A human systems biology approach to discover new drug targets in epilepsy

INTUITION: a data platform to integrate human epilepsy clinical care and support for discovery

To make appropriate clinical decisions, clinicians consider many types of data from multiple sources to arrive at a diagnosis and plan. However, the current health systems have siloed data, making it challenging to develop information platforms that integrate this process into a single place for comprehensive clinical evaluation and research. INTUITION is a human brain integrative data system that facilitates multimodal data integration, unified storage, cohort selection, and analysis of multidisciplinary datasets. In this article, we describe the use of INTUITION to include electronic health records together with co-registered neuroimaging and EEG from patients who undergo invasive brain surgery for epilepsy. In addition to providing clinically useful visualizations and analytics to help guide surgical planning, INTUITION also links a bank of human brain epileptic tissues from specific brain locations to quantitative EEG, imaging, histology, and omics studies in a unique, completely integrated informatics platform. Having a clinically useful platform for integrating multimodal datasets can not only aid in clinical management decisions but also in creating a unique resource for research and discovery when linked to spatially mapped tissue samples.

DUSP4 appears to be a highly localized endogenous inhibitor of epileptic signaling in human neocortex

BACKGROUND

We previously identified the Mitogen Activated Protein Kinase (MAPK) pathway as focally upregulated in brain regions with high epileptic activity and showed that inhibition of MAPK signaling reduces epileptic spiking in an animal model. Here we examined how activators and inhibitors of the MAPK pathway are expressed in human epileptic cortex and how these could contribute to the localization of epileptic signaling.

METHODS

We localized gene and protein expression in human epileptic neocortical tissues based on epileptic activities from 20 patients based on long-term intracranial recordings. Follow-up mechanistic studies by depolarization of human Sh-SY5Y cell line were used to model epileptic activity in the human brain.

RESULTS

A clustering algorithm of differentially expressed genes identified a unique gene expression cluster distinct from other MAPK genes. Within this cluster was dual specificity phosphatase 4 (DUSP4), a potent MAPK inhibitor. In situ hybridization studies revealed focal patches of DUSP4 mRNA in layer 2/3 brain regions associated with a dramatic reduction in MAPK signaling genes. In vitro depolarization led to the rapid and transient induction of DUSP4 protein, which, in turn, reduced MAPK activity. Activity-dependent induction of DUSP4 protein was transient and required MAPK signaling. Human epileptic brain regions with lower epileptic activity had lower MAPK activity and higher DUSP4 protein levels.

DISCUSSION

DUSP4 is a highly localized, endogenous feedback inhibitor of pro-epileptogenic MAPK signaling in the human epileptic brain. Increasing DUSP4 expression could therefore be a novel therapeutic approach to prevent the development and spread of epileptic circuits.

SIGNIFICANCE STATEMENT

Epilepsy is a chronic debilitating disease. Once it develops, epileptic circuits often persist throughout life. Fortunately, in focal forms of epilepsy, these circuits can remain highly localized and are amenable to surgical resections, suggesting that endogenous mechanisms restrict their spread to other brain regions. Using a high-throughput genomic analysis of human epileptic brain regions, we identified DUSP4 as an activity-dependent inhibitor of MAPK signaling expressed in focal patches surrounding human neocortical epileptic brain regions. Our results suggest that DUSP4, through local inhibition of MAPK signaling, acts as an endogenous, spatially segregated safety mechanism to prevent the spread of epileptic activity. Augmenting DUSP4 expression could be a novel disease-modifying approach to prevent or treat human epilepsy.

NMR-based metabolomics in pediatric drug resistant epilepsy - preliminary results

Epilepsy in children is the most frequent, heterogeneous and difficult to classify chronic neurologic condition with the etiology found in 35–40% of patients. Our aim is to detect the metabolic differences between the epileptic children and the children with no neurological abnormalities in order to define the metabolic background for therapy monitoring. The studied group included 28 epilepsy patients (median age 12 months) examined with a diagnostic protocol including EEG, videoEEG, 24-hour-EEG, tests for inborn errors of metabolism, chromosomal analysis and molecular study. The reference group consisted of 20 patients (median age 20 months) with no neurological symptoms, no development delay nor chronic diseases. ¹H-NMR serum spectra were acquired on 400 MHz spectrometer and analyzed using multivariate and univariate approach with the application of correction for age variation. The epilepsy group was characterized by increased levels of serum N-acetyl-glycoproteins, lactate, creatine, glycine and lipids, whereas the levels of citrate were decreased as compared to the reference group. Choline, lactate, formate and dimethylsulfone were significantly correlated with age. NMR-based metabolomics could provide information on the dynamic metabolic processes in drug-resistant epilepsy yielding not only disease-specific biomarkers but also profound insights into the disease course, treatment effects or drug toxicity.

