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

Identification of Novel Gene Variants in Children With Drug-Resistant Epilepsy: Expanding the Genetic Spectrum

BACKGROUND

Resistance to antiseizure drugs is an important problem in the treatment of individuals with epilepsy. Identifying the molecular etiology of drug-resistant epilepsy (DRE) is crucial for better management of epilepsy. Here, we explore the utility of whole exome sequencing (WES) in identifying causative gene variants in children with DRE.

METHODS

Forty-five children with DRE who underwent WES tests were included. Genetic examination of all patients included chromosomal analysis and clinical chromosomal microarray followed by WES. The identified variants by WES analysis were classified for pathogenicity based on the American College of Medical Genetics and Genomics guidelines and in silico protein prediction tools.

RESULTS

The overall diagnostic yield was 55.5% (25 of 45). A total of 26 variants spanning 22 genes were identified in 25 patients. Of note, only 19 of these genes were examined as novel. Ten patients (22.2%) had a pathogenic or likely pathogenic variant. There was a trend associated with a diagnostic genetic test result in girls compared with boys in DRE (P = 0.028).

CONCLUSION

Our findings expand the mutational spectrum of genes related to DRE. To form disease-specific treatment in children with DRE, the WES analysis should be included in the diagnostic algorithm because of its high diagnostic efficiency.

Anti-Epileptic Drug Target Perturbation and Intracranial Aneurysm Risk: Mendelian Randomization and Colocalization Study

BACKGROUND

In a genome-wide association study of intracranial aneurysms (IA), enrichment was found between genes associated with IA and genes encoding targets of effective anti-epileptic drugs. Our aim was to assess if this pleiotropy is driven by shared disease mechanisms that could potentially highlight a treatment strategy for IA.

METHODS

Using 2-sample inverse-variance weighted Mendelian randomization and genetic colocalization analyses we assessed: (1) if epilepsy liability in general affects IA risk, and (2) whether changes in gene- and protein-expression levels of anti-epileptic drug targets in blood and arterial tissue may causally affect IA risk.

RESULTS

We found no overall effect of epilepsy liability on IA. Expression of 21 genes and 13 proteins corresponding to anti-epileptic drug targets supported a causal effect (P<0.05) on IA risk. Of those genes and proteins, genetic variants affecting CNNM2 levels showed strong evidence for colocalization with IA risk (posterior probability>70%). Higher CNNM2 levels in arterial tissue were associated with increased IA risk (odds ratio, 3.02; [95% CI, 2.32-3.94]; P=3.39×10^-16). CNNM2 expression was best proxied by rs11191580. The magnitude of the effect of this variant was greater than would be expected if systemic blood pressure was the sole IA-causing mechanism in this locus.

CONCLUSIONS

CNNM2 is a driver of the pleiotropy between IA and anti-epileptic drug targets. Administration of the anti-epileptic drugs phenytoin, valproic acid, or carbamazepine may be expected to decrease CNNM2 levels and therefore subsequently decrease IA risk. CNNM2 is therefore an important target to investigate further for its role in the pathogenesis of IA.

Exploring the Causality Between Plasma Brain-Derived Neurotrophic Factor and Neurological Diseases: A Mendelian Randomization Study

BACKGROUND

Brain-derived neurotrophic factor (BDNF) is a protein synthesized in the brain and widely expressed in the nervous system. Previous studies have demonstrated a controversial role of BDNF in neurological diseases.

OBJECTIVE

In this study, we aimed to assess the association between BDNF levels and the risk of neurological diseases by Mendelian randomization analysis.

METHODS

From a genome-wide association analysis of plasma proteins comprising 3,301 European participants, we isolated 25 genetic variations as instrumental variables for BDNF levels. Summary statistics data on six common neurological diseases as outcome variables. Two-sample Mendelian randomization (MR) analysis was used to assess whether plasma BDNF is causally related to neurological diseases. We also performed sensitivity analysis to ensure the robustness of the results and reverse MR to exclude potential reverse causality.

RESULTS

We confirmed the significant causal relationship between BDNF levels and the risk of Alzheimer's disease (AD) (OR, 0.92; 95% CI, 0.85, 0.98; p = 0.013). Other methods have also shown similar results. We infer that BDNF also reduces the risk of epilepsy (OR, 0.94; 95% CI, 0.90, 0.98; p = 0.004). In reverse MR analysis, we also found that AD can affect the level of BDNF.

CONCLUSIONS

Our study suggests higher plasma BDNF was associated with the reduced risk of AD. Moreover, higher plasma BDNF is a protective factor on AD and focal epilepsy. The results provide credence to the idea that BDNF may play a significant role in the development of focal epilepsy and AD.

Mendelian randomization analysis does not reveal a causal influence of mental diseases on osteoporosis

Introduction

Osteoporosis (OP) is primarily diagnosed through bone mineral density (BMD) measurements, and it often leads to fracture. Observational studies suggest that several mental diseases (MDs) may be linked to OP, but the causal direction of these associations remain unclear. This study aims to explore the potential causal association between five MDs (Schizophrenia, Depression, Alzheimer's disease, Parkinson's disease, and Epilepsy) and the risk of OP.

Methods

First, single-nucleotide polymorphisms (SNPs) were filtered from summary-level genome-wide association studies using quality control measures. Subsequently, we employed two-sample Mendelian randomization (MR) analysis to indirectly analyze the causal effect of MDs on the risk of OP through bone mineral density (in total body, femoral neck, lumbar spine, forearm, and heel) and fractures (in leg, arm, heel, spine, and osteoporotic fractures). Lastly, the causal effect of the MDs on the risk of OP was evaluated directly through OP. MR analysis was performed using several methods, including inverse variance weighting (IVW)-random effects, IVW-fixed effects, maximum likelihood, weighted median, MR-Egger regression, and penalized weighted median.

Results

The results did not show any evidence of a causal relationship between MDs and the risk of OP (with almost all P values > 0.05). The robustness of the above results was proved to be good.

Discussion

In conclusion, this study did not find evidence supporting the claim that MDs have a definitive impact on the risk of OP, which contradicts many existing observational reports. Further studies are needed to determine the potential mechanisms of the associations observed in observational studies.

Epilepsy, Immunity and Neuropsychiatric Disorders

Several studies have focused on the emerging role of immunity and inflammation in a wide range of neurological disorders. Autoimmune diseases involving central nervous system share well defined clinical features including epileptic seizures and additional neuropsychiatric symptoms, like cognitive and psychiatric disturbances. The growing evidence about the role of immunity in the pathophysiologic mechanisms underlying these conditions lead to the concept of autoimmune epilepsy. This relatively-new term has been introduced to highlight the etiological and prognostic implications of immunity in epileptogenesis. In this review, we aim to discuss the role of autoimmunity in epileptogenesis and its clinical, neurophysiological, neuroimaging and therapeutic implications. Moreover, we wish to address the close relationship between immunity and additional symptoms, particularly cognitive and psychiatric features, which deeply impact clinical outcomes in these patients. To assess these aspects, we first analyzed Rasmussen's encephalitis. Subsequently, we have covered autoimmune encephalitis, particularly those associated with autoantibodies against surface neuronal antigens, as these autoantibodies express a direct immune-mediated mechanism, different from those against intracellular antigens. Then, we discussed the connection between systemic immune disorders and neurological manifestations. This review aims to highlight the need to expand knowledge about the role of inflammation and autoimmunity in the pathophysiology of neurological disorders and the importance to early recognize these clinical entities. Indeed, early identification may result in faster recovery and a better prognosis.

Sex hormones and risk of epilepsy: A bidirectional Mendelian randomization study

Background

Multiple evidence has suggested complex interaction between sex hormones and epilepsy. However, whether there exists a causal association and the effect direction remains controversial. Here we aimed to examine the causative role of hormones in the risk of epilepsy and vice versa.

Methods

We conducted a bidirectional two-sample Mendelian randomization analysis using summary statistics from genome-wide association studies of major sex hormones including testosterone (N = 425,097), estradiol (N = 311,675) and progesterone (N = 2,619), together with epilepsy (N = 44,889). We further performed sex-stratified analysis, and verified the significant results using summary statistics from another study on estradiol in males (N = 206,927).

Results

Genetically determined higher estradiol was associated with a reduced risk of epilepsy (OR: 0.90, 95% CI: 0.83-0.98, P = 9.51E-03). In the sex-stratified analysis, the protective effect was detected in males (OR: 0.92, 95% CI: 0.88-0.97, P = 9.18E-04), but not in females. Such association was further verified in the replication stage (OR: 0.44, 95% CI: 0.23-0.87, P = 0.017). In contrast, no association was identified between testosterone, progesterone and the risk of epilepsy. In the opposite direction, epilepsy was not causally associated with sex hormones.

