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

Spike-and-wave discharges of absence seizures in a sleep waves-constrained corticothalamic model

AIMS

Recurrent network activity in corticothalamic circuits generates physiological and pathological EEG waves. Many computer models have simulated spike-and-wave discharges (SWDs), the EEG hallmark of absence seizures (ASs). However, these models either provided detailed simulated activity only in a selected territory (i.e., cortical or thalamic) or did not test whether their corticothalamic networks could reproduce the physiological activities that are generated by these circuits.

METHODS

Using a biophysical large-scale corticothalamic model that reproduces the full extent of EEG sleep waves, including sleep spindles, delta, and slow (<1 Hz) waves, here we investigated how single abnormalities in voltage- or transmitter-gated channels in the neocortex or thalamus led to SWDs.

RESULTS

We found that a selective increase in the tonic γ-aminobutyric acid type A receptor (GABA-A) inhibition of first-order thalamocortical (TC) neurons or a selective decrease in cortical phasic GABA-A inhibition is sufficient to generate ~4 Hz SWDs (as in humans) that invariably start in neocortical territories. Decreasing the leak conductance of higher-order TC neurons leads to ~7 Hz SWDs (as in rodent models) while maintaining sleep spindles at 7-14 Hz.

CONCLUSION

By challenging key features of current mechanistic views, this simulated ictal corticothalamic activity provides novel understanding of ASs and makes key testable predictions.

Vulnerability of the Hippocampus to Insults: Links to Blood-Brain Barrier Dysfunction

The hippocampus is a critical brain substrate for learning and memory; events that harm the hippocampus can seriously impair mental and behavioral functioning. Hippocampal pathophysiologies have been identified as potential causes and effects of a remarkably diverse array of medical diseases, psychological disorders, and environmental sources of damage. It may be that the hippocampus is more vulnerable than other brain areas to insults that are related to these conditions. One purpose of this review is to assess the vulnerability of the hippocampus to the most prevalent types of insults in multiple biomedical domains (i.e., neuroactive pathogens, neurotoxins, neurological conditions, trauma, aging, neurodegenerative disease, acquired brain injury, mental health conditions, endocrine disorders, developmental disabilities, nutrition) and to evaluate whether these insults affect the hippocampus first and more prominently compared to other brain loci. A second purpose is to consider the role of hippocampal blood-brain barrier (BBB) breakdown in either causing or worsening the harmful effects of each insult. Recent research suggests that the hippocampal BBB is more fragile compared to other brain areas and may also be more prone to the disruption of the transport mechanisms that act to maintain the internal milieu. Moreover, a compromised BBB could be a factor that is common to many different types of insults. Our analysis indicates that the hippocampus is more vulnerable to insults compared to other parts of the brain, and that developing interventions that protect the hippocampal BBB may help to prevent or ameliorate the harmful effects of many insults on memory and cognition.

Identification of potential disease-associated variants in idiopathic generalized epilepsy using targeted sequencing

Many questions remain regarding the genetics of idiopathic generalized epilepsy (IGE), a subset of genetic generalized epilepsy (GGE). We aimed to identify the candidate coding variants of epilepsy panel genes in a cohort of affected individuals, using variant frequency information from a control cohort of the same region. We performed whole-exome sequencing analysis of 121 individuals and 10 affected relatives, focusing on variants of 950 candidate genes associated with epilepsy according to the Genes4Epilepsy curated panel. We identified 168 candidate variants (CVs) in 137 of 950 candidate genes in 88 of 121 affected individuals with IGE, of which 61 were novel variants. Notably, we identified five CVs in known GGE-associated genes (CHD2, GABRA1, RORB, SCN1A, and SCN1B) in five individuals and CVs shared by affected individuals in each of four family cases for other epilepsy candidate genes. The results of this study demonstrate that IGE is a disease with high heterogeneity and provide IGE-associated CVs whose pathogenicity should be proven by future studies, including advanced functional analysis. The low detection rate of CVs in the GGE-associated genes (4.1%) in this study suggests the current incompleteness of the Genes4Epilepsy panel for the diagnosis of IGE in clinical practice.

Causal relationship between coffee intake and neurological diseases: a Mendelian randomization study

BACKGROUND

Previous observational studies focused on the association of coffee consumption and neurological disease. However, it is not known whether these associations are causal.

METHODS

We used Mendelian randomization (MR) study to assess the causal relationship of coffee intake with the risk of neurological diseases, including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, multiple sclerosis, epilepsy, stroke, and migraine. Single-nucleotide polymorphisms (SNPs) which had genetic statistical significance with coffee intake were used as instrumental variable (IV). Genetic instruments were stretched from the MRC-IEU (MRC Integrative Epidemiology Unit) analysis on the UK Biobank. We performed MR analyses using the inverse variance weighted (IVW) method as the main approach. Sensitivity analyses were further performed using MR-Egger and MR-PRESSO to assess the robustness.

RESULTS

In the MR analysis, 40 SNPs were selected as IV, the F statistics for all SNPs ranged from 16 to 359. In IVW approach, our results provide genetic evidence supporting a potential causal association between coffee intake and a lower risk of migraine (OR = 0.528, 95% CI = 0.342-0.817, P = 0.004) and migraine with aura (OR = 0.374, 95% CI = 0.208-0.672, P = 0.001). However, we found no significant association between coffee intake and other neurological diseases along with their subtypes in this MR study.

CONCLUSION

Using genetic data, our MR study found significant evidence supporting a causal association between coffee intake and migraine. This suggests that coffee consumption is likely a trigger or a prevention strategy for migraine.

Identification of potential crucial genes and therapeutic targets for epilepsy

BACKGROUND

Epilepsy, a central neurological disorder, has a complex genetic architecture. There is some evidence suggesting that genetic factors play a role in both the occurrence of epilepsy and its treatment. However, the genetic determinants of epilepsy are largely unknown. This study aimed to identify potential therapeutic targets for epilepsy.

METHODS

Differentially expressed genes (DEGs) were extracted from the expression profiles of GSE44031 and GSE1834. Gene co-expression analysis was used to confirm the regulatory relationship between newly discovered epilepsy candidate genes and known epilepsy genes. Expression quantitative trait loci analysis was conducted to determine if epilepsy risk single-nucleotide polymorphisms regulate DEGs' expression in human brain tissue. Finally, protein-protein interaction analysis and drug-gene interaction analysis were performed to assess the role of DEGs in epilepsy treatment.

RESULTS

The study found that the protein tyrosine phosphatase receptor-type O gene (PTPRO) and the growth arrest and DNA damage inducible alpha gene (GADD45A) were significantly upregulated in epileptic rats compared to controls in both datasets. Gene co-expression analysis revealed that PTPRO was co-expressed with RBP4, NDN, PAK3, FOXG1, IDS, and IDS, and GADD45A was co-expressed with LRRK2 in human brain tissue. Expression quantitative trait loci analysis suggested that epilepsy risk single-nucleotide polymorphisms could be responsible for the altered PTPRO and GADD45A expression in human brain tissue. Moreover, the protein encoded by GADD45A had a direct interaction with approved antiepileptic drug targets, and GADD45A interacts with genistein and cisplatin.

CONCLUSIONS

The results of this study highlight PTPRO and GADD45A as potential genes for the diagnosis and treatment of epilepsy.

Genetic prediction of antihyperglycemic drug targets and risk of epilepsy: a mendelian randomisation study

A connection between diabetes and an increased risk of epilepsy has been suggested by observational studies. Animal studies have also shown that antihyperglycemic drugs can improve seizures. However, it is unclear whether antihyperglycemic drugs have a causal role in epilepsy in humans. To investigate this potential causal relationship, a Mendelian randomisation study was conducted using International League Against Epilepsy data as the discovery set and FinnGen data as the replication set. It was discovered that three antidiabetic drug target genes, ETFDH, CYP21A2 and CYP2D6, were involved in the occurrence of epilepsy. In particular, ETFDH was identified as a target gene in both the discovery set (inverse variance weighting [IVW], odds ratio [OR] = 1.018, 95% confidence interval [CI], 1.004-1.033, p = 0.009) and replication set (IVW, OR = 1.074, 95% CI, 1.034-1.114, p = 0.00016), and CYP21A2 was identified in the discovery set (IVW, OR = 1.029, 95% CI, 1.005-1.053, p = 0.016) and replication set (IVW, OR = 1.057, 95% CI, 1.001-1.116, p = 0.045) as having a causal association with an increased risk of epilepsy. Conversely, the CYP2D6 gene was found to be a protective factor for epilepsy in both the discovery set (IVW, OR = 0.0984, 95% CI, 0.969-0.998, p = 0.025) and replication set (IVW, OR = 0.977, 95% CI, 0.955-1.000, p = 0.046). A search of DrugBank revealed that metformin, an anti-glucose drug, is an inhibitor of the ETFDH gene and may have a potential therapeutic effect on epilepsy.