Identifying targets for preventing epilepsy using systems biology of the human brain

Approximately one third of all epilepsy patients are resistant to current therapeutic treatments. Some patients with focal forms of epilepsy benefit from invasive surgical approaches that can lead to large surgical resections of human epileptic neocortex. We have developed a systems biology approach to take full advantage of these resections and the brain tissues they generate as a means to understand underlying mechanisms of neocortical epilepsy and to identify novel biomarkers and therapeutic targets. In this review, we will describe our unique approach that has led to the development of a 'NeuroRepository' of electrically-mapped epileptic tissues and associated data. This 'Big Data' approach links quantitative measures of ictal and interictal activities corresponding to a specific intracranial electrode to clinical, imaging, histological, genomic, proteomic, and metabolomic measures. This highly characterized data and tissue bank has given us an extraordinary opportunity to explore the underlying electrical, cellular, and molecular mechanisms of the human epileptic brain. We describe specific examples of how an experimental design that compares multiple cortical regions with different electrical activities has led to discoveries of layer-specific pathways and how these can be 'reverse translated' from animal models back to humans in the form of new biomarkers and therapeutic targets. This article is part of the special issue entitled 'New Epilepsy Therapies for the 21st Century - From Antiseizure Drugs to Prevention, Modification and Cure of Epilepsy'.

Proteomic analysis of human epileptic neocortex predicts vascular and glial changes in epileptic regions

Epilepsy is a common neurological disorder, which is not well understood at the molecular level. Exactly why some brain regions produce epileptic discharges and others do not is not known. Patients who fail to respond to antiseizure medication (refractory epilepsy) can benefit from surgical removal of brain regions to reduce seizure frequency. The tissue removed in these surgeries offers an invaluable resource to uncover the molecular and cellular basis of human epilepsy. Here, we report a proteomic study to determine whether there are common proteomic patterns in human brain regions that produce epileptic discharges. We analyzed human brain samples, as part of the Systems Biology of Epilepsy Project (SBEP). These brain pieces are in vivo electrophysiologically characterized human brain samples withdrawn from the neocortex of six patients with refractory epilepsy. This study is unique in that for each of these six patients the comparison of protein expression was made within the same patient: a more epileptic region was compared to a less epileptic brain region. The amount of epileptic activity was defined for each patient as the frequency of their interictal spikes (electric activity between seizures that is a parameter strongly linked to epilepsy). Proteins were resolved from three subcellular fractions, using a 2D differential gel electrophoresis (2D-DIGE), revealing 31 identified protein spots that changed significantly. Interestingly, glial fibrillary acidic protein (GFAP) was found to be consistently down regulated in high spiking brain tissue and showed a strong negative correlation with spike frequency. We also developed a two-step analysis method to select for protein species that changed frequently among the patients and identified these proteins. A total of 397 protein spots of interest (SOI) were clustered by protein expression patterns across all samples. These clusters were used as markers and this analysis predicted proteomic changes due to both histological differences and molecular pathways, revealed by examination of gene ontology clusters. Our experimental design and proteomic data analysis predicts novel glial changes, increased angiogenesis, and changes in cytoskeleton and neuronal projections between high and low interictal spiking regions. Quantitative histological staining of these same tissues for both the vascular and glial changes confirmed these findings, which provide new insights into the structural and functional basis of neocortical epilepsy.

Altered metabolomic-genomic signature: A potential noninvasive biomarker of epilepsy

OBJECTIVE

This study aimed to identify noninvasive biomarkers of human epilepsy that can reliably detect and localize epileptic brain regions. Having noninvasive biomarkers would greatly enhance patient diagnosis, patient monitoring, and novel therapy development. At the present time, only surgically invasive, direct brain recordings are capable of detecting these regions with precision, which severely limits the pace and scope of both clinical management and research progress in epilepsy.

