What do genetic studies tell us about the heritable basis of common epilepsy? Polygenic or complex epilepsy?

Common epilepsy variants from the general population are not associated with epilepsy among individuals with tuberous sclerosis complex

Common genetic variants identified in the general population have been found to increase phenotypic risks among individuals with certain genetic conditions. Up to 90% of individuals with tuberous sclerosis complex (TSC) are affected by some type of epilepsy, yet the common variants contributing to epilepsy risk in the general population have not been evaluated in the context of TSC-associated epilepsy. Such knowledge is important to help uncover the underlying pathogenesis of epilepsy in TSC which is not fully understood, and critical as uncontrolled epilepsy is a major problem in this population. To evaluate common genetic modifiers of epilepsy, our study pooled phenotypic and genotypic data from 369 individuals with TSC to evaluate known and novel epilepsy common variants. We did not find evidence of enhanced genetic penetrance for known epilepsy variants identified across the largest genome-wide association studies of epilepsy in the general population, but identified support for novel common epilepsy variants in the context of TSC. Specifically, we have identified a novel signal in SLC7A1 that may be functionally involved in pathways relevant to TSC and epilepsy. Our study highlights the need for further evaluation of genetic modifiers in TSC to aid in further understanding of epilepsy in TSC and improve outcomes.

Clinically significant changes in genes and variants associated with epilepsy over time: implications for re-analysis

Despite the significant advances in understanding the genetic architecture of epilepsy, many patients do not receive a molecular diagnosis after genomic testing. Re-analysing existing genomic data has emerged as a potent method to increase diagnostic yields-providing the benefits of genomic-enabled medicine to more individuals afflicted with a range of different conditions. The primary drivers for these new diagnoses are the discovery of novel gene-disease and variants-disease relationships; however, most decisions to trigger re-analysis are based on the passage of time rather than the accumulation of new knowledge. To explore how our understanding of a specific condition changes and how this impacts re-analysis of genomic data from epilepsy patients, we developed Vigelint. This approach combines the information from PanelApp and ClinVar to characterise how the clinically relevant genes and causative variants available to laboratories change over time, and this approach to five clinical-grade epilepsy panels. Applying the Vigelint pipeline to these panels revealed highly variable patterns in new, clinically relevant knowledge becoming publicly available. This variability indicates that a more dynamic approach to re-analysis may benefit the diagnosis and treatment of epilepsy patients. Moreover, this work suggests that Vigelint can provide empirical data to guide more nuanced, condition-specific approaches to re-analysis.

Network-based analysis predicts interacting genetic modifiers from a meta-mapping study of spike-wave discharge in mice

Absence seizures are characterized by brief lapses in awareness accompanied by a hallmark spike-and-wave discharge (SWD) electroencephalographic pattern and are common to genetic generalized epilepsies (GGEs). While numerous genes have been associated with increased risk, including some Mendelian forms with a single causal allele, most cases of GGE are idiopathic and there are many unknown genetic modifiers of GGE influencing risk and severity. In a previous meta-mapping study, crosses between transgenic C57BL/6 and C3HeB/FeJ strains, each carrying one of three SWD-causing mutations (Gabrg2tm1Spet(R43Q) , Scn8a8j or Gria4spkw1 ), demonstrated an antagonistic epistatic interaction between loci on mouse chromosomes 2 and 7 influencing SWD. These results implicate universal modifiers in the B6 background that mitigate SWD severity through a common pathway, independent of the causal mutation. In this study, we prioritized candidate modifiers in these interacting loci. Our approach integrated human genome-wide association results with gene interaction networks and mouse brain gene expression to prioritize candidate genes and pathways driving variation in SWD outcomes. We considered candidate genes that are functionally associated with human GGE risk genes and genes with evidence for coding or non-coding allele effects between the B6 and C3H backgrounds. Our analyses output a summary ranking of gene pairs, one gene from each locus, as candidates for explaining the epistatic interaction. Our top-ranking gene pairs implicate microtubule function, cytoskeletal stability and cell cycle regulation as novel hypotheses about the source of SWD variation across strain backgrounds, which could clarify underlying mechanisms driving differences in GGE severity in humans.