Neurostimulation for Generalized Epilepsy: Should Therapy be Syndrome-specific?

Current applications of neurostimulation for generalized epilepsy use a one-target-fits-all approach that is agnostic to the specific epilepsy syndrome and seizure type being treated. The authors describe similarities and differences between the 2 "archetypes" of generalized epilepsy-Lennox-Gastaut syndrome and Idiopathic Generalized Epilepsy-and review recent neuroimaging evidence for syndrome-specific brain networks underlying seizures. Implications for stimulation targeting and programming are discussed using 5 clinical questions: What epilepsy syndrome does the patient have? What brain networks are involved? What is the optimal stimulation target? What is the optimal stimulation paradigm? What is the plan for adjusting stimulation over time?

Assessment of bidirectional relationships between multiple sclerosis and epilepsy: A two-sample Mendelian randomization study

BACKGROUND AND OBJECTIVE

Epidemiological studies indicate that multiple sclerosis (MS) is associated with epilepsy. However, the causality and directionality of this association remain under-elucidated. This study aimed to reveal the causality between MS and epilepsy.

METHODS

A two-sample Mendelian randomization (MR) analysis was performed by using summarized statistics derived from large genome-wide association studies of MS and epilepsy. We used the inverse variance weighted method as the primary approach, and then four other MR methods to bidirectionally evaluate the causality of the association between MS and epilepsy. Additional sensitivity analyses were performed to measure the robustness of the findings.

RESULTS

Genetically predicted MS was positively correlated with developing all epilepsy [odds ratio (OR) = 1.027 (1.003-1.051), P  =  0.028] and generalized epilepsy [OR = 1.050 (1.008-1.094), P = 0.019]. In the reverse MR analysis, all epilepsy [OR = 1.310 (1.112-1.543), P = 0.001], generalized epilepsy [OR = 1.173 (1.010-1.363), P = 0.037], and focal epilepsy [OR = 1.264 (1.069-1.494), P  =  0.006] elevated the risk of developing MS. The result remained robust and congruous across all sensitivity analyses conducted.

CONCLUSIONS

MS is potentially associated with a higher risk of developing epilepsy. Furthermore, epilepsy may be a causal determinant of MS risk. These findings may further the understanding of the interaction of the two conditions.

Exploring causal correlations between systemic inflammatory cytokines and epilepsy: A bidirectional Mendelian randomization study

BACKGROUND

Inflammation plays a role in the development and advancement of epilepsy, but the relationship between inflammatory cytokines and epilepsy is still not well understood. Herein, we use two-sample Mendelian randomization (MR) to examine the causal association between systemic inflammatory cytokines and epilepsy.

METHODS

We conducted a bidirectional two-sample MR analysis based on genome-wide association study data of 41 serum cytokines from 8293 Finnish individuals with various epilepsy subtypes from the International League against Epilepsy Consortium.

RESULTS

Our study showed that three inflammatory cytokines were associated with epilepsy, five were associated with generalized epilepsy, four were associated with focal epilepsy, one was associated with focal epilepsy-documented lesion negative, three were associated with juvenile absence epilepsy, one was associated with childhood absence epilepsy, two were associated with focal epilepsy-documented lesion other than hippocampal sclerosis, and two were associated with juvenile myoclonic epilepsy. Furthermore, the expression of systemic inflammatory cytokines was unaffected by genetically predicted epilepsy.

CONCLUSION

This study suggested that several inflammatory cytokines are probably the factors correlated with epilepsy. Additional research is required to ascertain if these biomarkers have therapeutic potential to prevent or manage epilepsy.

Epilepsies

Recent advances in genetic diagnosis have revealed the underlying etiology of many epilepsies and have identified pathogenic, causative variants in numerous ion and ligand-gated channel genes. This chapter describes the clinical presentations of epilepsy associated with different channelopathies including classic electroclinical syndromes and emerging gene-specific phenotypes. Also discussed are the archetypal epilepsy channelopathy, SCN1A-Dravet syndrome, considering the expanding phenotype. Clinical presentations where a channelopathy is suspected, such as sleep-related hypermotor epilepsy and epilepsy in association with movement disorders, are reviewed. Channelopathies pose an intriguing problem for the development of gene therapies. Design of targeted therapies requires physiologic insights into the often multifaceted impact of a pathogenic variant, coupled with an understanding of the phenotypic spectrum of a gene. As gene-specific novel therapies come online for the channelopathies, it is essential that clinicians are able to recognize epilepsy phenotypes likely to be due to channelopathy and institute early genetic testing in both children and adults. These findings are likely to have immediate management implications and to inform prognostic and reproductive counseling.

Ketogenic diet therapy for pediatric epilepsy is associated with alterations in the human gut microbiome that confer seizure resistance in mice

The gut microbiome modulates seizure susceptibility and the anti-seizure effects of the ketogenic diet (KD) in animal models, but whether these relationships translate to KD therapies for human epilepsy is unclear. We find that the clinical KD alters gut microbial function in children with refractory epilepsy. Colonizing mice with KD-associated microbes promotes seizure resistance relative to matched pre-treatment controls. Select metagenomic and metabolomic features, including those related to anaplerosis, fatty acid β-oxidation, and amino acid metabolism, are seen with human KD therapy and preserved upon microbiome transfer to mice. Mice colonized with KD-associated gut microbes exhibit altered hippocampal transcriptomes, including pathways related to ATP synthesis, glutathione metabolism, and oxidative phosphorylation, and are linked to susceptibility genes identified in human epilepsy. Our findings reveal key microbial functions that are altered by KD therapies for pediatric epilepsy and linked to microbiome-induced alterations in brain gene expression and seizure protection in mice.

Causal relationship between telomere length and epilepsy: A bidirectional Mendelian randomization study

OBJECTIVE

Observational studies have suggested a link between telomere length (TL) and epilepsy, but the direction of the effect and whether it is causal or not is still being debated. The objective of this study was to investigate the causal relationship between TL and epilepsy using Mendelian randomization (MR) analysis.

METHODS

We performed a bidirectional two-sample MR analysis using pooled statistics from genome-wide association studies (GWAS) of TL and epilepsy. Additionally, we conducted a replication analysis using data from another GWAS study on epilepsy to validate our findings. The final results were analyzed using five MR methods, with the inverse-variance weighted (IVW) method as the primary outcome. We applied methods such as radial MR, MR pleiotropy residual and outlier test and MR Steiger filters to exclude outliers. Sensitivity analyses were also conducted to assess heterogeneity and pleiotropy.

RESULTS

Our analysis found no evidence of a causal relationship between epilepsy and TL (all p-values >0.05). The sensitivity analysis confirms the robustness of these results.

SIGNIFICANCE

In summary, our study contradicts existing observational reports by not finding any evidence to support a causal relationship between epilepsy and TL. Further research is necessary to determine the underlying mechanism behind the association observed in observational studies.

Mendelian randomization reveals no causal relationship between COVID-19 susceptibility, hospitalization, or severity and epilepsy

OBJECTIVE

Observational studies have shown an association between COVID-19 and epilepsy. However, causality remains unproven. This study aimed to investigate the causative effect of genetically predicted COVID-19 phenotypes on epilepsy risk using a two-sample Mendelian randomization (MR) analysis.

METHODS

We retrieved summary-level datasets for three COVID-19 phenotypes (COVID-19 susceptibility, COVID-19 hospitalization, and COVID-19 severity) and epilepsy from the genome-wide association studies conducted by the COVID-19 Host Genetics Initiative (COVID-19 HGI) and International League Against Epilepsy (ILAE) consortium, respectively. To analyze the final results, nine MR analytic methods were utilized. The inverse-variance weighted (IVW) method was chosen as the primary approach for data analysis to evaluate the potential causal effect. Other MR analytic methods (MR-Egger regression, weighted median estimator, mode based-estimator, and MR-PRESSO) were used as a supplement to IVW to ensure the robustness of the results.