Conclusion

These results demonstrated higher estradiol could reduce the risk of epilepsy, especially in males. Future development of preventive or therapeutic interventions in clinical trials could attach importance to this.

Mendelian randomization study shows a causal effect of asthma on epilepsy risk

Objective

The relationship between asthma and epilepsy in observational studies is controversial. The purpose of this Mendelian randomization (MR) study is to investigate whether asthma causally contributes to epilepsy susceptibility.

Methods

Independent genetic variants strongly (P<5E-08) associated with asthma were from a recent meta-analysis of genome-wide association studies on 408,442 participants. Two independent summary statistics of epilepsy obtained from the International League Against Epilepsy Consortium (ILAEC, Ncases=15,212, and Ncontrols=29,677) and FinnGen Consortium (Ncases=6,260 and Ncontrols=176,107) were used in the discovery and replication stage, respectively. Several sensitivity analyses and heterogeneity analyses were further conducted to assess the stability of the estimates.

Results

Using the inverse-variance weighted approach, genetic predisposition to asthma was associated with an elevated risk of epilepsy in the discovery stage (ILAEC: odds ratio [OR]=1.112, 95% confidence intervals [CI]= 1.023-1.209, P = 0.012), but not verified in the replication stage (FinnGen: OR=1.021, 95%CI= 0.896-1.163, P =0.753). However, a further meta-analysis of both ILAEC and FinnGen showed a similar result (OR=1.085, 95% CI: 1.012-1.164, P = 0.022). There were no causal associations between the age onset of asthma and epilepsy. Sensitivity analyses yielded consistent causal estimates.

Conclusion

The present MR study suggests that asthma is associated with an increased risk of epilepsy independent of the age onset of asthma. Further studies are warranted to explain the underlying mechanisms of this association.

Whole-exome sequencing of a Saudi epilepsy cohort reveals association signals in known and potentially novel loci

BACKGROUND

Epilepsy, a serious chronic neurological condition effecting up to 100 million people globally, has clear genetic underpinnings including common and rare variants. In Saudi Arabia, the prevalence of epilepsy is high and caused mainly by perinatal and genetic factors. No whole-exome sequencing (WES) studies have been performed to date in Saudi Arabian epilepsy cohorts. This offers a unique opportunity for the discovery of rare genetic variants impacting this disease as there is a high rate of consanguinity among large tribal pedigrees.

RESULTS

We performed WES on 144 individuals diagnosed with epilepsy, to interrogate known epilepsy-related genes for known and functional novel variants. We also used an American College of Medical Genetics (ACMG) guideline-based variant prioritization approach in an attempt to discover putative causative variants. We identified 32 potentially causative pathogenic variants across 30 different genes in 44/144 (30%) of these Saudi epilepsy individuals. We also identified 232 variants of unknown significance (VUS) across 101 different genes in 133/144 (92%) subjects. Strong enrichment of variants of likely pathogenicity was observed in previously described epilepsy-associated loci, and a number of putative pathogenic variants in novel loci are also observed.

CONCLUSION

Several putative pathogenic variants in known epilepsy-related loci were identified for the first time in our population, in addition to several potential new loci which may be prioritized for further investigation.

The different clinical facets of SYN1-related neurodevelopmental disorders

Synapsin-I (SYN1) is a presynaptic phosphoprotein crucial for synaptogenesis and synaptic plasticity. Pathogenic SYN1 variants are associated with variable X-linked neurodevelopmental disorders mainly affecting males. In this study, we expand on the clinical and molecular spectrum of the SYN1-related neurodevelopmental disorders by describing 31 novel individuals harboring 22 different SYN1 variants. We analyzed newly identified as well as previously reported individuals in order to define the frequency of key features associated with these disorders. Specifically, behavioral disturbances such as autism spectrum disorder or attention deficit hyperactivity disorder are observed in 91% of the individuals, epilepsy in 82%, intellectual disability in 77%, and developmental delay in 70%. Seizure types mainly include tonic-clonic or focal seizures with impaired awareness. The presence of reflex seizures is one of the most representative clinical manifestations related to SYN1. In more than half of the cases, seizures are triggered by contact with water, but other triggers are also frequently reported, including rubbing with a towel, fever, toothbrushing, fingernail clipping, falling asleep, and watching others showering or bathing. We additionally describe hyperpnea, emotion, lighting, using a stroboscope, digestive troubles, and defecation as possible triggers in individuals with SYN1 variants. The molecular spectrum of SYN1 variants is broad and encompasses truncating variants (frameshift, nonsense, splicing and start-loss variants) as well as non-truncating variants (missense substitutions and in-frame duplications). Genotype-phenotype correlation revealed that epileptic phenotypes are enriched in individuals with truncating variants. Furthermore, we could show for the first time that individuals with early seizures onset tend to present with severe-to-profound intellectual disability, hence highlighting the existence of an association between early seizure onset and more severe impairment of cognitive functions. Altogether, we present a detailed clinical description of the largest series of individuals with SYN1 variants reported so far and provide the first genotype-phenotype correlations for this gene. A timely molecular diagnosis and genetic counseling are cardinal for appropriate patient management and treatment.

Drug resistance in idiopathic generalized epilepsies: Evidence and concepts

Although approximately 10%-15% of patients with idiopathic generalized epilepsy (IGE)/genetic generalized epilepsy remain drug-resistant, there is no consensus or established concept regarding the underlying mechanisms and prevalence. This review summarizes the recent data and the current hypotheses on mechanisms that may contribute to drug-resistant IGE. A literature search was conducted in PubMed and Embase for studies on mechanisms of drug resistance published since 1980. The literature shows neither consensus on the definition nor a widely accepted model to explain drug resistance in IGE or one of its subsyndromes. Large-scale genetic studies have failed to identify distinct genetic causes or affected genes involved in pharmacokinetics. We found clinical and experimental evidence in support of four hypotheses: (1) "network hypothesis"-the degree of drug resistance in IGE reflects the severity of cortical network alterations, (2) "minor focal lesion in a predisposed brain hypothesis"-minor cortical lesions are important for drug resistance, (3) "interneuron hypothesis"-impaired functioning of γ-aminobutyric acidergic interneurons contributes to drug resistance, and (4) "changes in drug kinetics"-genetically impaired kinetics of antiseizure medication (ASM) reduce the effectiveness of available ASMs. In summary, the exact definition and cause of drug resistance in IGE is unknown. However, published evidence suggests four different mechanisms that may warrant further investigation.

Integrative genomics reveals pathogenic mediator of valproate-induced neurodevelopmental disability

Prenatal exposure to the anti-seizure medication sodium valproate (VPA) is associated with an increased risk of adverse postnatal neurodevelopmental outcomes, including lowered intellectual ability, autism spectrum disorder and attention-deficit hyperactivity disorder. In this study, we aimed to clarify the molecular mechanisms underpinning the neurodevelopmental consequences of gestational VPA exposure using integrative genomics. We assessed the effect of gestational VPA on foetal brain gene expression using a validated rat model of valproate teratogenicity that mimics the human scenario of chronic oral valproate treatment during pregnancy at doses that are therapeutically relevant to the treatment of epilepsy. Two different rat strains were studied-inbred Genetic Absence Epilepsy Rats from Strasbourg, a model of genetic generalized epilepsy, and inbred non-epileptic control rats. Female rats were fed standard chow or VPA mixed in standard chow for 2 weeks prior to conception and then mated with same-strain males. In the VPA-exposed rats maternal oral treatment was continued throughout pregnancy. Foetuses were extracted via C-section on gestational Day 21 (1 day prior to birth) and foetal brains were snap-frozen and genome-wide gene expression data generated. We found that gestational VPA exposure via chronic maternal oral dosing was associated with substantial drug-induced differential gene expression in the pup brains, including dysregulated splicing, and observed that this occurred in the absence of evidence for significant neuronal gain or loss. The functional consequences of VPA-induced gene expression were explored using pathway analysis and integration with genetic risk data for psychiatric disease and behavioural traits. The set of genes downregulated by VPA in the pup brains were significantly enriched for pathways related to neurodevelopment and synaptic function and significantly enriched for heritability to human intelligence, schizophrenia and bipolar disorder. Our results provide a mechanistic link between chronic foetal VPA exposure and neurodevelopmental disability mediated by VPA-induced transcriptional dysregulation.

