Epilepsy Pharmacogenetics Published and Unpublished Research

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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of data relating to genetic association studies in the field of epilepsy, collects results from published and unpublished research in epilepsy genetics providing data to be used for meta-analyses and other scientific purposes. The susceptibility genes database compiles all studies related to putative epilepsy susceptibility genes (eg. interleukin-1-beta in TLE), while the pharmacogenetics studies in epilepsy (eg. ABCB1 studies) are stored in ‘phamacogenetics’. The meta-analysis database compiles all existing published epilepsy genetic meta-analyses, whether for susceptibility genes, or pharmacogenetics. This dataset is a summary of results of both published and unpublished studies showing the pharmacogenetic association of various drugs used to treat epilepsy. The dataset collects data from epilepsy pharmacogenetics research, displaying the studied genes, subjects of study, country, statistical significance, author, publication year and reference.

Complexity

“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.

Date Created

2009-01-31

Last Modified

2014-08-31

Version

2017-07-15

Update Frequency

Irregular

Temporal Coverage

2007-2014

Spatial Coverage

World

Source

John Snow Labs => Epilepsy Genetic Association Database (epiGAD)

Source License URL

John Snow Labs Standard License

Source License Requirements

N/A

Source Citation

Epilepsy genetic association database, E.P.I.G.A.D. (2016). Epigad.org. Retrieved 11 November, 2016.

Keywords

Epilepsy Data, Genetics Publications, Epilepsy Disease, Epilepsy Gene, Genetic Associations, Pharmacogenetics, Epilepsy Susceptibility, Epilepsy Meta Analysis

Other Titles

Epilepsy Gene Frequencies, GDA Epilepsy Pharmacogenetics, Genetic Predisposition to Epilepsy Disease, Epilepsy Genetic Variation, Epilepsy Genotype and Phenotype

NameDescriptionTypeConstraints
CasesSubjects of study. Name or initials of the type of response, adverse reaction, intolerance or resistance to the drug of the patients to study.stringrequired : 1
ControlsThe 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.stringrequired : 1
GeneShort form or acronym used to describe a specific gene examined in the studystring-
AlleleShort 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_CasesNumber of subjects in casesstringrequired : 1
Number_Of_ControlsThe total number of case subjects in the study.numberrequired : 1 level : Ratio
Control_SourceThe 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.stringrequired : 1
Country_Of_OriginThe geographic origin of the study patients.stringrequired : 1
P_ValueStatistical significance of the results of the study. A p-value less than 0.05 means that the results were significant.stringrequired : 1
Author1The first author of the study article.string-
Publication_YearYear in which the referred article was published.daterequired : 1
ReferenceWeblink from NCBI website showing reference to the article.stringrequired : 1
CasesControlsGeneAlleleNumber_Of_CasesNumber_Of_ControlsControl_SourceCountry_Of_OriginP_ValueAuthor1Publication_YearReference
Drug resistantDrug responsiveABCB1C3435T16450PChina0.520070
Drug resistantDrug responsiveABCB1C3435T3030PCroatia0.01120040
CBZ-MPEHealthyHLA-B*1502 allele3962PChinaNSWang2011http://www.ncbi.nlm.nih.gov/pubmed/21397523
CBZ-SCARCBZ-tolerantHLAA*31012450PKorea0.001Kim2011http://www.ncbi.nlm.nih.gov/pubmed/21917426
Drug-resistantHealthyMDR1G2677AT3992PTurkeyNSAlpman2010http://www.ncbi.nlm.nih.gov/pubmed/20448249
Drug-resistantHealthyMDR1C3435T3992PTurkey0.18Alpman2010http://www.ncbi.nlm.nih.gov/pubmed/20448249
SJS/TENDrug tolerantHLA-B*150226113PTaiwan0.0041Hung2010http://www.ncbi.nlm.nih.gov/pubmed/20235791
CBZ-SJS/TENCBZ-tolerantHLAB*15021721PChina<0.01Zhang2011http://www.ncbi.nlm.nih.gov/pubmed/21424386
CNS ADR-yesCNS ADR-noABCC2c.1247G>A4799PSeoul0.005Kim2010http://www.ncbi.nlm.nih.gov/pubmed/20216337
CBZ-SCARCBZ-tolerantHLAmultiple SNPs2450PKorea>0.05Kim2011http://www.ncbi.nlm.nih.gov/pubmed/21917426