RESULTS

The IVW approach demonstrated no causal association between any genetically predicted COVID-19 phenotype and the risk of epilepsy [COVID-19 susceptibility: odds ratio (OR) = 0.99, 95% confidence interval (CI) = 0.86-1.14, p = 0.92; COVID-19 hospitalization: OR = 1.00, 95% CI = 0.96-1.04, p = 0.95; COVID-19 severity: OR = 0.99, 95% CI = 0.96-1.01, p = 0.25]. Other MR complementary methods revealed consistent results. Additionally, no evidence for heterogeneity and horizontal pleiotropy was found.

SIGNIFICANCE

This MR study revealed no genetically predicted causal relationship between COVID-19 phenotypes and epilepsy.

Enhanced Membrane Incorporation of H289Y Mutant GluK1 Receptors from the Audiogenic Seizure-Prone GASH/Sal Model: Functional and Morphological Impacts on Xenopus Oocytes

Epilepsy is a neurological disorder characterized by abnormal neuronal excitability, with glutamate playing a key role as the predominant excitatory neurotransmitter involved in seizures. Animal models of epilepsy are crucial in advancing epilepsy research by faithfully replicating the diverse symptoms of this disorder. In particular, the GASH/Sal (genetically audiogenic seizure-prone hamster from Salamanca) model exhibits seizures resembling human generalized tonic-clonic convulsions. A single nucleotide polymorphism (SNP; C9586732T, p.His289Tyr) in the Grik1 gene (which encodes the kainate receptor GluK1) has been previously identified in this strain. The H289Y mutation affects the amino-terminal domain of GluK1, which is related to the subunit assembly and trafficking. We used confocal microscopy in Xenopus oocytes to investigate how the H289Y mutation, compared to the wild type (WT), affects the expression and cell-surface trafficking of GluK1 receptors. Additionally, we employed the two-electrode voltage-clamp technique to examine the functional effects of the H289Y mutation. Our results indicate that this mutation increases the expression and incorporation of GluK1 receptors into an oocyte's membrane, enhancing kainate-evoked currents, without affecting their functional properties. Although further research is needed to fully understand the molecular mechanisms responsible for this epilepsy, the H289Y mutation in GluK1 may be part of the molecular basis underlying the seizure-prone circuitry in the GASH/Sal model.

Polygenic risk scores as a marker for epilepsy risk across lifetime and after unspecified seizure events

A diagnosis of epilepsy has significant consequences for an individual but is often challenging in clinical practice. Novel biomarkers are thus greatly needed. Here, we investigated how common genetic factors (epilepsy polygenic risk scores, [PRSs]) influence epilepsy risk in detailed longitudinal electronic health records (EHRs) of > 360k Finns spanning up to 50 years of individuals' lifetimes. Individuals with a high genetic generalized epilepsy PRS (PRSGGE) in FinnGen had an increased risk for genetic generalized epilepsy (GGE) (hazard ratio [HR] 1.55 per PRSGGE standard deviation [SD]) across their lifetime and after unspecified seizure events. Effect sizes of epilepsy PRSs were comparable to effect sizes in clinically curated data supporting our EHR-derived epilepsy diagnoses. Within 10 years after an unspecified seizure, the GGE rate was 37% when PRSGGE > 2 SD compared to 5.6% when PRSGGE < -2 SD. The effect of PRSGGE was even larger on GGE subtypes of idiopathic generalized epilepsy (IGE) (HR 2.1 per SD PRSGGE). We further report significantly larger effects of PRSGGE on epilepsy in females and in younger age groups. Analogously, we found significant but more modest focal epilepsy PRS burden associated with non-acquired focal epilepsy (NAFE). We found PRSGGE specifically associated with GGE in comparison with >2000 independent diseases while PRSNAFE was also associated with other diseases than NAFE such as back pain. Here, we show that epilepsy specific PRSs have good discriminative ability after a first seizure event i.e. in circumstances where the prior probability of epilepsy is high outlining a potential to serve as biomarkers for an epilepsy diagnosis.

Identification of different MRI atrophy progression trajectories in epilepsy by subtype and stage inference

Artificial intelligence (AI)-based tools are widely employed, but their use for diagnosis and prognosis of neurological disorders is still evolving. Here we analyse a cross-sectional multicentre structural MRI dataset of 696 people with epilepsy and 118 control subjects. We use an innovative machine-learning algorithm, Subtype and Stage Inference, to develop a novel data-driven disease taxonomy, whereby epilepsy subtypes correspond to distinct patterns of spatiotemporal progression of brain atrophy.In a discovery cohort of 814 individuals, we identify two subtypes common to focal and idiopathic generalized epilepsies, characterized by progression of grey matter atrophy driven by the cortex or the basal ganglia. A third subtype, only detected in focal epilepsies, was characterized by hippocampal atrophy. We corroborate external validity via an independent cohort of 254 people and confirm that the basal ganglia subtype is associated with the most severe epilepsy.Our findings suggest fundamental processes underlying the progression of epilepsy-related brain atrophy. We deliver a novel MRI- and AI-guided epilepsy taxonomy, which could be used for individualized prognostics and targeted therapeutics.

Familial Mesial Temporal Lobe Epilepsy: Clinical Spectrum and Genetic Evidence for a Polygenic Architecture

OBJECTIVE

Familial mesial temporal lobe epilepsy (FMTLE) is an important focal epilepsy syndrome; its molecular genetic basis is unknown. Clinical descriptions of FMTLE vary between a mild syndrome with prominent déjà vu to a more severe phenotype with febrile seizures and hippocampal sclerosis. We aimed to refine the phenotype of FMTLE by analyzing a large cohort of patients and asked whether common risk variants for focal epilepsy and/or febrile seizures, measured by polygenic risk scores (PRS), are enriched in individuals with FMTLE.

METHODS

We studied 134 families with ≥ 2 first or second-degree relatives with temporal lobe epilepsy, with clear mesial ictal semiology required in at least one individual. PRS were calculated for 227 FMTLE cases, 124 unaffected relatives, and 16,077 population controls.

RESULTS

The age of patients with FMTLE onset ranged from 2.5 to 70 years (median = 18, interquartile range = 13-28 years). The most common focal seizure symptom was déjà vu (62% of cases), followed by epigastric rising sensation (34%), and fear or anxiety (22%). The clinical spectrum included rare cases with drug-resistance and/or hippocampal sclerosis. FMTLE cases had a higher mean focal epilepsy PRS than population controls (odds ratio = 1.24, 95% confidence interval = 1.06, 1.46, p = 0.007); in contrast, no enrichment for the febrile seizure PRS was observed.

INTERPRETATION

FMTLE is a generally mild drug-responsive syndrome with déjà vu being the commonest symptom. In contrast to dominant monogenic focal epilepsy syndromes, our molecular data support a polygenic basis for FMTLE. Furthermore, the PRS data suggest that sub-genome-wide significant focal epilepsy genome-wide association study single nucleotide polymorphisms are important risk variants for FMTLE. ANN NEUROL 2023;94:825-835.

Further advances in epilepsy

In 2017, one of us reviewed advances in epilepsy (Manford in J Neurol 264:1811-1824, 2017). The current paper brings that review up to date and gives a slight change in emphasis. Once again, the story is of evolution rather than revolution. In recognition that most of our current medications act on neurotransmitters or ion channels, and not on the underlying changes in connectivity and pathways, they have been renamed as antiseizure (ASM) medications rather than antiepileptic drugs. Cenobamate is the one newly licensed medication for broader use in focal epilepsy but there have been a number of developments for specific disorders. We review new players and look forward to new developments in the light of evolving underlying science. We look at teratogenicity; old villains and new concerns in which clinicians play a vital role in explaining and balancing the risks. Medical treatment of status epilepticus, long without evidence, has benefitted from high-quality trials to inform practice; like buses, several arriving at once. Surgical treatment continues to be refined with improvements in the pre-surgical evaluation of patients, especially with new imaging techniques. Alternatives including stereotactic radiotherapy have received further focus and targets for palliative stimulation techniques have grown in number. Individuals' autonomy and quality of life continue to be the subject of research with refinement of what clinicians can do to help persons with epilepsy (PWE) achieve control. This includes seizure management but extends to broader considerations of human empowerment, needs and desires, which may be aided by emerging technologies such as seizure detection devices. The role of specialist nurses in improving that quality has been reinforced by specific endorsement from the International League against Epilepsy (ILAE).

The impact of serum magnesium and calcium on the risk of epilepsy: A mendelian randomization study

AIMS

To investigate the causal role of serum magnesium and calcium in epilepsy or any of its subtypes through Mendelian randomization (MR) approach.