Genetically proxied gut microbiota, gut metabolites with risk of epilepsy and the subtypes: A bi-directional Mendelian randomization study

Background

An increasing number of observational studies have revealed an association among the gut microbiota, gut metabolites, and epilepsy. However, this association is easily influenced by confounders such as diet, and the causality of this association remains obscure.

Methods

Aiming to explore the causal relationship and ascertain specific gut microbe taxa for epilepsy, we conducted a bi-directional Mendelian randomization (MR) study based on the genome-wide association study (GWAS) data of epilepsy from the International League Against Epilepsy, with the gut microbiota GWAS results from MiBioGen, and summary-level GWAS data of gut microbiota-dependent metabolites trimethylamine N-oxide and its predecessors.

Results

Nine phyla, 15 classes, 19 orders, 30 families, and 96 genera were analyzed. A suggestive association of host-genetic-driven increase in family Veillonellaceae with a higher risk of childhood absence epilepsy (odds ratio [OR]: 1.033, confidential interval [CI]: 1.015–1.051, P_IVW = 0.0003), class Melainabacteria with a lower risk of generalized epilepsy with tonic-clonic seizures (OR = 0.986, CI = 0.979–0.994, P_IVW = 0.0002), class Betaproteobacteria (OR = 0.958, CI = 0.937–0.979, P_IVW = 0.0001), and order Burkholderiales (OR = 0.960, CI = 0.937–0.984, P_IVW = 0.0010) with a lower risk of juvenile myoclonic epilepsy were identified after multiple-testing correction. Our sensitivity analysis revealed no evidence of pleiotropy, reverse causality, weak instrument bias, or heterogeneity.

Conclusion

This is the first MR analysis to explore the potential causal relationship among the gut microbiota, metabolites, and epilepsy. Four gut microbiota features (two class levels, one order level, and one family level) were identified as potential interventional targets for patients with childhood absence epilepsy, generalized epilepsy with tonic-clonic seizures, and juvenile myoclonic epilepsy. Previous associations in numerous observational studies may had been interfered by confounders. More rigorous studies were needed to ascertain the relationship among the gut microbiota, metabolites, and epilepsy.

A single-cell transcriptome atlas of glial diversity in the human hippocampus across the postnatal lifespan

The molecular diversity of glia in the human hippocampus and their temporal dynamics over the lifespan remain largely unknown. Here, we performed single-nucleus RNA sequencing to generate a transcriptome atlas of the human hippocampus across the postnatal lifespan. Detailed analyses of astrocytes, oligodendrocyte lineages, and microglia identified subpopulations with distinct molecular signatures and revealed their association with specific physiological functions, age-dependent changes in abundance, and disease relevance. We further characterized spatiotemporal heterogeneity of GFAP-enriched astrocyte subpopulations in the hippocampal formation using immunohistology. Leveraging glial subpopulation classifications as a reference map, we revealed the diversity of glia differentiated from human pluripotent stem cells and identified dysregulated genes and pathological processes in specific glial subpopulations in Alzheimer's disease (AD). Together, our study significantly extends our understanding of human glial diversity, population dynamics across the postnatal lifespan, and dysregulation in AD and provides a reference atlas for stem-cell-based glial differentiation.

Individualised prediction of drug resistance and seizure recurrence after medication withdrawal in people with juvenile myoclonic epilepsy: A systematic review and individual participant data meta-analysis

Background

A third of people with juvenile myoclonic epilepsy (JME) are drug-resistant. Three-quarters have a seizure relapse when attempting to withdraw anti-seizure medication (ASM) after achieving seizure-freedom. It is currently impossible to predict who is likely to become drug-resistant and safely withdraw treatment. We aimed to identify predictors of drug resistance and seizure recurrence to allow for individualised prediction of treatment outcomes in people with JME.

Methods

We performed an individual participant data (IPD) meta-analysis based on a systematic search in EMBASE and PubMed - last updated on March 11, 2021 - including prospective and retrospective observational studies reporting on treatment outcomes of people diagnosed with JME and available seizure outcome data after a minimum one-year follow-up. We invited authors to share standardised IPD to identify predictors of drug resistance using multivariable logistic regression. We excluded pseudo-resistant individuals. A subset who attempted to withdraw ASM was included in a multivariable proportional hazards analysis on seizure recurrence after ASM withdrawal. The study was registered at the Open Science Framework (OSF; https://osf.io/b9zjc/).

Findings

Our search yielded 1641 articles; 53 were eligible, of which the authors of 24 studies agreed to collaborate by sharing IPD. Using data from 2518 people with JME, we found nine independent predictors of drug resistance: three seizure types, psychiatric comorbidities, catamenial epilepsy, epileptiform focality, ethnicity, history of CAE, family history of epilepsy, status epilepticus, and febrile seizures. Internal-external cross-validation of our multivariable model showed an area under the receiver operating characteristic curve of 0·70 (95%CI 0·68-0·72). Recurrence of seizures after ASM withdrawal (n = 368) was predicted by an earlier age at the start of withdrawal, shorter seizure-free interval and more currently used ASMs, resulting in an average internal-external cross-validation concordance-statistic of 0·70 (95%CI 0·68-0·73).

Interpretation

We were able to predict and validate clinically relevant personalised treatment outcomes for people with JME. Individualised predictions are accessible as nomograms and web-based tools.

Funding

MING fonds.

Causal relationship among obesity and body fat distribution and epilepsy subtypes

OBJECTIVE

The observational studies indicate an association between obesity and epilepsy, but it is unclear whether such an association responds to causality. The objective of this study was to determine the causal relationship between obesity and fat distribution and epilepsy subtypes based on waist circumference, hip circumference (HP), waist-hip ratio (WHR), and body mass index (BMI).

METHODS

A two-sample Mendelian randomization study was conducted separately for the four indicators of obesity and epilepsy and its seven subtypes, with reverse Mendelian randomization and multivariate Mendelian randomization for significant outcomes.

RESULTS

A two-sample Mendelian randomized analysis informed us that waist circumference was a risk factor for juvenile myoclonic epilepsy (beta = 0.0299, P = 4.60 × 10-3). The increase in hip circumference increased the risk of juvenile myoclonic epilepsy and epilepsy, with effect values of 0.0283 (P = 2.01 × 10-3) and 0.0928 (P = 1.40 × 10-2), respectively. Furthermore, children with a higher BMI exhibit a higher risk of epilepsy (beta = 0.0148 P = 1.05 × 10-3). The reverse Mendelian randomization study revealed that childhood absence epilepsy increased its BMI (beta = 0.8980, P = 7.52 × 10-7), and juvenile myoclonic epilepsy increased its waist circumference (beta = 0.7322, P = 3.26 × 10-2). Multivariate Mendelian randomization revealed that an increase in hip circumference and waist-hip ratio increased the risk of juvenile myoclonic epilepsy, with an effect value of 0.1051 (P = 9.75 × 10-4) and 0.1430 (P = 3.99 × 10-3), respectively, while an increase in BMI and waist circumference instead decreased their risk, with effect values of -0.0951 (P = 3.14 × 10-2) and-0.0541 (P = 1.71 × 10-2). In contrast, multivariate Mendelian randomization for childhood absence epilepsy and epilepsy did not identify any independent risk factors.

SIGNIFICANCE

Our findings provide novel evidence in favor of obesity as a risk factor for epilepsy and waist circumference as a risk factor for juvenile myoclonic epilepsy. Increased hip circumference confers an elevated risk of juvenile myoclonic epilepsy and epilepsy (all documented cases), and a high BMI increases the risk of childhood absence epilepsy. With this, new insights are provided into the energy metabolism of epilepsy, which supports further nutritional interventions and the search for new therapeutic targets.

Shared genetics and causality underlying epilepsy and attention-deficit hyperactivity disorder

The prevalence of attention deficit hyperactivity disorder (ADHD) in patients with epilepsy was much higher than prevalence in general population, and vice versa. The mechanisms underlying comorbid ADHD and epilepsy remained largely unknown. Here, we systematically analyzed the genetic correlation, causality, shared genetics and specific trait related tissues by using linkage disequilibrium score regression (LDSC), two sample Mendelian randomization (TwoSampleMR), bivariate causal mixture model (MiXeR), conjunctional false discovery rate (conjFDR) and LDSC applied to specifically expressed genes based on genome wide association studies (GWASs) data of ADHD and epilepsy. We found that ADHD had significant positive genetic association with epilepsy. Two-sample Mendelian randomization analysis with genome wide significant single nucleotide polymorphisms (SNPs) as instrument variables suggested a positively causal effect of ADHD on epilepsy. Using MiXeR, which estimates the total amount of shared variants, we observed 1 K causal variants overlapped between ADHD and epilepsy. At conjFDR <0.05, ADHD shared 2 distinct genomic loci with Epilepsy. Further disease-relevant tissues analysis showed that cortex, substantia nigra, amygdala and hippocampus were both associated with ADHD and epilepsy. Our results suggested that ADHD was genetically correlated with epilepsy, which might be due to the fact that they shared common pathogenic sites and tissues origin.

