Browse
Submit Data
Databases
API
Help

Dataset Information

18 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Genetic Diagnosis Spectrum and Multigenic Burden of Exome-Level Rare Variants in a Childhood Epilepsy Cohort.

ABSTRACT: Childhood epilepsy is a considerably heterogeneous neurological condition with a high worldwide incidence. Genetic diagnosis of childhood epilepsy provides the most accurate pathogenetic evidence; however, a large proportion of highly suspected cases remain undiagnosed. Accumulation of rare variants at the exome level as a multigenic burden contributing to childhood epilepsy should be further evaluated. In this retrospective analysis, exome-level sequencing was used to depict the mutation spectra of 294 childhood epilepsy patients from Shanghai Children's Medical Center, Department of Neurology. Furthermore, variant information from exome sequencing data was analyzed apart from monogenic diagnostic purposes to elucidate the possible multigenic burden of rare variants related to epilepsy pathogenesis. Exome sequencing reached a diagnostic rate of 30.61% and identified six genes not currently listed in the epilepsy-associated gene list. A multigenic burden study revealed a three-fold possibility that deleterious missense mutations in ion channel and synaptic genes in the undiagnosed cohort may contribute to the genetic risk of childhood epilepsy, whereas variants in the gene categories of cell growth, metabolic, and regulatory function showed no significant difference. Our study provides a comprehensive overview of the genetic diagnosis of a Chinese childhood epilepsy cohort and provides novel insights into the genetic background of these patients. Harmful missense mutations in genes related to ion channels and synapses are most likely to produce a multigenic burden in childhood epilepsy.

SUBMITTER: Yao R

PROVIDER: S-EPMC8725238 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Burden Testing of Rare Variants Identified through Exome Sequencing via Publicly Available Control Data.

Project description:The genetic causes of many Mendelian disorders remain undefined. Factors such as lack of large multiplex families, locus heterogeneity, and incomplete penetrance hamper these efforts for many disorders. Previous work suggests that gene-based burden testing-where the aggregate burden of rare, protein-altering variants in each gene is compared between case and control subjects-might overcome some of these limitations. The increasing availability of large-scale public sequencing databases such as Genome Aggregation Database (gnomAD) can enable burden testing using these databases as controls, obviating the need for additional control sequencing for each study. However, there exist various challenges with using public databases as controls, including lack of individual-level data, differences in ancestry, and differences in sequencing platforms and data processing. To illustrate the approach of using public data as controls, we analyzed whole-exome sequencing data from 393 individuals with idiopathic hypogonadotropic hypogonadism (IHH), a rare disorder with significant locus heterogeneity and incomplete penetrance against control subjects from gnomAD (n = 123,136). We leveraged presumably benign synonymous variants to calibrate our approach. Through iterative analyses, we systematically addressed and overcame various sources of artifact that can arise when using public control data. In particular, we introduce an approach for highly adaptable variant quality filtering that leads to well-calibrated results. Our approach "re-discovered" genes previously implicated in IHH (FGFR1, TACR3, GNRHR). Furthermore, we identified a significant burden in TYRO3, a gene implicated in hypogonadotropic hypogonadism in mice. Finally, we developed a user-friendly software package TRAPD (Test Rare vAriants with Public Data) for performing gene-based burden testing against public databases.

| S-EPMC6174288 | biostudies-literature

Genome-wide Polygenic Burden of Rare Deleterious Variants in Sudden Unexpected Death in Epilepsy.