METHODS

Single nucleotide polymorphisms (SNPs) associated with serum magnesium and calcium were used as the instrumental variables. MR analyses were performed using the summary-level data for epilepsy extracted from International League Against Epilepsy Consortium (15,212 cases and 29,677 controls) to obtain the causal estimates. The analyses were replicated using FinnGen data (7224 epilepsy cases and 208,845 controls), and a meta-analysis was then conducted.

RESULTS

The result of combined analyses showed that higher serum magnesium concentrations was associated with a reduced risk of overall epilepsy (odds ratios [OR] = 0.28, 95% confidence interval [CI], 0.12-0.62, p = 0.002). In ILAE, higher serum magnesium was suggestively associated with reduced risks of focal epilepsy (OR = 0.25, 95% CI 0.10-0.62, p = 0.003). However, the results cannot be repeated in sensitivity analyses. As for serum calcium, the results did not reach statistical significance with overall epilepsy (OR = 0.60, 95% CI, 0.31-1.17, p = 0.134). However, genetically predicted serum calcium concentrations showed an inverse association with risk of generalized epilepsy (OR = 0.35, 95% CI, 0.17-0.74, p = 0.006).

CONCLUSION

The current MR analysis did not support a causal relationship between serum magnesium and epilepsy, but showed a causally negative association between genetically determined serum calcium and generalized epilepsy.

SLCO5A1 and synaptic assembly genes contribute to impulsivity in juvenile myoclonic epilepsy

Elevated impulsivity is a key component of attention-deficit hyperactivity disorder (ADHD), bipolar disorder and juvenile myoclonic epilepsy (JME). We performed a genome-wide association, colocalization, polygenic risk score, and pathway analysis of impulsivity in JME (n = 381). Results were followed up with functional characterisation using a drosophila model. We identified genome-wide associated SNPs at 8q13.3 (P = 7.5 × 10-9) and 10p11.21 (P = 3.6 × 10-8). The 8q13.3 locus colocalizes with SLCO5A1 expression quantitative trait loci in cerebral cortex (P = 9.5 × 10-3). SLCO5A1 codes for an organic anion transporter and upregulates synapse assembly/organisation genes. Pathway analysis demonstrates 12.7-fold enrichment for presynaptic membrane assembly genes (P = 0.0005) and 14.3-fold enrichment for presynaptic organisation genes (P = 0.0005) including NLGN1 and PTPRD. RNAi knockdown of Oatp30B, the Drosophila polypeptide with the highest homology to SLCO5A1, causes over-reactive startling behaviour (P = 8.7 × 10-3) and increased seizure-like events (P = 6.8 × 10-7). Polygenic risk score for ADHD genetically correlates with impulsivity scores in JME (P = 1.60 × 10-3). SLCO5A1 loss-of-function represents an impulsivity and seizure mechanism. Synaptic assembly genes may inform the aetiology of impulsivity in health and disease.

Unraveling the role of non-coding rare variants in epilepsy

The discovery of new variants has leveled off in recent years in epilepsy studies, despite the use of very large cohorts. Consequently, most of the heritability is still unexplained. Rare non-coding variants have been largely ignored in studies on epilepsy, although non-coding single nucleotide variants can have a significant impact on gene expression. We had access to whole genome sequencing (WGS) from 247 epilepsy patients and 377 controls. To assess the functional impact of non-coding variants, ExPecto, a deep learning algorithm was used to predict expression change in brain tissues. We compared the burden of rare non-coding deleterious variants between cases and controls. Rare non-coding highly deleterious variants were significantly enriched in Genetic Generalized Epilepsy (GGE), but not in Non-Acquired Focal Epilepsy (NAFE) or all epilepsy cases when compared with controls. In this study we showed that rare non-coding deleterious variants are associated with epilepsy, specifically with GGE. Larger WGS epilepsy cohort will be needed to investigate those effects at a greater resolution. Nevertheless, we demonstrated the importance of studying non-coding regions in epilepsy, a disease where new discoveries are scarce.

Polygenic Risk of Epilepsy and Post-Stroke Epilepsy

Background and Aims

Epilepsy is highly heritable, with numerous known genetic risk loci. However, the genetic predisposition's role in post-acute brain injury epilepsy remains understudied. This study assesses whether a higher genetic predisposition to epilepsy raises post-stroke or Transient Ischemic Attack (TIA) survivor's risk of Post-Stroke Epilepsy (PSE).

Methods

We conducted a three-stage genetic analysis. First, we identified independent epilepsy-associated ( p <5x10 -8 ) genetic variants from public data. Second, we estimated PSE-specific variant weights in stroke/TIA survivors from the UK Biobank. Third, we tested for an association between a polygenic risk score (PRS) and PSE risk in stroke/TIA survivors from the All of Us Research Program. Primary analysis included all ancestries, while a secondary analysis was restricted to European ancestry only. A sensitivity analysis excluded TIA survivors. Association testing was conducted via multivariable logistic regression, adjusting for age, sex, and genetic ancestry.

Results

Among 19,708 UK Biobank participants with stroke/TIA, 805 (4.1%) developed PSE. Likewise, among 12,251 All of Us participants with stroke/TIA, 394 (3.2%) developed PSE. After establishing PSE-specific weights for 39 epilepsy-linked genetic variants in the UK Biobank, the resultant PRS was associated with elevated odds of PSE development in All of Us (OR:1.16[1.02-1.32]). A similar result was obtained when restricting to participants of European ancestry (OR:1.23[1.02-1.49]) and when excluding participants with a TIA history (OR:1.18[1.02-1.38]).

Conclusions

Our findings suggest that akin to other forms of epilepsy, genetic predisposition plays an essential role in PSE. Because the PSE data were sparse, our results should be interpreted cautiously.

The association between epilepsy and COVID-19: analysis based on Mendelian randomization and FUMA

Objective

A multitude of observational studies have underscored a substantial comorbidity between COVID-19 and epilepsy. This study was aimed at establishing a conclusive causal link between these two conditions.

Methods

We employed Mendelian randomization (MR) to evaluate the causal link between COVID-19 and epilepsy, as well as its focal and generalized subtypes. The GWAS for epilepsy and its subtypes database were abstracted from both FinnGen consortium and ILAE. Additionally, we leveraged functional mapping and annotation (FUMA) to integrate information from genome-wide association studies (GWAS) results.

Results

The MR analyses revealed that genetic liability to COVID-19 infection conferred a causal effect on epilepsy [FinnGen: OR: 1.5306; 95% confidence interval (CI): 1.1676-2.0062, PFDR (false discovery rate) = 0.0076; ILAE: OR: 1.3440; 95% CI: 1.0235-1.7649, PFDR = 0.0429], and generalized epilepsy (FinnGen: OR: 2.1155; 95% CI: 1.1734-3.8139, PFDR = 0.0327; ILAE: OR: 1.1245; 95% CI: 1.0444-1.2108, PFDR = 0.0114). Genetic liability to COVID-19 hospitalization conferred a causal effect on epilepsy (FinnGen: OR: 1.0934; 95% CI: 1.0097-1.1841, PFDR = 0.0422; ILAE: OR: 1.7381; 95% CI: 1.0467-2.8862, PFDR = 0.0451), focal epilepsy (ILAE: OR: 1.7549; 95% CI: 1.1063-2.7838, PFDR = 0.0338), and generalized epilepsy (ILAE: OR: 1.1827; 95% CI: 1.0215-1.3693, PFDR = 0.0406). Genetic liability to COVID-19 severity conferred a causal effect on epilepsy (FinnGen consortium: OR: 1.2454; 95% CI: 1.0850-1.4295, PFDR = 0.0162; ILAE: OR: 1.2724; 95% CI: 1.0347-1.5647, PFDR = 0.0403), focal epilepsy (FinnGen: OR: 1.6818; 95% CI: 1.1478-2.4642, PFDR = 0.0231; ILAE: OR: 1.6598; 95% CI: 1.2572-2.1914, PFDR = 0.0054), and generalized epilepsy (FinnGen: OR: 1.1486; 95% CI: 1.0274-1.2842, PFDR = 0.0335; ILAE: OR: 1.0439; 95% CI: 1.0159-1.0728, PFDR = 0.0086). In contrast, no causal linkage of epilepsy on COVID-19 was observed. Further, FUMA analysis identified six overlapping genes, including SMEK2, PNPT1, EFEMP1, CCDC85A, VRK2, and BCL11A, shared between COVID-19 and epilepsy. Tissue-specific expression analyses revealed that the disease-gene associations of COVID-19 were significantly enriched in lung, ovary, and spleen tissue compartments, while being significantly enriched in brain tissue for epilepsy.

