Association of ultra-rare coding variants with genetic generalized epilepsy: A case\u2013control 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\u2013control 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 \u3b3-aminobutyric acid type A [GABAA] receptors, 113 genes representing the GABAergic pathway). Results: GABRG2 was associated with GGE (p = 1.8  7 10 125), approaching study-wide significance in familial GGE (p = 3.0  7 10 126), 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\u20137.8, false discovery rate [FDR]-adjusted p =.0024), whereas their association with sporadic GGE had marginally lower odds (OR = 3.1, 95% CI = 1.3\u20136.7, FDR-adjusted p =.022). URVs in GABAergic pathway genes were associated with familial GGE (OR = 1.8, 95% CI = 1.3\u20132.5, FDR-adjusted p =.0024) but not with sporadic GGE (OR = 1.3, 95% CI =.9\u20131.9, 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

Revealing a brain network endophenotype in families with idiopathic generalised epilepsy

Idiopathic generalised epilepsy (IGE) has a genetic basis. The mechanism of seizure expression is not fully known, but is assumed to involve large-scale brain networks. We hypothesised that abnormal brain network properties would be detected using EEG in patients with IGE, and would be manifest as a familial endophenotype in their unaffected first-degree relatives. We studied 117 participants: 35 patients with IGE, 42 unaffected first-degree relatives, and 40 normal controls, using scalp EEG. Graph theory was used to describe brain network topology in five frequency bands for each subject. Frequency bands were chosen based on a published Spectral Factor Analysis study which demonstrated these bands to be optimally robust and independent. Groups were compared, using Bonferroni correction to account for nonindependent measures and multiple groups. Degree distribution variance was greater in patients and relatives than controls in the 6-9 Hz band (p = 0.0005, p = 0.0009 respectively). Mean degree was greater in patients than healthy controls in the 6-9 Hz band (p = 0.0064). Clustering coefficient was higher in patients and relatives than controls in the 6-9 Hz band (p = 0.0025, p = 0.0013). Characteristic path length did not differ between groups. No differences were found between patients and unaffected relatives. These findings suggest brain network topology differs between patients with IGE and normal controls, and that some of these network measures show similar deviations in patients and in unaffected relatives who do not have epilepsy. This suggests brain network topology may be an inherited endophenotype of IGE, present in unaffected relatives who do not have epilepsy, as well as in affected patients. We propose that abnormal brain network topology may be an endophenotype of IGE, though not in itself sufficient to cause epilepsy

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

Sub-genic intolerance, ClinVar, and the epilepsies: A whole-exome sequencing study of 29,165 individuals

Both mild and severe epilepsies are influenced by variants in the same genes, yet an explanation for the resulting phenotypic variation is unknown. As part of the ongoing Epi25 Collaboration, we performed a whole-exome sequencing analysis of 13,487 epilepsy-affected individuals and 15,678 control individuals. While prior Epi25 studies focused on gene-based collapsing analyses, we asked how the pattern of variation within genes differs by epilepsy type. Specifically, we compared the genetic architectures of severe developmental and epileptic encephalopathies (DEEs) and two generally less severe epilepsies, genetic generalized epilepsy and non-acquired focal epilepsy (NAFE). Our gene-based rare variant collapsing analysis used geographic ancestry-based clustering that included broader ancestries than previously possible and revealed novel associations. Using the missense intolerance ratio (MTR), we found that variants in DEE-affected individuals are in significantly more intolerant genic sub-regions than those in NAFE-affected individuals. Only previously reported pathogenic variants absent in available genomic datasets showed a significant burden in epilepsy-affected individuals compared with control individuals, and the ultra-rare pathogenic variants associated with DEE were located in more intolerant genic sub-regions than variants associated with non-DEE epilepsies. MTR filtering improved the yield of ultra-rare pathogenic variants in affected individuals compared with control individuals. Finally, analysis of variants in genes without a disease association revealed a significant burden of loss-of-function variants in the genes most intolerant to such variation, indicating additional epilepsy-risk genes yet to be discovered. Taken together, our study suggests that genic and sub-genic intolerance are critical characteristics for interpreting the effects of variation in genes that influence epilepsy

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

A prospective study of loss of consciousness in epilepsy using virtual reality driving simulation and other video games