The evolution of comprehensive genetic analysis in neurology: Implications for precision medicine

Technological advancements have facilitated the availability of reliable and thorough genetic analysis in many medical fields, including neurology. In this review, we focus on the importance of selecting the appropriate genetic test to aid in the accurate identification of disease utilizing currently employed technologies for analyzing monogenic neurological disorders. Moreover, the applicability of comprehensive analysis via NGS for various genetically heterogeneous neurological disorders is reviewed, revealing its efficiency in clarifying a frequently cloudy diagnostic picture and delivering a conclusive and solid diagnosis that is essential for the proper management of the patient. The feasibility and effectiveness of medical genetics in neurology require interdisciplinary cooperation among several medical specialties and geneticists, to select and perform the most relevant test according to each patient's medical history, using the most appropriate technological tools. The prerequisites for a comprehensive genetic analysis are discussed, highlighting the utility of appropriate gene selection, variant annotation, and classification. Moreover, genetic counseling and interdisciplinary collaboration could improve diagnostic yield further. Additionally, a sub-analysis is conducted on the 1,502,769 variation records with submitted interpretations in the Clinical Variation (ClinVar) database, with a focus on neurology-related genes, to clarify the value of suitable variant categorization. Finally, we review the current applications of genetic analysis in the diagnosis and personalized management of neurological patients and the advances in the research and scientific knowledge of hereditary neurological disorders that are evolving the utility of genetic analysis towards the individualization of the treatment strategy.

Translational veterinary epilepsy: A win-win situation for human and veterinary neurology

Epilepsy is a challenging multifactorial disorder with a complex genetic background. Our current understanding of the pathophysiology and treatment of epilepsy has substantially increased due to animal model studies, including canine studies, but additional basic and clinical research is required. Drug-resistant epilepsy is an important problem in both dogs and humans, since seizure freedom is not achieved with the available antiseizure medications. The evaluation and exploration of pharmacological and particularly non-pharmacological therapeutic options need to remain a priority in epilepsy research. Combined efforts and sharing knowledge and expertise between human medical and veterinary neurologists are important for improving the treatment outcomes or even curing epilepsy in dogs. Such interactions could offer an exciting approach to translate the knowledge gained from people and rodents to dogs and vice versa. In this article, a panel of experts discusses the similarities and knowledge gaps in human and animal epileptology, with the aim of establishing a common framework and the basis for future translational epilepsy research.

Genetic interaction between GABRA1 and ERBB4 variants in the pathogenesis of genetic generalized epilepsy

Epilepsy is a complex neurological disease that can be caused by both genetic and environmental factors. Many studies have been conducted to investigate the genetic risk variants and molecular mechanisms of epilepsy. Disruption of excitation-inhibition balance (E/I balance) is one of the widely accepted disease mechanisms of epilepsy. The maintenance of E/I balance is an intricate process that is governed by multiple proteins. Using whole exome sequencing (WES), we identified a novel GABRA1 c.448G>A (p.E150K) variant and ERBB4 c.1972A>T (p.I658F, rs190654033) variant in a Malaysian Chinese family with genetic generalized epilepsy (GGE). The GGE may be triggered by dysregulation of E/I balance mechanism. Segregation of the variants in the family was verified by Sanger sequencing. All family members with GGE inherited both variants. However, family members who carried only one of the variants did not show any symptoms of GGE. Both the GABRA1 and ERBB4 variants were predicted damaging by MutationTaster and CADD, and protein structure analysis showed that the variants had resulted in the formation of additional hydrogen bonds in the mutant proteins. GABRA1 variant could reduce the efficiency of GABA_A receptors, and constitutively active ERBB4 receptors caused by the ERBB4 variant promote internalization of GABA_A receptors. The interaction between the two variants may cause a greater disruption in E/I balance, which is more likely to induce a seizure. Nevertheless, this disease model was derived from a single small family, further studies are still needed to confirm the verifiability of the purported disease model.

Identification of RNA N6-methyladenosine regulation in epilepsy: Significance of the cell death mode, glycometabolism, and drug reactivity

Epilepsy, a functional disease caused by abnormal discharge of neurons, has attracted the attention of neurologists due to its complex characteristics. N6-methyladenosine (m6A) is a reversible mRNA modification that plays essential role in various biological processes. Nevertheless, no previous study has systematically evaluated the role of m6A regulators in epilepsy. Here, using gene expression screening in the Gene Expression Omnibus GSE143272, we identified seven significant m6A regulator genes in epileptic and non-epileptic patients. The random forest (RF) model was applied to the screening, and seven m6A regulators (HNRNPC, WATP, RBM15, YTHDC1, YTHDC2, CBLL1, and RBMX) were selected as the candidate genes for predicting the risk of epilepsy. A nomogram model was then established based on the seven-candidate m6A regulators. Decision curve analysis preliminarily showed that patients with epilepsy could benefit from the nomogram model. The consensus clustering method was performed to divide patients with epilepsy into two m6A patterns (clusterA and clusterB) based on the selected significant m6A regulators. Principal component analysis algorithms were constructed to calculate the m6A score for each sample to quantify the m6A patterns. Patients in clusterB had higher m6A scores than those in clusterA. Furthermore, the patients in each cluster had unique immune cell components and different cell death patterns. Meanwhile, based on the M6A classification, a correlation between epilepsy and glucose metabolism was laterally verified. In conclusion, the m6A regulation pattern plays a vital role in the pathogenesis of epilepsy. The research on m6A regulatory factors will play a key role in guiding the immune-related treatment, drug selection, and identification of metabolism conditions and mechanisms of epilepsy in the future.