Conclusion

Our study demonstrates that COVID-19 can be a contributing factor to epilepsy, but we found no evidence that epilepsy contributes to COVID-19.

GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment.

Widespread genomic influences on phenotype in Dravet syndrome, a 'monogenic' condition

Dravet syndrome is an archetypal rare severe epilepsy, considered 'monogenic', typically caused by loss-of-function SCN1A variants. Despite a recognizable core phenotype, its marked phenotypic heterogeneity is incompletely explained by differences in the causal SCN1A variant or clinical factors. In 34 adults with SCN1A-related Dravet syndrome, we show additional genomic variation beyond SCN1A contributes to phenotype and its diversity, with an excess of rare variants in epilepsy-related genes as a set and examples of blended phenotypes, including one individual with an ultra-rare DEPDC5 variant and focal cortical dysplasia. The polygenic risk score for intelligence was lower, and for longevity, higher, in Dravet syndrome than in epilepsy controls. The causal, major-effect, SCN1A variant may need to act against a broadly compromised genomic background to generate the full Dravet syndrome phenotype, whilst genomic resilience may help to ameliorate the risk of premature mortality in adult Dravet syndrome survivors.

Identifying Novel Drug Targets for Epilepsy Through a Brain Transcriptome-Wide Association Study and Protein-Wide Association Study with Chemical-Gene-Interaction Analysis

Epilepsy is a severe neurological condition affecting 50-65 million individuals worldwide that can lead to brain damage. Nevertheless, the etiology of epilepsy remains poorly understood. Meta-analyses of genome-wide association studies involving 15,212 epilepsy cases and 29,677 controls of the ILAE Consortium cohort were used to conduct transcriptome-wide association studies (TWAS) and protein-wide association studies (PWAS). Furthermore, a protein-protein interaction (PPI) network was generated using the STRING database, and significant epilepsy-susceptible genes were verified using chip data. Chemical-related gene set enrichment analysis (CGSEA) was performed to determine novel drug targets for epilepsy. TWAS analysis identified 21,170 genes, of which 58 were significant (TWASfdr < 0.05) in ten brain regions, and 16 differentially expressed genes were verified based on mRNA expression profiles. The PWAS identified 2249 genes, of which 2 were significant (PWASfdr < 0.05). Through chemical-gene set enrichment analysis, 287 environmental chemicals associated with epilepsy were identified. We identified five significant genes (WIPF1, IQSEC1, JAM2, ICAM3, and ZNF143) that had causal relationships with epilepsy. CGSEA identified 159 chemicals that were significantly correlated with epilepsy (Pcgsea < 0.05), such as pentobarbital, ketone bodies, and polychlorinated biphenyl. In summary, we performed TWAS, PWAS (for genetic factors), and CGSEA (for environmental factors) analyses and identified several epilepsy-associated genes and chemicals. The results of this study will contribute to our understanding of genetic and environmental factors for epilepsy and may predict novel drug targets.

Cortical microstructural gradients capture memory network reorganization in temporal lobe epilepsy

Temporal lobe epilepsy (TLE), one of the most common pharmaco-resistant epilepsies, is associated with pathology of paralimbic brain regions, particularly in the mesiotemporal lobe. Cognitive dysfunction in TLE is frequent, and particularly affects episodic memory. Crucially, these difficulties challenge the quality of life of patients, sometimes more than seizures, underscoring the need to assess neural processes of cognitive dysfunction in TLE to improve patient management. Our work harnessed a novel conceptual and analytical approach to assess spatial gradients of microstructural differentiation between cortical areas based on high-resolution MRI analysis. Gradients track region-to-region variations in intracortical lamination and myeloarchitecture, serving as a system-level measure of structural and functional reorganization. Comparing cortex-wide microstructural gradients between 21 patients and 35 healthy controls, we observed a reorganization of this gradient in TLE driven by reduced microstructural differentiation between paralimbic cortices and the remaining cortex with marked abnormalities in ipsilateral temporopolar and dorsolateral prefrontal regions. Findings were replicated in an independent cohort. Using an independent post-mortem dataset, we observed that in vivo findings reflected topographical variations in cortical cytoarchitecture. We indeed found that macroscale changes in microstructural differentiation in TLE reflected increased similarity of paralimbic and primary sensory/motor regions. Disease-related transcriptomics could furthermore show specificity of our findings to TLE over other common epilepsy syndromes. Finally, microstructural dedifferentiation was associated with cognitive network reorganization seen during an episodic memory functional MRI paradigm and correlated with interindividual differences in task accuracy. Collectively, our findings showing a pattern of reduced microarchitectural differentiation between paralimbic regions and the remaining cortex provide a structurally-grounded explanation for large-scale functional network reorganization and cognitive dysfunction characteristic of TLE.

Identifying Suitable Targets for Alzheimer's Disease and Other Eight Common Neurological Disorders Using the Human Plasma Proteome: A Mendelian Randomization Study

Background

Neurological disorders, such as Alzheimer's disease (AD), comprise a major cause of health-related disabilities in human. However, biomarkers towards pathogenesis or novel targets are still limited.

Objective

To identify the causality between plasma proteins and the risk of AD and other eight common neurological diseases using a Mendelian randomization (MR) study.

Methods

Exposure data were obtained from a genome-wide association study (GWAS) of 2,994 plasma proteins in 3,301 healthy adults, and outcome datasets included GWAS summary statistics of nine neurological disorders. Inverse variance-weighted MR method as the primary analysis was used to estimate causal effects.

Results

Higher genetically proxied plasma myeloid cell surface antigen CD33 level was found to be associated with increased risk of AD (odds ratio [OR] 1.079, 95% confidence interval [CI] 1.047-1.112, p = 8.39×10-7). We also discovered the causality between genetically proxied elevated prolactin and higher risk of epilepsy (OR = 1.068, 95% CI = 1.034-1.102; p = 5.46×10-5). Negative associations were identified between cyclin-dependent kinase 8 and ischemic stroke (OR = 0.927, 95% CI = 0.896-0.959, p = 9.32×10-6), between neuralized E3 ubiquitin-protein ligase 1 and migraine (OR = 0.914, 95% CI = 0.878-0.952, p = 1.48×10-5), and between Fc receptor-like protein 4 and multiple sclerosis (MS) (OR = 0.929, 95% CI = 0.897-0.963, p = 4.27×10-5).

Conclusion

The findings identified MR-level protein-disease associations for AD, epilepsy, ischemic stroke, migraine, and MS.

Multimodal mapping of regional brain vulnerability to focal cortical dysplasia

Focal cortical dysplasia (FCD) type II is a highly epileptogenic developmental malformation and a common cause of surgically treated drug-resistant epilepsy. While clinical observations suggest frequent occurrence in the frontal lobe, mechanisms for such propensity remain unexplored. Here, we hypothesized that cortex-wide spatial associations of FCD distribution with cortical cytoarchitecture, gene expression and organizational axes may offer complementary insights into processes that predispose given cortical regions to harbour FCD. We mapped the cortex-wide MRI distribution of FCDs in 337 patients collected from 13 sites worldwide. We then determined its associations with (i) cytoarchitectural features using histological atlases by Von Economo and Koskinas and BigBrain; (ii) whole-brain gene expression and spatiotemporal dynamics from prenatal to adulthood stages using the Allen Human Brain Atlas and PsychENCODE BrainSpan; and (iii) macroscale developmental axes of cortical organization. FCD lesions were preferentially located in the prefrontal and fronto-limbic cortices typified by low neuron density, large soma and thick grey matter. Transcriptomic associations with FCD distribution uncovered a prenatal component related to neuroglial proliferation and differentiation, likely accounting for the dysplastic makeup, and a postnatal component related to synaptogenesis and circuit organization, possibly contributing to circuit-level hyperexcitability. FCD distribution showed a strong association with the anterior region of the antero-posterior axis derived from heritability analysis of interregional structural covariance of cortical thickness, but not with structural and functional hierarchical axes. Reliability of all results was confirmed through resampling techniques. Multimodal associations with cytoarchitecture, gene expression and axes of cortical organization indicate that prenatal neurogenesis and postnatal synaptogenesis may be key points of developmental vulnerability of the frontal lobe to FCD. Concordant with a causal role of atypical neuroglial proliferation and growth, our results indicate that FCD-vulnerable cortices display properties indicative of earlier termination of neurogenesis and initiation of cell growth. They also suggest a potential contribution of aberrant postnatal synaptogenesis and circuit development to FCD epileptogenicity.