METHODS

We compared high versus low or nonspiking regions in nine medically intractable epilepsy surgery patients by performing integrated metabolomic-genomic-histological analyses of electrically mapped human cortical regions using high-resolution magic angle spinning proton magnetic resonance spectroscopy, cDNA microarrays, and histological analysis.

RESULTS

We found a highly consistent and predictive metabolite logistic regression model with reduced lactate and increased creatine plus phosphocreatine and choline, suggestive of a chronically altered metabolic state in epileptic brain regions. Linking gene expression, cellular, and histological differences to these key metabolites using a hierarchical clustering approach predicted altered metabolic vascular coupling in the affected regions. Consistently, these predictions were validated histologically, showing both neovascularization and newly discovered, millimeter-sized microlesions.

SIGNIFICANCE

Using a systems biology approach on electrically mapped human cortex provides new evidence for spatially segregated, metabolic derangements in both neurovascular and synaptic architecture in human epileptic brain regions that could be a noninvasively detectable biomarker of epilepsy. These findings both highlight the immense power of a systems biology approach and identify a potentially important role that magnetic resonance spectroscopy can play in the research and clinical management of epilepsy.

WONOEP appraisal: Development of epilepsy biomarkers-What we can learn from our patients?

OBJECTIVE

Current medications for patients with epilepsy work in only two of three patients. For those medications that do work, they only suppress seizures. They treat the symptoms, but do not modify the underlying disease, forcing patients to take these drugs with significant side effects, often for the rest of their lives. A major limitation in our ability to advance new therapeutics that permanently prevent, reduce the frequency of, or cure epilepsy comes from a lack of understanding of the disease coupled with a lack of reliable biomarkers that can predict who has or who will get epilepsy.

METHODS

The main goal of this report is to present a number of approaches for identifying reliable biomarkers from observing patients with brain disorders that have a high probability of producing epilepsy.

RESULTS

A given biomarker, or more likely a profile of biomarkers, will have both a quantity and a time course during epileptogenesis that can be used to predict who will get the disease, to confirm epilepsy as a diagnosis, to identify coexisting pathologies, and to monitor the course of treatments.

SIGNIFICANCE

Additional studies in patients and animal models could identify common and clinically valuable biomarkers to successfully translate animal studies into new and effective clinical trials.

Epigenetics in epilepsy

Approximately 50 million people have epilepsy, making it the most common chronic and severe neurological disease worldwide, with increased risk of mortality and psychological and socioeconomic consequences impairing quality of life. More than 30% of patients with epilepsy have inadequate control of their seizures with drug therapy. Any structural brain lesion can provoke epilepsy. However, progression of seizure activity as well as the development of drug-resistance remains difficult to predict, irrespective of the underlying epileptogenic condition, i.e., traumatic brain injury, developmental brain lesions, brain tumors or genetic inheritance. Mutated DNA sequences in genes encoding for ion channels or neurotransmitter receptors have been identified in hereditary focal or generalized epilepsies, but genotype-phenotype correlations are poor, arguing for additional factors determining the effect of a genetic predisposition. The dynamics of epigenetic mechanisms (e.g. DNA methylation, histone modifications, chromatin remodelling, and non-coding RNAs) provide likely explanations for common features in epilepsy and other complex diseases, including late onset, parent-of-origin effects, discordance of monozygotic twins, and fluctuation of symptoms. In addition, many focal epilepsies, including focal cortical dysplasias (FCDs), glio-neuronal tumors (e.g. ganglioglioma), or temporal lobe epilepsy with hippocampal sclerosis (TLE-HS), do not seem to primarily associate with hereditary traits, suggesting other pathogenic mechanisms. Herein we will discuss the many faces of the epigenetic machinery, which provides powerful tools and mechanisms to propagate epileptogenicity and likely also contribute to the epileptogenic memory in chronic and difficult-to-treat epilepsies.

