Genetic analysis of genes associated with epilepsy.
Ontology highlight
ABSTRACT: Background and aim
Epilepsy is a neurological disorder in which the altered activity of neurons causes convulsions, periods of unusual behavior and, sometimes, loss of consciousness. The aim of this mini-review is to summarize all the syndromes characterized by epilepsy and for which the associated gene is known.Methods
We searched those syndromes in PubMed and OMIM database.Results
Genetic causes underlie epilepsy in about 40% of individuals. Epilepsies are phenotypically and genetically heterogeneous. Inheritance can be autosomal dominant or recessive or X-linked recessive/dominant.Conclusion
Since epilepsy has high genetic heterogeneity, in diagnostics, the parallel sequencing of a panel of genes may speed up the determination of the molecular etiology and/or establish a risk of recurrence in family members for the purpose of planning appropriate preventive and/or therapeutic measures.
SUBMITTER: Guerri G
PROVIDER: S-EPMC8023140 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Epilepsy is a severe neurological disorder affecting a large number of individuals, yet the underlying genetic risk factors for epilepsy remain unclear. Recent studies have revealed several recurrent copy number variations (CNVs) that are more likely to be associated with epilepsy. The responsible gene(s) within these regions have yet to be definitively linked to the disorder, and the implications of their interactions are not fully understood. Identification of these genes may contribute to a better pathological understanding of epilepsy, and serve to implicate novel therapeutic targets for further research.In this study, we examined genes within heterozygous deletion regions identified in a recent large-scale study, encompassing a diverse spectrum of epileptic syndromes. By integrating additional protein-protein interaction data, we constructed subnetworks for these CNV-region genes and also those previously studied for epilepsy. We observed 20 genes common to both networks, primarily concentrated within a small molecular network populated by GABA receptor, BDNF/MAPK signaling, and estrogen receptor genes. From among the hundreds of genes in the initial networks, these were designated by convergent evidence for their likely association with epilepsy. Importantly, the identified molecular network was found to contain complex interrelationships, providing further insight into epilepsy's underlying pathology. We further performed pathway enrichment and crosstalk analysis and revealed a functional map which indicates the significant enrichment of closely related neurological, immune, and kinase regulatory pathways.The convergent framework we proposed here provides a unique and powerful approach to screening and identifying promising disease genes out of typically hundreds to thousands of genes in disease-related CNV-regions. Our network and pathway analysis provides important implications for the underlying molecular mechanisms for epilepsy. The strategy can be applied for the study of other complex diseases.
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Project description:Epilepsy is a highly prevalent neurological disorder characterized by recurrent seizures. Patients exhibit broad genetic, molecular, and clinical diversity involving mild to severe comorbidities. The factors that contribute to this phenotypic diversity remain unclear. We used publicly available datasets to systematically interrogate the expression pattern of 247 epilepsy-associated genes across human tissues, developmental stages, and central nervous system (CNS) cellular subtypes. We grouped genes based on their curated phenotypes into 3 broad classes: core epilepsy genes (CEG), where seizures are the core syndrome, developmental and epileptic encephalopathy genes (DEEG) that are associated with developmental delay, and seizure-related genes (SRG), which are characterized by developmental delay and gross brain malformations. We find that DEEGs are highly expressed within the CNS, while SRGs are most abundant in non-CNS tissues. DEEGs and CEGs exhibit highly dynamic expression in various brain regions across development, spiking during the prenatal to infancy transition. Lastly, the abundance of CEGs and SRGs is comparable within cellular subtypes in the brain, while the average expression level of DEEGs is significantly higher in GABAergic neurons and non-neuronal cells. Our analysis provides an overview of the expression pattern of epilepsy-associated genes with spatiotemporal resolution and establishes a broad expression-phenotype correlation in epilepsy.
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Project description:Epilepsy is a common, serious neurological disorder worldwide. Although this disease can be successfully treated in most cases, not all patients respond favorably to medical treatments, which can lead to pharmacoresistant epilepsy. Drug?resistant epilepsy can be caused by a number of mechanisms that may involve environmental and genetic factors, as well as disease? and drug?related factors. In recent years, numerous studies have demonstrated that genetic variation is involved in the drug resistance of epilepsy, especially genetic variations found in drug resistance?related genes, including the voltage?dependent sodium and potassium channels genes, and the metabolizer of endogenous and xenobiotic substances genes. The present review aimed to highlight the genetic variants that are involved in the regulation of drug resistance in epilepsy; a comprehensive understanding of the role of genetic variation in drug resistance will help us develop improved strategies to regulate drug resistance efficiently and determine the pathophysiological processes that underlie this common human neurological disease.
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Project description:Background and aimDementia is a disease associated with cognitive and/or behavioral changes that interfere with the ability to perform daily activities. Alzheimer's disease is the most common type of dementia. The aim of this mini-review is to summarize all the syndromes characterized by dementia and for which the associated gene is known.MethodsWe searched those syndromes in PubMed and OMIM database.ResultsTwo forms of dementia exist: the multifactorial dementia results from the interaction of different genetic and environmental factors, the hereditary dementia associated with a single gene. Individuals with a family history of dementia and early onset of the disease are more likely to have a hereditary form of dementia. Dementias are mainly autosomal dominant, but they can also be autosomal recessive or X-linked.ConclusionsSince dementia has high clinical and genetic heterogeneity, the use in diagnostics of a large panel of genes may greatly help to speed up the determination of the molecular diagnosis and/or establish a risk of recurrence in family members for the purpose of planning appropriate preventive and/or therapeutic measures.