A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records

BACKGROUND

The identification of new uses for existing drug therapies has the potential to identify treatments for comorbid conditions that have the added benefit of glycemic control while also providing a rapid, low-cost approach to drug (re)discovery.

METHODS

We developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically-predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug-gene pairs. These drug-gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR).

FINDINGS

After filtering on sample size, 20 candidate drug-gene pairs were validated and various medications demonstrated evidence of glycemic regulation including two anti-hypertensive classes: angiotensin-converting enzyme inhibitors as well as calcium channel blockers (CCBs). The CCBs demonstrated the strongest evidence of glycemic reduction in both validation approaches (SCCS HbA1c and glucose reduction: -0.11%, p = 0.01 and -0.85 mg/dL, p = 0.02, respectively; MR: OR = 0.84, 95% CI = 0.81, 0.87, p = 5.0 x 10-25).

INTERPRETATION

Our results support CCBs as a strong candidate medication for blood glucose reduction in addition to cardiovascular disease reduction. Further, these results support the adaptation of this approach for use in future drug-repurposing efforts for other conditions.

FUNDING

National Institutes of Health, Medical Research Council Integrative Epidemiology Unit at the University of Bristol, UK Medical Research Council, American Heart Association, and Department of Veterans Affairs (VA) Informatics and Computing Infrastructure and VA Cooperative Studies Program.

Alzheimer Disease and Epilepsy: A Mendelian Randomization Study

BACKGROUND AND OBJECTIVES

Observational studies suggested a bidirectional relationship between Alzheimer disease (AD) and epilepsies. However, it remains debated whether and in which direction a causal association exists. This study aims to explore the relationship between genetic predisposition to AD, CSF biomarkers of AD (β-amyloid [Aβ] 42 and phosphorylated tau [pTau]), and epilepsies with 2-sample, bidirectional Mendelian randomization (MR) method.

METHODS

Genetic instruments were obtained from large-scale genome-wide meta-analysis of AD (Ncase/proxy = 111,326, Ncontrol = 677,663), CSF biomarkers of AD (Aβ42 and pTau, N = 13,116), and epilepsy (Ncase = 15,212, Ncontrol = 29,677) of European ancestry. Epilepsy phenotypes included all epilepsy, generalized epilepsy, focal epilepsy, childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy, generalized epilepsy with tonic-clonic seizures, focal epilepsy with hippocampal sclerosis (focal HS), and lesion-negative focal epilepsy. Main analyses were performed using generalized summary data-based MR. Sensitivity analyses included inverse variance weighted, MR pleiotropy residual sum and outlier, MR-Egger, weighted mode, and weighted median.

RESULTS

For forward analysis, genetic predisposition to AD was associated with an increased risk of generalized epilepsy (odds ratio [OR] 1.053, 95% CI 1.002-1.105, p = 0.038) and focal HS (OR 1.013, 95% CI 1.004-1.022, p = 0.004). These associations were consistent across sensitivity analyses and replicated using a separate set of genetic instruments from another AD genome-wide association study. For reverse analysis, there was a suggestive effect of focal HS on AD (OR 3.994, 95% CI 1.172-13.613, p = 0.027). In addition, genetically predicted lower CSF Aβ42 was associated with an increased risk of generalized epilepsy (β = 0.090, 95% CI 0.022-0.158, p = 0.010).

DISCUSSION

This MR study supports a causal link between AD, amyloid pathology, and generalized epilepsy. This study also indicates a close association between AD and focal HS. More effort should be made to screen seizure in AD, unravel its clinical implications, and explore its role as a putative modifiable risk factor.

Prioritizing genes associated with brain disorders by leveraging enhancer-promoter interactions in diverse neural cells and tissues

BACKGROUND

Prioritizing genes that underlie complex brain disorders poses a considerable challenge. Despite previous studies have found that they shared symptoms and heterogeneity, it remained difficult to systematically identify the risk genes associated with them.

METHODS

By using the CAGE (Cap Analysis of Gene Expression) read alignment files for 439 human cell and tissue types (including primary cells, tissues and cell lines) from FANTOM5 project, we predicted enhancer-promoter interactions (EPIs) of 439 cell and tissue types in human, and examined their reliability. Then we evaluated the genetic heritability of 17 diverse brain disorders and behavioral-cognitive phenotypes in each neural cell type, brain region, and developmental stage. Furthermore, we prioritized genes associated with brain disorders and phenotypes by leveraging the EPIs in each neural cell and tissue type, and analyzed their pleiotropy and functionality for different categories of disorders and phenotypes. Finally, we characterized the spatiotemporal expression dynamics of these associated genes in cells and tissues.

RESULTS

We found that identified EPIs showed activity specificity and network aggregation in cell and tissue types, and enriched TF binding in neural cells played key roles in synaptic plasticity and nerve cell development, i.e., EGR1 and SOX family. We also discovered that most neurological disorders exhibit heritability enrichment in neural stem cells and astrocytes, while psychiatric disorders and behavioral-cognitive phenotypes exhibit enrichment in neurons. Furthermore, our identified genes recapitulated well-known risk genes, which exhibited widespread pleiotropy between psychiatric disorders and behavioral-cognitive phenotypes (i.e., FOXP2), and indicated expression specificity in neural cell types, brain regions, and developmental stages associated with disorders and phenotypes. Importantly, we showed the potential associations of brain disorders with brain regions and developmental stages that have not been well studied.

CONCLUSIONS

Overall, our study characterized the gene-enhancer regulatory networks and genetic mechanisms in the human neural cells and tissues, and illustrated the value of reanalysis of publicly available genomic datasets.

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice.

Epilepsies of presumed genetic etiology show enrichment of rare variants that occur in the general population

Previous studies suggested that severe epilepsies, e.g., developmental and epileptic encephalopathies (DEEs), are mainly caused by ultra-rare de novo genetic variants. For milder disease, rare genetic variants could contribute to the phenotype. To determine the importance of rare variants for different epilepsy types, we analyzed a whole-exome sequencing cohort of 9,170 epilepsy-affected individuals and 8,436 control individuals. Here, we separately analyzed three different groups of epilepsies: severe DEEs, genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We required qualifying rare variants (QRVs) to occur in control individuals with an allele count ≥ 1 and a minor allele frequency ≤ 1:1,000, to be predicted as deleterious (CADD ≥ 20), and to have an odds ratio in individuals with epilepsy ≥ 2. We identified genes enriched with QRVs primarily in NAFE (n = 72), followed by GGE (n = 32) and DEE (n = 21). This suggests that rare variants may play a more important role for causality of NAFE than for DEE. Moreover, we found that genes harboring QRVs, e.g., HSGP2, FLNA, or TNC, encode proteins that are involved in structuring the brain extracellular matrix. The present study confirms an involvement of rare variants for NAFE that occur also in the general population, while in DEE and GGE, the contribution of such variants appears more limited.

Individualised human phenotype ontology gene panels improve clinical whole exome and genome sequencing analytical efficacy in a cohort of developmental and epileptic encephalopathies

BACKGROUND

The majority of genetic epilepsies remain unsolved in terms of specific genotype. Phenotype-based genomic analyses have shown potential to strengthen genomic analysis in various ways, including improving analytical efficacy.

METHODS

We have tested a standardised phenotyping method termed 'Phenomodels' for integrating deep-phenotyping information with our in-house developed clinical whole exome/genome sequencing analytical pipeline. Phenomodels includes a user-friendly epilepsy phenotyping template and an objective measure for selecting which template terms to include in individualised Human Phenotype Ontology (HPO) gene panels. In a pilot study of 38 previously solved cases of developmental and epileptic encephalopathies, we compared the sensitivity and specificity of the individualised HPO gene panels with the clinical epilepsy gene panel.

RESULTS

The Phenomodels template showed high sensitivity for capturing relevant phenotypic information, where 37/38 individuals' HPO gene panels included the causative gene. The HPO gene panels also had far fewer variants to assess than the epilepsy gene panel.

CONCLUSION

We have demonstrated a viable approach for incorporating standardised phenotype information into clinical genomic analyses, which may enable more efficient analysis.

The P2X7 receptor contributes to seizures and inflammation-driven long-lasting brain hyperexcitability following hypoxia in neonatal mice

BACKGROUND AND PURPOSE

Neonatal seizures represent a clinical emergency. However, current anti-seizure medications fail to resolve seizures in ~50% of infants. The P2X7 receptor (P2X7R) is an important driver of inflammation, and evidence suggests that P2X7R contributes to seizures and epilepsy in adults. However, no genetic proof has yet been provided to determine what contribution P2X7R makes to neonatal seizures, its effects on inflammatory signalling during neonatal seizures, and the therapeutic potential of P2X7R-based treatments on long-lasting brain excitability.

