Project description:The epilepsies represent one of the most common neurological disorders. Mesial temporal lobe epilepsies (MTLE) are the most frequent form of partial epilepsies and display frequent resistance to anti-epileptic drugs thus representing a major health care problem. In TLE, the origin of seizure activity typically involves the hippocampal formation, which displays major neuropathological features, described with the term hippocampal sclerosis (HS). HS is the most frequent pathological substrate of refractory mesial temporal lobe epilepsy. Complex partial seizures (CPS) are the predominant seizure type associated with medial temporal lobe epilepsy. MTLE is commonly due to mesial temporal sclerosis (MTS). The biology underlying the epilepstic seizures and the transcriptome associated to the seizure in intractable medial temporal lobe epilepsy is ill understood. The aim of the study was to identify potential biomarkers that could identify epileptic seizure. Thus we performed transcriptome profiling of ten medial temporal lobe epilepsy cases which are resistant to the drug and underwent temporal lobectomy. The cases constitutes of patients with intractable complex partial seizure, treated medically and have undergone detailed presurgical evaluation and subjected to surgery for standard temporal lobectomy and amygdalo-hippocampectomy. The spiking areas identified after the electrocorticography will form the test tissues, which compared with the nonspiking areas removed during the surgery, from the same patient. This could probably form one of the appropriate controls, as test and control are from same patient, which eliminates the genome variations that could incur due to the comparison with the tissues from the another patient. Also this could get rid of expression changes due to the treatments undergone by the patient. We performed two color microarray wherein we labled seizure focus (spiking area) with Cy5 and non-seizure region tissues (non-spiking) with Cy3. As a strategy to test the possibility of potential diagnostic biomarkers we are intended to test the differentially regulated molecules in an independent set of epilepsy samples. Two color experiment

Project description:The epilepsies represent one of the most common neurological disorders. Mesial temporal lobe epilepsies (MTLE) are the most frequent form of partial epilepsies and display frequent resistance to anti-epileptic drugs thus representing a major health care problem. In TLE, the origin of seizure activity typically involves the hippocampal formation, which displays major neuropathological features, described with the term hippocampal sclerosis (HS). HS is the most frequent pathological substrate of refractory mesial temporal lobe epilepsy. Complex partial seizures (CPS) are the predominant seizure type associated with medial temporal lobe epilepsy. MTLE is commonly due to mesial temporal sclerosis (MTS). The biology underlying the epilepstic seizures and the transcriptome associated to the seizure in intractable medial temporal lobe epilepsy is ill understood. The aim of the study was to identify potential biomarkers that could identify epileptic seizure. Thus we performed transcriptome profiling of ten medial temporal lobe epilepsy cases which are resistant to the drug and underwent temporal lobectomy. The cases constitutes of patients with intractable complex partial seizure, treated medically and have undergone detailed presurgical evaluation and subjected to surgery for standard temporal lobectomy and amygdalo-hippocampectomy. The spiking areas identified after the electrocorticography will form the test tissues, which compared with the nonspiking areas removed during the surgery, from the same patient. This could probably form one of the appropriate controls, as test and control are from same patient, which eliminates the genome variations that could incur due to the comparison with the tissues from the another patient. Also this could get rid of expression changes due to the treatments undergone by the patient. We performed two color microarray wherein we labled seizure focus (spiking area) with Cy5 and non-seizure region tissues (non-spiking) with Cy3. As a strategy to test the possibility of potential diagnostic biomarkers we are intended to test the differentially regulated molecules in an independent set of epilepsy samples.

Project description:Neither the molecular basis of the pathologic tendency of neuronal circuits to generate spontaneous seizures (epileptogenicity) nor anti-epileptogenic mechanisms that maintain a seizure-free state are well understood. Here, we performed transcriptomic analysis in the intrahippocampal kainate model of temporal lobe epilepsy in rats using both Agilent and Codelink microarray platforms to characterize the epileptic processes. The experimental design allowed subtraction of the confounding effects of the lesion, identification of expression changes associated with epileptogenicity, and genes upregulated by seizures with potential homeostatic anti-epileptogenic effects. Using differential expression analysis, we identified several hundred expression changes in chronic epilepsy, including candidate genes associated with epileptogenicity such as Bdnf and Kcnj13. To analyze these data from a systems perspective, we applied weighted gene co-expression network analysis (WGCNA) to identify groups of co-expressed genes (modules) and their central (hub) genes. One such module contained genes upregulated in the epileptogenic region, including multiple epileptogenicity candidate genes, and was found to be involved the protection of glial cells against oxidative stress, implicating glial oxidative stress in epileptogenicity. Another distinct module corresponded to the effects of chronic seizures and represented changes in neuronal synaptic vesicle trafficking. We found that the network structure and connectivity of one hub gene, Sv2a, showed significant changes between normal and epileptogenic tissue, becoming more highly connected in epileptic brain. Since Sv2a is a target of the antiepileptic levetiracetam, this module may be important in controlling seizure activity. Bioinformatic analysis of this module also revealed a potential mechanism for the observed transcriptional changes via generation of longer alternatively polyadenlyated transcripts through the upregulation of the RNA binding protein HuD. In summary, combining conventional statistical methods and network analysis allowed us to interpret the differentially regulated genes from a systems perspective, yielding new insight into several biological pathways underlying homeostatic anti-epileptogenic effects and epileptogenicity.