Project description:Sudden unexpected death in epilepsy (SUDEP) represents the most severe degree of the spectrum of epilepsy severity and is the commonest cause of epilepsy-related premature mortality. The precise pathophysiology and the genetic architecture of SUDEP remain elusive. Aiming to elucidate the genetic basis of SUDEP, we analysed rare, protein-changing variants from whole-exome sequences of 18 people who died of SUDEP, 87 living people with epilepsy and 1479 non-epilepsy disease controls. Association analysis revealed a significantly increased genome-wide polygenic burden per individual in the SUDEP cohort when compared to epilepsy (P = 5.7 × 10(- 3)) and non-epilepsy disease controls (P = 1.2 × 10(- 3)). The polygenic burden was driven both by the number of variants per individual, and over-representation of variants likely to be deleterious in the SUDEP cohort. As determined by this study, more than a thousand genes contribute to the observed polygenic burden within the framework of this study. Subsequent gene-based association analysis revealed five possible candidate genes significantly associated with SUDEP or epilepsy, but no one single gene emerges as common to the SUDEP cases. Our findings provide further evidence for a genetic susceptibility to SUDEP, and suggest an extensive polygenic contribution to SUDEP causation. Thus, an overall increased burden of deleterious variants in a highly polygenic background might be important in rendering a given individual more susceptible to SUDEP. Our findings suggest that exome sequencing in people with epilepsy might eventually contribute to generating SUDEP risk estimates, promoting stratified medicine in epilepsy, with the eventual aim of reducing an individual patient's risk of SUDEP.

| S-EPMC4588398 | biostudies-literature

Whole-exome DNA sequencing in childhood anxiety disorders identifies rare de novo damaging coding variants.

Project description:BackgroundGenetic factors contribute to the development of anxiety disorders, yet few risk genes have been previously identified. One genomic approach that has achieved success in identifying risk genes in related childhood neuropsychiatric conditions is investigations of de novo variants, which has yet to be leveraged in childhood anxiety disorders.MethodsWe performed whole-exome DNA sequencing in 76 parent-child trios (68 trios after quality control) recruited from a childhood anxiety disorder clinic and compared rates of rare and ultra-rare de novo variants with 790 previously sequenced control trios (783 trios after quality control). We then explored overlap with risk genes for other neuropsychiatric conditions and enrichment in biologic pathways.ResultsRare and ultra-rare de novo likely gene disrupting and predicted damaging missense genetic variants are enriched in anxiety disorder probands compared with controls (rare variant rate ratio 1.97, 95% confidence interval [CI]: 1.11-3.34, p = .03; ultra-rare variant rate ratio 2.59, 95% CI: 1.35-4.70, p = .008). These de novo damaging variants occur in individuals with a variety of childhood anxiety disorders and impact genes that have been associated with other neuropsychiatric conditions. Exploratory network analyses reveal enrichment of deleterious variants in canonical biological pathways.ConclusionsThese findings provide a path for identifying risk genes and promising biologic pathways in childhood anxiety disorders by de novo genetic variant detection. Our results suggest the discovery potential of applying this approach in larger anxiety disorder cohorts to advance our understanding of the underlying biology of these common and debilitating conditions.

| S-EPMC9246845 | biostudies-literature

EXOME-EPILEPSY

Project description:Whole‐Exome Sequencing of a Saudi Epilepsy Cohort Reveals Association Signals in Known and Potentially Novel Loci

| PRJEB57558 | ENA

Economic burden of childhood autism spectrum disorders.

Project description:ObjectiveTo estimate the associations between autism spectrum disorder (ASD) diagnoses and service use, caregiver time, and cost outcomes.MethodsWe used national data from the Medical Expenditure Panel Survey linked to the National Health Interview Survey and a study-specific survey to estimate the annual utilization and costs for health care, school, ASD-related therapy, family-coordinated services, as well as caregiver time in children aged 3 to 17 years, with and without parent-reported ASD. Regression analyses estimated the association between ASD diagnosis and cost, controlling for child gender, age, race/ethnicity, insurance status, household income, country region and urban/rural classification, and non-ASD-related illnesses.ResultsChildren with parent-reported ASD had higher levels of health care office visits and prescription drug use compared with children without ASD (P < .05). A greater proportion of children in the ASD group used special educational services (76% vs. 7% in the control group, P < .05). After adjusting for child demographic characteristics and non-ASD-associated illnesses, ASD was associated with $3020 (95% confidence interval [CI]: $1017-$4259) higher health care costs and $14,061 (95% CI: $4390-$24,302) higher aggregate non-health care costs, including $8610 (95% CI: $6595-$10,421) higher school costs. In adjusted analyses, parents who reported that their child had ASD did not have significantly higher out-of-pocket costs or spend more time on caregiving activities compared with control parents.ConclusionsThe economic burden associated with ASD is substantial and can be measured across multiple sectors of our society. Previous analyses that focused on health care underestimated this economic burden, particularly for school systems.

| S-EPMC7034397 | biostudies-literature

Burden of rare variants in synaptic genes in patients with severe tinnitus: An exome based extreme phenotype study.