EXPERIMENTAL APPROACH

Neonatal seizures were induced by global hypoxia in 7-day-old mouse pups (P7). The role of P2X7Rs during seizures was analysed in P2X7R-overexpressing and knockout mice. Treatment of wild-type mice after hypoxia with the P2X7R antagonist JNJ-47965567 was used to determine the effects of the P2X7R on long-lasting brain hyperexcitability. Cell type-specific P2X7R expression was analysed in P2X7R-EGFP reporter mice. RNA sequencing was used to monitor P2X7R-dependent hippocampal downstream signalling.

KEY RESULTS

P2X7R deletion reduced seizure severity, whereas P2X7R overexpression exacerbated seizure severity and reduced responsiveness to anti-seizure medication. P2X7R deficiency led to an anti-inflammatory phenotype in microglia, and treatment of mice with a P2X7R antagonist reduced long-lasting brain hyperexcitability. RNA sequencing identified several pathways altered in P2X7R knockout mice after neonatal hypoxia, including a down-regulation of genes implicated in inflammation and glutamatergic signalling.

CONCLUSION AND IMPLICATIONS

Treatments based on targeting the P2X7R may represent a novel therapeutic strategy for neonatal seizures with P2X7Rs contributing to the generation of neonatal seizures, driving inflammatory processes and long-term hyperexcitability states.

Technological and computational approaches to detect somatic mosaicism in epilepsy

Lesional epilepsy is a common and severe disease commonly associated with malformations of cortical development, including focal cortical dysplasia and hemimegalencephaly. Recent advances in sequencing and variant calling technologies have identified several genetic causes, including both short/single nucleotide and structural somatic variation. In this review, we aim to provide a comprehensive overview of the methodological advancements in this field while highlighting the unresolved technological and computational challenges that persist, including ultra-low variant allele fractions in bulk tissue, low availability of paired control samples, spatial variability of mutational burden within the lesion, and the issue of false-positive calls and validation procedures. Information from genetic testing in focal epilepsy may be integrated into clinical care to inform histopathological diagnosis, postoperative prognosis, and candidate precision therapies.

Neurological and psychiatric comorbidities of migraine: Concepts and future perspectives

BACKGROUND

This narrative review aims to discuss several common neurological and psychiatric disorders that show comorbidity with migraine. Not only can we gain pathophysiological insights by studying these disorders, comorbidities also have important implications for treating migraine patients in clinical practice.

METHODS

A literature search on PubMed and Embase was conducted with the keywords "comorbidity", "migraine disorders", "migraine with aura", "migraine without aura", "depression", "depressive disorders", "epilepsy", "stroke", "patent foramen ovale", "sleep wake disorders", "restless legs syndrome", "genetics", "therapeutics".

RESULTS

Several common neurological and psychiatric disorders show comorbidity with migraine. Major depression and migraine show bidirectional causality and have shared genetic factors. Dysregulation of both hypothalamic and thalamic pathways have been implicated as a possibly cause. The increased risk of ischaemic stroke in migraine likely involves spreading depolarizations. Epilepsy is not only bidirectionally related to migraine, but is also co-occurring in monogenic migraine syndromes. Neuronal hyperexcitability is an important overlapping mechanism between these conditions. Hypothalamic dysfunction is suggested as the underlying mechanism for comorbidity between sleep disorders and migraine and might explain altered circadian timing in migraine.

CONCLUSION

These comorbid conditions in migraine with distinct pathophysiological mechanisms have important implications for best treatment choices and may provide clues for future approaches.

HCN channels and absence seizures

Hyperpolarization-activation cyclic nucleotide-gated (HCN) channels were for the first time implicated in absence seizures (ASs) when an abnormal Ih (the current generated by these channels) was reported in neocortical layer 5 neurons of a mouse model. Genetic studies of large cohorts of children with Childhood Absence Epilepsy (where ASs are the only clinical symptom) have identified only 3 variants in HCN1 (one of the genes that code for the 4 HCN channel isoforms, HCN1-4), with one (R590Q) mutation leading to loss-of-function. Due to the multi-faceted effects that HCN channels exert on cellular excitability and neuronal network dynamics as well as their modulation by environmental factors, it has been difficult to identify the detailed mechanism by which different HCN isoforms modulate ASs. In this review, we systematically and critically analyze evidence from established AS models and normal non-epileptic animals with area- and time-selective ablation of HCN1, HCN2 and HCN4. Notably, whereas knockout of rat HCN1 and mouse HCN2 leads to the expression of ASs, the pharmacological block of all HCN channel isoforms abolishes genetically determined ASs. These seemingly contradictory results could be reconciled by taking into account the well-known opposite effects of Ih on cellular excitability and network function. Whereas existing evidence from mouse and rat AS models indicates that pan-HCN blockers may provide a novel approach for the treatment of human ASs, the development of HCN isoform-selective drugs would greatly contribute to current research on the role for these channels in ASs generation and maintenance as well as offer new potential clinical applications.

The genetic architecture of the corpus callosum and its genetic overlap with common neuropsychiatric diseases

BACKGROUND

The corpus callosum (CC) is the main structure transferring information between the cerebral hemispheres. Although previous large-scale genome-wide association study (GWAS) has illustrated the genetic architecture of white matter integrity of CC, CC volume is less stressed.

METHODS

Using MRI data from 33,861 individuals in UK Biobank, we conducted univariate and multivariate GWAS for CC fractional anisotropy (FA) and volume with PLINK 2.0 and MOSTest. All discovered SNPs in the multivariate framework were functionally annotated in FUMA v1.3.8. In the meanwhile, a series of gene property analyses was conducted simultaneously. In addition, we estimated genetic relationship between CC metrics and other neuropsychiatric traits and diseases.

RESULTS

We identified a total of 36 and 82 significant genomic loci for CC FA and volume (P < 5 × 10^-8). And 53 and 27 genes were respectively mapped by four mapping strategies. For CC volume, gene-set analysis revealed pathways mainly relating to cell migration; cell-type analysis found the top enrichment in neuroglia while for CC FA in GABAergic neurons. Furthermore, we found a lot of genetic overlap and shared loci between CC FA and volume and common neuropsychiatric diseases.

DISCUSSION

Collectively, this study helps to better understand the genetic architecture of whole CC and CC subregions. However, the way to divide CC FA and volume in our study restricts the interpretations of our results. Future work will be needed to pay attention to the genetic structure of white matter volume, and an appropriate division of CC may help to better understand CC structure.

Epilepsy genetics: a practical guide for adult neurologists

An understanding of epilepsy genetics is important for adult neurologists, as making a genetic diagnosis gives clinical benefit. In this review, we describe the key features of different groups of genetic epilepsies. We describe the common available genetic tests for epilepsy, and how to interpret them.

The genetic link between systemic autoimmune disorders and temporal lobe epilepsy: A bioinformatics study

OBJECTIVE

We aimed to explore the underlying pathomechanisms of the comorbidity between three common systemic autoimmune disorders (SADs) [i.e., insulin-dependent diabetes mellitus (IDDM), systemic lupus erythematosus (SLE), and rheumatoid arthritis (RA)] and temporal lobe epilepsy (TLE), using bioinformatics tools. We hypothesized that there are shared genetic variations among these four conditions.

METHODS

Different databases (DisGeNET, Harmonizome, and Enrichr) were searched to find TLE-associated genes with variants; their single nucleotide polymorphisms (SNPs) were gathered from the literature. We also did a separate literature search using PubMed with the following keywords for original articles: "TLE" or "Temporal lobe epilepsy" AND "genetic variation," "single nucleotide polymorphism," "SNP," or "genetic polymorphism." In the next step, the SNPs associated with TLE were searched in the LitVar database to find the shared gene variations with RA, SLE, and IDDM.

RESULTS

Ninety unique SNPs were identified to be associated with TLE. LitVar search identified two SNPs that were shared between TLE and all three SADs (i.e., IDDM, SLE, and RA). The first SNP was rs16944 on the Interleukin-1β (IL-1β) gene. The second genetic variation was ε4 variation of apolipoprotein E (APOE) gene.

SIGNIFICANCE

The shared genetic variations (i.e., rs16944 on the IL-1β gene and ε4 variation of the APOE gene) may explain the underlying pathomechanisms of the comorbidity between three common SADs (i.e., IDDM, SLE, and RA) and TLE. Exploring such shared genetic variations may help find targeted therapies for patients with TLE, especially those with drug-resistant seizures who also have comorbid SADs.

