Genetic Profile of Patients with Epilepsy on First-Line Antiepileptic Drugs and Potential Directions for Personalized Treatment

Abstract

Interethnic differences were elucidated for several polymorphisms that might be responsible for differential serum drug levels and optimal dose requirement for efficacious treatment.

Effects of Polymorphisms in Six Candidate Genes on Phenytoin Maintenance Therapy in Han Chinese Patients

“…There were interethnic differences in the frequencies of genetic variants in the SCN1A, CYP2C9 and CYP2C19 genes. According to the HapMap database and a recent study [45], the minor allele frequencies of SCN1A IVS5-91G>A were lower in Africans but similar in Caucasians and Indians compared with the present study. The minor allele frequencies of CYP2C9*3 were higher in Caucasians and Indians but lower in African-Americans compared with the present study.…”

“…Although UGT1A1 is the enzyme responsible for the conjugation of the PHT oxidative metabolites [45], the activity of UGT1A1 has not been reported to be relevant to PHT concentrations. Therefore, variants in the UGT1A1 gene were not included.…”

Genetic association analysis of transporters identifies ABCC2 loci for seizure control in women with epilepsy on first-line antiepileptic drugs

“…CYP2C9, CYP2C19), drug transport (ABCB1, ABCC1, ABCC2), and drug action (e.g. SCN1A) [45]. On the basis of our current understanding of epilepsy pharmacogenomics, an alteration in the expression or the activity of AED transporters is most likely to influence the drug response, possibly by reducing the effective AED concentration at their site of action [26].…”

“…To continue to make inroads into the discovery of true markers of AED response, it is critical to capture all the AED as well as sex hormone transporters as a next logical step in the development and utilization of AEDs [45,51]. We note that it is essential to systematically analyze genetic variants across all the genes encoding ABC transporters and understand the role of an underlying LD pattern on drug response in large epilepsy populations worldwide.…”

Validation of a multigenic model to predict seizure control in newly treated epilepsy

“…With relatively few positive associations, and even fewer successful replications, there has been a growing acceptance that the complexities of treatment response are unlikely to be explained by a single genetic variant. Pharmacogenetic investigations in the epilepsy field now routinely include multiple genes implicated in both the pathogenesis of epilepsy and the pharmacokinetic and pharmacodynamic pathways of AEDs (Cavalleri et al, 2011;Grover et al, 2010;Johnson et al, 2011;Petrovski et al, 2009;Sánchez et al, 2010). Such studies generate a large volume of data and have necessarily precipitated an interest in analytical approaches, such as the development of machine learning algorithms, to efficiently identify patterns of genetic variants that associate with phenotypes of interest in highdimensional data (Nicodemus and Malley, 2009).…”