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Project description:BackgroundEpilepsy is one of the most common brain disorders worldwide. It is usually hard to be identified properly, and a third of patients are drug-resistant. Genes related to the progression and prognosis of epilepsy are particularly needed to be identified.MethodsIn our study, we downloaded the Gene Expression Omnibus (GEO) microarray expression profiling dataset GSE143272. Differentially expressed genes (DEGs) with a fold change (FC) >1.2 and a P-value <0.05 were identified by GEO2R and grouped in male, female and overlapping DEGs. Functional enrichment analysis and Protein-Protein Interaction (PPI) network analysis were performed.ResultsIn total, 183 DEGs overlapped (77 ups and 106 downs), 302 DEGs (185 ups and 117 downs) in the male dataset, and 750 DEGs (464 ups and 286 downs) in the female dataset were obtained from the GSE143272 dataset. These DEGs were markedly enriched under various Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms. 16 following hub genes were identified based on PPI network analysis: ADCY7, C3AR1, DEGS1, CXCL1 in male-specific DEGs, TOLLIP, ORM1, ELANE, QPCT in female-specific DEGs and FCAR, CD3G, CLEC12A, MOSPD2, CD3D, ALDH3B1, GPR97, PLAUR in overlapping DEGs.ConclusionThis discovery-driven study may be useful to provide a novel insight into the diagnosis and treatment of epilepsy. However, more experiments are needed in the future to study the functional roles of these genes in epilepsy.
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Project description:Despite the significant advances in understanding the genetic architecture of epilepsy, many patients do not receive a molecular diagnosis after genomic testing. Re-analysing existing genomic data has emerged as a potent method to increase diagnostic yields-providing the benefits of genomic-enabled medicine to more individuals afflicted with a range of different conditions. The primary drivers for these new diagnoses are the discovery of novel gene-disease and variants-disease relationships; however, most decisions to trigger re-analysis are based on the passage of time rather than the accumulation of new knowledge. To explore how our understanding of a specific condition changes and how this impacts re-analysis of genomic data from epilepsy patients, we developed Vigelint. This approach combines the information from PanelApp and ClinVar to characterise how the clinically relevant genes and causative variants available to laboratories change over time, and this approach to five clinical-grade epilepsy panels. Applying the Vigelint pipeline to these panels revealed highly variable patterns in new, clinically relevant knowledge becoming publicly available. This variability indicates that a more dynamic approach to re-analysis may benefit the diagnosis and treatment of epilepsy patients. Moreover, this work suggests that Vigelint can provide empirical data to guide more nuanced, condition-specific approaches to re-analysis.
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Project description:BACKGROUND:Patients with glioma exhibit a great variability in clinical symptoms apart from variations in response to therapy and survival. Many patients present with epileptic seizures at disease onset, especially in case of low-grade gliomas, but not all have seizures. A large proportion of patients develop refractory seizures. It is likely that the variability in epileptic symptoms cannot exclusively be explained by tumor-related factors, but rather reflects complex interaction between tumor-related, environmental and hereditary factors. MATERIAL AND METHODS:No data exist on susceptibility genes associated with epileptic symptoms in patients with glioma. However, an increasing number of candidate genes have been proposed for other focal epilepsies such as temporal lobe epilepsy. Some of the susceptibility candidate genes associated with focal epilepsy may contribute to epileptic symptoms also in patients with glioma. RESULTS:This review presents an update on studies on genetic polymorphisms and focal epilepsy and brings forward putative candidate genes for tumor-associated epilepsy, based on the assumption that common etiological pathways may exist for glioma development and glioma-associated seizures. Conclusion. Genes involved in the immune response, in synaptic transmission and in cell cycle control are discussed that may play a role in the pathogenesis of tumor growth as well as epileptic symptoms in patients with gliomas.
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Project description:It is challenging to estimate genetic variant burden across different subtypes of epilepsy. Herein, we used a comparative approach to assess the genetic variant burden and genotype-phenotype correlations in four most common brain lesions in patients with drug-resistant focal epilepsy. Targeted sequencing analysis was performed for a panel of 161 genes with a mean coverage of >400×. Lesional tissue was histopathologically reviewed and dissected from hippocampal sclerosis (n = 15), ganglioglioma (n = 16), dysembryoplastic neuroepithelial tumors (n = 8), and focal cortical dysplasia type II (n = 15). Peripheral blood (n = 12) or surgical tissue samples histopathologically classified as lesion-free (n = 42) were available for comparison. Variants were classified as pathogenic or likely pathogenic according to American College of Medical Genetics and Genomics guidelines. Overall, we identified pathogenic and likely pathogenic variants in 25.9% of patients with a mean coverage of 383×. The highest number of pathogenic/likely pathogenic variants was observed in patients with ganglioglioma (43.75%; all somatic) and dysembryoplastic neuroepithelial tumors (37.5%; all somatic), and in 20% of cases with focal cortical dysplasia type II (13.33% somatic, 6.67% germline). Pathogenic/likely pathogenic positive genes were disorder specific and BRAF V600E the only recurrent pathogenic variant. This study represents a reference for the genetic variant burden across the four most common lesion entities in patients with drug-resistant focal epilepsy. The observed large variability in variant burden by epileptic lesion type calls for whole exome sequencing of histopathologically well-characterized tissue in a diagnostic setting and in research to discover novel disease-associated genes.
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