Predicting novel histopathological microlesions in human epileptic brain through transcriptional clustering

Although epilepsy is associated with a variety of abnormalities, exactly why some brain regions produce seizures and others do not is not known. We developed a method to identify cellular changes in human epileptic neocortex using transcriptional clustering. A paired analysis of high and low spiking tissues recorded in vivo from 15 patients predicted 11 cell-specific changes together with their 'cellular interactome'. These predictions were validated histologically revealing millimetre-sized 'microlesions' together with a global increase in vascularity and microglia. Microlesions were easily identified in deeper cortical layers using the neuronal marker NeuN, showed a marked reduction in neuronal processes, and were associated with nearby activation of MAPK/CREB signalling, a marker of epileptic activity, in superficial layers. Microlesions constitute a common, undiscovered layer-specific abnormality of neuronal connectivity in human neocortex that may be responsible for many 'non-lesional' forms of epilepsy. The transcriptional clustering approach used here could be applied more broadly to predict cellular differences in other brain and complex tissue disorders.

Systems biology, complexity, and the impact on antiepileptic drug discovery

The number of available anticonvulsant drugs increased in the period spanning over more than a century, amounting to the current panoply of nearly two dozen so-called antiepileptic drugs (AEDs). However, none of them actually prevents/reduces the post-brain insult development of epilepsy in man, and in no less than a third of patients with epilepsy, the seizures are not drug-controlled. Plausibly, the enduring limitation of AEDs' efficacy derives from the insufficient understanding of epileptic pathology. This review pinpoints the unbalanced reductionism of the analytic approaches that overlook the intrinsic complexity of epilepsy and of the drug resistance in epilepsy as the core conceptual flaw hampering the discovery of truly antiepileptogenic drugs. A rising awareness of the complexity of epileptic pathology is, however, brought about by the emergence of nonreductionist systems biology (SB) that considers the networks of interactions underlying the normal organismic functions and of SB-based systems (network) pharmacology that aims to restore pathological networks. By now, the systems pharmacology approaches of AED discovery are fairly meager, but their forthcoming development is both a necessity and a realistic prospect, explored in this review.

Epilepsy biomarkers

A biomarker is defined as an objectively measured characteristic of a normal or pathologic biologic process. Identification and proper validation of biomarkers of epileptogenesis (the development of epilepsy) and ictogenesis (the propensity to generate spontaneous seizures) might predict the development of an epilepsy condition; identify the presence and severity of tissue capable of generating spontaneous seizures; measure progression after the condition is established; and determine pharmacoresistance. Such biomarkers could be used to create animal models for more cost-effective screening of potential antiepileptogenic and antiseizure drugs and devices, and to reduce the cost of clinical trials by enriching the trial population, and acting as surrogate markers to shorten trial duration. The objectives of the biomarker subgroup for the London Workshop were to define approaches for identifying possible biomarkers for these purposes. Research to identify reliable biomarkers may also reveal underlying mechanisms that could serve as therapeutic targets for the development of new antiepileptogenic and antiseizure compounds.

Layer-specific CREB target gene induction in human neocortical epilepsy

Epilepsy is a disorder of recurrent seizures that affects 1% of the population. To understand why some areas of cerebral cortex produce seizures and others do not, we identified differentially expressed genes in human epileptic neocortex compared with nearby regions that did not produce seizures. The transcriptome that emerged strongly implicates MAPK signaling and CREB-dependent transcription, with 74% of differentially expressed genes containing a cAMP response element (CRE) in their proximal promoter, more than half of which are conserved. Despite the absence of recent seizures in these patients, epileptic brain regions prone to seizures showed persistent activation of ERK and CREB. Persistent CREB activation was directly linked to CREB-dependent gene transcription by chromatin immunoprecipitation that showed phosphorylated CREB constitutively associated with the proximal promoters of many of the induced target genes involved in neuronal signaling, excitability, and synaptic plasticity. A distinct spatial pattern of ERK activation was seen in superficial axodendritic processes of epileptic neocortex that colocalized with both CREB phosphorylation and CREB target gene induction in well demarcated populations of layer 2/3 neurons. These same neuronal lamina showed a marked increase in synaptic density. The findings generated in this study generate a robust and spatially restricted pattern of epileptic biomarkers and associated synaptic changes that could lead to new mechanistic insights and potential therapeutic targets for human epilepsy.

