileptic seizures.

The prevention of epilepsy and its progression after initial diagnosis represents one of the most challenging goals of epilepsy research (1). Although epilepsy diagnoses lack a formal component of disease stage, anecdotal clinical observation suggests that individual patients usually fall into one of at least three types of presentation: an easily treated type that is responsive to the first or second antiseizure medications tried, a relapsing/remitting type in which seizure control is intermittent, and a drug-resistant type in which the patient never achieves seizure control with medication (2). As drug-resistant epilepsy is extremely difficult to treat, the successful prevention of epilepsy in at-risk patients may provide the best strategy to alleviate the negative impact of epilepsy. Benchmark II aims to establish therapeutic approaches for preventing the development and progression of epilepsy by 1) understanding epileptogenic processes related to genetic or neurodevelopmental causes, 2) understanding epileptogenic processes related to acquired brain injuries, 3) identifying biomarkers for monitoring epileptogenesis, 4) developing models closely aligned with etiologies of human epilepsies, and 5) identifying molecular targets that drive epileptogenesis or are opposed to it.

Complex neurological conditions can give rise to large scale transcriptomic changes that drive disease progression. It is likely that alterations in one or a few transcription factors or cofactors underlie these transcriptomic alterations. Identifying the driving transcription factors/ cofactors is a non-trivial problem and a limiting step in the understanding of neurological disorders. Epilepsy has a prevalence of 1% and is the fourth most common neurological disorder. While a number of anti-seizure drugs exist to treat seizures symptomatically, none is curative or preventive. This reflects a lack of understanding of disease progression. We used a novel systems approach to mine transcriptome profiles of rodent and human epileptic brain samples to identify regulators of transcriptional networks in the epileptic brain. We find that Enhancer of Zeste Homolog 2 (EZH2) regulates differentially expressed genes in epilepsy across multiple rodent models of acquired epilepsy. EZH2 undergoes a prolonged upregulation in the epileptic brain. A transient inhibition of EZH2 immediately after status epilepticus (SE) robustly increases spontaneous seizure burden weeks later. This suggests that EZH2 upregulation is a protective. These findings are the first to characterize a role for EZH2 in opposing epileptogenesis and debut a bioinformatic approach to identify nuclear drivers of complex transcriptional changes in disease.

Objective: Seizures develop in 80% of patients with anti–N-methyl-d-aspartate receptor (NMDAR) encephalitis, and these represent a major cause of morbidity and mortality. Anti-NMDAR antibodies have been linked to memory loss in encephalitis; however, their role in seizures has not been established. We determined whether anti-NMDAR antibodies from autoimmune encephalitis patients are pathogenic for seizures. Methods: We performed continuous intracerebroventricular infusion of cerebrospinal fluid (CSF) or purified immunoglobulin (IgG) from the CSF of patients with anti-NMDAR encephalitis or polyclonal rabbit anti-NMDAR IgG, in male C57BL/6 mice. Seizure status during a 2-week treatment was assessed with video-electroencephalography. We assessed memory, anxiety-related behavior, and motor function at the end of treatment and assessed the extent of neuronal damage and gliosis in the CA1 region of hippocampus. We also performed whole-cell patch recordings from the CA1 pyramidal neurons in hippocampal slices of mice with seizures. Results: Prolonged exposure to rabbit anti-NMDAR IgG, patient CSF, or human IgG purified from the CSF of patients with encephalitis induced seizures in 33 of 36 mice. The median number of seizures recorded in 2 weeks was 13, 39, and 35 per mouse in these groups, respectively. We observed only 18 brief nonconvulsive seizures in 11 of 29 control mice (median seizure count of 0) infused with vehicle (n = 4), normal CSF obtained from patients with noninflammatory central nervous system (CNS) conditions (n = 12), polyclonal rabbit IgG (n = 7), albumin (n = 3), and normal human IgG (n = 3). We did not observe memory deficits, anxiety-related behavior, or motor impairment measured at 2 weeks in animals treated with CSF from affected patients or rabbit IgG. Furthermore, there was no evidence of hippocampal cell loss or astrocyte proliferation in the same mice. Significance: Our findings indicate that autoantibodies can induce seizures in anti-NMDAR encephalitis and offer a model for testing novel therapies for refractory autoimmune seizures.

"Good science" means answering important questions convincingly, a challenging endeavor under the best of circumstances. Our inability to replicate many biomedical studies has been the subject of numerous commentaries both in the scientific and lay press. In response, statistics has re-emerged as a necessary tool to improve the objectivity of study conclusions. However, psychological aspects of decision making introduce preconceived preferences into scientific judgment that cannot be eliminated by any statistical method. The psychology of decision making, expounded by Kahneman, Tversky, and Thayer, is well known in the field of economics, but the underlying concepts of cognitive psychology are also relevant to scientific judgments. I repeated experiments carried out on undergraduates by Kahneman and colleagues four to five decades ago, but with scientists, and obtained essentially the same results. The experiments were in the form of written reactions to scenarios, and participants were scientists at all career stages. The findings reinforce the roles that two inherent intuitions play in scientific decision making: our drive to create a coherent narrative from new data regardless of its quality or relevance and our inclination to seek patterns in data whether they exist or not. Moreover, we do not always consider how likely a result is regardless of its p value. Low statistical power and inattention to principles underpinning Bayesian statistics reduce experimental rigor, but mitigating skills can be learned. Overcoming our natural human tendency to make quick decisions and jump to conclusions is a deeper obstacle to doing good science; this too can be learned.

Global expression profiling of neurologic or psychiatric disorders has been confounded by variability among laboratories, animal models, tissues sampled, and experimental platforms, with the result being that few genes demonstrate consistent expression changes. We attempted to minimize these confounds by pooling dentate granule cell transcriptional profiles from 164 rats in seven laboratories, using three status epilepticus (SE) epilepsy models (pilocarpine, kainate, self-sustained SE), plus amygdala kindling. In each epilepsy model, RNA was harvested from laser-captured dentate granule cells from six rats at four time points early in the process of developing epilepsy, and data were collected from two independent laboratories in each rodent model except SSSE. Hierarchical clustering of differentially-expressed transcripts in the three SE models revealed complete separation between controls and SE rats isolated 1 day after SE. However, concordance of gene expression changes in the SE models was only 26-38% between laboratories, and 4.5% among models, validating the consortium approach. Transcripts with unusually highly variable control expression across laboratories provide a 'red herring' list for low-powered studies.