Precision medicine for genetic epilepsy on the horizon: Recent advances, present challenges, and suggestions for continued progress

The genetic basis of many epilepsies is increasingly understood, giving rise to the possibility of precision treatments tailored to specific genetic etiologies. Despite this, current medical therapy for most epilepsies remains imprecise, aimed primarily at empirical seizure reduction rather than targeting specific disease processes. Intellectual and technological leaps in diagnosis over the past 10 years have not yet translated to routine changes in clinical practice. However, the epilepsy community is poised to make impressive gains in precision therapy, with continued innovation in gene discovery, diagnostic ability, and bioinformatics; increased access to genetic testing and counseling; fuller understanding of natural histories; agility and rigor in preclinical research, including strategic use of emerging model systems; and engagement of an evolving group of stakeholders (including patient advocates, governmental resources, and clinicians and scientists in academia and industry). In each of these areas, we highlight notable examples of recent progress, new or persistent challenges, and future directions. The future of precision medicine for genetic epilepsy looks bright if key opportunities on the horizon can be pursued with strategic and coordinated effort.

Assessing the causal association between human blood metabolites and the risk of epilepsy

Background

Metabolic disturbance has been reported in patients with epilepsy. Still, the evidence about the causal role of metabolites in facilitating or preventing epilepsy is lacking. Systematically investigating the causality between blood metabolites and epilepsy would help provide novel targets for epilepsy screening and prevention.

Methods

We conducted two-sample Mendelian randomization (MR) analysis. Data for 486 human blood metabolites came from a genome-wide association study (GWAS) comprising 7824 participants. GWAS data for epilepsy were obtained from the International League Against Epilepsy (ILAE) consortium for primary analysis and the FinnGen consortium for replication and meta-analysis. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy.

Results

482 out of 486 metabolites were included for MR analysis following rigorous genetic variants selection. After IVW and sensitivity analysis filtration, six metabolites with causal effects on epilepsy were identified from the ILAE consortium. Only four metabolites remained significant associations with epilepsy when combined with the FinnGen consortium [uridine: odds ratio (OR) = 2.34, 95% confidence interval (CI) = 1.48–3.71, P = 0.0003; 2-hydroxystearate: OR = 1.61, 95% CI = 1.19–2.18, P = 0.002; decanoylcarnitine: OR = 0.82, 95% CI = 0.72–0.94, P = 0.004; myo-inositol: OR = 0.77, 95% CI = 0.62–0.96, P = 0.02].

Conclusion

The evidence that the four metabolites mentioned above are associated with epilepsy in a causal way provides a novel insight into the underlying mechanisms of epilepsy by integrating genomics with metabolism, and has an implication for epilepsy screening and prevention.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03648-5.

Integrative Analyses Identify KCNJ15 as a Candidate Gene in Patients with Epilepsy

INTRODUCTION

Although there is accumulating evidence that genetic factors play a vital role in the pathogenesis of epilepsy, few epilepsy-associated genes have been identified. Additionally, the role of KCNJ15 in epilepsy has not been evaluated so far.

METHODS

Here, we performed differentially expressed gene analysis, expression quantitative trait loci analysis, gene co-expression analysis, and protein-protein interaction analysis to evaluate the role of KCNJ15 in epilepsy.

RESULTS

Analysis of gene expression and expression quantitative trait loci data revealed that KCNJ15 was significantly downregulated in patients with epilepsy (adjusted P = 0.0146 and log₂ Fold change = - 1.0025), and an epilepsy-associated polymorphism (rs2833098) was linked to altered KCNJ15 expression level in human temporal lobe brain tissue (P = 0.0036). Gene co-expression analysis revealed that KCNJ15 was co-expressed with genes that have been reported to be associated with epilepsy in human brain tissue. Furthermore, protein-protein interaction analysis revealed strong supportive evidence for the role of KCNJ15 in epilepsy.

CONCLUSION

Our results show that KCNJ15 may be a candidate target for epilepsy. Functional analysis of KCNJ15 may provide novel insights for epilepsy treatment.

The associations between plasma soluble Trem1 and neurological diseases: a Mendelian randomization study

Background

Triggering receptor expressed on myeloid cell 1 (Trem1) is an important regulator of cellular inflammatory responses. Neuroinflammation is a common thread across various neurological diseases. Soluble Trem1 (sTrem1) in plasma is associated with the development of central nervous system disorders. However, the extent of any causative effects of plasma sTrem1 on the risk of these disorders is still unclear.

Method

Genetic variants for plasma sTrem1 levels were selected as instrumental variables. Summary-level statistics of neurological disorders, including Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS), epilepsy, cerebrovascular diseases, and migraine were collected from genome-wide association studies (GWASs). Whether plasma sTrem1 was causally associated with neurological disorders was assessed using a two-sample Mendelian randomization (MR) analysis, with false discovery rate (FDR)-adjusted methods applied.

Results

We inferred suggestive association of higher plasma sTrem1 with the risk of AD (odds ratio [OR] per one standard deviation [SD] increase = 1.064, 95% CI 1.012–1.119, P = 0.014, P_FDR = 0.056). Moreover, there was significant association between plasma sTrem1 level and the risk of epilepsy (OR per one SD increase = 1.044, 95% CI 1.016–1.072, P = 0.002, P_FDR = 0.032), with a modest statistical power of 41%. Null associations were found for plasma sTrem1 with other neurological diseases and their subtypes.

Conclusions

Taken together, this study indicates suggestive association between plasma sTrem1 and AD. Moreover, higher plasma sTrem1 was associated with the increased risk of epilepsy. The findings support the hypothesis that sTrem1 may be a vital element on the causal pathway to AD and epilepsy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02582-z.

Interactome overlap between risk genes of epilepsy and targets of anti-epileptic drugs

Aanti-epileptic drugs have been used for treating epilepsy for decades, meanwhile, more than one hundred genes have been identified to be associated with risk of epilepsy; however, the interaction mechanism between anti-epileptic drugs and risk genes of epilepsy was still not clearly understood. In this study, we systematically explored the interaction of epilepsy risk genes and anti-epileptic drug targets through a network-based approach. Our results revealed that anti-epileptic drug targets were significantly over-represented in risk genes of epilepsy with 17 overlapping genes and P-value = 2.2 ×10 −16. We identified a significantly localized PPI network with 55 epileptic risk genes and 94 anti-epileptic drug target genes, and network overlap analysis showed significant interactome overlap between risk genes and drug targets with P-value = 0.04. Besides, genes from PPI network were significantly enriched in the co-expression network of epilepsy with 22 enriched genes and P-value = 1.3 ×10 −15; meanwhile, cell type enrichment analysis indicated genes in this network were significantly enriched in 4 brain cell types (Interneuron, Medium Spiny Neuron, CA1 pyramidal Neuron, and Somatosensory pyramidal Neuron). These results provide evidence for significant interactions between epilepsy risk genes and anti-epileptic drug targets from the perspective of network biology.

Local molecular and global connectomic contributions to cross-disorder cortical abnormalities

Numerous brain disorders demonstrate structural brain abnormalities, which are thought to arise from molecular perturbations or connectome miswiring. The unique and shared contributions of these molecular and connectomic vulnerabilities to brain disorders remain unknown, and has yet to be studied in a single multi-disorder framework. Using MRI morphometry from the ENIGMA consortium, we construct maps of cortical abnormalities for thirteen neurodevelopmental, neurological, and psychiatric disorders from N = 21,000 participants and N = 26,000 controls, collected using a harmonised processing protocol. We systematically compare cortical maps to multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination (molecular vulnerability), as well as global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability). We find a relationship between molecular vulnerability and white-matter architecture that drives cortical disorder profiles. Local attributes, particularly neurotransmitter receptor profiles, constitute the best predictors of both disorder-specific cortical morphology and cross-disorder similarity. Finally, we find that cross-disorder abnormalities are consistently subtended by a small subset of network epicentres in bilateral sensory-motor, inferior temporal lobe, precuneus, and superior parietal cortex. Collectively, our results highlight how local molecular attributes and global connectivity jointly shape cross-disorder cortical abnormalities.

Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression

Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.

Evidence for correlations between BMI-associated SNPs and circRNAs

Circular RNAs (circRNAs) are regulators of processes like adipogenesis. Their expression can be modulated by SNPs. We analysed links between BMI-associated SNPs and circRNAs. First, we detected an enrichment of BMI-associated SNPs on circRNA genomic loci in comparison to non-significant variants. Analysis of sex-stratified GWAS data revealed that circRNA genomic loci encompassed more genome-wide significant BMI-SNPs in females than in males. To explore whether the enrichment is restricted to BMI, we investigated nine additional GWAS studies. We showed an enrichment of trait-associated SNPs in circRNAs for four analysed phenotypes (body height, chronic kidney disease, anorexia nervosa and autism spectrum disorder). To analyse the influence of BMI-affecting SNPs on circRNA levels in vitro, we examined rs4752856 located on hsa_circ_0022025. The analysis of heterozygous individuals revealed an increased level of circRNA derived from the BMI-increasing SNP allele. We conclude that genetic variation may affect the BMI partly through circRNAs.

The potential role of DNA methylation as preventive treatment target of epileptogenesis

Pharmacological therapy of epilepsy has so far been limited to symptomatic treatment aimed at neuronal targets, with the result of an unchanged high proportion of patients lacking seizure control. The dissection of the intricate pathological mechanisms that transform normal brain matter to a focus for epileptic seizures—the process of epileptogenesis—could yield targets for novel treatment strategies preventing the development or progression of epilepsy. While many pathological features of epileptogenesis have been identified, obvious shortcomings in drug development are now believed to be based on the lack of knowledge of molecular upstream mechanisms, such as DNA methylation (DNAm), and as well as a failure to recognize glial cell involvement in epileptogenesis. This article highlights the potential role of DNAm and related gene expression (GE) as a treatment target in epileptogenesis.

Epigenetic genes and epilepsy - emerging mechanisms and clinical applications

An increasing number of epilepsies are being attributed to variants in genes with epigenetic functions. The products of these genes include factors that regulate the structure and function of chromatin and the placing, reading and removal of epigenetic marks, as well as other epigenetic processes. In this Review, we provide an overview of the various epigenetic processes, structuring our discussion around five function-based categories: DNA methylation, histone modifications, histone-DNA crosstalk, non-coding RNAs and chromatin remodelling. We provide background information on each category, describing the general mechanism by which each process leads to altered gene expression. We also highlight key clinical and mechanistic aspects, providing examples of genes that strongly associate with epilepsy within each class. We consider the practical applications of these findings, including tissue-based and biofluid-based diagnostics and precision medicine-based treatments. We conclude that variants in epigenetic genes are increasingly found to be causally involved in the epilepsies, with implications for disease mechanisms, treatments and diagnostics.

Genetic causes of rare and common epilepsies: What should the epileptologist know?

In past decades, the identification of genes involved in epileptic disorders has grown exponentially. The pace of gene identification in epileptic disorders began to accelerate in the late 2000s, driven by new technologies such as molecular cytogenetics and next-generation sequencing (NGS). These technologies have also been applied to genetic diagnostics, with different configurations, such as gene panels, whole-exome sequencing and whole-genome sequencing. The clinician must be aware that any technology has its limitations and complementary techniques must still be used to establish a diagnosis for specific diseases. In addition, increasing the amount of genetic information available in a larger patient sample also increases the need for rigorous interpretation steps, when taking into account the clinical, electroclinical, and when available, functional data. Local, multidisciplinary discussions have proven valuable in difficult diagnostic situations, especially in cases where precision medicine is being considered. They also serve to improve genetic counseling in complex situations. In this article, we will briefly review the genetic basis of rare and common epilepsies, the current strategies used for molecular diagnosis, including their limitations, and some pitfalls for data interpretation, in the context of etiological diagnosis and genetic counseling.

Assessment of burden and segregation profiles of CNVs in patients with epilepsy

Objective

Microdeletions are associated with different forms of epilepsy but show incomplete penetrance, which is not well understood. We aimed to assess whether unmasked variants or double CNVs could explain incomplete penetrance.

Methods

We analyzed copy number variants (CNVs) in 603 patients with four different subgroups of epilepsy and 945 controls. CNVs were called from genotypes and validated on whole‐genome (WGS) or whole‐exome sequences (WES). CNV burden difference between patients and controls was obtained by fitting a logistic regression. CNV burden was assessed for small and large (>1 Mb) deletions and duplications and for deletions overlapping different gene sets.

Results

Large deletions were enriched in genetic generalized epilepsies (GGE) compared to controls. We also found enrichment of deletions in epilepsy genes and hotspots for GGE. We did not find truncating or functional variants that could have been unmasked by the deletions. We observed a double CNV hit in two patients. One patient also carried a de novo deletion in the 22q11.2 hotspot.

Interpretation

We could corroborate previous findings of an enrichment of large microdeletions and deletions in epilepsy genes in GGE. We could also replicate that microdeletions show incomplete penetrance. However, we could not validate the hypothesis of unmasked variants nor the hypothesis of double CNVs to explain the incomplete penetrance. We found a de novo CNV on 22q11.2 that could be of interest. We also observed GGE families carrying a deletion on 15q13.3 hotspot that could be investigated in the Quebec founder population.

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.

Genetics and gene therapy in Dravet syndrome

Dravet syndrome is a well-established electro-clinical condition first described in 1978. A main genetic cause was identified with the discovery of a loss-of-function SCN1A variant in 2001. Mechanisms underlying the phenotypic variations have subsequently been a main topic of research. Various genetic modifiers of clinical severities have been elucidated through many rigorous studies on genotype-phenotype correlations and the recent advances in next generation sequencing technology. Furthermore, a deeper understanding of the regulation of gene expression and remarkable progress on genome-editing technology using the CRISPR-Cas9 system provide significant opportunities to overcome hurdles of gene therapy, such as enhancing Na_V1.1 expression. This article reviews the current understanding of genetic pathology and the status of research toward the development of gene therapy for Dravet syndrome. This article is part of the Special Issue "Severe Infantile Epilepsies".

Imaging Genetics in Epilepsy: Current Knowledge and New Perspectives

Epilepsy is a neurological network disease with genetics playing a much greater role than was previously appreciated. Unfortunately, the relationship between genetic basis and imaging phenotype is by no means simple. Imaging genetics integrates multidimensional datasets within a unified framework, providing a unique opportunity to pursue a global vision for epilepsy. This review delineates the current knowledge of underlying genetic mechanisms for brain networks in different epilepsy syndromes, particularly from a neural developmental perspective. Further, endophenotypes and their potential value are discussed. Finally, we highlight current challenges and provide perspectives for the future development of imaging genetics in epilepsy.

Benchmarking of univariate pleiotropy detection methods applied to epilepsy

Pleiotropy is a widespread phenomenon that may increase insight into the etiology of biological and disease traits. Since genome-wide association studies frequently provide information on a single trait only, only univariate pleiotropy detection methods are applicable, with yet unknown comparative performance. Here, we compared five such methods with respect to their ability to detect pleiotropy, including meta-analysis, ASSET, cFDR, CPBayes, and PLACO, by performing extended computer simulations that varied the underlying etiological model for pleiotropy for a pair of traits, including the number of causal variants, degree of traits' overlap, effect sizes as well as trait prevalence, and varying sample sizes. Our results indicate that ASSET provides the best trade-off between power and protection against false positives. We then applied ASSET to a previously published ILAE consortium dataset on complex epilepsies, comprising genetic generalized epilepsy and focal epilepsy cases and corresponding controls. We identified a novel candidate locus at 17q21.32 and confirmed locus 2q24.3, previously identified to act pleiotropically on both epilepsy subtypes by a mega-analysis. Functional annotation, tissue-specific expression and regulatory function analysis as well as Bayesian co-localization analysis corroborated this result, rendering 17q21.32 a worthwhile candidate for follow-up studies on pleiotropy in epilepsies. This article is protected by copyright. All rights reserved.

