- Epilepsy Gene Frequencies
- GDA Epilepsy Pharmacogenetics
- Genetic Predisposition to Epilepsy Disease
- Epilepsy Genetic Variation
- Epilepsy Genotype and Phenotype
- Epilepsy Data
- Genetics Publications
- Epilepsy Disease
- Epilepsy Gene
- Genetic Associations
- Epilepsy Susceptibility
- Epilepsy Meta Analysis
Epilepsy Pharmacogenetics Published and Unpublished Research
The Epilepsy Genetic Association Database (epiGAD) of the International League Against Epilepsy is an online repository of data relating to genetic association studies in the field of epilepsy, collects results from published and unpublished research in epilepsy genetics providing data to be used for meta-analyses and other scientific purposes.
Get The Data
- ResearchNon-Commercial, Share-Alike, Attribution Free Forever
- CommercialCommercial Use, Remix & Adapt, White Label Log in to download
“Epilepsy is defined as a brain disorder characterized by an enduring predisposition to generate … seizures.” (1) The causes of epilepsy can vary, but there are genetic syndromes that can cause epilepsy, such as metabolic diseases and specific gene mutations. Even though there is known of some specific genetic diseases that can cause epilepsy, the majority of cases are of unknown cause, for which research efforts exist on finding a cause, mainly focused in finding genetic alterations in epileptic patients. Among the different types of epilepsy, drug-resistant epilepsy (where seizures don’t cease with any of the available medications) is of major concern and research focuses on finding the characteristics of the genes linked to it. Epilepsy with a familial pattern is also a field of genetic study.
Metabolism is a group of biochemical pathways that work in the human body with the object of degrading and using properly all substrates that go into the body (i.e. food, drugs). The pace of metabolism and the effectiveness of this to certain substrates can vary from one person to another, this is due to the uniqueness of every individual thanks to their genetic information; metabolism can also be influenced by different conditions (e.g. stress) and diseases. Pharmacogenomics is the study of the types of different genetic variants that influence individuals drug metabolism, this includes evaluating adverse reactions and resistance to respond to treatments linking them to a certain gene and/or gene variants.
Anticonvulsants are used as a treatment for epilepsy, these prevent and/or stop seizure events. There is a large list of anticonvulsants that are indicated according to the types of seizures and patient characteristics; among them, there is carabamazepine, ethosuximide, lamotrigine, levetiracetam, phenytoin, phenobarbital (a barbiturate), and others.
“A genetic association study is, in essence, a case-control study (Hattersley et al, Lancet 2005) It examines the frequency of an allele in a particular gene in patients with the disease, compared against controls. Genetic association studies have proliferated in the past 5 years, particularly in the field of epilepsy, with the aim of understanding the common genes and polymorphisms that may increase the risk of common epilepsies. Results of such studies have however been inconsistent (Tan et al, Epilepsia 2004)
The goal of epiGAD is to collate all association studies in epilepsy, whether published or unpublished. This will help researchers in this area identify all the available gene-disease associations, as well as facilitate future meta-analyses and studies on publication bias (Munafo et al, Trends Genet 2004). It is also hoped that epiGAD will foster collaboration between the different epilepsy genetics groups around the world, and facilitate the formation of a network of investigators in epilepsy genetics (Ioannidis et al, Am J Epi 2005) epiGAD is funded by NMRC, Singapore, and also through an educational grant from UCB Pharma.
There are 4 databases within epiGAD:
the susceptibility genes database
the epilepsy pharmacogenetics database
the meta-analysis database
the genome-wide association studies (GWAS) database”
“Publications were primarily identified using a Pubmed search. Additional searches were done using HuGE Net, Google Scholar and ISI Web of Science. Genetic association studies identified with the first-pass search terms were then used as the basis for the ‘Related Articles’ subsearch in Pubmed. Subsequent studies identified were then used for ‘Related Articles’ for 2 more iterations. Data from the identified studies were extracted in a standardized manner and included in epiGAD.”
1. David y ko, D.Y.K. (2017). Medscapecom. Retrieved 4 January, 2017.
Description source: Epilepsy genetic association database, E.P.I.G.A.D. (2016). Epigad.org. Retrieved 11 November, 2016.
About this Dataset
John Snow Labs; Epilepsy Genetic Association Database (epiGAD);
|Source License URL|
|Source License Requirements||
Epilepsy genetic association database, E.P.I.G.A.D. (2016). Epigad.org. Retrieved 11 November, 2016.
Epilepsy Data, Genetics Publications, Epilepsy Disease, Epilepsy Gene, Genetic Associations, Pharmacogenetics, Epilepsy Susceptibility, Epilepsy Meta Analysis
Epilepsy Gene Frequencies, GDA Epilepsy Pharmacogenetics, Genetic Predisposition to Epilepsy Disease, Epilepsy Genetic Variation, Epilepsy Genotype and Phenotype
|Cases||Subjects of study. Name or initials of the type of response, adverse reaction, intolerance or resistance to the drug of the patients to study.||string||required : 1|
|Controls||The condition of the control subjects. Control subjects are a group of patients that are compared to the subjects of study; this group could be healthy, with a different condition than the cases group or with an opposite response to the drug.||string||required : 1|
|Gene||Short form or acronym used to describe a specific gene examined in the study||string||-|
|Allele||Short form or acronym used to describe a specific allele examined in the study. An allele is a variant of a gene; as everyone has two copies of every gene in their DNA, one person can have two different alleles of the same gene, as well as only one same allele in both copies. Alleles determine the physical or biological differences between one person and another, as well as, for example, the severity of a disease. In this case, the allele could determine the response to the anticonvulsant drug.||string||-|
|Number_Of_Cases||Number of subjects in cases||string||required : 1|
|Number_Of_Controls||The total number of case subjects in the study.||number||required : 1 level : Ratio|
|Control_Source||The type of controls used - population-based (P), family-based (F), or both (PF). If both are used (PF), the number of cases and controls shown will be the number used for the population-based analysis.||string||required : 1|
|Country_Of_Origin||The geographic origin of the study patients.||string||required : 1|
|P_Value||Statistical significance of the results of the study. A p-value less than 0.05 means that the results were significant.||string||required : 1|
|Author1||The first author of the study article.||string||-|
|Publication_Year||Year in which the referred article was published.||date||required : 1|
|Reference||Weblink from NCBI website showing reference to the article.||string||required : 1|
|Drug resistant||Drug responsive||ABCB1||C3435T||164||50||P||China||0.5||2007||0|
|Drug resistant||Drug responsive||ABCB1||C3435T||30||30||P||Croatia||0.011||2004||0|
|CNS ADR-yes||CNS ADR-no||ABCC2||c.1247G>A||47||99||P||Seoul||0.005||Kim||2010||http://www.ncbi.nlm.nih.gov/pubmed/20216337|