Project description:Backgroundtinnitus is a heterogeneous condition associated with audiological and/or mental disorders. Chronic, severe tinnitus is reported in 1% of the population and it shows a relevant heritability, according to twins, adoptees and familial aggregation studies. The genetic contribution to severe tinnitus is unknown since large genomic studies include individuals with self-reported tinnitus and large heterogeneity in the phenotype. The aim of this study was to identify genes for severe tinnitus in patients with extreme phenotype.Methodsfor this extreme phenotype study, we used three different cohorts with European ancestry (Spanish with Meniere disease (MD), Swedes tinnitus and European generalized epilepsy). In addition, four independent control datasets were also used for comparisons. Whole-exome sequencing was performed for the MD and epilepsy cohorts and whole-genome sequencing was carried out in Swedes with tinnitus.Findingswe found an enrichment of rare missense variants in 24 synaptic genes in a Spanish cohort, the most significant being PRUNE2, AKAP9, SORBS1, ITGAX, ANK2, KIF20B and TSC2 (p < 2E-04), when they were compared with reference datasets. This burden was replicated for ANK2 gene in a Swedish cohort with 97 tinnitus individuals, and in a subset of 34 Swedish patients with severe tinnitus for ANK2, AKAP9 and TSC2 genes (p < 2E-02). However, these associations were not significant in a third cohort of 701 generalized epilepsy individuals without tinnitus. Gene ontology (GO) and gene-set enrichment analyses revealed several pathways and biological processes involved in severe tinnitus, including membrane trafficking and cytoskeletal protein binding in neurons.Interpretationa burden of rare variants in ANK2, AKAP9 and TSC2 is associated with severe tinnitus. ANK2, encodes a cytoskeleton scaffolding protein that coordinates the assembly of several proteins, drives axonal branching and influences connectivity in neurons.

| S-EPMC8047463 | biostudies-literature

Burden of rare exome sequence variants in PROC gene is associated with venous thromboembolism: a population-based study.

Project description:BackgroundRare coding mutations underlying deficiencies of antithrombin and proteins C and S contribute to familial venous thromboembolism (VTE). It is uncertain whether rare variants play a role in the etiology of VTE in the general population.ObjectivesWe conducted a deep whole-exome sequencing (WES) study to investigate the associations between rare coding variants and the risk of VTE in two population-based prospective cohorts.Patients/methodsWhole-exome sequencing was performed in the Longitudinal Investigation of Thromboembolism Etiology (LITE), which combines the Atherosclerosis Risk in Communities (ARIC) study (316 incident VTE events among 3159 African Americans [AAs] and 458 incident VTEs among 7772 European Americans [EAs]) and the Cardiovascular Healthy Study (CHS; 60 incident VTEs among 1751 EAs). We performed gene-based tests of rare variants (allele frequency < 1%, exome-wide significance P < 1.47 × 10-6 ) separately in each study and ancestry group, and meta-analyzed the results for the EAs in ARIC and CHS.ResultsIn the meta-analysis of EAs, we identified one gene, PROC, in which the burden of rare, coding variants was significantly associated with increased risk of VTE (HR = 5.42 [3.11, 9.42] for carriers versus non-carriers, P = 2.27 × 10-9 ). In ARIC EAs, carriers of the PROC rare variants had on average 0.75 standard deviation (SD) lower concentrations of plasma protein C and 0.28 SD higher D-dimer (P < .05) than non-carriers. Adjustment for low protein C status did not eliminate the association of PROC burden with VTE. In AAs, rare coding PROC variants were not associated with VTE.ConclusionsRare coding variants in PROC contribute to increased VTE risk in EAs in this general population sample.

| S-EPMC7787541 | biostudies-literature

Presence of epilepsy-associated variants in large exome databases.

