EXOME-EPILEPSY
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB57558 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR10619300_1.fastq.gz | Fastqsanger.gz | |||
| ERR10619300_2.fastq.gz | Fastqsanger.gz | |||
| ERR10619301_1.fastq.gz | Fastqsanger.gz | |||
| ERR10619301_2.fastq.gz | Fastqsanger.gz | |||
| ERR10619302_1.fastq.gz | Fastqsanger.gz |
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Project description:Purpose Identification of potential biomarkers of seizures. Methods In this exploratory study, we quantified plasma protein intensities in 15 patients with recent seizures compared to 15 patients with long-standing seizure freedom. Using TMT-based proteomics we found fifty-one differentially expressed proteins. Results Network analyses including co-expression networks and protein-protein interaction networks, using the STRING database, followed by network centrality and modularity analyses revealed 22 protein modules, with one module showing a significant association with seizures. The protein-protein interaction network centered around this module identified a subnetwork of 125 proteins, grouped into four clusters. Notably, one cluster (mainly enriching inflammatory pathways and Gene Ontology terms) demonstrated the highest enrichment of known epilepsy-related genes. Conclusion Overall, our network-based approach identified a protein module linked with seizures. The module contained known markers of epilepsy and inflammation. The results also demonstrate the potential of network analysis in discovering new biomarkers for improved epilepsy management.
2024-11-19 | PXD057292 | Pride
Project description:The identification of multiple signals at individual loci could explain additional phenotypic variance ('missing heritability') of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work. Gene expression data was determined of peripheral blood samples (n=705) from InChianti cohort.
2013-06-21 | E-GEOD-48152 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE27015: Rat model of MTLE: Animals with epilepsy vs animals without epilepsy (Agilent) GSE27166: Rat model of MTLE: Animals with epilepsy vs animals without epilepsy (codelink) Refer to individual Series
2011-02-13 | E-GEOD-27268 | biostudies-arrayexpress
Project description:Epilepsy is characterized by hypersynchronous neuronal discharges, which are associated with an increased cerebral metabolic rate of oxygen and ATP demand. Uncontrolled seizure activity (status epilepticus) results in mitochondrial exhaustion and ATP depletion, which potentially generate energy mismatch and neuronal loss. Many cells can adapt to increased energy demand by increasing metabolic capacities. However, acute metabolic adaptation during epileptic activity and its relationship to chronic epilepsy remains poorly understood. We elicited seizure-like events (SLEs) in an in vitro model of status epilepticus for eight hours. Electrophysiological recording and tissue oxygen partial pressure recordings were performed. After eight hours of ongoing SLEs, we used proteomics-based kinetic modeling to evaluate changes in metabolic capacities. We compared our findings regarding acute metabolic adaptation to published proteomic and transcriptomic data from chronic epilepsy patients. Epileptic tissue acutely responded to uninterrupted SLEs by upregulating ATP production capacity. This was achieved by a coordinated increase in the abundance of proteins from the respiratory chain and oxidative phosphorylation system. In contrast, chronic epileptic tissue shows a 25-40% decrease in ATP production capacity. In summary, our study reveals that epilepsy leads to dynamic metabolic changes. Acute epileptic activity boosts ATP production, while chronic epilepsy reduces it significantly.
2024-09-12 | PXD055090 | Pride
Project description:We aimed to replicate association signals between candidate SNPs and admixed Brazilian patients with Genetic Generalized Epilepsy
2021-05-27 | PRJEB45235 | EVA
Project description:Introduction: The relationship between epilepsy and cognitive dysfunction has been investigated in canines, and memory impairment was prevalent in dogs with epilepsy. There is some evidence that canines with epilepsy have greater amyloid-β (Aβ) accumulation and neuronal degeneration than healthy controls. The present study investigated plasma Aβ42 levels and performed proteomic profiling in dogs with refractory epilepsy and healthy dogs. Methods: In total, eight dogs, including four healthy dogs and four dogs with epilepsy, were included in the study. Blood samples were collected to analyze Aβ42 levels and perform proteomic profiling. Changes in the plasma proteomic profiles of dogs were determined by nano LC-MS/MS. Results and discussion: The plasma Aβ42 level was significantly higher in dogs with epilepsy (99 pg/mL) than in healthy dogs (5.9 pg/mL). In total, 155 proteins were identified, and of these, the expression of 40 proteins was altered in epilepsy. Among these proteins, which are linked to neurodegenerative diseases, 10 (25%) were downregulated in dogs with epilepsy, whereas 12 (30%) were upregulated. The expression of the acute phase proteins haptoglobin and α2-macroglobulin significantly differed between the groups. Complement factor H and ceruloplasmin were only detected in epilepsy dogs, suggesting that neuroinflammation plays a role in epileptic seizures. Gelsolin, which is involved in cellular processes and cytoskeletal organization, was only detected in healthy dogs. Gene Ontology annotation revealed that epilepsy can potentially interfere with biological processes, including cellular processes, localization, and responses to stimuli. Seizures compromised key molecular functions, including catalytic activity, molecular function regulation, and binding. Defense/immunity proteins were most significantly modified during the development of epilepsy. In Kyoto Encyclopedia of Genes and Genomes pathway analysis, complement and coagulation cascades were the most relevant signaling pathways affected by seizures. The findings suggested that haptoglobin, ceruloplasmin, α2-macroglobulin, complement factor H, and gelsolin play roles in canine epilepsy and Aβ levels based on proteomic profiling. These proteins could represent diagnostic biomarkers that, after clinical validation, could be used in veterinary practice as well as proteins relevant to disease response pathways. To determine the precise mechanisms underlying these relationships and their implications in canine epilepsy, additional research is required.
2023-12-12 | PXD043962 | Pride
Project description:Pediatric epilepsy is a neurological condition that causes repeated and unprovoked seizures and is more common in 1–5-year-old children. Drug resistance has been indicated as a key challenge in improving the clinical outcomes of patients with pediatric epilepsy. In the present study, we aimed to identify serum small extracellular vesicles (sEVs) derived microRNAs (miRNAs) from the serum samples of children for predicting the prognosis in patients with epilepsy and drug-resistant epilepsy
2022-01-20 | GSE193842 | GEO
Project description:We report genome-wide association study results for the levels of A1, A2 and fetal hemoglobins, analyzed for the first time concurrently. Integrating high-density array genotyping and whole-genome sequencing in a large general population cohort from Sardinia, we detected 23 associations at 10 loci. Five signals are due to variants at previously undetected loci: MPHOSPH9, PLTP-PCIF1, ZFPM1 (FOG1), NFIX and CCND3. Among the signals at known loci, ten are new lead variants and four are new independent signals. Half of all variants also showed pleiotropic associations with different hemoglobins, which further corroborated some of the detected associations and identified features of coordinated hemoglobin species production.
| EGAS00001003645 | EGA