Rodent Models of Audiogenic Epilepsy: Genetic Aspects, Advantages, Current Problems and Perspectives

Animal models of epilepsy are of great importance in epileptology. They are used to study the mechanisms of epileptogenesis, and search for new genes and regulatory pathways involved in the development of epilepsy as well as screening new antiepileptic drugs. Today, many methods of modeling epilepsy in animals are used, including electroconvulsive, pharmacological in intact animals, and genetic, with the predisposition for spontaneous or refractory epileptic seizures. Due to the simplicity of manipulation and universality, genetic models of audiogenic epilepsy in rodents stand out among this diversity. We tried to combine data on the genetics of audiogenic epilepsy in rodents, the relevance of various models of audiogenic epilepsy to certain epileptic syndromes in humans, and the advantages of using of rodent strains predisposed to audiogenic epilepsy in current epileptology.

The Seizure-Associated Genes Across Species (SAGAS) database offers insights into epilepsy genes, pathways and treatments

OBJECTIVE

Decades of genetic studies on people with many different epilepsies, and on many nonhuman species, using many different technologies, have generated a huge body of literature about the genes associated with seizures/epilepsy. Collating these data can help uncover epilepsy genes, pathways, and treatments that would otherwise be overlooked. We aimed to collate and structure these data into a database, and use the database to identify novel epilepsy genes and pathways, and to prioritize promising treatments.

METHODS

We collated all the genes associated with all types of seizures/epilepsy in all species, and quantified the supporting evidence for each gene, by manually screening ~10 000 publications, and by extracting data from existing databases.

RESULTS

The largest published dataset of epilepsy genes includes only 977 genes, whereas our database (www.sagas.ac) includes 2876 genes, which demonstrates that the number of genes that can potentially contribute to seizures/epilepsy is much higher than previously envisaged. We use our database to identify 12 hitherto unreported polygenic epilepsy genes, 479 high-confidence monogenic epilepsy genes, and 394 more biological pathways than identified using the previously largest epilepsy gene dataset. We use a unique feature of Seizure-Associated Genes Across Species-the number of citations for each gene-to demonstrate that a drug is more likely to affect seizures if there is more evidence that the genes it affects are associated with seizures, and we use these data to identify promising candidate antiseizure drugs.

SIGNIFICANCE

This database offers insights into the causes of epilepsy and its treatments, and can accelerate future epilepsy research.

Combined electrophysiological and morphological phenotypes in patients with genetic generalized epilepsy and their healthy siblings

OBJECTIVE

Genetic generalized epilepsy is characterized by aberrant neuronal dynamics and subtle structural alterations. We evaluated whether a combination of magnetic and electrical neuronal signals and cortical thickness would provide complementary information about network pathology in GGE. We also investigated if these imaging phenotypes were present in healthy siblings of the patients to test for genetic influence.

METHODS

In this cross-sectional study, we analyzed five minutes of resting-state data acquired using electroencephalography (EEG) and magnetoencephalography (MEG) in patients, their siblings, and controls, matched for age and sex. We computed source-reconstructed power and connectivity in six frequency bands (1-40 Hz) and cortical thickness (derived from magnetic resonance imaging (MRI)). Group differences were assessed using permutation analysis of linear models for each modality separately and jointly for all modalities using a non-parametric combination.

RESULTS

Patients with GGE (n = 23) had higher power than controls (n = 35) in all frequencies, with a more posterior focus in MEG than EEG. Connectivity was also increased, particularly in frontotemporal and central regions in theta (strongest in EEG) and low beta frequencies (strongest in MEG), which was eminent in the joint EEG/MEG analysis. EEG showed weaker connectivity differences in higher frequencies, possibly related to drug effects. The inclusion of cortical thickness reinforced group differences in connectivity and power. Siblings (n = 18) had functional and structural patterns intermediate between those of patients and controls.

SIGNIFICANCE

EEG detected increased connectivity and power in GGE similar to MEG, but with different spectral sensitivity, highlighting the importance of theta and beta oscillations. Cortical thickness reductions in GGE corresponded to functional imaging patterns. Our multimodal approach extends the understanding of the resting-state in GGE and points to genetic underpinnings of the imaging markers studied, providing new insights into the causes and consequences of epilepsy.