Activity-dependent human brain coding/noncoding gene regulatory networks

While most gene transcription yields RNA transcripts that code for proteins, a sizable proportion of the genome generates RNA transcripts that do not code for proteins, but may have important regulatory functions. The brain-derived neurotrophic factor (BDNF) gene, a key regulator of neuronal activity, is overlapped by a primate-specific, antisense long noncoding RNA (lncRNA) called BDNFOS. We demonstrate reciprocal patterns of BDNF and BDNFOS transcription in highly active regions of human neocortex removed as a treatment for intractable seizures. A genome-wide analysis of activity-dependent coding and noncoding human transcription using a custom lncRNA microarray identified 1288 differentially expressed lncRNAs, of which 26 had expression profiles that matched activity-dependent coding genes and an additional 8 were adjacent to or overlapping with differentially expressed protein-coding genes. The functions of most of these protein-coding partner genes, such as ARC, include long-term potentiation, synaptic activity, and memory. The nuclear lncRNAs NEAT1, MALAT1, and RPPH1, composing an RNAse P-dependent lncRNA-maturation pathway, were also upregulated. As a means to replicate human neuronal activity, repeated depolarization of SY5Y cells resulted in sustained CREB activation and produced an inverse pattern of BDNF-BDNFOS co-expression that was not achieved with a single depolarization. RNAi-mediated knockdown of BDNFOS in human SY5Y cells increased BDNF expression, suggesting that BDNFOS directly downregulates BDNF. Temporal expression patterns of other lncRNA-messenger RNA pairs validated the effect of chronic neuronal activity on the transcriptome and implied various lncRNA regulatory mechanisms. lncRNAs, some of which are unique to primates, thus appear to have potentially important regulatory roles in activity-dependent human brain plasticity.

Systems biology impact on antiepileptic drug discovery

Systems biology (SB), a recent trend in bioscience research to consider the complex interactions in biological systems from a holistic perspective, sees the disease as a disturbed network of interactions, rather than alteration of single molecular component(s). SB-relying network pharmacology replaces the prevailing focus on specific drug-receptor interaction and the corollary of rational drug design of "magic bullets", by the search for multi-target drugs that would act on biological networks as "magic shotguns". Epilepsy being a multi-factorial, polygenic and dynamic pathology, SB approach appears particularly fit and promising for antiepileptic drug (AED) discovery. In fact, long before the advent of SB, AED discovery already involved some SB-like elements. A reported SB project aimed to find out new drug targets in epilepsy relies on a relational database that integrates clinical information, recordings from deep electrodes and 3D-brain imagery with histology and molecular biology data on modified expression of specific genes in the brain regions displaying spontaneous epileptic activity. Since hitting a single target does not treat complex diseases, a proper pharmacological promiscuity might impart on an AED the merit of being multi-potent. However, multi-target drug discovery entails the complicated task of optimizing multiple activities of compounds, while having to balance drug-like properties and to control unwanted effects. Specific design tools for this new approach in drug discovery barely emerge, but computational methods making reliable in silico predictions of poly-pharmacology did appear, and their progress might be quite rapid. The current move away from reductionism into network pharmacology allows expecting that a proper integration of the intrinsic complexity of epileptic pathology in AED discovery might result in literally anti-epileptic drugs.

Identifying targets for preventing epilepsy using systems biology

While there are a plethora of medications that block seizures, these same drugs have little effect on preventing or curing epilepsy. This suggests that the molecular pathways for epileptogenesis are distinct from those that produce acute seizures and therefore will require the identification of novel truly 'antiepileptic' therapeutics. Identification and testing of potential antiepileptic drug targets first in animal models and then in humans is thus becoming an important next step in the battle against epilepsy. In focal forms of human epilepsy the battle, however, is complicated by the large and varied types of brain abnormalities capable of producing a state of chronic, recurrent seizures. Unfortunately, once the epileptic state develops, it often persists to produce a life-long seizure disorder that can only be suppressed by anticonvulsant medications, and cured only in some through surgical resection of the seizure focus. While deductive approaches to drug target identification use our current state of knowledge, based mostly on animal models of epileptogenesis, a growing reductionist approach often referred to as systems biology takes advantage of newer high-throughput technologies to profile large numbers and types of molecules simultaneously. Some of these approaches, such as functional genomics, proteomics, and metabolomics have been undertaken in both human and animal epileptic brain tissues and are beginning to hone in on new therapeutic targets. While these methods are highly sensitive, this same sensitivity also produces a high rate of false positives due to variables other than those of interest. The experimental design, therefore, needs to be tightly controlled to reduce these unintended results that can be misleading. Most importantly, epileptogenic targets need to be validated in animal models of epileptogenesis, so that, if successful, these new methods have the potential to identify unbiased, important new therapeutics.