Genetic mechanisms in generalized epilepsies

The genetic generalized epilepsies (GGEs) have been proved to generate from genetic impact by twin studies and family studies. The genetic mechanisms of generalized epilepsies are always updating over time. Although the genetics of GGE is complex, there are always new susceptibility genes coming up as well as copy number variations which can lead to important breakthroughs in exploring the problem. At the same time, the development of ClinGen fades out some of the candidate genes. This means we have to figure out what accounts for a reliable gene for GGE, in another word, which gene has sufficient evidence for GGE. This will improve our understanding of the genetic mechanisms of GGE. In this review, important up-to-date genetic mechanisms of GGE were discussed.

The role of rare genetic variants enrichment in epilepsies of presumed genetic etiology

Previous studies suggested that severe epilepsies e.g., developmental and epileptic encephalopathies (DEE) are mainly caused by ultra-rare de novo genetic variants. For milder phenotypes, rare genetic variants could contribute to the phenotype. To determine the importance of rare variants for different epilepsy types, we analyzed a whole-exome sequencing cohort of 9,170 epilepsy-affected individuals and 8,436 controls. Here, we separately analyzed three different groups of epilepsies : severe DEEs, genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We required qualifying rare variants (QRVs) to occur in controls at a minor allele frequency ≤ 1:1,000, to be predicted as deleterious (CADD≥20), and to have an odds ratio in epilepsy cases ≥2. We identified genes enriched with QRVs in DEE (n=21), NAFE (n=72), and GGE (n=32) - the number of enriched genes are found greatest in NAFE and least in DEE. This suggests that rare variants may play a more important role for causality of NAFE than in DEE. Moreover, we found that QRV-carrying genes e.g., HSGP2, FLNA or TNC are involved in structuring the brain extracellular matrix. The present study confirms an involvement of rare variants for NAFE, while in DEE and GGE, the contribution of such variants appears more limited.

Analysis of common genetic variation across targets of microRNAs dysregulated both in ASD and epilepsy reveals negative correlation

Genetic overlap involving rare disrupting mutations may contribute to high comorbidity rates between autism spectrum disorders and epilepsy. Despite their polygenic nature, genome-wide association studies have not reported a significant contribution of common genetic variation to comorbidity between both conditions. Analysis of common genetic variation affecting specific shared pathways such as miRNA dysregulation could help to elucidate the polygenic mechanisms underlying comorbidity between autism spectrum disorders and epilepsy. We evaluated here the role of common predisposing variation to autism spectrum disorders and epilepsy across target genes of 14 miRNAs selected through bibliographic research as being dysregulated in both disorders. We considered 4,581 target genes from various in silico sources. We described negative genetic correlation between autism spectrum disorders and epilepsy across variants located within target genes of the 14 miRNAs selected (p = 0.0228). Moreover, polygenic transmission disequilibrium test on an independent cohort of autism spectrum disorders trios (N = 233) revealed an under-transmission of autism spectrum disorders predisposing alleles within miRNAs’ target genes across autism spectrum disorders trios without comorbid epilepsy, thus reinforcing the negative relationship at the common genetic variation between both traits. Our study provides evidence of a negative relationship between autism spectrum disorders and epilepsy at the common genetic variation level that becomes more evident when focusing on the miRNA regulatory networks, which contrasts with observed clinical comorbidity and results from rare variation studies. Our findings may help to conceptualize the genetic heterogeneity and the comorbidity with epilepsy in autism spectrum disorders.

Causal relationship between human blood omega-3 fatty acids and the risk of epilepsy: A two-sample Mendelian randomization study

Background

Though omega-3 fatty acids reduce seizures in several animal models, considerable controversy exists regarding the association between omega-3 fatty acids and epilepsy in human.

Objective

To assess whether genetically determined human blood omega-3 fatty acids are causally associated with the risk of epilepsy outcomes.

Methods

We conducted a two-sample Mendelian randomization (MR) analysis by applying summary statistics of genome-wide association study datasets of both exposure and outcomes. Single nucleotide polymorphisms significantly associated with blood omega-3 fatty acids levels were selected as instrumental variables to estimate the causal effects on epilepsy. Five MR analysis methods were conducted to analyze the final results. The inverse-variance weighted (IVW) method was used as the primary outcome. The other MR analysis methods (MR-Egger, weighted median, simple mode, and weighted mode) were conducted as the complement to IVW. Sensitivity analyses were also conducted to evaluate heterogeneity and pleiotropy.

Results

Genetically predicted the increase of human blood omega-3 fatty acids levels was associated with a higher risk of epilepsy (OR = 1.160, 95%CI = 1.051–1.279, P = 0.003).

Conclusions

This study revealed a causal relationship between blood omega-3 fatty acids and the risk of epilepsy, thus providing novel insights into the development mechanism of epilepsy.

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.

Mendelian randomization approach shows no causal effects of gestational age on epilepsy in offspring

BACKGROUND

Observational studies have suggested that gestational age was associated with the risk of epilepsy later in life. However, it remains unclear whether the association is of a causal nature.

METHODS

Two-sample Mendelian randomization (MR) was performed to assess the causal effect of fetal gestational age on epilepsy. Genome-wide association studies (GWAS) summary statistics of gestational duration, early preterm birth, preterm birth, and postterm birth were from the Early Growth Genetics (EGG) Consortium. GWAS summary-level data on epilepsy were obtained from the International League Against Epilepsy Consortium (ILAEC) and FinnGen Consortium. The inverse-variance weighted (IVW) was applied as the primary method to calculate estimates, which were further validated using other sensitivity analyses.

RESULTS

There was not yet strong evidence of causal associations between gestational age and epilepsy of ILAEC (early preterm birth: odds ratio [OR]=1.01, 95% CI: 0.99-1.03, P = 0.441; preterm birth: OR=1.01, 95% CI: 0.96-1.07, P = 0.617; postterm birth: OR=0.96, 95% CI: 0.89-1.04, P = 0.357; gestational duration: OR=0.90, 95% CI: 0.75-1.07, P = 0.214). Similar results were obtained in the replication stage using epileptic samples from the FinnGen Consortium. Finally, a meta-analysis of the causal estimates from the ILAEC and FinnGen Consortium showed consistent results. No obvious pleiotropy was found throughout the MR study.

CONCLUSIONS

The present study indicated that gestational age, either preterm birth or postterm birth, might not be causally associated with the risk of epilepsy. Further studies are warranted to evaluate the potential mechanisms underlying the epidemiological relationship between preterm birth and epilepsy.

Genetic architecture of the white matter connectome of the human brain

White matter tracts form the structural basis of large-scale brain networks. We applied brain-wide tractography to diffusion images from 30,810 adults (U.K. Biobank) and found significant heritability for 90 node-level and 851 edge-level network connectivity measures. Multivariate genome-wide association analyses identified 325 genetic loci, of which 80% had not been previously associated with brain metrics. Enrichment analyses implicated neurodevelopmental processes including neurogenesis, neural differentiation, neural migration, neural projection guidance, and axon development, as well as prenatal brain expression especially in stem cells, astrocytes, microglia, and neurons. The multivariate association profiles implicated 31 loci in connectivity between core regions of the left-hemisphere language network. Polygenic scores for psychiatric, neurological, and behavioral traits also showed significant multivariate associations with structural connectivity, each implicating distinct sets of brain regions with trait-relevant functional profiles. This large-scale mapping study revealed common genetic contributions to variation in the structural connectome of the human brain.

The phenotypic spectrum associated with loss-of-function variants in monogenic epilepsy genes in the general population

Variants in monogenic epilepsy genes can cause phenotypes of varying severity. For example, pathogenic variants in the SCN1A gene can cause the severe, sporadic, and drug-resistant Dravet syndrome or the milder familiar GEFS + syndrome. We hypothesized that coding variants in epilepsy-associated genes could lead to other disease-related phenotypes in the general population. We selected 127 established monogenic epilepsy genes and explored rare loss-of-function (LoF) variant associations with 3700 phenotypes across 281,850 individuals from the UK Biobank with whole-exome sequencing data. For 5.5% of epilepsy genes, we found significant associations of LoF variants with non-epilepsy phenotypes, mostly related to mental health. These findings suggest that LoF variants in epilepsy genes are associated with neurological or psychiatric phenotypes in the general population. The evidence provided may warrant further research and genetic screening of patients with atypical presentation and inform clinical care of comorbid disorders in individuals with monogenic epilepsy forms.