Polygenic risk heterogeneity among focal epilepsies

Focal epilepsy (FE) is clinically highly heterogeneous. It has been shown recently that not only rare but also a subset of common genetic variants confer risk for FE. The relatively modest power of genetic studies in FE suggests a high genetic heterogeneity of FE when grouped as one disorder. We hypothesize that the clinical heterogeneity of FE is correlated with genetic heterogeneity on a common risk variant level. To test the hypothesis, we used an FE polygenic risk score "FE-PRS" that combines small effect sizes of thousands of common variants from the largest FE-GWAS (genome-wide association study) into a single measure. We grouped 414 individuals with FE according to common clinical features into subgroups, either by one feature at a time or by all features combined in a cluster analysis. We examined their association with FE-PRS compared to 20 435 matched population controls and observed heterogeneous FE-PRS burden among the subgroups. The highest phenotypic variance explained by FE-PRS was identified in a cluster analysis-defined FE subgroup where all individuals had unknown etiologies and psychiatric comorbidities, and the majority had early onset seizures. Our results indicate that genetic factors associated with FE have differential burden among FE subtypes. Future studies using better-powered FE-PRS might have clinical utility.Peer reviewe

APOE ɛ4 is associated with postictal confusion in patients with medically refractory temporal lobe epilepsy

This study examined the relationship between the APOE ɛ4 allele and postictal confusion in patients with medically intractable temporal lobe epilepsy (TLE). Patients with at least one ɛ4 allele (n = 22) were three times more likely to exhibit postictal confusion (68%) than the 63 patients without ɛ4 (43%). These preliminary results demonstrate that APOE ɛ4 is associated with an increased risk of postictal confusion in patients with medically intractable TLE, suggesting possible dysfunction in neuronal recovery mechanisms

Neurological disorder-associated genetic variants in individuals with psychogenic nonepileptic seizures

Psychogenic nonepileptic seizures (PNES) are diagnosed in approximately 30% of patients referred to tertiary care epilepsy centers. Little is known about the molecular pathology of PNES, much less about possible underlying genetic factors. We generated whole-exome sequencing and whole-genome genotyping data to identify rare, pathogenic (P) or likely pathogenic (LP) variants in 102 individuals with PNES and 448 individuals with focal (FE) or generalized (GE) epilepsy. Variants were classified for all individuals based on the ACMG-AMP 2015 guidelines. For research purposes only, we considered genes associated with neurological or psychiatric disorders as candidate genes for PNES. We observe in this first genetic investigation of PNES that six (5.88%) individuals with PNES without coexistent epilepsy carry P/LP variants (deletions at 10q11.22-q11.23, 10q23.1-q23.2, distal 16p11.2, and 17p13.3, and nonsynonymous variants in NSD1 and GABRA5). Notably, the burden of P/LP variants among the individuals with PNES was similar and not significantly different to the burden observed in the individuals with FE (3.05%) or GE (1.82%) (PNES vs. FE vs. GE (3x2 chi (2)), P=0.30; PNES vs. epilepsy (2x2 chi (2)), P=0.14). The presence of variants in genes associated with monogenic forms of neurological and psychiatric disorders in individuals with PNES shows that genetic factors are likely to play a role in PNES or its comorbidities in a subset of individuals. Future large-scale genetic research studies are needed to further corroborate these interesting findings in PNES.Peer reviewe

Polygenic burden in focal and generalized epilepsies.

Rare genetic variants can cause epilepsy, and genetic testing has been widely adopted for severe, paediatric-onset epilepsies. The phenotypic consequences of common genetic risk burden for epilepsies and their potential future clinical applications have not yet been determined. Using polygenic risk scores (PRS) from a European-ancestry genome-wide association study in generalized and focal epilepsy, we quantified common genetic burden in patients with generalized epilepsy (GE-PRS) or focal epilepsy (FE-PRS) from two independent non-Finnish European cohorts (Epi25 Consortium, n = 5705; Cleveland Clinic Epilepsy Center, n = 620; both compared to 20 435 controls). One Finnish-ancestry population isolate (Finnish-ancestry Epi25, n = 449; compared to 1559 controls), two European-ancestry biobanks (UK Biobank, n = 383 656; Vanderbilt biorepository, n = 49 494), and one Japanese-ancestry biobank (BioBank Japan, n = 168 680) were used for additional replications. Across 8386 patients with epilepsy and 622 212 population controls, we found and replicated significantly higher GE-PRS in patients with generalized epilepsy of European-ancestry compared to patients with focal epilepsy (Epi25: P = 1.64×10-15; Cleveland: P = 2.85×10-4; Finnish-ancestry Epi25: P = 1.80×10-4) or population controls (Epi25: P = 2.35×10-70; Cleveland: P = 1.43×10-7; Finnish-ancestry Epi25: P = 3.11×10-4; UK Biobank and Vanderbilt biorepository meta-analysis: P = 7.99×10-4). FE-PRS were significantly higher in patients with focal epilepsy compared to controls in the non-Finnish, non-biobank cohorts (Epi25: P = 5.74×10-19; Cleveland: P = 1.69×10-6). European ancestry-derived PRS did not predict generalized epilepsy or focal epilepsy in Japanese-ancestry individuals. Finally, we observed a significant 4.6-fold and a 4.5-fold enrichment of patients with generalized epilepsy compared to controls in the top 0.5% highest GE-PRS of the two non-Finnish European cohorts (Epi25: P = 2.60×10-15; Cleveland: P = 1.39×10-2). We conclude that common variant risk associated with epilepsy is significantly enriched in multiple cohorts of patients with epilepsy compared to controls-in particular for generalized epilepsy. As sample sizes and PRS accuracy continue to increase with further common variant discovery, PRS could complement established clinical biomarkers and augment genetic testing for patient classification, comorbidity research, and potentially targeted treatment