Common risk variants for epilepsy are enriched in families previously targeted for rare monogenic variant discovery

BACKGROUND

The epilepsies are highly heritable conditions that commonly follow complex inheritance. While monogenic causes have been identified in rare familial epilepsies, most familial epilepsies remain unsolved. We aimed to determine (1) whether common genetic variation contributes to familial epilepsy risk, and (2) whether that genetic risk is enriched in familial compared with non-familial (sporadic) epilepsies.

METHODS

Using common variants derived from the largest epilepsy genome-wide association study, we calculated polygenic risk scores (PRS) for patients with familial epilepsy (n = 1,818 from 1,181 families), their unaffected relatives (n = 771), sporadic patients (n = 1,182), and population controls (n = 15,929). We also calculated separate PRS for genetic generalised epilepsy (GGE) and focal epilepsy. Statistical analyses used mixed-effects regression models to account for familial relatedness, sex, and ancestry.

FINDINGS

Patients with familial epilepsies had higher epilepsy PRS compared to population controls (OR 1·20, p_adj = 5×10^-9), sporadic patients (OR 1·11, p_adj = 0.008), and their own unaffected relatives (OR 1·12, p_adj = 0.01). The top 1% of the PRS distribution was enriched 3.8-fold for individuals with familial epilepsy when compared to the lowest decile (p_adj = 5×10^-11). Familial PRS enrichment was consistent across epilepsy type; overall, polygenic risk was greatest for the GGE clinical group. There was no significant PRS difference in familial cases with established rare variant genetic etiologies compared to unsolved familial cases.

INTERPRETATION

The aggregate effects of common genetic variants, measured as polygenic risk scores, play an important role in explaining why some families develop epilepsy, why specific family members are affected while their relatives are not, and why families manifest specific epilepsy types. Polygenic risk contributes to the complex inheritance of the epilepsies, including in individuals with a known genetic etiology.

FUNDING

National Health and Medical Research Council of Australia, National Institutes of Health, American Academy of Neurology, Thomas B and Jeannette E Laws McCabe Fund, Mirowski Family Foundation.

SCN1A overexpression, associated with a genomic region marked by a risk variant for a common epilepsy, raises seizure susceptibility

Mesial temporal lobe epilepsy with hippocampal sclerosis and a history of febrile seizures is associated with common variation at rs7587026, located in the promoter region of SCN1A. We sought to explore possible underlying mechanisms. SCN1A expression was analysed in hippocampal biopsy specimens of individuals with mesial temporal lobe epilepsy with hippocampal sclerosis who underwent surgical treatment, and hippocampal neuronal cell loss was quantitatively assessed using immunohistochemistry. In healthy individuals, hippocampal volume was measured using MRI. Analyses were performed stratified by rs7587026 type. To study the functional consequences of increased SCN1A expression, we generated, using transposon-mediated bacterial artificial chromosome transgenesis, a zebrafish line expressing exogenous scn1a, and performed EEG analysis on larval optic tecta at 4 day post-fertilization. Finally, we used an in vitro promoter analysis to study whether the genetic motif containing rs7587026 influences promoter activity. Hippocampal SCN1A expression differed by rs7587026 genotype (Kruskal-Wallis test P = 0.004). Individuals homozygous for the minor allele showed significantly increased expression compared to those homozygous for the major allele (Dunn's test P = 0.003), and to heterozygotes (Dunn's test P = 0.035). No statistically significant differences in hippocampal neuronal cell loss were observed between the three genotypes. Among 597 healthy participants, individuals homozygous for the minor allele at rs7587026 displayed significantly reduced mean hippocampal volume compared to major allele homozygotes (Cohen's D = - 0.28, P = 0.02), and to heterozygotes (Cohen's D = - 0.36, P = 0.009). Compared to wild type, scn1lab-overexpressing zebrafish larvae exhibited more frequent spontaneous seizures [one-way ANOVA F(4,54) = 6.95 (P < 0.001)]. The number of EEG discharges correlated with the level of scn1lab overexpression [one-way ANOVA F(4,15) = 10.75 (P < 0.001]. Finally, we showed that a 50 bp promoter motif containing rs7587026 exerts a strong regulatory role on SCN1A expression, though we could not directly link this to rs7587026 itself. Our results develop the mechanistic link between rs7587026 and mesial temporal lobe epilepsy with hippocampal sclerosis and a history of febrile seizures. Furthermore, we propose that quantitative precision may be important when increasing SCN1A expression in current strategies aiming to treat seizures in conditions involving SCN1A haploinsufficiency, such as Dravet syndrome.

ILAE definition of the Idiopathic Generalized Epilepsy Syndromes: Position statement by the ILAE Task Force on Nosology and Definitions

In 2017, the International League Against Epilepsy (ILAE) Classification of Epilepsies described the "genetic generalized epilepsies" (GGEs), which contained the "idiopathic generalized epilepsies" (IGEs). The goal of this paper is to delineate the four syndromes comprising the IGEs, namely childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy, and epilepsy with generalized tonic-clonic seizures alone. We provide updated diagnostic criteria for these IGE syndromes determined by the expert consensus opinion of the ILAE's Task Force on Nosology and Definitions (2017-2021) and international external experts outside our Task Force. We incorporate current knowledge from recent advances in genetic, imaging, and electroencephalographic studies, together with current terminology and classification of seizures and epilepsies. Patients that do not fulfill criteria for one of these syndromes, but that have one, or a combination, of the following generalized seizure types: absence, myoclonic, tonic-clonic and myoclonic-tonic-clonic seizures, with 2.5-5.5 Hz generalized spike-wave should be classified as having GGE. Recognizing these four IGE syndromes as a special grouping among the GGEs is helpful, as they carry prognostic and therapeutic implications.

Transethnic meta-analysis of exome-wide variants identifies new loci associated with male-specific metabolic syndrome

BACKGROUND

Metabolic syndrome (MetS) is a group of very common human conditions promoting strong understand the impact of rare variants, beyond exome-wide association studies, to potentially discover causative variants, across different ethnic populations.

OBJECTIVE

We performed transethnic, exome-wide MetS association studies on MetS in men.

METHODS

We analyzed genotype data of 5302 European subjects (2658 cases and 2644 controls), in the discovery stage of the European METabolic Syndrome In Men study, generated from exome chips, and 2481 subjects (714 cases and 1767 controls), in the replication stage, across 6 independent cohorts of 5 ancestries (T2D-GENES consortium), using whole-exome sequencing. We therefore evaluated gene-level and variant-level associations, of rare variants for MetS, using logistic regression (LR) and multivariate analyses (MulA).

RESULTS

Gene-based association found the gene for the cholesteryl ester transfer protein (CETP) (from MulA, p value = 4.67 × 10-9; from LR, p value = 0.009) to well associate with MetS. At two missense variants, from 8 rare variants in CETP, Ala390Pro (rs5880) (from MulA, p value = 1.28 × 10-7; from LR, p value = 1.34 × 10-4) and Arg468Gln (rs1800777) (from MulA, p value = 2.40 × 10-5; from LR, p value = 1.49 × 10-3) significantly associated with MetS across five ancestries.

CONCLUSIONS

Our findings highlight novel rare variants of genes that confer MetS susceptibility, in Europeans, that are shared with diverse populations, emphasizing an opportunity to further understand the biological target or genes that underlie MetS, across populations.

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.

Potential Pleiotropic Genes and Shared Biological Pathways in Epilepsy and Depression Based on GWAS Summary Statistics

Current epidemiological and experimental studies have indicated the overlapping genetic foundation of epilepsy and depression. However, the detailed pleiotropic genetic etiology and neurobiological pathways have not been well understood, and there are many variants with underestimated effect on the comorbidity of the two diseases. Utilizing genome-wide association study (GWAS) summary statistics of epilepsy (15,212 cases and 29,677 controls) and depression (170,756 cases and 329,443 controls) from large consortia, we assessed the integrated gene-based association with both diseases by Multimarker Analysis of Genomic Annotation (MAGMA) and Fisher's meta-analysis. On the one hand, shared genes with significantly altered transcripts in Gene Expression Omnibus (GEO) data sets were considered as possible pleiotropic genes. On the other hand, the pathway enrichment analysis was conducted based on the gene lists with nominal significance in the gene-based association test of each disease. We identified a total of two pleiotropic genes (CD3G and SLCO3A1) with gene expression analysis validated and interpreted twenty-five common biological process supported with literature mining. This study indicates the potentially shared genes associated with both epilepsy and depression based on gene expression, meta-data analysis, and pathway enrichment strategy along with traditional GWAS and provides insights into the possible intersecting pathways that were not previously reported.

