Genetic predictors for epilepsy development, treatment response and dosing

Antiepileptic drug (AED) treatment is the first line strategy for seizure control in the majority of individuals with epilepsy but remains challenging, not least because of interindividual variability in efficacy, tolerability and dosing. The studies presented in this thesis set out to explore that variability from a genomic perspective in patients with newly diagnosed epilepsy from across the UK. Single nucleotide polymorphisms (SNPs) in genes encoding drug metabolising enzymes (DMEs) may be associated with the dose of carbamazepine (CBZ) required for seizure control. A cohort of 159 individuals who were seizure-free for 12 months on a stable dose of CBZ monotherapy was genotyped for 51 SNPs across six DMEs. Haplotype analysis identified 8 haplotype blocks across the genes. No single SNPs or haplotype blocks were associated with CBZ dose. Thus, it is unlikely that genetic variability in DMEs accounts for the individual differences in CBZ dose requirement. A splice site SNP (rs3812718) in the SCN1A gene was previously shown to influence maximum doses of AEDs. This SNP was genotyped in 817 patients and tested for association with maximum and maintenance doses of several AEDs. An association was identified between rs3812718 and maximum AED dose, with an interaction analysis suggestive of a drug specific effect. These findings suggest that this SCN1A variant contributes to variability in the limit of tolerability to AEDs. Response to AED treatment is multifactorial and likely to be influenced by multiple genes. Five SNPs previously reported to predict treatment outcome in epilepsy were genotyped in 772 patients and the resulting data, together with data from an Australian cohort, incorporated into a predictive algorithm. The algorithm failed to predict treatment outcome in general but was partially successful in identifying responders to CBZ and valproate. These five SNPs may be relevant to the prognosis of epilepsy, particularly when treated with specific AEDs. Primary generalised epilepsies (PGEs) are highly heritable and believed to be polygenic in origin. Predictive algorithms were employed to explore genetic influences on seizure (absence vs. myoclonus) and epilepsy (PGE vs. focal) type using 1,840 SNP genotypes available from 436 patients with PGE. Although the algorithms failed to distinguish PGE patients on the basis of genetic variants, they showed improved association over univariate methods of analysis. Such an approach may be suitable for future investigations using large genomic datasets. A recent genome-wide association study identified multiple genetic variants that approached genome-wide significance for association with 12 month remission from seizures. Five of these SNPs were genotyped in an independent cohort of 424 patients and tested for association with remission and time to remission. No significant associations were found, questioning the validity of the original observation or the method of replication. Further work is required to understand this outcome. In conclusion, the genetic bases of epilepsy, AED response and AED dose requirement are multigenic and thus far undetectable using traditional association studies in modestly-sized patient cohorts. Further advances in genomic, bioinformatics and statistical methodologies are required before the genetic contribution to heterogeneity in epilepsy-related phenotypes can be translated into improved clinical care.