Highlights From the Annual Meeting of the American Epilepsy Society 2022

With more than 6000 attendees between in-person and virtual offerings, the American Epilepsy Society Meeting 2022 in Nashville, felt as busy as in prepandemic times. An ever-growing number of physicians, scientists, and allied health professionals gathered to learn a variety of topics about epilepsy. The program was carefully tailored to meet the needs of professionals with different interests and career stages. This article summarizes the different symposia presented at the meeting. Basic science lectures addressed the primary elements of seizure generation and pathophysiology of epilepsy in different disease states. Scientists congregated to learn about anti-seizure medications, mechanisms of action, and new tools to treat epilepsy including surgery and neurostimulation. Some symposia were also dedicated to discuss epilepsy comorbidities and practical issues regarding epilepsy care. An increasing number of patient advocates discussing their stories were intertwined within scientific activities. Many smaller group sessions targeted more specific topics to encourage member participation, including Special Interest Groups, Investigator, and Skills Workshops. Special lectures included the renown Hoyer and Lombroso, an ILAE/IBE joint session, a spotlight on the impact of Dobbs v. Jackson on reproductive health in epilepsy, and a joint session with the NAEC on coding and reimbursement policies. The hot topics symposium was focused on traumatic brain injury and post-traumatic epilepsy. A balanced collaboration with the industry allowed presentations of the latest pharmaceutical and engineering advances in satellite symposia

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

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

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

Establishing the cross-cultural applicability of a harmonized approach to cognitive diagnostics in epilepsy: Initial results of the International Classification of Cognitive Disorders in Epilepsy in a Spanish-speaking sample.

OBJECTIVE: This study was undertaken to evaluate the cross-cultural application of the International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) to a cohort of Spanish-speaking patients with temporal lobe epilepsy (TLE) living in the United States. METHODS: Eighty-four Spanish-speaking patients with TLE completed neuropsychological measures of memory, language, executive function, visuospatial functioning, and attention/processing speed as part of the Neuropsychological Screening Battery for Hispanics. The contribution of demographic and clinical variables to cognitive performance was evaluated. A sensitivity analysis was conducted by examining the base rates of impairment across several impairment thresholds. The IC-CoDE taxonomy was then applied, and the base rate of cognitive phenotypes for each cutoff was calculated. The distribution of phenotypes was compared to the published IC-CoDE taxonomy data, which utilized a large, multicenter cohort of English-speaking patients with TLE. RESULTS: Across the different impairment cutoffs, memory was the most impaired cognitive domain, with impairments in list learning ranging from 50% to 78%. Application of the IC-CoDE taxonomy utilizing a -1.5-SD cutoff revealed an intact cognitive profile in 47.6% of patients, single-domain impairment in 23.8% of patients, bidomain impairment in 14.3% of patients, and generalized impairment in 14.3% of the sample. This distribution was comparable to the phenotype distribution observed in the IC-CoDE validation sample. SIGNIFICANCE: We demonstrate a similar pattern and distribution of cognitive phenotypes in a Spanish-speaking epilepsy cohort compared to an English-speaking sample. This suggests stability in the underlying phenotypes associated with TLE and applicability of the IC-CoDE for guiding cognitive diagnostics in epilepsy research that can be applied to culturally and linguistically diverse samples

Assessment of depression in epilepsy: the utility of common and disease-specific self-report depression measures

OBJECTIVES: Depression is common in epilepsy, with rates ranging from 20 to 55% in most samples and reports as high as 70% in patients with intractable epilepsy. However, some contend that depression may be over- and/or under-reported and treated in this population. This may be due to the use of common self-report depression measures that fail to take into account the overlap of disease and depressive symptoms and also the host of side effects associated with antiepileptic medication, which may also be construed as depression. METHODS: The present study examined the utility of common self-report depression measures and those designed specifically for the medically ill, including a proposed new measure, to determine which may be more appropriate for use among people with epilepsy. RESULTS: We found that common self-report depression measures are useful for screening depression in epilepsy, particularly with a raised cutoff for one, with sensitivities ranging from .91 to .96. A measure designed for the medically ill obtained the greatest specificity of .91, suggesting its use as a diagnostic tool with a slightly raised cutoff. The positive likelihood ratio of this latter measure was 8.76 with an overall classification accuracy of 88%. CONCLUSIONS: Assessment of depression in epilepsy can be improved when utilizing self-report measures that better differentiate disease symptoms from neurovegetative symptoms of depression (e.g. fatigue, sleep disturbance). This was demonstrated in the present study. Clinical implications are discussed