Patients with epilepsy are at risk of traffic accidents when they have seizures while driving. However, driving is an essential part of normal daily life in many communities, and depriving patients of driving privileges can have profound consequences for their economic and social well-being. In the current study, we collected ictal performance data from a driving simulator and two other video games in patients undergoing continuous video/EEG monitoring. We captured 22 seizures in 13 patients and found that driving impairment during seizures differed in terms of both magnitude and character, depending on the seizure type. Our study documents the feasibility of a prospective study of driving and other behaviors during seizures through the use of computer-based tasks. This methodology may be applied to further describe differential driving impairment in specific types of seizures and to gain data on anatomical networks disrupted in seizures that impair consciousness and driving safety

Clinical use of ictal SPECT in secondarily generalized tonic–clonic seizures

Partial seizures produce increased cerebral blood flow in the region of seizure onset. These regional cerebral blood flow increases can be detected by single photon emission computed tomography (ictal SPECT), providing a useful clinical tool for seizure localization. However, when partial seizures secondarily generalize, there are often questions of interpretation since propagation of seizures could produce ambiguous results. Ictal SPECT from secondarily generalized seizures has not been thoroughly investigated. We analysed ictal SPECT from 59 secondarily generalized tonic–clonic seizures obtained during epilepsy surgery evaluation in 53 patients. Ictal versus baseline interictal SPECT difference analysis was performed using ISAS (http://spect.yale.edu). SPECT injection times were classified based on video/EEG review as either pre-generalization, during generalization or in the immediate post-ictal period. We found that in the pre-generalization and generalization phases, ictal SPECT showed significantly more regions of cerebral blood flow increases than in partial seizures without secondary generalization. This made identification of a single unambiguous region of seizure onset impossible 50% of the time with ictal SPECT in secondarily generalized seizures. However, cerebral blood flow increases on ictal SPECT correctly identified the hemisphere (left versus right) of seizure onset in 84% of cases. In addition, when a single unambiguous region of cerebral blood flow increase was seen on ictal SPECT, this was the correct localization 80% of the time. In agreement with findings from partial seizures without secondary generalization, cerebral blood flow increases in the post-ictal period and cerebral blood flow decreases during or following seizures were not useful for localizing seizure onset. Interestingly, however, cerebral blood flow hypoperfusion during the generalization phase (but not pre-generalization) was greater on the side opposite to seizure onset in 90% of patients. These findings suggest that, with appropriate cautious interpretation, ictal SPECT in secondarily generalized seizures can help localize the region of seizure onset

Impaired consciousness in temporal lobe seizures: role of cortical slow activity

Impaired consciousness requires altered cortical function. This can occur either directly from disorders that impair widespread bilateral regions of the cortex or indirectly through effects on subcortical arousal systems. It has therefore long been puzzling why focal temporal lobe seizures so often impair consciousness. Early work suggested that altered consciousness may occur with bilateral or dominant temporal lobe seizure involvement. However, other bilateral temporal lobe disorders do not impair consciousness. More recent work supports a ‘network inhibition hypothesis’ in which temporal lobe seizures disrupt brainstem–diencephalic arousal systems, leading indirectly to depressed cortical function and impaired consciousness. Indeed, prior studies show subcortical involvement in temporal lobe seizures and bilateral frontoparietal slow wave activity on intracranial electroencephalography. However, the relationships between frontoparietal slow waves and impaired consciousness and between cortical slowing and fast seizure activity have not been directly investigated. We analysed intracranial electroencephalography recordings during 63 partial seizures in 26 patients with surgically confirmed mesial temporal lobe epilepsy. Behavioural responsiveness was determined based on blinded review of video during seizures and classified as impaired (complex-partial seizures) or unimpaired (simple-partial seizures). We observed significantly increased delta-range 1–2 Hz slow wave activity in the bilateral frontal and parietal neocortices during complex-partial compared with simple-partial seizures. In addition, we confirmed prior work suggesting that propagation of unilateral mesial temporal fast seizure activity to the bilateral temporal lobes was significantly greater in complex-partial than in simple-partial seizures. Interestingly, we found that the signal power of frontoparietal slow wave activity was significantly correlated with the temporal lobe fast seizure activity in each hemisphere. Finally, we observed that complex-partial seizures were somewhat more common with onset in the language-dominant temporal lobe. These findings provide direct evidence for cortical dysfunction in the form of bilateral frontoparietal slow waves associated with impaired consciousness in temporal lobe seizures. We hypothesize that bilateral temporal lobe seizures may exert a powerful inhibitory effect on subcortical arousal systems. Further investigations will be needed to fully determine the role of cortical-subcortical networks in ictal neocortical dysfunction and may reveal treatments to prevent this important negative consequence of temporal lobe epilepsy