59 research outputs found

    Does etiology really matter for epilepsy surgery outcome?

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    Multiple factors influence the outcomes of epilepsy surgery. Prognostic indicators varying from clinical characteristics, imaging findings, ictal, and interictal electrophysiological activity have been linked to surgical outcomes. In this review, we focus on the relatively under-studied role of the underlying epilepsy histopathology in driving post-surgical outcomes, specifically focusing on the broad categories of seizure outcomes and cognitive outcomes. For each of these two outcomes of interest, we answer two questions: 1)- does etiology matter? and 2)- how could it matter? The goal is to review the existing literature on the relationship between etiology and surgical outcomes to provide the best possible judgment as to whether a causal relationship exists between histopathology and the ultimate surgical outcome as an initial step. Then, we delve into the possible mechanisms via which such relationships can be explained. We conclude with a call to action to the epilepsy surgery and histopathology research community to push the mechanistic understanding of the pathology-outcome interaction and identify actionable knowledge and biomarkers that could inform patient care in a timely fashion

    Polygenic risk heterogeneity among focal epilepsies

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    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

    Exit Strategy: Balancing the Risks and Rewards of Antiseizure Medication Withdrawal

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    The majority of people with epilepsy achieves long-term seizure-freedom and may consider withdrawal of their anti-seizure medications (ASMs). Withdrawal of ASMs can yield substantial benefits but may be associated with potential risks. This review critically examines the existing literature on ASM withdrawal, emphasizing evidence-based recommendations, where available. Our focus encompasses deprescribing strategies for individuals who have attained seizure freedom through medical treatment, those who have undergone successful epilepsy surgery, and individuals initiated on ASMs following acute symptomatic seizures. We explore state-of-the-art prognostic models in these scenarios that could guide the decision-making process. The review underscores the importance of a collaborative shared-decision approach between patients, caregivers, and physicians. We describe the subjective and objective factors influencing these decisions and illustrate how trade-offs may be effectively managed in practice

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

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    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

    Network medicine links SARS-CoV-2/COVID-19 infection to brain microvascular injury and neuroinflammation in dementia-like cognitive impairment

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    Background Dementia-like cognitive impairment is an increasingly reported complication of SARS-CoV-2 infection. However, the underlying mechanisms responsible for this complication remain unclear. A better understanding of causative processes by which COVID-19 may lead to cognitive impairment is essential for developing preventive and therapeutic interventions. Methods In this study, we conducted a network-based, multimodal omics comparison of COVID-19 and neurologic complications. We constructed the SARS-CoV-2 virus-host interactome from protein-protein interaction assay and CRISPR-Cas9-based genetic assay results and compared network-based relationships therein with those of known neurological manifestations using network proximity measures. We also investigated the transcriptomic profiles (including single-cell/nuclei RNA-sequencing) of Alzheimer’s disease (AD) marker genes from patients infected with COVID-19, as well as the prevalence of SARS-CoV-2 entry factors in the brains of AD patients not infected with SARS-CoV-2. Results We found significant network-based relationships between COVID-19 and neuroinflammation and brain microvascular injury pathways and processes which are implicated in AD. We also detected aberrant expression of AD biomarkers in the cerebrospinal fluid and blood of patients with COVID-19. While transcriptomic analyses showed relatively low expression of SARS-CoV-2 entry factors in human brain, neuroinflammatory changes were pronounced. In addition, single-nucleus transcriptomic analyses showed that expression of SARS-CoV-2 host factors (BSG and FURIN) and antiviral defense genes (LY6E, IFITM2, IFITM3, and IFNAR1) was elevated in brain endothelial cells of AD patients and healthy controls relative to neurons and other cell types, suggesting a possible role for brain microvascular injury in COVID-19-mediated cognitive impairment. Overall, individuals with the AD risk allele APOE E4/E4 displayed reduced expression of antiviral defense genes compared to APOE E3/E3 individuals. Conclusion Our results suggest significant mechanistic overlap between AD and COVID-19, centered on neuroinflammation and microvascular injury. These results help improve our understanding of COVID-19-associated neurological manifestations and provide guidance for future development of preventive or treatment interventions, although causal relationship and mechanistic pathways between COVID-19 and AD need future investigations

    Polygenic burden in focal and generalized epilepsies.

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    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

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

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    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

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

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    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
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