Project description:Mutations in more than 20 genes have been found to cause idiopathic epilepsies, and screening for these variants could facilitate the clinical diagnosis of epilepsy. However, many of the studies that reported putative pathogenic variants for epilepsy tested a relatively small number of control samples, making it more likely that a rare nonpathogenic variant could be mistaken as causal. To test the robustness of inferences based on small sample sizes, we investigated whether variants previously reported to cause epilepsy were present in the resequencing data from the large control populations of the 1000 Genomes Project and the National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project. A list of variants associated with epilepsy was compiled using a manual review of the literature for genes associated with epilepsy from a recent International League Against Epilepsy (ILAE) report and two comprehensive genetic studies. We checked for the presence of those variants in the 1000 Genomes Project database and the NHLBI Exome Variant Server (EVS). Of 208 epilepsy-associated variants that we identified from our literature review, only 7 were found among 17 thousand chromosomes across 1000 Genomes and the EVS. Consistent with recent published reports, we also found many variants with predicted pathogenicity in epilepsy-associated genes in the genomic databases. Our findings suggest that the 1000 Genomes and the EVS data sets may be a valuable resource of control data in research aimed at identifying genes for epilepsy specifically when the model predicts a highly penetrant allele. These databases also elucidate the array of genetic variation in putative epilepsy genes in the general population.

| S-EPMC3672316 | biostudies-literature

Automated diagnosis of epilepsy using EEG power spectrum.

Project description:Interictal electroencephalography (EEG) has clinically meaningful limitations in its sensitivity and specificity in the diagnosis of epilepsy because of its dependence on the occurrence of epileptiform discharges. We have developed a computer-aided diagnostic (CAD) tool that operates on the absolute spectral energy of the routine EEG and has both substantially higher sensitivity and negative predictive value than the identification of interictal epileptiform discharges. Our approach used a multilayer perceptron to classify 156 patients admitted for video-EEG monitoring. The patient population was diagnostically diverse; 87 were diagnosed with either generalized or focal seizures. The remainder of the patients were diagnosed with nonepileptic seizures. The sensitivity was 92% (95% confidence interval [CI] 85-97%) and the negative predictive value was 82% (95% CI 67-92%). We discuss how these findings suggest that this CAD can be used to supplement event-based analysis by trained epileptologists.

| S-EPMC3447367 | biostudies-literature

Exome sequencing followed by large-scale genotyping fails to identify single rare variants of large effect in idiopathic generalized epilepsy.

Project description:Idiopathic generalized epilepsy (IGE) is a complex disease with high heritability, but little is known about its genetic architecture. Rare copy-number variants have been found to explain nearly 3% of individuals with IGE; however, it remains unclear whether variants with moderate effect size and frequencies below what are reliably detected with genome-wide association studies contribute significantly to disease risk. In this study, we compare the exome sequences of 118 individuals with IGE and 242 controls of European ancestry by using next-generation sequencing. The exome-sequenced epilepsy cases include study subjects with two forms of IGE, including juvenile myoclonic epilepsy (n = 93) and absence epilepsy (n = 25). However, our discovery strategy did not assume common genetic control between the subtypes of IGE considered. In the sequence data, as expected, no variants were significantly associated with the IGE phenotype or more specific IGE diagnoses. We then selected 3,897 candidate epilepsy-susceptibility variants from the sequence data and genotyped them in a larger set of 878 individuals with IGE and 1,830 controls. Again, no variant achieved statistical significance. However, 1,935 variants were observed exclusively in cases either as heterozygous or homozygous genotypes. It is likely that this set of variants includes real risk factors. The lack of significant association evidence of single variants with disease in this two-stage approach emphasizes the high genetic heterogeneity of epilepsy disorders, suggests that the impact of any individual single-nucleotide variant in this disease is small, and indicates that gene-based approaches might be more successful for future sequencing studies of epilepsy predisposition.

| S-EPMC3415540 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data