Respiratory alkalosis provokes spike-wave discharges in seizure-prone rats

Hyperventilation reliably provokes seizures in patients diagnosed with absence epilepsy. Despite this predictable patient response, the mechanisms that enable hyperventilation to powerfully activate absence seizure-generating circuits remain entirely unknown. By utilizing gas exchange manipulations and optogenetics in the WAG/Rij rat, an established rodent model of absence epilepsy, we demonstrate that absence seizures are highly sensitive to arterial carbon dioxide, suggesting that seizure-generating circuits are sensitive to pH. Moreover, hyperventilation consistently activated neurons within the intralaminar nuclei of the thalamus, a structure implicated in seizure generation. We show that intralaminar thalamus also contains pH-sensitive neurons. Collectively, these observations suggest that hyperventilation activates pH-sensitive neurons of the intralaminar nuclei to provoke absence seizures.

Using common genetic variants to find drugs for common epilepsies

Better drugs are needed for common epilepsies. Drug repurposing offers the potential of significant savings in the time and cost of developing new treatments. In order to select the best candidate drug(s) to repurpose for a disease, it is desirable to predict the relative clinical efficacy that drugs will have against the disease. Common epilepsy can be divided into different types and syndromes. Different antiseizure medications are most effective for different types and syndromes of common epilepsy. For predictions of antiepileptic efficacy to be clinically translatable, it is essential that the predictions are specific to each form of common epilepsy, and reflect the patterns of drug efficacy observed in clinical studies and practice. These requirements are not fulfilled by previously published drug predictions for epilepsy. We developed a novel method for predicting the relative efficacy of drugs against any common epilepsy, by using its Genome-Wide Association Study summary statistics and drugs' activity data. The methodological advancement in our technique is that the drug predictions for a disease are based upon drugs' effects on the function and abundance of proteins, and the magnitude and direction of those effects, relative to the importance, degree and direction of the proteins' dysregulation in the disease. We used this method to predict the relative efficacy of all drugs, licensed for any condition, against each of the major types and syndromes of common epilepsy. Our predictions are concordant with findings from real-world experience and randomized clinical trials. Our method predicts the efficacy of existing antiseizure medications against common epilepsies; in this prediction, our method outperforms the best alternative existing method: area under receiver operating characteristic curve (mean ± standard deviation) 0.83 ± 0.03 and 0.63 ± 0.04, respectively. Importantly, our method predicts which antiseizure medications are amongst the more efficacious in clinical practice, and which antiseizure medications are amongst the less efficacious in clinical practice, for each of the main syndromes of common epilepsy, and it predicts the distinct order of efficacy of individual antiseizure medications in clinical trials of different common epilepsies. We identify promising candidate drugs for each of the major syndromes of common epilepsy. We screen five promising predicted drugs in an animal model: each exerts a significant dose-dependent effect upon seizures. Our predictions are a novel resource for selecting suitable candidate drugs that could potentially be repurposed for each of the major syndromes of common epilepsy. Our method is potentially generalizable to other complex diseases.

Transcriptome of the Krushinsky-Molodkina Audiogenic Rat Strain and Identification of Possible Audiogenic Epilepsy-Associated Genes

Audiogenic epilepsy (AE), inherent to several rodent strains is widely studied as a model of generalized convulsive epilepsy. The molecular mechanisms that determine the manifestation of AE are not well understood. In the present work, we compared transcriptomes from the corpora quadrigemina in the midbrain zone, which are crucial for AE development, to identify genes associated with the AE phenotype. Three rat strains without sound exposure were compared: Krushinsky-Molodkina (KM) strain (100% AE-prone); Wistar outbred rat strain (non-AE prone) and “0” strain (partially AE-prone), selected from F2 KM × Wistar hybrids for their lack of AE. The findings showed that the KM strain gene expression profile exhibited a number of characteristics that differed from those of the Wistar and “0” strain profiles. In particular, the KM rats showed increased expression of a number of genes involved in the positive regulation of the MAPK signaling cascade and genes involved in the positive regulation of apoptotic processes. Another characteristic of the KM strain which differed from that of the Wistar and “0” rats was a multi-fold increase in the expression level of the Ttr gene and a significant decrease in the expression of the Msh3 gene. Decreased expression of a number of oxidative phosphorylation-related genes and a few other genes was also identified in the KM strain. Our data confirm the complex multigenic nature of AE inheritance in rodents. A comparison with data obtained from other independently selected AE-prone rodent strains suggests some common causes for the formation of the audiogenic phenotype.