Project description:Neither the molecular basis of the pathologic tendency of neuronal circuits to generate spontaneous seizures (epileptogenicity) nor anti-epileptogenic mechanisms that maintain a seizure-free state are well understood. Here, we performed transcriptomic analysis in the intrahippocampal kainate model of temporal lobe epilepsy in rats using both Agilent and Codelink microarray platforms to characterize the epileptic processes. The experimental design allowed subtraction of the confounding effects of the lesion, identification of expression changes associated with epileptogenicity, and genes upregulated by seizures with potential homeostatic anti-epileptogenic effects. Using differential expression analysis, we identified several hundred expression changes in chronic epilepsy, including candidate genes associated with epileptogenicity such as Bdnf and Kcnj13. To analyze these data from a systems perspective, we applied weighted gene co-expression network analysis (WGCNA) to identify groups of co-expressed genes (modules) and their central (hub) genes. One such module contained genes upregulated in the epileptogenic region, including multiple epileptogenicity candidate genes, and was found to be involved the protection of glial cells against oxidative stress, implicating glial oxidative stress in epileptogenicity. Another distinct module corresponded to the effects of chronic seizures and represented changes in neuronal synaptic vesicle trafficking. We found that the network structure and connectivity of one hub gene, Sv2a, showed significant changes between normal and epileptogenic tissue, becoming more highly connected in epileptic brain. Since Sv2a is a target of the antiepileptic levetiracetam, this module may be important in controlling seizure activity. Bioinformatic analysis of this module also revealed a potential mechanism for the observed transcriptional changes via generation of longer alternatively polyadenlyated transcripts through the upregulation of the RNA binding protein HuD. In summary, combining conventional statistical methods and network analysis allowed us to interpret the differentially regulated genes from a systems perspective, yielding new insight into several biological pathways underlying homeostatic anti-epileptogenic effects and epileptogenicity. Four condition experiment with five samples per condition. The samples include right dentate gyrus from animals with seizures, left dentate gyrus from animals with seizures, right dentate gyrus from animals without seizures, and left dentate gyrus from animals without seizures. A dye swap was included.

Project description:Neither the molecular basis of the pathologic tendency of neuronal circuits to generate spontaneous seizures (epileptogenicity) nor anti-epileptogenic mechanisms that maintain a seizure-free state are well understood. Here, we performed transcriptomic analysis in the intrahippocampal kainate model of temporal lobe epilepsy in rats using both Agilent and Codelink microarray platforms to characterize the epileptic processes. The experimental design allowed subtraction of the confounding effects of the lesion, identification of expression changes associated with epileptogenicity, and genes upregulated by seizures with potential homeostatic anti-epileptogenic effects. Using differential expression analysis, we identified several hundred expression changes in chronic epilepsy, including candidate genes associated with epileptogenicity such as Bdnf and Kcnj13. To analyze these data from a systems perspective, we applied weighted gene co-expression network analysis (WGCNA) to identify groups of co-expressed genes (modules) and their central (hub) genes. One such module contained genes upregulated in the epileptogenic region, including multiple epileptogenicity candidate genes, and was found to be involved the protection of glial cells against oxidative stress, implicating glial oxidative stress in epileptogenicity. Another distinct module corresponded to the effects of chronic seizures and represented changes in neuronal synaptic vesicle trafficking. We found that the network structure and connectivity of one hub gene, Sv2a, showed significant changes between normal and epileptogenic tissue, becoming more highly connected in epileptic brain. Since Sv2a is a target of the antiepileptic levetiracetam, this module may be important in controlling seizure activity. Bioinformatic analysis of this module also revealed a potential mechanism for the observed transcriptional changes via generation of longer alternatively polyadenlyated transcripts through the upregulation of the RNA binding protein HuD. In summary, combining conventional statistical methods and network analysis allowed us to interpret the differentially regulated genes from a systems perspective, yielding new insight into several biological pathways underlying homeostatic anti-epileptogenic effects and epileptogenicity. Four condition experiment with five samples per condition. The samples include right dentate gyrus from animals with seizures, left dentate gyrus from animals with seizures, right dentate gyrus from animals without seizures, and left dentate gyrus from animals without seizures.

Dataset Information

Transcriptome profile on epileptogenic zones of patients with neocortical epilepsy

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure