Epilepsy is the most prevalent chronic neurological disorder, affecting at least 50 million people worldwide (Duncan et al., 2006). Studies in new-onset epilepsy indicate that seizures can be controlled by antiepileptic drugs (AEDs) in up to 70% of patients (Sillanpää & Schmidt, 2006). Yet, for someone developing the disease, key questions are whether or not their seizures will cease, what the optimal dose of an AED is, and whether serious adverse effects will occur. Although the incidence of rash differs among AEDs, predicting serious hypersensitivity reaction in an individual patient exposed to a drug that may cause a rash is currently not possible. Furthermore, the optimal doses of AEDs may differ four-fold among individuals (Kwan & Brodie, 2001). In addition, prognosis varies considerably among the different types of epilepsy (Semah et al., 1998). Moreover, the treatment outcome may vary even between patients with seemingly the same epilepsy syndrome, and its determinants are largely unknown (Schmidt & Löscher, 2005). Although many factors may contribute to variability of clinical outcome in individual patients, unpredictability may, at least in part, result from genetic variation. The influence of genes on outcome of drug treatment is a rapidly evolving field termed pharmacogenetics over 40 years ago by the German geneticist Friedrich Vogel (Vogel, 1959). The ultimate goal of pharmacogenetics is to use the genetic makeup of an individual to predict drug response and efficacy, as well as potential adverse drug events. The topic of pharmacogenetics in epilepsy has recently been covered in several excellent review articles (Ferraro & Buono, 2005; Sisodiya, 2005; Depondt, 2006; Ferraro et al., 2006; Szoeke et al., 2006; Mann & Pons, 2007; Tate & Sisodiya, 2007), and several aspects of this topic are described in much greater detail in some of these recent reviews. The primary aim of the present review is to critically evaluate if and to what degree genetic variation is affecting outcome of medical treatment of epilepsies in the individual patient. For this purpose, we subdivided the review in two main sections: (1) genetic variation that has a potential effect on clinical efficacy of AEDs and (2) gene variants that may affect tolerability and safety of AEDs, with particular emphasis on more recent studies that have not yet been covered by previous reviews.
Drug treatment of epilepsy is characterized by unpredictability of efficacy, adverse drug reactions, and optimal doses in individual patients, which, at least in part, is a consequence of genetic variation. Since genetic variability in drug metabolism was reported to affect the treatment with phenytoin more than 25 years ago, the ultimate goal of pharmacogenetics is to use the genetic makeup of an individual to predict drug response and efficacy, as well as potential adverse drug events. However, determining the practical relevance of pharmacogenetic variants remains difficult, in part because of problems with study design and replication. This article reviews the published work with particular emphasis on pharmacogenetic alterations that may affect efficacy, tolerability, and safety of antiepileptic drugs (AEDs), including variation in genes encoding drug target (SCN1A), drug transport (ABCB1), drug metabolizing (CYP2C9, CYP2C19), and human leucocyte antigen (HLA) proteins. Although the current studies associating particular genes and their variants with seizure control or adverse events have inherent weaknesses and have not provided unifying conclusions, several results, for example that Asian patients with a particular HLA allele, HLA-B*1502, are at a higher risk for Stevens-Johnson syndrome when using carbamazepine, are helpful to increase our knowledge how genetic variation affects the treatment of epilepsy. Although genetic testing raises ethical and social issues, a better understanding of the genetic influences on epilepsy outcome is key to developing the much needed new therapeutic strategies for individuals with epilepsy.
The Promise of Pharmacogenetics in Clinical Practice
The concept of “personalized” medicine is receiving much attention, and expectations have been raised that pharmacogenetics may be an important tool to optimize the treatment of epilepsy for the individual patient. As outlined above, treatment of epilepsy with AEDs is complicated by unpredictability of efficacy, adverse drug reactions (ADRs), and optimal doses in individual patients. At least in part, this unpredictability may result from individual genes whose variations exert a measurable influence on the effect of a given drug. It is becoming increasingly clear that genetic polymorphisms play an integral role in variability of both AED pharmacokinetics and pharmacodynamics. Single nucleotide polymorphisms (SNPs), variations at a single site in the DNA, are the most frequent form of sequence variations in the human genome and may affect the efficacy, tolerability, safety, and duration of action of AEDs. With a better molecular understanding of the variability of drug action, there is some hope for the future to cope better with this pertinent clinical problem by incorporating pharmacogenetic principles (Pirazzoli & Recchia, 2004; Kirchheiner et al., 2005; Lewis, 2005; Phillips & van Bebber, 2005; Kalow, 2006; Goldstein et al., 2007;Lesko, 2007). The present article will critically evaluate the clinical evidence how the treatment of epilepsy could in fact benefit from considering and applying pharmacogenetic principles. For this review, we will follow the course of an AED tablet from drug absorption in the gastrointestinal tract to drug distribution to the brain, drug actions at brain targets, and finally hepatic metabolism and renal excretion (both processes contributing to drug elimination) as illustrated in Fig. 1. Following this course, we will consider how genetic variations of these individual processes may affect the efficacy of AED treatment. In addition, we will discuss the impact of gene variation on side effects of AEDs, which may involve several of the above processes. At the end of each subsection, we will briefly assess the potential clinical impact. Finally, we will briefly consider medicoeconomic issues, availability of genetic testing, legal aspects, and the ethical issues at stake.
Genetic Variation That May Affect Clinical Efficacy of Antiepileptic Drugs
In general, as with other drugs, the absorption and distribution and, hence clinical efficacy, of AEDs depend on their physicochemical characteristics such as lipophilicity, solubility, molecular weight, and ionic state. Most AEDs are sufficiently lipophilic to penetrate biomembranes by passive diffusion (Löscher & Potschka, 2005a). However, drug efflux transporters at the gastrointestinal tract and blood-brain barrier (BBB) may limit absorption and brain uptake of AEDs, so that genetic variation in the expression and functionality of such transporters may determine clinical outcome (Fig. 1). Furthermore, polymorphisms in brain targets of AEDs may affect their effectiveness. Finally, genetic variation in drug metabolism and elimination may contribute to interindividual variability in drug response (Fig. 1).
Traditionally, drug absorption has been considered as a passive process governed mainly by the physicochemical properties of the drug. However, in addition to passive transcellular and paracellular transport mechanisms, carrier-mediated transport across membranes plays an important role in drug and nutrient absorption (Anderle et al., 2004). The role of such transporters for absorption of AEDs from the intestine in the blood stream is largely unknown, with two prominent exceptions, namely, gabapentin (GBP) and pregabalin (PGB). GBP is absorbed via the large neutral amino acid carrier, system L, in the proximal small intestine, resulting in dose-dependent absorption (due to saturation of this transport system) and inhibition of intestinal uptake of GBP by several large neutral amino acids (Piyapolrungroj et al., 2001; Anderle et al., 2004). Despite the structural similarity between GBP and PGB, PGB absorption exhibits nearly linear pharmacokinetics, which is explained by lower affinity of PGB for the L-type system and involvement of other amino acid transport systems in the intestinal uptake of PGB (Piyapolrungroj et al., 2001; Su et al., 2005). Whether polymorphisms in these carriers affect the intestinal uptake of GBP or PGB is not known.
Transporters can also play a crucial role in limiting drug absorption through drug secretion into the intestinal lumen. A number of drug efflux transporters are expressed by enterocytes, including P-glycoprotein (Pgp), members of the multidrug resistance-associated protein (MRP) family, and breast cancer-related protein (BCRP) (Anderle et al., 2004; Fromm, 2004; Ito et al., 2005). Furthermore, enterocytes express the major drug-metabolizing enzymes CYP3A4 and CYP2C9/19, which, in concert with efflux transporters, may restrict the oral bioavailability of drugs that are substrates for CYP enzymes and/or drug efflux transporters such as Pgp (Fromm, 2004). Drugs, including AEDs such as carbamazepine (CBZ), may induce the expression of drug-metabolizing enzymes and drug efflux transporters in the intestinal tract, thereby reducing their own absorption (Giessmann et al., 2004; Christians et al., 2005). Furthermore, genetic and environmental factors probably have a major role in the regulation of the basal expression and function of intestinal CYP3A4 and Pgp (Fromm, 2004). Many drugs, including several AEDs, are Pgp substrates, so that genetic variation in the ABCB1[multidrug resistance 1 (MDR1)] gene that encodes Pgp may have dramatic consequences for the pharmacological behavior of substrate drugs (Marzolini et al., 2004; Löscher & Potschka, 2005a, 2005b).
The human ABCB1 gene is composed of 29 exons (for details see latest data releases at http://www.ensembl.org and http://www.ncbi.nlm.nih.gov). A synonymous SNP in exon 27 (C3435T) was the first variant to be associated with altered protein expression in the human intestinal tract, although the SNP does not change the encoded amino acid (Hoffmeyer et al., 2000). Pgp expression in the duodenum of individuals with the CC genotype was noted to be two-fold higher when compared with that in individuals with the TT genotype, which was associated with significantly decreased plasma concentrations of the Pgp substrate digoxin after oral administration, suggesting lower drug absorption in individuals with high intestinal Pgp levels (Hoffmeyer et al., 2000). The observation that the 3435C allele in exon 27 is associated with lower digoxin levels was confirmed by some, but not all subsequent studies (Marzolini et al., 2004). The synonymous 3435C>T polymorphism is in linkage disequilibrium with a synonymous SNP in exon 13 (1236C>T) and a nonsynonymous SNP in exon 22 (2677G>TA), suggesting that the observed functional differences in Pgp, initially attributed to the exon 27 synonymous SNP, may be the result of the associated nonsynonymous polymorphism in exon 22, which results in amino acid exchanges (Ala893Ser or Ala893Thr) (Marzolini et al., 2004). However, a recent study by Gottesman's group showed that the synonymous C3435T SNP in exon 27, although not resulting in amino acid changes itself, is not “silent,” but results in Pgp with altered drug and inhibitor interactions (Kimchi-Sarfaty et al., 2007). Similar messenger RNA (mRNA) and protein levels, but altered conformations, were found for wild-type and polymorphic Pgp. Kimchi-Safarty et al. (2007) hypothesized that the presence of a rare codon, marked by the synonymous polymorphism, affects the timing of cotranslational folding and insertion of Pgp into the membrane, thereby altering the structure of substrate and inhibitor interaction sites. This study is of immense importance, as it demonstrates for the first time that naturally occurring silent SNPs can lead to the synthesis of protein product with the same amino acid sequence but different structural and functional properties. Thus, silent SNPs should no longer be neglected in determining the likelihood of development of various diseases and should be taken into account in personalized drug treatment and development programs (Komar, 2007).
Polymorphisms in ABCB1 change not only the oral bioavailability of digoxin, but also that of several other Pgp substrates, although data are conflicting (Marzolini et al., 2004). Kerb et al. (2001) studied whether levels of phenytoin (PHT), which is a substrate of Pgp, correlate with the C3435T polymorphism in the ABCB1 gene. Genotyping and analyses of plasma levels of PHT after oral administration in 96 healthy Turkish volunteers showed that the 3435C>T polymorphism affects PHT plasma levels. The CC genotype was significantly more common in volunteers with low PHT levels. The effect of the C3435T polymorphism on oral bioavailability of PHT was also determined in 35 PHT-treated patients with epilepsy (Kerb et al., 2001). In a more recent study by Simon et al. (2007) in patients with epilepsy, intestinal Pgp expression and PHT and CBZ dose requirements were influenced by the genotype in position 3435 and 2677 of the ABCB1 gene, thus confirming the data of Kerb et al. (2001). Furthermore, Ebid et al. (2007) reported that the 3435 genotype affected plasma levels of PHT in epilepsy patients in that subjects with the CC genotype were more likely to have low PHT levels (<10 μg/ml) than patients with the TT phenotype. In this respect, it is also interesting to note that Lazarowski and colleagues reported that some patients with refractory epilepsy and high expression of brain Pgp have persistently subtherapeutic plasma levels of CBZ, valproate (VPA) or PHT despite administration of high doses of these AEDs, suggesting that absorption and/or elimination of AEDs in such patients may be affected by increased expression of Pgp in the periphery (Lazarowski et al., 1999, 2004, 2007). However, data on whether ABCB1 3435CC genotype is indeed associated with increased Pgp level in duodenal enterocytes are conflicting (Goto et al., 2002; Nakamura et al., 2002; Sakaeda et al., 2002). As a result, it remains circumferential that any reduction in bioavailability of AEDs observed can be attributed to ABCB1 3435 genotype.
As mentioned above, presystemic drug elimination can occur already during the intestinal absorption process of drugs, because drug metabolizing enzymes are also expressed along the human gastrointestinal tract (Ding & Kaminsky, 2003; Glaeser et al., 2005; Thörn et al., 2005). However, this intestinal metabolic capacity is regarded as much less effective as that in the liver (Lin et al., 1999), and there are no data demonstrating that the oral bioavailability of any AED is affected to a significant extent by an intestinal first-pass effect.
Overall, one may conclude that the clinical contribution of genetic mutations of drug metabolizing enzymes to the interindividual variability in drug absorption can be neglected for most patients. However, it is possible that mutations in genes encoding proteins involved in drug absorption are more relevant in patients with compromised liver function taking a CYP-metabolized AED, or for patients with reduced kidney function who may be taking a drug that undergoes primarily renal excretion. It remains unclear if the increased expression of intestinal Pgp, which has been suggested to lead to poor biovailability of AEDs, contributes to poor seizure control in some patients.
For drugs such as AEDs that act on targets in the brain, sufficient penetration through the BBB is a prerequisite for therapeutic efficacy (Fig. 1). The BBB is a physical and metabolic barrier between the brain and the systemic circulation, which serves to protect and regulate the microenvironment of the brain (Huber et al., 2001). Most AEDs are quite lipophilic (c.f., DrugBank, http://redpoll.pharmacy.ualberta.ca/drugbank/index.html), so that they can easily penetrate through the brain capillary endothelial cells that form the BBB (Löscher & Potschka, 2005a). However, efflux transporters such as Pgp, which are located at the apical (luminal) membrane of brain capillary endothelial cells and protect the brain from intoxication by lipophilic xenobiotics, may restrict the brain uptake of AEDs and mediate extrusion of AEDs from the brain (Kwan & Brodie, 2005; Löscher & Potschka, 2005a). Because most AEDs are only weak substrates for Pgp, the basal (constitutive) expression of Pgp at the BBB is unlikely to restrict brain penetration of AEDs to any clinically important extent (Löscher & Potschka, 2005a). However, intrinsic or acquired overexpression of Pgp in the BBB may critically limit drug penetration into the brain, leading to resistance against all AEDs that are substrates of Pgp (Kwan & Brodie, 2005; Löscher & Potschka, 2005a, 2005b). Such Pgp overexpression can result from the effects of disease or drug treatment on Pgp expression or from ABCB1 polymorphisms and might explain the clinical observation that patients with refractory epilepsy are usually resistant to a broad range of AEDs with different mechanisms of action (Kwan & Brodie, 2005).
Increased expression of Pgp and other drug efflux transporters has been determined in epileptogenic brain tissue of patients with refractory epilepsy (Fig. 2A) and in rodent models of AED-resistant epilepsy (Kwan & Brodie, 2005; Löscher & Potschka, 2005a). In rodent models of temporal lobe epilepsy (TLE), the increased Pgp expression in the hippocampus and parahippocampal regions was associated with significantly decreased concentrations of AEDs in these regions (Rizzi et al., 2002; Van Vliet et al., 2007). In patients with oxcarbazepine (OXC)-resistant epilepsy, the brain tissue expression of ABCB1 mRNA was found to be inversely correlated with brain levels of 10,11-dihydro-10-hydroxy-5H-dibenzo(b,f)azepine-5-carboxamide (10-OHCBZ), the active metabolite of OXC, indicating that Pgp may play a role in the pharmacoresistance to OXC by causing insufficient concentrations of its active metabolite at neuronal targets (Marchi et al., 2005). Using an in vitro BBB model with human capillary endothelial cells from either normal brain or drug-resistant epileptic brain, Cucullo et al. (2007) recently reported a dramatically reduced permeability of PHT across the in vitro BBB formed from endothelial cells of patients with refractory epilepsy, which could be partially counteracted by the selective Pgp inhibitor tariquidar (Fig. 2B). In line with this finding, the decrease in brain concentrations and resistance to AEDs, such as PHT or phenobarbital (PB), associated with Pgp overexpression in rodent models could be counteracted by tariquidar in vivo, suggesting a causal association between Pgp overexpression and AED resistance (Brandt et al., 2006; van Vliet et al., 2006; van Vliet et al., 2007).
In 2003, Siddiqui et al. reported the C3435T polymorphism in the ABCB1 gene as being associated with resistance to multiple AEDs, leading to the suggestion that drug resistance in epilepsy might be genetically determined, which could open new therapeutic avenues. In the genetic association study of Siddiqui et al. (2003), which was performed as a retrospective case-control study by comparing the frequencies of the ABCB1 C3435T variant in 115 AED responders with 200 AED-resistant patients and 200 nonepileptic controls, it was shown that patients with multidrug-resistant epilepsy were significantly more likely to be homozygous for the C allele than the T allele. Because the CC genotype has been associated with increased expression of intestinal Pgp (Hoffmeyer et al., 2000), the data of Siddiqui et al. (2003) suggested that the CC genotype may be associated with increased expression and functionality of Pgp also at the BBB, leading to reduced AED levels at their brain targets.
In a follow-up study by the same group (Soranzo et al., 2004), the association of AED resistance with the 3435C>T polymorphism was confirmed in a larger group of patients, and intronic sites that are strongly associated with the 3435C>T polymorphism were identified. The increased prevalence of the CC genotype of ABCB1 3435 in patients with drug-resistant epilepsy reported by Siddiqui et al. (2003) initiated several subsequent genetic association studies, using a candidate gene approach with either one SNP or a haplotype (Table 1). Six of these studies, genotyping either ABCB1 3435 or the common haplotype combination, ABCB1 3435C>T-2677G>T-1236C>T, confirmed the association between the 3435 SNP or the three-SNP haplotype (containing the 3435 SNP) and AED-resistant epilepsy. However, in two studies in non-Caucasian subjects, the association was in the reverse direction compared to studies in Caucasian subjects in that patients with drug-resistant epilepsy were more likely to have the TT genotype compared with those with drug-responsive epilepsy (Seo et al., 2006; Kwan et al., 2007), highlighting the complexity of the possible role of ABCB1 polymorphisms in AED response in different ethnic populations.
|Polymorphism||Number of epilepsy patients||Type of||Association of|
|Authors||Origin||in MDR1||Responders||Nonresponders||epilepsy/AEDs||polymorphism with resistance|
|Siddiqui et al., 2003||UK||3435C>T||115||200||Various/various||Yes|
|Soranzo et al., 2004||UK||3435C>T||135||286||Various/various||Yes|
|IVS 26 + 80T>C||Yes|
|Zimprich et al., 2004||Austria||3-SNP haplotypea||—||210||TLE/various||Yes (within the resistant group)|
|Hung et al., 2005||Taiwan||3-SNP haplotypea||223||108||Various/various||Yes|
|Seo et al., 2006||Japan||3-SNP haplotypea||84||126||Various/CBZ||Yes (but in reverse direction)|
|Kwan et al., 2007||China (Hong||3435C>T||297||221||Various/various||Yes (but in reverse direction)|
|Ebid et al., 2007||Egypt||3435C>T||37||63||Various/PHT||Yes|
|Hung et al., 2007||Taiwan||3435C>T and 2677G>T||213||114||Various/various||Yes|
|Tan et al., 2004||Australia||3435C>T||208||401||Various/various||No|
|Sills et al., 2005||Scotland||3435C>T||170||230||Various/various||No|
|Kim et al., 2006a||Korea||3435C>T||108||63||Various/various||No|
|Kim et al., 2006b||Korea||3-SNP haplotypea||108||99||Various/various||No|
|Leschziner et al., 2006||UK||3435C>T||503||Various/various||No|
|3-SNP haplotypea||(prospective response evaluation)||No|
|Ozgon et al., 2007||Turkey||3435C>T||53||44||Various/CBZ||No|
|Shahwan et al., 2007||Ireland||3435C>T and other SNPs||242||198||Various/various||No|
|and SNP haplotypes|
In contrast to studies showing an association of ABCB1 polymorphisms and AED resistance, six other retrospective association studies and one prospective cohort study in either Caucasian or non-Caucasian subjects did not identify any significant association between ABCB1 polymorphisms and response to AEDs (Table 1). However, only one of these negative studies (Tan et al., 2004) was an exact replication of the first report by Siddiqui et al. (2003), so that the authors of the first report argued that phenotypic differences between studies may explain the failure to robustly identify a role for Pgp from such genetic association studies (Sisodiya et al., 2005; Sisodiya & Goldstein, 2007; Tate & Sisodiya, 2007). In addition to inconsistent phenotype definition (i.e., definition of resistance versus response to AEDs) among studies, there are various other potential explanations for the discordant results, including inadequate power, potential confounding by comorbidity and comedication, population substructure, genotyping error, overlap in substrate specificity between Pgp and other drug efflux transporters, and inclusion of AEDs that might not be Pgp substrates (Leschziner et al., 2007). Twelve of the 15 genetic association studies summarized in Table 1 included patients on treatment with various AEDs, for several of which it is either not yet known whether they are transported by Pgp or which do not seem to be transported by Pgp (e.g., VPA) (Baltes et al., 2007). Only three studies (Seo et al., 2006, Ebid et al., 2007; Ozgon et al., 2007) included patients on a single AED, either PHT or CBZ. For CBZ, data on transport by Pgp are at best equivocal (Owen et al., 2001; Potschka et al., 2001; Rizzi et al., 2002), whereas there is ample evidence that PHT is transported by Pgp (Löscher & Potschka, 2005a), which could explain the recent finding of Ebid et al. (2007) that the CC genotype of ABCB1 3435 is significantly associated with PHT resistance in patients with epilepsy (Fig. 2C). It should be noted that the results of the Ebid et al. (2007) study differed substantially from other similar studies, in that a highly significant association between 3435CC and resistance to PHT was found despite a smaller sample size (100 patients only compared with >300 in most other studies). A number of concerns exist about the clarity of the report and the study design. The original report did not make it clear whether PHT was used as monotherapy, and “response” was evaluated over a 3-month period only. Patients were already taking PHT at enrollment, but the baseline seizure frequency was unknown. The underlying epilepsy syndromes, which strongly influence outcome, were unknown and not accounted for in the analysis.
All except one of the studies on ABCB1 polymorphisms and AED resistance summarized in Table 1 were retrospective association studies with the inherent potential biases of a retrospective case-control design. Only in one study the association of the ABCB1 gene with drug withdrawal due to poor seizure control or adverse effects was determined prospectively in 503 patients with mostly new-onset epilepsy (Leschziner et al., 2006). Although all patients were followed prospectively to determine the response to medication, ABCB1 3435C>T polymorphism and three-SNP haplotype, plus a comprehensive set of tag SNPs across ABCB1 and adjacent ABCB4, were genotyped retrospectively (i.e., after outcomes were known). Randomly selected genome-wide HapMap SNPs (n = 129) were genotyped in all patients for genomic control. There was no association of the ABCB1 3435C>T polymorphism, the three-SNP haplotype, or any gene-wide tag SNP with time to first seizure after starting drug therapy, time to 12-month remission, or time to drug withdrawal due to unacceptable side-effects or to lack of seizure control (Leschziner et al., 2006). The limitations of this important first prospective study include a wide heterogeneity of the study population and the drug treatment. The study population was taking a number of different AEDs, none accounting for more than 25%. Topiramate (TPM) and lamotrigine (LTG) were the most commonly prescribed AEDs, followed by CBZ, GBP, OXC, and VPA. Thus, one explanation why this study did not find the reported association between ABCB1 genotype and drug resistence is that Pgp may only be of relevance in the context of some AEDs and not others. The study population was also heterogeneous in terms of their treatment, 80% of patients were previously untreated, 17% had monotherapy with suboptimal seizure control, and 3% had recent seizures after remission. Thus it is difficult to compare the conflicting results of studies in chronic drug-resistant epilepsy with the results in mostly newly treated epilepsy.
For directly addressing whether ABCB1 polymorphisms affect drug distribution into the human brain, positron emission tomography (PET) with the Pgp substrate 11C-verapamil was used. Healthy volunteers differing in ABCB1 haplotypes did not differ in brain distribution of 11C-verapamil (Brunner et al., 2005; Takano et al., 2006). However, verapamil is not an ideal PET ligand to study functional consequences of overexpression of Pgp at the BBB, because it hardly crosses the BBB in humans at constitutive BBB expression of Pgp (Sasongko et al., 2005). Using single photon emission computed tomography (SPECT) with the Pgp substrate [99mTc]-sestamibi, Jensen et al. (2006) recently reported in an abstract reduced brain uptake of [99mTc]-sestamibi in epilepsy patients with the C3435C and G2677G ABCB1 genotypes, which was correlated with AED resistance. Although the latter study may indicate that the 3535C>T SNP is associated with higher expression of Pgp in the brain, direct evidence for such an association is missing as yet. To our knowledge, there are only two studies that determined expression of Pgp in brain tissue of patients genotyped for the C3435T polymorphism (Vogelgesang et al., 2002, 2004). In one study, brain tissue samples were obtained at autopsy from 243 nondemented subjects for determination of vascular Pgp expression in the medial temporal lobe. The highest Pgp expression was determined in the 3435CC genotype, but the difference to the other 3435 genotypes was not statistically significant (Vogelgesang et al., 2002). In the second study, brain specimens were obtained from 14 patients with dysembryoplastic neuroepithelial tumors (DNT) undergoing temporal lobectomy because of intractable epilepsy. In all patients, the expression of Pgp was significantly higher in DNT compared with peritumoral tissue. The by far highest Pgp expression was found in one patient with the 3435CC genotype, who exhibited three times higher Pgp expression than the 10 CT and 3 TT carriers (Vogelgesang et al., 2004). However, the small sample size did not allow concluding whether there was a significant correlation between Pgp expression and C3435T genotype in patients with epilepsy.
The most convincing evidence for an association between ABCB1 genotype and Pgp expression, function and therapeutic drug response was recently reported by Basic et al. (2008), who studied in a prospective fashion whether the C3435T polymorphism affects the brain uptake of PB in patients with generalized epilepsy. Genotyping was performed in 60 patients with idiopathic generalized epilepsy with tonic–clonic seizures on PB monotherapy. PB analysis in plasma and cerebrospinal fluid (CSF) demonstrated that, while the C3435T polymorphism did not affect plasma levels of PB (Fig. 3A), the CC genotype of 3435 was associated with significantly lower PB levels in CSF (Fig. 3B) and a significantly lower CSF/plasma ratio (Fig. 3C) than the CT or TT genotypes (Basic et al., 2008). Furthermore, patients with the CC genotype had a significantly higher seizure frequency than patients with the CT or TT genotype (Fig. 3D). The daily doses of PB did not differ significantly between genotypes. Furthermore, in the same group of patients, the G2677T/A polymorphism in the ABCB1 gene had no effect of CSF levels of PB. Although valuable, the study by Basic et al. (2008) has its limitations. Important clinical data are missing, for example if the patients had other seizure types such as absence or myoclonic seizures in addition to the reported generalized tonic seizures, which would be common for idiopathic generalized epilepsies. Another concern is that the patients were treated with PB, which is not recommended for first-line treatment of idiopathic generalized epilepsies mainly because of its sedative side effects and poor efficacy against absence seizures (Benbadis, 2005). The study of Basic et al. (2008) seems to confirm the association between the CC genotype at ABCB1 3435 and AED resistance described by Siddiqui et al. (2003) and several other groups, although the effect size may be small. However, causality has not been proven in any of these studies, but all reported findings remain associations.
Furthermore, several of the many association studies on ABCB1 in epilepsy not only analyzed drug responsive and nonresponsive epilepsy patients, they also analyzed ABCB1 genotypes in control subjects without epilepsy and found that in fact ABCB1 genotypes were associated with the disease per se rather than specifically with drug responsiveness. This suggests that the reported association studies on this gene may be looking simply at the random segregation of epilepsy patients into the two drug response groups such that in half of the studies an association was found and in the other half of the studies the results were negative.
Almost all previous studies on gene variation that might affect AED distribution have dealt with polymorphisms in the ABCB1 gene that encodes Pgp. However, there are polymorphisms in other drug efflux transporters, such as members of the MRP family that may affect the distribution of AEDs (Löscher & Potschka, 2005a) and need further investigation. One of these transporters, RLIP76, has been suggested to be involved in AED resistance by transporting both CBZ and PHT at the BBB (Awasthi et al., 2005), but a recent genetic analysis of RLIP76 genotypic and haplotypic frequencies in 783 patients with epilepsy and 359 healthy controls showed no significant differences for genotypic frequencies between drug-resistant and drug-responsive patients (Soranzo et al., 2007).
In conclusion, the role of genetic variation in drug efflux transporter genes for AED distribution and efficacy remains uncertain at present. The recent prospective study of Basic et al. (2008) showing a significant and clinically relevant effect of the ABCB1 C3435T polymorphism on CSF levels of PB in patients with epilepsy (Fig. 3) indicates that the study design is of crucial importance for any definite conclusions. However, even though certain polymorphisms, such as the 3435C>T in ABCB1, may play a role in the phenomenon of refractory epilepsy, this cannot explain the fact that by definition such patients are refractory to multiple AEDs, which are generally chemically and pharmacologically diverse. Not all AEDs have a common element of pharmacology (e.g., not all AEDs are substrates for Pgp, and not all AEDs have the same therapeutic target), so that a single gene variant cannot affect responsiveness to multiple and diverse drugs. Rather, as a complex trait, drug responsiveness is expected to be determined in part by the effects of multiple genes acting both independently and in interaction with each other, so that in the end, individual responsiveness will be determined by the effects of many variations, including genes involved in drug distribution and genes encoding drug targets.
In summary, with so many methodological problems of previous studies and inconsistent results, the evidence of association between ABCB1 polymorphisms and AED response is at best conflicting and does not support a major role for the C3435T polymorphism. However, more recent genetic association studies on AEDs known to be transported by Pgp are encouraging (Ebid et al., 2007; Basic et al., 2008), but these studies need to be replicated. Even if these data can be replicated, it should be noted that, as discussed above, association is not causation, so that studies that directly address whether ABCB1 polymorphisms significantly alter brain uptake of AEDs in patients with refractory epilepsy by PET imaging or analysis of brain tissue are needed.
Once an AED has successfully passed the BBB, its next step is to reach its molecular target in the brain. Although presently available AEDs appear to be directed against a relatively small number of targets—mainly ion channels or other components of the synaptic machinery—matters are complicated by the fact that many AEDs seem to work through multiple mechanisms, some of which are still unresolved (Rogawski & Löscher, 2004). Recent efforts have revealed interesting genetic polymorphisms in some of these AED targets. However, it has to be stressed that, at present, we still know very little about the functionality of such polymorphisms and to what extent such variations have a clinically relevant impact on AED treatment.
So far the most interesting data have been accrued for voltage-dependent Na+ channels, which are the primary targets for a number of important AEDs such as CBZ, PHT, or LTG (Rogawski & Löscher, 2004). Early observations had indicated that mutations in sodium channels may affect the clinical response to AEDs. The Dravet syndrome, which can be caused by de novo truncation mutations in the SCN1A sodium channel gene, is characterized by a marked aggravation of seizures upon treatment with LTG (Guerrini et al., 1998). This was explained by the preferential expression of SCN1A on inhibitory interneurons and the further reduction of this inhibitory component by Na+ channel blocking agents such as LTG (Yu et al., 2006). Recently, genetic variations in sodium channels have received further attention because of suggestions that Na+ channels might exhibit different electrophysiological properties in patients with pharmacoresistant epilepsy as compared to responsive patients. This idea originated from a study in which sodium currents were recorded in hippocampal neurons collected from 10 surgical specimens of patients with AED-resistant TLE and Ammon's horn sclerosis (AHS) (Remy et al., 2003). Recordings from three AED-responsive patients with partial epilepsy but without AHS were taken as controls. The authors then investigated the use-dependent block of CBZ on Na+ channels, which is considered to be the main mechanism responsible for the antiepileptic action of this drug. In neurons from AHS-patients who were preoperatively shown to be resistant to CBZ, the use-dependent block of CBZ on voltage dependent sodium channels was lost and seizure activity elicited in vitro was resistant to CBZ. In the three non-AHS control cases, who were considered CBZ-responsive, the use-dependent block of CBZ was either still detectable (one case) or the in vitro seizure activity was responsive to CBZ (two cases). The main conclusion of this study—that these functional differences were the cause of the pharmacoresistance—was, however, questioned by many other researchers given the (inevitable) limitations of the few control samples. (The controls exhibited a different pathology, and the clinical CBZ responsiveness was not adequately established as one patient received no CBZ at all and two other patients only for 2 to 3 months).
Still, even if the causal connection between these functional differences in Na+ channels and the response to AED treatment remains as yet unsolved, the mechanism underlying the loss (or lack) of the use-dependent block appears very interesting. In particular, the question arose as to whether genetic factors might influence this phenomenon, by, for instance, determining the subunit composition or the structure of voltage-dependent Na+ channels (Remy & Beck, 2006). The fact that functional properties of ion channels can be dynamically regulated via genetic mechanisms is actually well established. The best known example is probably the evolutionary well-conserved alternative splicing of exons coding for voltage sensors of ion channels (Plummer & Meisler, 1999). The voltage sensor regions determine the gating properties of the channels and, in the case of sodium channels, are thought to influence the interaction with classical Na+ channel AEDs such as CBZ and PHT. In insects it has been shown that such alternatively spliced Na+ channels can have strikingly different pharmacological properties by exhibiting markedly different sensitivities to pyrethroid insecticides (Tan et al., 2002).
Given these data, recent studies investigated alternative splicing processes in humans, in the SCN1A gene, which is one of the Na+ channel genes of the brain. In particular, the question was addressed whether the alternative splicing affecting the voltage sensor regions could be influenced by genetic polymorphisms and if there is a relationship to pharmacoresistance in epilepsy. In the SCN1A gene, exon 5 codes for one of the four voltage sensors of the channel, the domain I-S4 voltage sensor. Two alternatively spliced versions of this exon are present in the genomic DNA, a “neonatal” and an “adult” copy, which differ by three amino acids in the final product (Tate et al., 2005). Normally both exons are coexpressed in the adult brain. The neonatal exon can be drastically upregulated under several circumstances which also include seizures according to some but not all studies (Gastaldi et al., 1997; Aronica et al., 2001; Tate et al., 2005; Heinzen et al., 2007).
The focus of two recent studies was a functional SNP (rs3812718) in the intron adjacent to exon 5 (Fig, 4). This SNP lies within a 5′ slice donor site, a consensus sequence important for the splicing process (Tate et al., 2005; Heinzen et al., 2007). Apparently, this SNP determines whether the neonatal or the adult version of exon 5 is incorporated into the final channel. The ancestral G allele allows both exons to be expressed, whereas the “mutant” A allele almost abolishes the expression of the neonatal exon by disrupting the consensus sequence. The fact that the expression of these two alternatively spliced products is tightly controlled by the regulatory protein Nova-2 points to the existence of some functionality (Heinzen et al., 2007). However, at present we do not have any further information on how these alternatively spliced channels might differ from each other, as electrophysiological or pharmacological data are still lacking.
Given the probable functionality, this SCN1A-SNP was further investigated in a large pharmacogenetic study involving 425 patients from the UK (Tate et al., 2005). The maximal doses of two AEDs (CBZ and PHT), prescribed during a routine clinical setting, were retrospectively associated with the genotypes. Although the retrospective design prevented the authors from establishing that the maximal doses reported were actually needed for seizure control, the presence of the splice site interrupting (“mutant”) A alleles was linearly correlated with a higher dose of either AED. AA homozygote patients were on average prescribed higher doses of CBZ or PHT than heterozygotes, and heterozygotes showed higher doses than wild-type GG homozygotes. A further drawback of this study was that no information was given how many patients were seizure-free or had side effects at the maximal doses reported.
A second, smaller study by the same researchers in 71 Chinese patients failed to provide a similar association with prescribed PHT maintenance dosages (Tate et al., 2006). However in the same patients there was a marginally significant association with PHT serum levels. These results were therefore considered by the authors as a tentative confirmation of their initial findings, although in a strict statistical sense, the study did not provide a positive replication. As a further note of caution, it has to be added that a third association study has failed to detect similar results (Zimprich et al., 2008). In this study, the maintenance dosages of CBZ were analyzed in 369 patients with mainly pharmacoresistant focal epilepsies and did not correlate with the genotype. Further replication studies are still absent. And finally it has to be noted, that the magnitude of the observed effect in the initial study was on average modest—230 mg difference between the two homozygote genotypes for CBZ and 47 mg for PHT with a large overlapping range. The clinical relevance of this polymorphism in terms of its ability to predict an individuals' dosage requirement is therefore still doubtful.
However, it has to be kept in mind that even truly functional polymorphisms in single AED targets might be very hard to catch in clinical studies if the AED under investigation really works through multiple mechanisms. In the case of CBZ, several additional targets have been demonstrated, among them acetylcholine receptors, which also underlie genetic variations. Missense mutations in α4 subunits, for example, have been linked to a rare form of epilepsy, dominant nocturnal frontal lobe epilepsy (ADNFLE). Such mutated α4β2 acetylcholine receptor channels—when reconstituted in Xenopus oocytes—display a three-fold higher sensitivity to CBZ than wild-type channels (Picard et al., 1999). This was taken as a possible explanation why patients with ADNFLE respond better to CBZ than other AEDs (Picard et al., 1999; Bertrand et al., 2002). Such complementary modes of AED-actions might differ between individuals depending on their genetic background. Obviously, such a constellation would make it much more difficult to detect variations in individual AED targets and would necessitate larger pharmacogenetic studies investigating the effects of several AED-target polymorphisms at the same time.
Other AED targets, where functional polymorphisms could possibly influence the clinical treatment response, are GABAA receptors. On the one hand, GABAA receptors might themselves display pathogenic mutations or variations that determine the type of AED to be used. Animal models have taught us that the disruption of GABAAβ3 subunits may lead to abnormally synchronized thalamocortical oscillations, which are considered the basis for absence seizures. Ethosuximide, a blocker of T-type calcium channels, has been shown to effectively dampen these pathological oscillations and is therefore a drug of choice for absence seizures (DeLorey & Olsen, 1999; Handforth et al., 2005). However, at present, the decision when to treat with ethosuximide is solely based on clinical experience and not on any genetic data.
On the other hand, GABAA receptors also constitute the targets for benzodiazepines and other AEDs (Rogawski & Löscher, 2004). In several studies it could be shown that the pharmacological properties of the final pentameric GABAA receptors depend critically on the combination of subunits of which there are more than 20 to choose from (Brooks-Kayal et al., 1998). In dentate gyrus granule cells of chronically epileptic rats a downregulation of α1 subunits and a concomitant upregulation of α4 subunits has been observed which is paralleled by a decreased sensitivity to the GABAA receptor agonist zolpidem (Brooks-Kayal et al., 1998). In human samples the subunit composition of GABA receptors has also been shown to differ markedly between TLE and control tissue (Loup et al., 2000). The differential expression of GABAA receptor subunits is very complex being dynamically regulated by the interaction of a multitude of transcription factors with an even wider range of cis-regulatory DNA elements (Steiger & Russek, 2004). Functional polymorphisms at expression-regulating DNA sites are known to be abundant and are thought to be main factors determining interindividual diversity in general (Wray, 2007). To what extent cis-regulatory polymorphisms in GABAergic genes, like the recently discovered one for the GABAA receptor β3 subunit, are pharmacogenetically relevant remains to be determined (Urak et al., 2006).
At present, we still know very little about the functionality of polymorphisms of drug targets and to what extent such variations have a clinically relevant impact on AED treatment.
Drug metabolism and elimination
Elimination of drugs including AEDs is accomplished by the hepatic (metabolism) and/or renal (excretion) route (Fig. 1). In general, drug metabolism represents the prominent pathway, both in qualitative and quantitative terms, which comprises so-called phase I (e.g., oxidative reactions catalyzed by various cytochrome P-450 enzymes) and phase II (e.g., conjugations like glucuronidation) reactions. Within the most important cytochrome P(CYP)-450 superfamily some polymorphic enzymes have been detected such as CYP2C9 or CYP2C19 (Ingelman-Sundberg, 2004; Gardiner & Begg, 2005; Wilkinson, 2005), which contribute partly to the metabolism of a few AEDs. However, many old and especially new AEDs are eliminated independently of polymorphic drug metabolizing enzymes (see Table 2). In this respect, it is important to note that CYP3A4, which is involved in the metabolism of several AEDs (Table 2), is not polymorphically expressed to any relevant extent. Diazepam and PHT represent good examples for a genotype-dependent elimination as CYP2C19 (for both drugs) and CYP2C9 (only PHT) are relevant enzymes involved in their metabolism (Klotz, 2007).
|AED||t1/2, h||Elimination pattern (involved enzymes)|
|Carbamazepine||12–24||CYP3A4; mEH1 for CBZ-10,11-epoxide|
|Clonazepam||19–60||CYP3A4 (?); acetylation, reduction|
|Ethosuximide||36–60||CYP3A4 (?); 10%–20% renal|
|Felbamate||14–23||40%–60% renal; hydroxylation, glucuronidation|
|Gabapentin||5–7||Renal elimination (including tubular secretion by OCTN1)|
|Lamotrigine||24–36||Glucuronidation; 8% renal|
|Levetiracetam||6–8||66% renal; nonhepatic hydrolysis (in blood)|
|Oxcarbazepine||1–2||Reduction to active MHDa, which is glucuronidated (t1/2: 8–12 h)|
|Phenobarbital||72–96||CYP2C19 (p-OH), glucuronidation; 25% renal|
|Phenytoin||20–50||CYP2C9 and 2C19|
|Pregabalin||5–7||98% renal elimination (depends on serum creatinine)|
|Primidone||10–20||Partly to PB (see above) and PEMAb (t1/2: 24–48 h)|
|Tiagabine||4–13||CYP3A4, 25% renal|
|Topiramate||20–30||60%–80% renal; oxidation, hydrolysis, glucuronidation|
|Valproic acid||8–16||CYP2C9; glucuronidation; β- and ω-oxidation|
|Vigabatrin||5–10||60%–80% renal elimination|
|Zonisamide||50–70||CYP3A4, N-acetylation (15% by NAT2c), glucuronidation; 30% renal|
|105 (in erythrocytes)|
In one major pathway, diazepam (about 60% of the dose) is demethylated primarily by CYP2C19 (CYP3A4 is also involved) to the active N-desmethyldiazepam (DD; nordiazepam), which subsequently is hydroxylated by CYP2C19 to the active oxazepam. In a second pathway, diazepam is hydroxylated by CYP3A4 to the active temazepam. In a panel study, the pharmacokinetics of diazepam and DD were assessed following a single oral dose of 10 mg diazepam and DD in 13 extensive metabolizers (EM) and 3 poor metabolizers (PM) of CYP2C19 (also called mephenytoin hydroxylase). For both benzodiazepines there was a 50% reduction in the plasma clearance and a two-fold prolongation of the elimination half-life between PM and EM (Bertilsson et al., 1989, 1990). As benzodiazepines possess a wide margin of safety, it remains questionable whether such a moderate difference in pharmacokinetics is of clinical relevance (Desta et al., 2002). In a recent study in Japanese patients, recovery from general anesthesia with sevoflurane including a preanesthetic intravenous (IV) dose of diazepam (0.1 mg/kg) was differentiated according to the CYP2C19 phenotype (Inomata et al., 2005). In addition, plasma concentrations of diazepam were compared by using area under the concentration/time curves (AUC). In PMs (n = 14), AUC-values were 48% higher than in EMs (n = 20), which resulted in a longer recovery time (median 18 min) in PMs if compared to EMs (10 min) (Inomata et al., 2005).
Recent evidence suggests that CYP2C19 is partly (approximately 40%) involved in the p-hydroxylation of PB, while about 60% seem to be catalyzed by other enzymes. Furthermore, only 7.7% to 12.5% of a dose is excreted as p-OH-PB and other elimination routes are much more important for the overall elimination of PB (Desta et al., 2002). Therefore it can be concluded that the phenotype/genotype of CYP2C19 will not have a significant impact on the clinical outcome of this AED, even if according to a pharmacokinetic population study in Japanese patients with epilepsy PMs had a 19% lower clearance (CL) than EMs (Mamiya et al., 2000). This effect was not confirmed in a subsequent study as AUC and CL of PB were not different between 5 EMs and 5 PMs of CYP2C19 (Hadama et al., 2001).
The complex metabolism of PHT includes saturable (nonlinear) pathways. The major and rate-limiting step is stereoselective p-hydroxylation to 4′-OH-phenyl-5-phenylhydantoin (HPPH) by CYP2C9, but CYP2C19 is also involved in the formation of HPPH (its contribution appears to increase with increasing PHT concentration) and secondary metabolites (3′-HPPH; 3′, 4′-diHPPH), which is reasonable regarding the close structural and metabolic similarity with the typical CYP2C19 substrate mephenytoin (Bajpai et al., 1996; Mamija et al., 1998; Desta et al., 2002).
In 101 unrelated genotyped (CYP2C9) Turkish volunteers, the plasma concentrations of PHT and HPPH were measured 12 h after a single oral dose of 300 mg (Aynacioglu et al., 1999). The metabolic ratio (HPPH/PHT) was significantly lower in all mutant genotypes (0.14–0.26) if compared with the wild-type (CYP2C9*1/1; 0.43); likewise, plasma levels of PHT were higher (up to 40%) in the subjects with allele variants. The authors concluded that 31% of total variability in PHT levels could be explained by the CYP2C9 genotype and that the metabolic ratio could be a sensitive indicator for the individual CYP2C9 activity (Aynacioglu et al., 1999). In 27 healthy subjects from south India this metabolic ratio varied widely but did not differ significantly between the various genotypes of CYP2C9 and CYP2C19 (Rosemary et al., 2006). The different outcome of both studies could be due to the variable ethnic background and the relative low number of subjects involved in the Indian study.
In a recent retrospective analysis of 269 epileptic patients (age range at start of treatment 1–72 years) from the UK discussed above, the maximal dose of PHT was differentiated according to the CYP2C9 genotype of the patients (Tate et al., 2005). A relationship was found only for the numbers of the *3 allele and the used dosages. Carriers of one *3 allele (14.5%) or of two *3 alleles (0.4%) apparently needed a 13% and 30% lower dosage, respectively. Overall, the polymorphisms could explain only 6.5% of the total variation (Tate et al., 2005).
According to genotyping results for CYP2C9 and CYP2C19, 169 epileptic patients from Taiwan receiving PHT (55% of patients were also on other AEDs) were retrospectively divided into five groups (Hung et al., 2004). From the measured plasma concentrations of PHT the pharmacokinetic parameters (Km, Vmax, CLintrinsic) were calculated by population analysis (see Table 3). A clinically relevant decrease in Vmax and CLintrinsic was observed only when the patients were carriers of mutated alleles for both CYPs (e.g., hetEM for CYP2C9 and C19 or hetEM for CYP2C9 and PM for C19), a constellation that is very rare in Caucasian patients (Bertilsson et al., 1995;Desta et al., 2002; Andersson et al., 2005). Based on the calculated population kinetics, Hung et al. (2004) recommended reducing the normal dosage of PHT (5–7 mg/kg/day) to 2–4 mg/kg/day for these two subgroups. Concerning ADRs such as cutaneous drug reactions or gingival hyperplasia, it is not yet clear whether there is an association with CYP2C9 polymorphisms (Lee et al., 2004; Soga et al., 2004; Rosemary et al., 2006).
|EM of both (n = 47)||EM9/hetEM19 (n = 88)||EM9/PM19 (n = 16)||hetEM9/hetEM19 (n = 17)||hetEM9/PM19 (n = 1)|
|Dosage range [mg/kg/d]||5.5–7||5–7||5–6||3–4||2–3|
The inducer CBZ is primarily metabolized by CYP3A4 to its active CBZ-10,11-epoxide, which subsequently is transformed by microsomal epoxide hydrolase (mEH) to the inactive CBZ-10,11-diol, which finally is excreted into the urine in free and conjugated forms (Tomson et al., 1983). As some of the adverse effects of CBZ can be attributed to its epoxide, the enzyme mEH could be of importance, especially as recently 29 SNPs of mEH have been identified in the corresponding gene of 96 Japanese epileptic patients (Nakajima et al., 2005). It is possible that differences in the plasma levels of CBZ, CBZ-10,11-epoxide, or the metabolic ratios can be attributed to the observed genetic variation. In that respect, it may be of interest that the clinical practice of adding VPA, which is an inhibitor of mEH (Bernus et al., 1997), to CBZ may contribute significantly to CNS side effects of CBZ when both AEDs are given together. However, it is not known if the observed genetic variation predisposes patients to have more side effects from the combination of CBZ and VPA.
So far there are no treatment guidelines taking genotypes of CYP2C9 or CYP2C19 into account. This is not too surprising when considering the elimination of AEDs, as only the PHT combined polymorphisms of CYP2C9/19 (which are very rare in Caucasians) have some clinical impact.
Genetic variation involving genotypes of drug-metabolizing such as CYP2C9 or CYP2C19 has limited clinical impact on the treatment of epilepsy, because the elimination of most AEDs is not affected by polymorphic enzymes in the liver.
Some AEDs, especially the newer ones, are partly eliminated by the renal route (see Table 2), which comprises glomerular filtration, tubular secretion, and reabsorption. To our knowledge, with the exception of GBP, there are no published data on whether polymorphic transporter proteins in the kidney affect the active secretory processes involved in renal excretion of AEDs. GBP is primarily cleared by glomerular filtration. In addition, renal secretion by the organic cation transporter OCTN1 expressed in the apical membrane of the kidney might contribute to its renal clearance. A genetic variant of OCTN1, L503F, is quite common in individuals of European descent (allele frequency approximately 42%). In such subjects renal clearance averaged 110 ml/min and was lower (p = 0.045) than in the wild-type (141 ml/min) indicating some genetic variation in active drug secretion (Urban et al., 2008).
The recent data on GBP provide first clinical evidence of the role of genetic variation in renal drug transporters in active AED secretion in vivo.
Genetic Variation That May Affect Tolerability and Safety of Antiepileptic Drugs
Now that we have discussed the influence of gene variation on clinical efficacy of AEDs following the path of an AED ranging from absorption to excretion, this section summarizes the impact of these factors on treatment-limiting, dose-related, and idiosyncratic adverse reactions to AEDs.
Dose-related adverse reactions
Genetic variation associated with a decreased capacity to metabolize AEDs has been reported to lead to adverse reactions through AED accumulation of parent drug or metabolites in a limited number of patients taking PHT, mephenytoin, and CBZ. In one female African-American treated with 100 mg PHT three times daily, CNS toxicity was observed 13 days after starting treatment. The plasma concentration was 49.5 μg/ml, and AUC was 5.8 times that of an extensive metabolizer. It was found that the patient was homozygous for a new CYP2C9*6 allele, which frequency was estimated to be 0.6% in African-Americans, but 0% in 172 Caucasians (Kidd et al., 2001). A phenytoin intoxication has been reported in a 31-year-old woman who was treated with oral phenytoin (100 mg tid) for 10 days to prevent posttraumatic seizures (Brandolese et al., 2001). The elimination half-life of phenytoin was 103 hours, which is about 5 times longer than the mean value generally quoted (22 hours). Genotyping revealed that the patient was homozygous for the CYP2C9*3 allele (CYP2C9*3/*3) and heterozygous for the CYP2C19*2 allele (CYP2C19*1/*2). In view of the markedly reduced metabolic activity of CYP2C*3 in comparison with the wild-type enzyme (about one-fifth) and of the minor role of CYP2C19 in phenytoin metabolism, the CYP2C9*3 mutation was considered responsible for the drug overdose (Brandolese et al. 2001). However, overall, the clinical impact of genetic variation in AED metabolism is likely to be low. This view is based on several considerations: (1) very few patients have been shown to be affected, in the range of <1%; (2) clinical monitoring will quickly detect side effects, and the dose is routinely lowered or, if the dose is low, another AED is given, and (3) several modern AEDs that are increasingly used are not metabolized hepatically (Table 2), which means that genetic variation of hepatic enzymes is of no concern. Nevertheless, it is useful to know that genetic variation may play a role in a patient developing side effects of hepatically metabolized AEDs, even if it seems to be rare.
Idiosyncratic adverse reactions to AEDs
Genetic influences may play a pathogenic role in idiosyncratic adverse reactions of AEDs. The occurrence of similar idiosyncratic reactions to AEDs in twins, siblings, and in families suggests a genetically determined predisposition (Shear & Spielberg, 1988, Edwards et al., 1999). Although pharmacogenetics are suspected to play a role in many idiosyncratic side effects, such as neural tube defects in women using VPA or vigabatrin-associated concentric visual field defects, which will be discussed below, immune-mediated hypersensivity reactions to AEDs have received the most attention.
Immune-mediated hypersensivity reactions
AEDs are one of the most common causes of cutaneous adverse drug reactions (cADRs). The manifestation of cADRs ranges from a mild maculopapular exanthema (MPE) to life-threatening severe cutaneous reaction (SCR), which includes Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), and drug hypersensitivity syndrome (HSS). The incidence of AED-induced cADRs varies from drug to drug. Overall, isolated rash related to AEDs occurs in up to 10% of patients (Marson et al., 2007a), while the incidence of SCR is estimated to be 1:10,000 exposures. More than 90% of SCR occurs in the first 2 months of AED use (Zaccara et al., 2007). AEDs associated with increased risk of SCR include CBZ, PB, PHT, and LTG (Zaccara et al., 2007). cADRs represent a significant burden on the health care system, and SCR mortality reaches up to 30% (Svensson et al., 2001). Identification of genetic polymorphisms predisposing to development of AED-induced SCR offers the possibility of avoiding these high-risk drugs in genetically susceptible individuals (Krauss, 2006, Zaccara et al., 2007). Inflammatory mediators, such as human leucocyte antigen (HLA) genes and tumor necrosis factor (TNF) are important in cutaneous and systemic adverse reactions to AEDs (Krauss, 2006).
Investigations on genes that control immune-inflammatory responses have shown interesting results that are relevant for clinical practice. A number of recent studies suggest a strong association between HLA-B*1502 and CBZ-induced SJS in subjects of Chinese/Asian ethnicity (Chung et al., 2004; Hung et al., 2006; Lonjou et al., 2006; Man et al., 2007). Chung and coworkers (2004) genotyped 44 Han Chinese patients with CBZ-induced SJS, 101 CBZ-tolerant patients, and 93 healthy controls without a history of CBZ use. HLA-B*1502 allele was present in 100% of CBZ-SJS patients but in only 3% of CBZ-tolerant patients and in 9% of the control population. In a follow-up study with an overlapping cohort, HLA-B*1502 was found to be strongly associated with CBZ-SJS/TEN, but not with MPE or HSS (Hung et al., 2006). The association between HLA-B*1502 and cADRs induced by CBZ as well as by other AEDs was further examined in 24 Hong Kong Han Chinese subjects. They were matched with 48 AED-tolerant controls. HLA-B*1502 was associated with SCR induced by AEDs, which included CBZ, PHT, and LTG [p = 0.001, odds ratio (OR) = 17.6], but was not associated with MPE (Man et al., 2007). It is noteworthy to mention that in the Man et al. (2007) study, consistent with the Chung (2004) study, HLA-B*1502 was absent in patients with HSS, but was present in all the patients with SJS/TEN. So that when confining the analysis to patients with SJS/TEN alone, the OR of association with HLA-B*1502 was much higher [OR 71.9, 95% confidence interval (CI): 3.7–1416].
The role of ethnicity in these reactions is emphasized by recent data confirming that an association between CBZ-induced SJS and the HLA-B*1502 allele is present in Asians (Lonjou et al., 2006), but does not appear to occur in Caucasians (Alfirevic et al., 2006a; Lonjou et al., 2006). Overall, these data suggest that genetic susceptibility may account for the much higher incidence of CBZ-induced SJS in Chinese compared with Caucasians.
The fact that dangerous or even fatal skin reactions (SJS and TEN) to CBZ are significantly more common in Asian patients with a particular HLA allele, HLA-B*1502, has important implications for clinical practice. This allele occurs almost exclusively in patients from and with ancestry across broad areas of Asia, including South Asian Indians. Genetic tests for HLA-B*1502 are already used to check for compatibility before tissue transplants. Patients with ancestry from areas in which HLA-B*1502 is present should be screened for the HLA-B*1502 allele before starting treatment with CBZ. According to an alert from the U.S. Food and Drug Administration (FDA, 2007a), CBZ should not be started if the patient tests positive unless the expected benefit clearly outweighs the increased risk of serious skin reactions. Patients who have been taking CBZ for more than a few months without developing skin reactions are at low risk of these events ever developing from CBZ. This is true for patients of any ethnicity or genotype, including patients positive for HLA-B*1502. This new safety information will be reflected in updated product labeling (FDA ALERT, 2007a). Patients who test positive for HLA-B*1502 may be at increased risk of SJS/TEN from other AEDs that have been associated with SJS/TEN. Therefore, in HLA-B*1502-positive patients, doctors should consider avoiding use of other AEDs associated with SJS/TEN when alternative therapies are equally acceptable (FDA ALERT, 2007a). Tested patients who are found to be negative for HLA-B*1502 have a low risk of SJS/TEN from CBZ, but SJS/TEN can still rarely occur, so healthcare professionals should still watch for symptoms in these patients.
The study by Hung et al. (2006) also showed that genetic susceptibility to CBZ-induced cADR is specific for the phenotype of SJS and does not extend to other forms of cutaneous hypersensitivity reactions such as the benign rash. Furthermore, Hung and coworkers (2006) showed that CBZ-associated maculopapular eruptions were associated with the HLA-A*3101 variant allele, while CBZ HSS was associated with polymorphisms in the motilin gene, which is located terminal to the major histocompatibility complex (MHC) class II genes. Since MHC proteins expressed by human chromosome 6 help determine whether molecules such as AEDs are presented as foreign antigens, it may be possible in the future to develop an MHC library to determine individual susceptibility to HSS. The data by Naisbitt et al. (2003a) provide evidence that T cells are involved in the pathogenesis of some LTG hypersensitivity reactions. The identification of drug-specific cells that express cutaneous lymphocyte antigen and type 1 cytokines after T cell receptor activation is consistent with the clinical symptoms. Furthermore, identification of large numbers of Vbeta 5.1(+) T cells suggests that polymorphisms within T cell receptor genes might act as determinants of susceptibility (Naisbitt et al., 2003a). Interestingly, the proliferation of drug-specific T cells in CBZ-hypersensitive patients that are phenotypically different from T cells involved in other serious cADR, shows a dose-dependent CBZ-specific and CBZ-10,11-epoxide-specific proliferation in vitro (Naisbitt et al., 2003b). This observation is of particular clinical interest because high doses, rapid titration, or high serum concentrations of AEDs such as CBZ and LTG appear to increase the risk of rash and possibly of serious hypersensitivity reactions (Zaccara et al., 2007).
To date, studies of genetically determined alterations in AED metabolism as predisposing factors to idiosyncratic ADRs have yielded conflicting results. Impaired detoxication of reactive metabolites has been demonstrated in vitro in peripheral blood mononuclear cells from patients with hypersensitivity reactions to PHT and CBZ and their siblings (Gennis et al., 1991). However, potential genetic defects impairing the activity of mEH1, an enzyme that detoxifies epoxide metabolites, were not found in patients with CBZ-induced idiosyncratic reactions (Green et al., 1995). In a search for genetically determined abnormalities in CBZ metabolism in 91 patients with CBZ-induced cADR, 278 SNPs including CYP3A4, 2B6, 2C8, 2C9, 1A2, and mEH1 were screened. The results showed that SNPs involved in the metabolism of CBZ were not associated with CBZ-induced cADR (Hung et al., 2006). However, despite negative results on a wide panel of candidate genes, the results of this single study of a restricted ethnic group may not be widely applicable (e.g., the effect of the HLA B allele in SJS only in Asians) and suggest that these genes should be investigated in other populations. Lee and coworkers (2004) reported that PHT-induced cutaneous reactions were associated with a polymorphism of the CYP2C9 gene, which codes for a major enzyme involved in the conversion of PHT to its pHPPH metabolite. A heterozygous CYP2C9*3 variant allele was found in 3 of 10 patients with such reactions. Since the CYP2C9*3 allele codes for a CYP enzyme with less activity, the role of reactive pHPPH precursors in the pathogenesis of PHT-induced hypersensitivity is questionable (Zaccara et al., 2007).
In addition, serious skin hypersensitivity to CBZ has been associated with a polymorphism at position 308 of the TNFα promotor region gene and with variants of the HLA gene allels DR3 and Q2 (Pirmohamed et al., 2001). The same group showed that serious CBZ-induced hypersensitivity reactions are associated with the heatshock protein 70 (HSP70) gene cluster in the MHC class III region (Alfirevic et al., 2006b). However, the association may not be causative, but merely reflect linkage disequilibrium with another closely located gene. Remarkably, HSP70 genes code for proteins that are upregulated under stress, and thus can be involved at various stages (e.g., antigen processing, inflammation, cell damage) of immune-mediated hypersensitivity.
Neural tube defects in women using valproate
Although neural tube defects are among the most common of all human birth defects, their etiological basis remains poorly understood and includes genetic and environmental components such as VPA exposure during pregnancy (Finnell et al., 2000). Here we review the evidence for a genetic susceptibility that increases the risk of neural tube defects in the offspring of women using VPA during early pregnancy. Despite evidence that higher doses of VPA are associated with increased likelihood of malformations, the vast majority of women have normal babies (Duncan et al., 2001). Although genetic factors are undoubtedly implicated in teratogenesis (Duncan, 2007), the fact that the vast majority of women on VPA have normal babies does not suggest a genetic influence per se; environmental factors are as likely to be responsible. In support of pharmacogenetic susceptibility, two reports have described fetal VPA syndrome occurring in seven sibling pairs (Kozma, 2001; Malm et al., 2002). Furthermore, three women with epilepsy taking VPA had repeated pregnancies with neural tube defects despite folate supplementation (Omtzigt et al., 1992; Duncan et al., 2001). One of the two women had a healthy child after switching from VPA to another AED. In humans, there is evidence that polymorphism in the 5′-10′-methylenetetrahydrofolate reductase (MTHFR) gene is a risk factor for neural tube defects (Christensen et al., 1999). Mothers of infants with fetal anticonvulsant syndrome are more likely to carry mutations in the MTHFR gene (Dean et al., 1999). Women having repeated pregnancies with neural tube defects despite taking folate supplementation have been suggested to be more susceptible to the effects of VPA because of failure to upregulate the human form of folate binding protein (FR α and FR β), MTHFR, or some of the other candidate genes thought to play a role in neural tube development (Christensen et al., 1999). Although folate supplementation may reduce the risk of neural tube defects, albeit only shown in studies where women with epilepsy were excluded, epidemiological studies have not established an association between polymorphisms in the human folate receptor gene and neural tube defects (Finnell et al., 2000).
The teratogenic effects of VPA may involve numerous genes including those regulated by histone deacetylases (HDACs) (Kultima et al., 2004). VPA, and some of its metabolites, like the 4-ene, may mediate teratogenicity by inhibition of HDACs (Eikel et al., 2006). In that respect, it may be of interest that in addition to VPA, TPM and the major carboxylic acid metabolite of levetiracetam (LEV) in humans, but not LEV itself, have been shown in vitro to inhibit HDACs (Eyal et al., 2004). The challenges in linking genetic polymorphisms to fetal phenotype have been reviewed by Van Dyke et al. (2000). At the time of their review, insufficient correlations between polymorphisms and phenotype were noted. However, as pointed out by Sankar (2007), phenotypic correlations with a specific polymorphism may not be readily discernible due to possible coexistence of polymorphisms in other genes that may modify the risk.
Continued efforts are necessary to reveal the mechanism how VPA causes neural tube defects and to clarify the nature of the gene(s) responsible for human neural tube defects. Until these abnormalities have been clarified, the occurrence of a neural tube defect in the offspring of a woman appears to present a higher risk for subsequent pregnancies and alternative drugs are suggested. However, the risk-benefit balance of alternative drugs such as LTG needs to be carefully evaluated and must include the recent confirmation that LTG is less efficacious than VPA for treatment of idiopathic generalized or unclassified epilepsy as confirmed in a large randomized trial (Marson et al., 2007b).
Fetal AED syndrome
In a prospective study of 19 pregnancies monitored by amniocentesis, four were identified to be at risk for congenital malformations attributed to PHT based on very low mEH activity (Buehler et al., 1990). All those four pregnancies resulted in infants that had findings consistent with the fetal hydantoin syndrome, while the other 15 infants did not (Buehler et al., 1990). The enzyme mEH (gene symbol EPHX1) is known to exhibit polymorphisms in the human (Hassett et al., 1997). Thus, as suggested by Sankar (2007), it may be worthwhile to evaluate if polymorphisms of mEH may play a role in the generation of PHT fetal syndrome.
It is well known that in rare cases, VPA can cause liver damage, which may be due to the CYP-catalyzed formation of the hepatoxic metabolite 4-ene-VPA (Rettie et al., 1987). Major metabolic pathways of VPA comprise glucuronidation, β- and ω-oxidation (Cotariu & Zaidman, 1988). Risk factors for this idiosyncratic hepatotoxicity include an age of less than 2 years, multiple AEDs intake, and concurrent medical disorders (Davis et al., 1994). From in vitro studies, it was concluded that CYP2C9 mediates the metabolic conversion of VPA to form 4-ene-VPA (Sadeque et al., 1997). However, cDNA-expressed CYP2C9*2 and *3 variants were less efficient than the CYP2C9*1 wild-type in catalyzing the formation of this reactive metabolite (Ho et al., 2003). Thus, it remains unresolved whether rare, yet unknown genetic variants of CYP2C9 could be responsible for the hepatotoxic potential of VPA. As VPA can cause oxidative stress in rats, which precedes the onset of hepatotoxicity, a CYP-independent mechanism might also be responsible (Tong et al., 2005). However, to date, the data are still conflicting.
Vigabatrin-associated concentric visual field defects
In two referral centers for refractory epilepsy, correlations of 32 tag-SNPs from six candidate genes (possibly involved in the hypothesized mechanisms of toxicity of vigabatrin) with vigabatrin-associated concentric visual field defects were evaluated. The following genes were selected: GABA transporters GAT1-3 (SLC6A1, SLC6A13, SCL6A11), GABA transaminase (ABAT), and the rho subunits of the GABAC receptor (GABRR1 and GABRR2). The degree of visual field constriction correlated with three SNPs and one haplotype in one center but not the other (Kinirons et al., 2006). Further studies are needed.
Genetic variation in AED metabolism may play a role in a patient developing side effects of hepatically metabolized AEDs, even if it seems to be rare. The most convincing evidence for the clinical impact of genetic variation exists for CBZ-induced SJS/TEN in patients from Asia and of Asian descent who test positive for HLA-B*1502. Genetic testing offers the possibility of avoiding serious and often fatal SJS/TEN in genetically susceptible individuals. This new safety information has been reflected in updated product labeling for CBZ products by the FDA. In addition, patients who test positive for HLA-B*1502 may be at increased risk of SJS/TEN from other AEDs that have been associated with SJS/TEN. Therefore, in HLA-B*1502-positive patients, doctors should consider avoiding use of other AEDs associated with SJS/TEN when alternative therapies are equally acceptable. Although the teratogenic effects of VPA, and possibly other AEDs, may involve numerous genes, more data is required to assess the potential clinical impact of genetic testing.
Ethical, Legal, and Social Issues of Genetic Testing
Emerging genetic information and the availability of genetic testing has the potential to increase our understanding of the disease and to improve the clinical management, at least in some patients. However, genetic testing is also likely to raise significant ethical, legal, and social issues for individuals with epilepsy and their family members (Shostak & Ottman, 2006). Although being able to predict the risk of side effects before AED treatment through genetic testing is undoubtedly beneficial, a number of potential issues need to be considered. These include cost-effectiveness and other medicoeconomic matters, availability of testing, legal aspects, and the ethical issues at stake. Pharmacogenetic insight reviewed above suggest that patients from Asia or of Asian descent are at clinically significant risk for SJS when exposed to CBZ, may have legal and ethical implications. Legal liability may arise when patients at risk are treated with CBZ without prior genetic testing. There is a general concern that genetic information may lead to discrimination by insurers and in the workplace. In the U.S., for example, a “Genetic Information Nondiscrimination Act of 2007” was passed to protect individuals against discrimination. Genetic information may be used to limit or cancel health insurance or to ask for a higher premium. Employers could discriminate against people that are genetically predisposed to a more severe (and more costly) form of disease and treatment including surgery, for example, if genetic testing for drug resistance in epilepsy should become available in the future. Public fears may lead to refusal of patients to have genetic tests that help researchers and physicians to identify and treat diseases. Ethical implications in genetic counseling issues include failure to inform family members or employers and insurance companies about the result of genetic testing. Illicit mining of genetic data from public agencies, employers, or insurance companies, or from researchers represents another danger (Mann & Pons, 2007). As long as no guidelines specific for epilepsy have been developed, a reasonable approach calls for a case-by-case determination of the benefit-harm balance of genetic testing versus the protection against genetic discrimination and the informational autonomy of the patient (Godard & Cardinal, 2004).
Finally, as genetic testing, particularly pharmacogenetic tests, become increasingly available, ethical, legal, and social considerations deserve careful consideration.
The promise of pharmacogenetics lies in its potential to identify sources of interindividual variability in drug response (both effectiveness and toxicity); this information may make it possible to individualize therapy with the intent of maximizing effectiveness and minimizing risk (FDA, 2005). With respect to AEDs, the most convincing example is the identification of HLA-B*1502-positive persons of Asian ancestry who have an increased risk of SJS/TEN when being treated with CBZ. The fact that dangerous or even fatal skin reactions to CBZ are significantly more common in Asian patients with a particular HLA allele, HLA-B*1502, has important implications for clinical practice. It is reasonable to expect that once libraries of MHC and enzyme-subtypes associated with serious drug reactions have been established, it may be possible to develop patterns indicating individual susceptibility to HSS and other serious drug reactions of AEDs.
However, the field of pharmacogenetics in epilepsy is still in early developmental stages in other areas, and the promise of individualized therapy has not (yet) been fulfilled for drug efficacy or common adverse events in response to AEDs. Consequently, there are currently no AED treatment guidelines that are based on pharmacogenetic data (Ferraro et al., 2006). The question why this is so has no single answer. The lack of clear conclusions in these areas probably reflects methodological limitations of most studies performed to date. The quality of the evidence is often limited, interesting data (e.g., by Basic et al., 2008) require replication, findings in Asian patients need to be explored in other ethnic groups. Except for the partly prospective study of Leschziner et al. (2006), which was negative, all other studies had a retrospective design. Implementation of knowledge may be another factor. For instance, reduced metabolism of PHT in people with certain CYP2C9 alleles has been known for decades. One could ask why testing for CYP2C9 alleles is not routinely used in clinical practice. The answer is probably multifaceted and includes the limited availability of genetic testing and diverse issues such as the fear of patients that the data may result in genetic discrimination when they find their way to employers or insurance agencies.
Nevertheless, the field of pharmacogenetics in epilepsy has been suggested to be one of the few areas where there has been some degree of consistency in terms of outcome studied (Leschziner et al., 2007). As an indicator that genetic variation is increasingly recognized as useful for clinical management, the FDA has recently issued two alerts, one on warfarin (FDA, 2007b) and one concerning genetic testing to predict the high risk of serious skin reactions to CBZ in predisposed individuals from Asia or of Asian descent (FDA, 2007a). The ethnic variability of genetic risk factors is probably another reason why the impact of genetic testing is still limited. One further issue is the growing recognition that association is not causation, so that, for example, more direct evidence for an involvement of the ABCB1 3435C>T SNP in AED resistance is needed, before this genetic variation can be accepted as a factor contributing to pharmacoresistance. Another reason why genetic testing has had a limited clinical impact is that exaggerated expectations may have lead to disappointment. For example, attempts to correlate multifaceted clinical issues such as “refractory epilepsy” with a single variable, such as SNP in ABCB1, without considering the complex biology of the epileptic circuit and channel excitabilities have significant limitations. In fact, as discussed above, it is reasonable to expect that individual responsiveness will be determined by the effects of many variations (and by environmental factors), and it will not be possible to make any one finding clinically useful until all (or many) of them are elucidated. As a consequence, the view that because the effect of a particular polymorphism (e.g., ABCB1 3435C>T) is small, it may have little clinical relevance, may be misleading, because it may act in concert with other polymorphisms to determine a complex trait such as pharmacoresistance.
One potential strategy to determine the clinical impact of ABCB1 polymorphisms on AED resistance in patients with epilepsy are clinical studies with Pgp inhibitors. Anecdotal reports suggest that inhibition of Pgp may improve seizure control in apparently drug-resistant epilepsy (Summers et al., 2004; Iannetti et al., 2005). Future ongoing studies with more specific Pgp inhibitors may be promising and be able to extend the evidence for the ABCB1 3435C>T SNP from association to causation. In this respect, it is also interesting to note that a recent study by Uhr et al. (2008) on antidepressant drugs indicates that the combined consideration of both the medication's capacity to act as an ABCB1-transporter substrate and the patient's ABCB1 genotype are strong predictors for achieving a remission, a strategy that may also be valid for treatment of epilepsy.
Another area where studies have not yet proven causation between drug response in epilepsy and genetic variation are drug target alterations, which appear in part to be determined by genetic polymorphisms. In particular, alterations in voltage-dependent sodium channels, which are a target of commonly used AEDs such as CBZ, might at least contribute to the poorer efficacy of CBZ in some patients. Many of these and other AED targets are assumed to be functionally polymporphic (Ferraro & Buono, 2005), providing ample opportunity for pharmacogenetic factors to operate on AED targets. It will be one of the priorities in coming years to systematically screen AED-target genes for such variations. Although more difficult to detect, particular emphasis should be placed on regulatory polymorphisms that affect gene expression or mRNA processing. Once the functionality of such polymorphisms has been appropriately demonstrated, it will then be the challenge to clinicians to perform meticulous association studies to assess the clinical relevance of such variations.
What can we learn from failures of the past? Clearly, this is not a problem limited to genetic association studies in epilepsy, and guidelines for both candidate gene and genome-wide association studies in human molecular genetics have been proposed to improve the research environment in this field (Freimer & Sabatti, 2005; see also Leschziner et al., 2006). Furthermore, the FDA has prepared guidelines to facilitate scientific progress in the field of pharmacogenetics and to facilitate the use of pharmacogenetic data in drug development (FDA, 2005). Future pharmacogenetic studies in patients with epilepsy should adhere to such guidelines and be designed in ways that are readily reproducible and applied across centers. Furthermore, with the recent advent of high-throughput genotyping platforms, instead of relying on current biological knowledge in choosing candidate genes, whole genome association studies are now feasible, which will increase our understanding on how genetic variation affects the treatment of epilepsy (Tate & Sisodiya, 2007). Hopefully, using the tools of genomics and proteomics may help to better predict response to AEDs and thus will allow to direct treatment to the individual's best outcome.
What, then, are the implications of the current database of pharmacogenetics for clinical practice? With respect to the development of adverse events in individual patients, from a pragmatic perspective, the major current treatment option for serious idiosyncratic reactions is immediate removal of the precipitating AED. Until we have better data, the current best strategy to avoid genetically determined dose-related and idiosyncratic adverse reactions is single-drug treatment with modern AEDs such as GBP, PGB, or LEV, which are neither metabolized hepatically nor involved in idiosyncratic reactions. It is reassuring that serious consequences of idiosyncratic reactions can be minimized by knowledge of risk factors including (1) genetic markers, (2) counseling of family members about increased risk of siblings of patients who had immune-mediated idiosyncratic reactions to an aromatic AED such as PHT, CBZ, PB, and primidone, (3) avoidance of specific AEDs in subpopulations at risk, (4) cautious dose titration, and (5) careful monitoring of clinical response. As research in this area advances rapidly, it is likely that in the future genetic testing (as it is already the case for HLA-B*1502) will become an important tool to identify patients at risk for idiosyncratic reactions.
We thank the reviewers for their thoughtful comments and suggestions that helped to strengthen our article. Furthermore, we thank Dr. Silvio Basic (Department of Neurology, University Hospital Zagreb, Croatia) for providing early information on his study on phenobarbital, which is in press. In addition, we thank Dr. Silke Vogelgesang (Department of Neuropathology, University of Greifswald, Germany) for providing information on her Pgp studies in human brain tissue, including a correction to her study of 2002 (Vogelgesang et al., 2002), in which the highest Pgp expression was determined in patients with the 3435CC genotype, not the 3435TT phenotype, as incorrectly stated in that paper.
Conflict of interest: We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines. We declare that we have no conflicts of interest in relation to this paper.