Genome sequencing identifies rare tandem repeat expansions and copy number variants in Lennox-Gastaut syndrome

Epilepsies are a group of common neurological disorders with a substantial genetic basis. Despite this, the molecular diagnosis of epilepsies remains challenging due to its heterogeneity. Studies utilizing whole-genome sequencing may provide additional insights into genetic causes of epilepsies of unknown aetiology. Whole-genome sequencing was used to evaluate a cohort of adults with unexplained developmental and epileptic encephalopathies (n = 30), for whom prior genetic tests, including whole-exome sequencing in some cases, were negative or inconclusive. Rare single nucleotide variants, insertions/deletions, copy number variants and tandem repeat expansions were analysed. Seven pathogenic or likely pathogenic single nucleotide variants, and two pathogenic deleterious copy number variants were identified in nine patients (32.1% of the cohort). One of the copy number variants, identified in a patient with Lennox–Gastaut syndrome, was too small to be detected by chromosomal microarray techniques. We also identified two tandem repeat expansions with clinical implications in two other patients with Lennox–Gastaut syndrome: a CGG repeat expansion in the 5′untranslated region of DIP2B, and a CTG expansion in ATXN8OS (previously implicated in spinocerebellar ataxia type 8). Three patients had KCNA2 pathogenic variants. One of them died of sudden unexpected death in epilepsy. The other two patients had, in addition to a KCNA2 variant, a second de novo variant impacting potential epilepsy-relevant genes (KCNIP4 and UBR5). Overall, whole-genome sequencing provided a genetic explanation in 32.1% of the total cohort. This is also the first report of coding and non-coding tandem repeat expansions identified in patients with Lennox–Gastaut syndrome. This study demonstrates that using whole-genome sequencing, the examination of multiple types of rare genetic variation, including those found in the non-coding region of the genome, can help resolve unexplained epilepsies.

Genome-Wide Meta-Analysis Identifies Two Novel Risk Loci for Epilepsy

Epilepsy (affects about 70 million people worldwide) is one of the most prevalent brain disorders and imposes a huge economic burden on society. Epilepsy has a strong genetic component. In this study, we perform the largest genome-wide meta-analysis of epilepsy (N = 8,00,869 subjects) by integrating four large-scale genome-wide association studies (GWASs) of epilepsy. We identified three genome-wide significant (GWS) (p < 5 × 10^–8) risk loci for epilepsy. The risk loci on 7q21.11 [lead single nucleotide polymorphism (SNP) rs11978015, p = 9.26 × 10^–9] and 8p23.1 (lead SNP rs28634186, p = 4.39 × 10^–8) are newly identified in the present study. Of note, rs11978015 resides in upstream of GRM3, which encodes glutamate metabotropic receptor 3. GRM3 has pivotal roles in neurotransmission and is involved in most aspects of normal brain function. In addition, we also identified three genes (TTC21B, RP11-375N15.2, and TNKS) whose cis-regulated expression level are associated with epilepsy, indicating that risk variants may confer epilepsy risk through regulating the expression of these genes. Our study not only provides new insights into genetic architecture of epilepsy but also prioritizes potential molecular targets (including GRM3 and TTC21B) for development of new drugs and therapeutics for epilepsy.

Genetics in Epilepsy

The presence of unprovoked, recurrent seizures, particularly when drug resistant and associated with cognitive and behavioral deficits, warrants investigation for an underlying genetic cause. This article provides an overview of the major classes of genes associated with epilepsy phenotypes divided into functional categories along with the recommended work-up and therapeutic considerations. Gene discovery in epilepsy supports counseling and anticipatory guidance but also opens the door for precision medicine guiding therapy with a focus on those with disease-modifying effects.

New avenues in molecular genetics for the diagnosis and application of therapeutics to the epilepsies

Genetic epidemiology studies have shown that most epilepsies involve some genetic cause. In addition, twin studies have helped strengthen the hypothesis that in most patients with epilepsy, a complex inheritance is involved. More recently, with the development of high-density single-nucleotide polymorphism (SNP) microarrays and next-generation sequencing (NGS) technologies, the discovery of genes related to the epilepsies has accelerated tremendously. Especially, the use of whole exome sequencing (WES) has had a considerable impact on the identification of rare genetic variants with large effect sizes, including inherited or de novo mutations in severe forms of childhood epilepsies. The identification of pathogenic variants in patients with these childhood epilepsies provides many benefits for patients and families, such as the confirmation of the genetic nature of the diseases. This process will allow for better genetic counseling, more accurate therapy decisions, and a significant positive emotional impact. However, to study the genetic component of the more common forms of epilepsy, the use of high-density SNP arrays in genome-wide association studies (GWAS) seems to be the strategy of choice. As such, researchers can identify loci containing genetic variants associated with the common forms of epilepsy. The knowledge generated over the past two decades about the effects of the mutations that cause the monogenic epilepsy is tremendous; however, the scientific community is just starting to apply this information in order to generate better target treatments.

Heritability of Magnetoencephalography Phenotypes Among Patients With Genetic Generalized Epilepsy and Their Siblings

Objective

To assess whether neuronal signals in patients with genetic generalized epilepsy (GGE) are heritable, we examined magnetoencephalography resting-state recordings in patients and their healthy siblings.

Methods

In a prospective, cross-sectional design, we investigated source-reconstructed power and functional connectivity in patients, siblings, and controls. We analyzed 5 minutes of cleaned and awake data without epileptiform discharges in 6 frequency bands (1–40 Hz). We further calculated intraclass correlations to estimate heritability for the imaging patterns within families.