CSF sTREM2 in neurological diseases: a two-sample Mendelian randomization study

Background

Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in cerebrospinal fluid (CSF) has been described as a biomarker for microglial activation, which were observed increased in a variety of neurological disorders.

Objective

Our objective was to explore whether genetically determined CSF sTREM2 levels are causally associated with different neurological diseases by conducting a two-sample Mendelian randomization (MR) study.

Methods

Single nucleotide polymorphisms significantly associated with CSF sTREM2 levels were selected as instrumental variables to estimate the causal effects on clinically common neurological diseases, including stroke, Alzheimer’s diseases, Parkinson’s diseases, amyotrophic lateral sclerosis, multiple sclerosis, and epilepsy and their subtypes. Summary-level statistics of both exposure and outcomes were applied in an MR framework.

Results

Genetically predicted per 1 pg/dL increase of CSF sTREM2 levels was associated with higher risk of multiple sclerosis (OR = 1.038, 95%CI = 1.014–1.064, p = 0.002). Null association was found in risk of other included neurological disorders.

Conclusions

These findings provide support for a potential causal relationship between elevated CSF sTREM2 levels and higher risk of multiple sclerosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02443-9.

Genetic variants associated with longitudinal changes in brain structure across the lifespan

Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.

Alcohol, Coffee, and Milk Intake in Relation to Epilepsy Risk

Alcohol, coffee and milk intakes have been explored in relation to epilepsy risk in observational studies; however, the results were not consistent. We performed a Mendelian randomisation (MR) study to evaluate the causality of these relationships. Genetic variants associated with alcohol, coffee and milk intake were adopted as instrumental variables. We obtained the summary data of epilepsy from the International League Against Epilepsy (ILAE) Consortium (15,212 cases and 29,677 controls) and FinnGen consortium (4588 cases and 144,780 controls). Genetically predicted alcohol intake was associated with a higher risk of epilepsy in the ILAE Consortium (odds ratio (OR): 1.22, 95% confidence intervals (CI): 1.02-1.45). The association in the FinnGen consortium remained consistent in direction. Combined analysis of ILAE and FinnGen databases further indicated that genetically predicted alcohol intake was associated with a higher risk of epilepsy (OR = 1.24; 95% CI, 1.06-1.47, p = 0.009). Genetically predicted coffee intake was not related to epilepsy risk, while higher genetically predicted milk intake was related to a lower risk of epilepsy (OR = 0.957; 95% CI, 0.917-0.999, p = 0.044). Our results suggest a detrimental effect of alcohol intake on the risk of epilepsy, while milk intake might be associated with a decreased risk of epilepsy.

Seizure outcome trajectories in a well-defined cohort of newly diagnosed juvenile myoclonic epilepsy patients

OBJECTIVE

To investigate the temporal course of medication response and associated prognostic factors in a cohort of juvenile myoclonic epilepsy (JME) patients over a long-term follow-up.

MATERIALS AND METHODS

Data from 113 JME patients diagnosed according to recently proposed class II criteria were retrospectively reviewed. Early sustained remission was defined as 4-year seizure remission starting within 2 years from the first antiseizure medication (ASM) intake, as opposed to delayed sustained remission. Spontaneous relapse rate (ie, not related to ASM withdrawal) was also investigated, along with factors associated with seizure relapse.

RESULTS

Four-year seizure remission was obtained by 76/113 (67.3%) subjects. Early sustained remission was achieved by 45/76 (59.2%) patients. Absence seizures were significantly associated with no-remission at multivariable multinomial logistic regression analysis. Catamenial seizures and earlier age at epilepsy onset significantly predicted delayed sustained remission. Spontaneous seizure relapse after 4-year remission occurred in 15.7% of patients with early sustained remission and in 35.5% of those with delayed sustained remission (p = 0.045). The most common concomitant factors for a spontaneous relapse were irregular lifestyle habits and pregnancy-related switch from valproate to another ASM. Patients with a history of catamenial seizures were more likely to experience a spontaneous generalized tonic-clonic seizure relapse after 4-year remission at univariable analysis.

SIGNIFICANCE

Our data support the prognostic relevance of early medication response in JME patients. Furthermore, the prognostic significance of catamenial seizures and the impact of valproate switch on seizure relapse after a prolonged remission account for the challenging therapeutic management of women with childbearing potential.

Drosophila carrying epilepsy-associated variants in the vitamin B6 metabolism gene PNPO display allele- and diet-dependent phenotypes

Both genetic and environmental factors contribute to epilepsy. Understanding their contributions and interactions helps disease management. However, it is often challenging to study gene–environment interaction in humans due to their heterogeneous genetic background and less controllable environmental factors. The fruit fly, Drosophila melanogaster, has been proven to be a powerful model to study human diseases, including epilepsy. We generated knock-in flies carrying different epilepsy-associated pyridox(am)ine 5^′-phosphate oxidase (PNPO) alleles and studied the developmental, behavioral, electrophysiological, and fitness effects of each mutant allele under different dietary conditions. We showed that phenotypes in knock-in flies are allele and diet dependent, providing clues for timely and specific diet interventions. Our results offer biological insights into mechanisms underlying phenotypic variations and specific therapeutic strategies.

Pyridox(am)ine 5^′-phosphate oxidase (PNPO) catalyzes the rate-limiting step in the synthesis of pyridoxal 5^′-phosphate (PLP), the active form of vitamin B6 required for the synthesis of neurotransmitters gamma-aminobutyric acid (GABA) and the monoamines. Pathogenic variants in PNPO have been increasingly identified in patients with neonatal epileptic encephalopathy and early-onset epilepsy. These patients often exhibit different types of seizures and variable comorbidities. Recently, the PNPO gene has also been implicated in epilepsy in adults. It is unclear how these phenotypic variations are linked to specific PNPO alleles and to what degree diet can modify their expression. Using CRISPR-Cas9, we generated four knock-in Drosophila alleles, h^WT, h^R116Q, h^D33V , and h^R95H, in which the endogenous Drosophila PNPO was replaced by wild-type human PNPO complementary DNA (cDNA) and three epilepsy-associated variants. We found that these knock-in flies exhibited a wide range of phenotypes, including developmental impairments, abnormal locomotor activities, spontaneous seizures, and shortened life span. These phenotypes are allele dependent, varying with the known biochemical severity of these mutations and our characterized molecular defects. We also showed that diet treatments further diversified the phenotypes among alleles, and PLP supplementation at larval and adult stages prevented developmental impairments and seizures in adult flies, respectively. Furthermore, we found that h^R95H had a significant dominant-negative effect, rendering heterozygous flies susceptible to seizures and premature death. Together, these results provide biological bases for the various phenotypes resulting from multifunction of PNPO, specific molecular and/or genetic properties of each PNPO variant, and differential allele–diet interactions.

Association of ultra-rare coding variants with genetic generalized epilepsy: A case-control whole exome sequencing study

OBJECTIVE

We aimed to identify genes associated with genetic generalized epilepsy (GGE) by combining large cohorts enriched with individuals with a positive family history. Secondarily, we set out to compare the association of genes independently with familial and sporadic GGE.

METHODS

We performed a case-control whole exome sequencing study in unrelated individuals of European descent diagnosed with GGE (previously recruited and sequenced through multiple international collaborations) and ancestry-matched controls. The association of ultra-rare variants (URVs; in 18 834 protein-coding genes) with epilepsy was examined in 1928 individuals with GGE (vs. 8578 controls), then separately in 945 individuals with familial GGE (vs. 8626 controls), and finally in 1005 individuals with sporadic GGE (vs. 8621 controls). We additionally examined the association of URVs with familial and sporadic GGE in two gene sets important for inhibitory signaling (19 genes encoding γ-aminobutyric acid type A [GABAA ] receptors, 113 genes representing the GABAergic pathway).

RESULTS

GABRG2 was associated with GGE (p = 1.8 × 10-5 ), approaching study-wide significance in familial GGE (p = 3.0 × 10-6 ), whereas no gene approached a significant association with sporadic GGE. Deleterious URVs in the most intolerant subgenic regions in genes encoding GABAA receptors were associated with familial GGE (odds ratio [OR] = 3.9, 95% confidence interval [CI] = 1.9-7.8, false discovery rate [FDR]-adjusted p = .0024), whereas their association with sporadic GGE had marginally lower odds (OR = 3.1, 95% CI = 1.3-6.7, FDR-adjusted p = .022). URVs in GABAergic pathway genes were associated with familial GGE (OR = 1.8, 95% CI = 1.3-2.5, FDR-adjusted p = .0024) but not with sporadic GGE (OR = 1.3, 95% CI = .9-1.9, FDR-adjusted p = .19).