Results

Compared with controls (n = 45), patients with GGE (n = 25) showed widespread increased functional connectivity (θ to γ frequency bands) and power (δ to γ frequency bands) across the spectrum. Siblings (n = 18) fell between the levels of patients and controls. Heritability of the imaging metrics was observed in regions where patients strongly differed from controls, mainly in β frequencies, but also for δ and θ power. Network connectivity in GGE was heritable in frontal, central, and inferior parietal brain areas and power in central, temporo-parietal, and subcortical structures. Presence of generalized spike-wave activity during recordings and medication were associated with the network patterns, whereas other clinical factors such as age at onset, disease duration, or seizure control were not.

Conclusion

Metrics of brain oscillations are well suited to characterize GGE and likely relate to genetic factors rather than the active disease or treatment. High power and connectivity levels co-segregated in patients with GGE and healthy siblings, predominantly in the β band, representing an endophenotype of GGE.

Modelling epilepsy in the mouse: challenges and solutions

In most mouse models of disease, the outward manifestation of a disorder can be measured easily, can be assessed with a trivial test such as hind limb clasping, or can even be observed simply by comparing the gross morphological characteristics of mutant and wild-type littermates. But what if we are trying to model a disorder with a phenotype that appears only sporadically and briefly, like epileptic seizures? The purpose of this Review is to highlight the challenges of modelling epilepsy, in which the most obvious manifestation of the disorder, seizures, occurs only intermittently, possibly very rarely and often at times when the mice are not under direct observation. Over time, researchers have developed a number of ways in which to overcome these challenges, each with their own advantages and disadvantages. In this Review, we describe the genetics of epilepsy and the ways in which genetically altered mouse models have been used. We also discuss the use of induced models in which seizures are brought about by artificial stimulation to the brain of wild-type animals, and conclude with the ways these different approaches could be used to develop a wider range of anti-seizure medications that could benefit larger patient populations.

Summary: This Review discusses the challenges of modelling epilepsy in mice, a condition in which the outward manifestation of the disorder appears only sporadically, and reviews possible solutions encompassing both genetic and induced models.

Exome sequencing in genetic disease: recent advances and considerations

Over the past decade, exome sequencing (ES) has allowed significant advancements to the field of disease research. By targeting the protein-coding regions of the genome, ES combines the depth of knowledge on protein-altering variants with high-throughput data generation and ease of analysis. New discoveries continue to be made using ES, and medical science has benefitted both theoretically and clinically from its continued use. In this review, we describe recent advances and successes of ES in disease research. Through selected examples of recent publications, we explore how ES continues to be a valuable tool to find variants that might explain disease etiology or provide insight into the biology underlying the disease. We then discuss shortcomings of ES in terms of variant discoveries made by other sequencing technologies that would be missed because of the scope and techniques of ES. We conclude with a brief outlook on the future of ES, suggesting that although newer and more thorough sequencing methods will soon supplant ES, its results will continue to be useful for disease research.

Polygenic risk scores of several subtypes of epilepsies in a founder population

Objective

Polygenic risk scores (PRSs) are used to quantify the cumulative effects of a number of genetic variants, which may individually have a very small effect on susceptibility to a disease; we used PRSs to better understand the genetic contribution to common epilepsy and its subtypes.

Methods

We first replicated previous single associations using 373 unrelated patients. We then calculated PRSs in the same French Canadian patients with epilepsy divided into 7 epilepsy subtypes and population-based controls. We fitted a logistic mixed model to calculate the variance explained by the PRS using pseudo-R² statistics.

Results

We show that the PRS explains more of the variance in idiopathic generalized epilepsy than in patients with nonacquired focal epilepsy. We also demonstrate that the variance explained is different within each epilepsy subtype.

Conclusions

Globally, we support the notion that PRSs provide a reliable measure to rightfully estimate the contribution of genetic factors to the pathophysiologic mechanism of epilepsies, but further studies are needed on PRSs before they can be used clinically.

Analysis of gene variants in the GASH/Sal model of epilepsy

Epilepsy is a complex neurological disorder characterized by sudden and recurrent seizures, which are caused by various factors, including genetic abnormalities. Several animal models of epilepsy mimic the different symptoms of this disorder. In particular, the genetic audiogenic seizure hamster from Salamanca (GASH/Sal) animals exhibit sound-induced seizures similar to the generalized tonic seizures observed in epileptic patients. However, the genetic alterations underlying the audiogenic seizure susceptibility of the GASH/Sal model remain unknown. In addition, gene variations in the GASH/Sal might have a close resemblance with those described in humans with epilepsy, which is a prerequisite for any new preclinical studies that target genetic abnormalities. Here, we performed whole exome sequencing (WES) in GASH/Sal animals and their corresponding controls to identify and characterize the mutational landscape of the GASH/Sal strain. After filtering the results, moderate- and high-impact variants were validated by Sanger sequencing, assessing the possible impact of the mutations by “in silico” reconstruction of the encoded proteins and analyzing their corresponding biological pathways. Lastly, we quantified gene expression levels by RT-qPCR. In the GASH/Sal model, WES showed the presence of 342 variations, in which 21 were classified as high-impact mutations. After a full bioinformatics analysis to highlight the high quality and reliable variants, the presence of 3 high-impact and 15 moderate-impact variants were identified. Gene expression analysis of the high-impact variants of Asb14 (ankyrin repeat and SOCS Box Containing 14), Msh3 (MutS Homolog 3) and Arhgef38 (Rho Guanine Nucleotide Exchange Factor 38) genes showed a higher expression in the GASH/Sal than in control hamsters. In silico analysis of the functional consequences indicated that those mutations in the three encoded proteins would have severe functional alterations. By functional analysis of the variants, we detected 44 significantly enriched pathways, including the glutamatergic synapse pathway. The data show three high-impact mutations with a major impact on the function of the proteins encoded by these genes, although no mutation in these three genes has been associated with some type of epilepsy until now. Furthermore, GASH/Sal animals also showed gene variants associated with different types of epilepsy that has been extensively documented, as well as mutations in other genes that encode proteins with functions related to neuronal excitability, which could be implied in the phenotype of the GASH/Sal. Our findings provide valuable genetic and biological pathway data associated to the genetic burden of the audiogenic seizure susceptibility and reinforce the need to validate the role of each key mutation in the phenotype of the GASH/Sal model.

Quantitative structure-activity relationship models for compounds with anticonvulsant activity

Introduction: Third-generation antiepileptic drugs have seemingly failed to improve the global figures of seizure control and can still be regarded as symptomatic treatments. Quantitative structure-activity relationships (QSAR) can be used to guide hit-to-lead and lead optimization projects and applied to the large-scale virtual screening of chemical libraries. Areas covered: In this review, the authors cover reports on QSAR models related to antiepileptic drugs and drug targets in epilepsy, analyzing whether they refer to classic or non-classic QSAR and if they apply QSAR as a descriptive or predictive approach, among other considerations. The article finally focuses on a more detailed discussion of those predictive studies which include some sort of experimental validation, i.e. papers in which the reported models have been used to identify novel active compounds which have been tested in vitro and/or in vivo. Expert opinion: There are significant opportunities to apply the QSAR methodology to assist the discovery of more efficacious antiepileptic drugs. Considering the intrinsic complexity of the disorder, such applications should focus on state-of-the-art approximations (e.g. systemic, multi-target and multi-scale QSAR as well as ensemble and deep learning) and modeling the effects on novel drug targets and modern screening tools.

Epilepsy in adults

Epilepsy is one of the most common serious brain conditions, affecting over 70 million people worldwide. Its incidence has a bimodal distribution with the highest risk in infants and older age groups. Progress in genomic technology is exposing the complex genetic architecture of the common types of epilepsy, and is driving a paradigm shift. Epilepsy is a symptom complex with multiple risk factors and a strong genetic predisposition rather than a condition with a single expression and cause. These advances have resulted in the new classification of epileptic seizures and epilepsies. A detailed clinical history and a reliable eyewitness account of a seizure are the cornerstones of the diagnosis. Ancillary investigations can help to determine cause and prognosis. Advances in brain imaging are helping to identify the structural and functional causes and consequences of the epilepsies. Comorbidities are increasingly recognised as important aetiological and prognostic markers. Antiseizure medication might suppress seizures in up to two-thirds of all individuals but do not alter long-term prognosis. Epilepsy surgery is the most effective way to achieve long-term seizure freedom in selected individuals with drug-resistant focal epilepsy, but it is probably not used enough. With improved understanding of the gradual development of epilepsy, epigenetic determinants, and pharmacogenomics comes the hope for better, disease-modifying, or even curative, pharmacological and non-pharmacological treatment strategies. Other developments are clinical implementation of seizure detection devices and new neuromodulation techniques, including responsive neural stimulation.

Genome-wide mega-analysis identifies 16 loci and highlights diverse biological mechanisms in the common epilepsies

The epilepsies affect around 65 million people worldwide and have a substantial missing heritability component. We report a genome-wide mega-analysis involving 15,212 individuals with epilepsy and 29,677 controls, which reveals 16 genome-wide significant loci, of which 11 are novel. Using various prioritization criteria, we pinpoint the 21 most likely epilepsy genes at these loci, with the majority in genetic generalized epilepsies. These genes have diverse biological functions, including coding for ion-channel subunits, transcription factors and a vitamin-B6 metabolism enzyme. Converging evidence shows that the common variants associated with epilepsy play a role in epigenetic regulation of gene expression in the brain. The results show an enrichment for monogenic epilepsy genes as well as known targets of antiepileptic drugs. Using SNP-based heritability analyses we disentangle both the unique and overlapping genetic basis to seven different epilepsy subtypes. Together, these findings provide leads for epilepsy therapies based on underlying pathophysiology.