SIGNIFICANCE

URVs in GABRG2 are likely an important risk factor for familial GGE. The association of gene sets of GABAergic signaling with familial GGE is more prominent than with sporadic GGE.

A genome-wide association study of outcome from traumatic brain injury

BACKGROUND

Factors such as age, pre-injury health, and injury severity, account for less than 35% of outcome variability in traumatic brain injury (TBI). While some residual outcome variability may be attributable to genetic factors, published candidate gene association studies have often been underpowered and subject to publication bias.

METHODS

We performed the first genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in TBI. The study population consisted of 5268 patients from prospective European and US studies, who attended hospital within 24 h of TBI, and satisfied local protocols for computed tomography.

FINDINGS

The estimated heritability of TBI outcome was 0·26. GWAS revealed no genetic variants with genome-wide significance (p < 5 × 10-8), but identified 83 variants in 13 independent loci which met a lower pre-specified sub-genomic statistical threshold (p < 10-5). Similarly, none of the genes tested in TWAS met tissue-wide significance. An exploratory analysis of 75 published candidate variants associated with 28 genes revealed one replicable variant (rs1800450 in the MBL2 gene) which retained significance after correction for multiple comparison (p = 5·24 × 10-4).

INTERPRETATION

While multiple novel loci reached less stringent thresholds, none achieved genome-wide significance. The overall heritability estimate, however, is consistent with the hypothesis that common genetic variation substantially contributes to inter-individual variability in TBI outcome. The meta-analytic approach to the GWAS and the availability of summary data allows for a continuous extension with additional cohorts as data becomes available.

FUNDING

A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

NCOR2 is a novel candidate gene for migraine-epilepsy phenotype

HYPOTHESIS

To identify genetic factors predisposing to migraine-epilepsy phenotype utilizing a multi-generational family with known linkage to chr12q24.2-q24.3.

METHODS

We used single nucleotide polymorphism (SNP) genotyping and next-generation sequencing technologies to perform linkage, haplotype, and variant analyses in an extended Finnish migraine-epilepsy family (n = 120). In addition, we used a large genome-wide association study (GWAS) dataset of migraine and two biobank studies, UK Biobank and FinnGen, to test whether variants within the susceptibility region associate with migraine or epilepsy related phenotypes in a population setting.

RESULTS

The family showed the highest evidence of linkage (LOD 3.42) between rs7966411 and epilepsy. The haplotype shared among 12 out of 13 epilepsy patients in the family covers almost the entire NCOR2 and co-localizes with one of the risk loci of the recent GWAS on migraine. The haplotype harbors nine low-frequency variants with potential regulatory functions. Three of them, in addition to two common variants, show nominal associations with neurological disorders in either UK Biobank or FinnGen.

CONCLUSION

We provide several independent lines of evidence supporting association between migraine-epilepsy phenotype and NCOR2. Our study suggests that NCOR2 may have a role in both migraine and epilepsy and thus would provide evidence for shared pathophysiology underlying these two diseases.

Discovery of genomic loci of the human cerebral cortex using genetically informed brain atlases

To determine the impact of genetic variants on the brain, we used genetically informed brain atlases in genome-wide association studies of regional cortical surface area and thickness in 39,898 adults and 9136 children. We uncovered 440 genome-wide significant loci in the discovery cohort and 800 from a post hoc combined meta-analysis. Loci in adulthood were largely captured in childhood, showing signatures of negative selection, and were linked to early neurodevelopment and pathways associated with neuropsychiatric risk. Opposing gradations of decreased surface area and increased thickness were associated with common inversion polymorphisms. Inferior frontal regions, encompassing Broca's area, which is important for speech, were enriched for human-specific genomic elements. Thus, a mixed genetic landscape of conserved and human-specific features is concordant with brain hierarchy and morphogenetic gradients.

A systems-level analysis highlights microglial activation as a modifying factor in common epilepsies

AIMS

The causes of distinct patterns of reduced cortical thickness in the common human epilepsies, detectable on neuroimaging and with important clinical consequences, are unknown. We investigated the underlying mechanisms of cortical thinning using a systems-level analysis.

METHODS

Imaging-based cortical structural maps from a large-scale epilepsy neuroimaging study were overlaid with highly spatially resolved human brain gene expression data from the Allen Human Brain Atlas. Cell-type deconvolution, differential expression analysis and cell-type enrichment analyses were used to identify differences in cell-type distribution. These differences were followed up in post-mortem brain tissue from humans with epilepsy using Iba1 immunolabelling. Furthermore, to investigate a causal effect in cortical thinning, cell-type-specific depletion was used in a murine model of acquired epilepsy.

RESULTS

We identified elevated fractions of microglia and endothelial cells in regions of reduced cortical thickness. Differentially expressed genes showed enrichment for microglial markers and, in particular, activated microglial states. Analysis of post-mortem brain tissue from humans with epilepsy confirmed excess activated microglia. In the murine model, transient depletion of activated microglia during the early phase of the disease development prevented cortical thinning and neuronal cell loss in the temporal cortex. Although the development of chronic seizures was unaffected, the epileptic mice with early depletion of activated microglia did not develop deficits in a non-spatial memory test seen in epileptic mice not depleted of microglia.

CONCLUSIONS

These convergent data strongly implicate activated microglia in cortical thinning, representing a new dimension for concern and disease modification in the epilepsies, potentially distinct from seizure control.

Correction of the hypomorphic Gabra2 splice site variant in mouse strain C57BL/6J modifies the severity of Scn8a encephalopathy

De novo gain-of-function mutations of SCN8A are a significant cause of developmental and epileptic encephalopathy (DEE) (MIM: 614558). The severely affected individuals exhibit refractory seizures, developmental delay, and cognitive disabilities, often accompanied by impaired movement. Individuals with the identical SCN8A variant often differ in clinical course, suggesting a role for modifier genes in disease severity. In a previous study we demonstrated genetic linkage between a hypomorphic mutation in the Gabra2 gene and seizure severity in a mouse model of the human SCN8A pathogenic variant p.Arg1872Trp. Homozygosity for the hypomorphic Gabra2 mutation was associated with early seizure onset and shortened lifespan. We have now confirmed Gabra2 as the modifier gene using a knock-in allele that corrects the splice site variant in strain C57BL/6J. Correction of the Gabra2 variant restores transcript abundance, increases the age of seizure onset, and extends survival of the Scn8a mutant mice. GABRA2 encodes the α2 subunit of the GABA_A receptor that provides inhibitory input to dendrites and the the axon initial segment of excitatory neurons. Quantitative variation in human GABA_A receptor expression could contribute to variation in the severity of genetic epilepsies and suggests a potential therapeutic intervention.

Genome-wide association study of febrile seizures implicates fever response and neuronal excitability genes

Febrile seizures represent the most common type of pathological brain activity in young children and are influenced by genetic, environmental and developmental factors. In a minority of cases, febrile seizures precede later development of epilepsy.

We conducted a genome-wide association study of febrile seizures in 7635 cases and 83 966 controls identifying and replicating seven new loci, all with P < 5 × 10⁻¹⁰.

Variants at two loci were functionally related to altered expression of the fever response genes PTGER3 and IL10, and four other loci harboured genes (BSN, ERC2, GABRG2, HERC1) influencing neuronal excitability by regulating neurotransmitter release and binding, vesicular transport or membrane trafficking at the synapse. Four previously reported loci (SCN1A, SCN2A, ANO3 and 12q21.33) were all confirmed. Collectively, the seven novel and four previously reported loci explained 2.8% of the variance in liability to febrile seizures, and the single nucleotide polymorphism heritability based on all common autosomal single nucleotide polymorphisms was 10.8%. GABRG2, SCN1A and SCN2A are well-established epilepsy genes and, overall, we found positive genetic correlations with epilepsies (r_g = 0.39, P = 1.68 × 10⁻⁴). Further, we found that higher polygenic risk scores for febrile seizures were associated with epilepsy and with history of hospital admission for febrile seizures. Finally, we found that polygenic risk of febrile seizures was lower in febrile seizure patients with neuropsychiatric disease compared to febrile seizure patients in a general population sample.

In conclusion, this largest genetic investigation of febrile seizures to date implicates central fever response genes as well as genes affecting neuronal excitability, including several known epilepsy genes. Further functional and genetic studies based on these findings will provide important insights into the complex pathophysiological processes of seizures with and without fever.