Epilepsies are common brain disorders and are classified based on clinical phenotyping, imaging and genetics. Here, the authors perform genome-wide association studies for 3 broad and 7 subtypes of epilepsy and identify 16 loci - 11 novel - that are further annotated by eQTL and partitioned heritability analyses.

Clinical and genetic study of Tunisian families with genetic generalized epilepsy: contribution of CACNA1H and MAST4 genes

Genetic generalized epilepsies (GGE) (childhood absence epilepsy (CAE), juvenile myoclonic epilepsy (JME) and epilepsy with generalized tonic-clonic seizures (GTCS)) are mainly determined by genetic factors. Since few mutations were identified in rare families with autosomal dominant GGE, a polygenic inheritance was suspected in most patients. Recent studies on large American or European cohorts of sporadic cases showed that susceptibility genes were numerous although their variants were rare, making their identification difficult. Here, we reported clinical and genetic characteristics of 30 Tunisian GGE families, including 71 GGE patients. The phenotype was close to that in sporadic cases. Nineteen pedigrees had a homogeneous type of GGE (JME-CAE-CGTS), and 11 combined these epileptic syndromes. Rare non-synonymous variants were selected in probands using a targeted panel of 30 candidate genes and their segregation was determined in families. Molecular studies incriminated different genes, mainly CACNA1H and MAST4. The segregation of at least two variants in different genes in some pedigrees was compatible with the hypothesis of an oligogenic inheritance, which was in accordance with the relatively low frequency of consanguineous probands. Since at least 2 susceptibility genes were likely shared by different populations, genetic factors involved in the majority of Tunisian GGE families remain to be discovered. Their identification should be easier in families with a homogeneous type of GGE, in which an intra-familial genetic homogeneity could be suspected.

[Trends and expectations the research on the molecular background of epileptic encephalopathies - state of the art in 2017]

Epilepsy is common neurological condition affecting 0.8-1% of the human population. Since 80% of patients are under 20 years of age, it is mainly a disease of the developmental period. The causes of epilepsy are heterogeneous, but the disease has always been considered a genetic disorder, which no longer doubted. Epilepsy genetics has undergone a revolution since the discovery of the first gene responsible for epilepsy. This is mainly because of introduction of the next generation sequencing as research and diagnostic tool, and transition from studies of pedigrees with epilepsy to the analysis of cases of epileptic encephalopathies. In a short time more than 50 early infantile epileptic encephalopathies were recognized due to the causative genes. Whole exome or targeted panel sequencing has been used as a diagnostic tool with a diagnostic yield of about 30-40%. The "genetic diagnosis" that is obtained makes it possible to introduce targeted treatment in an increasing number of cases. Since epileptic encephalopaties are often regarded as the model disease for epilepsy, these therapeutic strategies can provide treatment for patients with common epilepsies.

The impact of genetic and experimental studies on classification and therapy of the epilepsies

Different types of epilepsy are associated with gene mutations, in which seizures can be the only symptom (genetic epilepsies) or be one of the elements of complex clinical pictures that are often progressive over time (epileptic or epileptogenic encephalopathies). In epileptogenic encephalopathies, epileptic seizures and other neurological and cognitive signs are symptoms of genetically determined neuropathological or neurochemical disorders. In epileptic encephalopathies, epileptic activity itself is thought to contribute to severe cognitive and behavioral impairments above and beyond what might be expected from the underlying pathology alone. The distinction is conceptually clear and clinically relevant, as the different categories have a different prognosis in terms of both epilepsy and associated neurological and cognitive picture, but the boundaries are sometimes difficult to define in the clinical practice. Here we review the genetic epilepsies from the clinician perspective. A monogenic inheritance has been defined only in a minority of idiopathic epilepsies making improper to rename genetic the category of idiopathic epilepsies, until the presumptive multigenic mechanism will be demonstrated. A search for gene mutations must be done in any patient with candidate genetic types of epilepsy or epileptic/epileptogenic encephalopathy (e.g. familial forms) to complete the diagnostic process, define the prognosis and optimize the therapy. Advanced methods are available to express the gene variant in experimental model systems and test its effect on the properties of the affected protein, on neuronal excitability and on phenotypes in model organisms, and may help in identifying treatments with compatible action mechanisms. The influence of genetic studies on epilepsy taxonomy is now a matter of discussion: their impact on the international classification of the epilepsies will hopefully be defined soon.