Development of individualized medicine for epilepsy based on genetic information.

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Development of individualized medicine for epilepsy based on genetic information Expert Rev. Clin. Pharmacol. 1(5), 661–681 (2008)

Sunao Kaneko†, Shuichi Yoshida, Kazuaki Kanai, Norio Yasui-Furukori and Hiroto Iwasa † Author for correspondence Department of Neuropsychiatry, Hirosaki, University Graduate School of Medicine, Zaifu-cho 5, Hirosaki 036-8562, Japan Tel.: +81 172 395 066 Fax: +81 172 395 067 [email protected]

Despite the continuous development and release of new anti-epileptic drugs (AEDs), almost one in four patients are resistant to AED therapy. Current therapy requires trial and error to determine the most effective AED and dosage for a patient. The development of individualized medicine for epilepsy is critical for improving AED treatment, particularly that based on genetic information. However, several crucial issues remain to be resolved before the development of AED therapy can proceed further. The epilepsy genes responsible for common phenotypes have not yet been identified and ongoing pharmacogenetic studies continue to search for an explanation as to why 20–25% of patients do not respond to AEDs. There is no convincing clinical evidence that P-glycoprotein at the blood–brain barrier limits the uptake of AEDs into the brain of epileptic patients and contributes to the development of the drug-resistant phenotype. This article provides a critical review of the status and perspectives for the development of individualized medicine for epilepsy, based on genetic polymorphisms/mutations in relation to three major components: the pharmacodynamic pathway, the pharmacokinetic pathway and the mechanisms of action of AEDs. The development of multiplex assay technologies, together with the generation of epilepsy animal models bearing human epilepsy genes, are also discussed. Keywords : ATP-binding cassette transporter • epilepsy • epilepsy animal model • gene chip • individualized medicine • ion channel gene • pharmacogenetic testing • receptor gene

Epilepsy, defined by the recurrence of unprovoked seizures, is a complex disorder that occurs when the electrical signals in the brain are disrupted, leading to repetitive seizures. Epilepsy is one of the most common neurological disorders, affecting approximately 0.6–0.8% of the general population [1] . It is estimated that 20–25% of patients with epilepsy fail to achieve good control with anti-epileptic drugs (AEDs) [2] . At present, none of the AEDs can eliminate epileptogenesis or ictogenesis. Surgical treatment – resection of focal, epileptogenic brain tissue – is considered to be the only curative treatment available for patients with epilepsy; However, patients are still required to continue AED treatment after surgery to ensure that they remain free from seizures [3] . Thus, AED treatment will continue to be the major therapy for epilepsy until more successful curative measures become available. Currently, AED selection is made according to seizure phenotype rather than epilepsy genotype and the optimal dosage is determined by www.expert-reviews.com

10.1586/17512433.1.5.661

trial and error. However, the molecular revolution in epilepsy research during the last two decades is beginning to have a significant impact on the diagnosis and treatment of epilepsy. In a clinical setting, genetic information can be used pretherapeutically to optimize the selection of AEDs and their dosage. Well-characterized genotype–phenotype relationships for cytochrome P450 (CYP) transporters and drug targets (ion channels, receptors and other proteins) will make it possible for clinicians to refer to pharmacogenetic tests that will aid greatly in the selection of appropriate AEDs and dosages in the future. For individualized medicine to become a reality, it is necessary to develop tools that could assess the degree of variability with regard to both pharmacokinetics and pharmacodynamics, as well as establish a well-defined model of the mechanism of action of AEDs. In this review, we discuss the current status and perspectives of the development of individualized medicine for epilepsy based on genetic information.

© 2008 Expert Reviews Ltd

ISSN 1751-2433

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Kaneko, Yoshida, Kanai, Yasui-Furukori & Iwasa

Mutations of epilepsy genes as biomarkers for the selection of AEDs

In the context of true individualized medicine, pharmacodynamic analysis is the key for evaluating therapeutic response. Although epilepsy is a heterogeneous group of diseases, some epilepsy syndromes are caused by a single gene mutation and show Mendelian inheritance. Recently, genes have been uncovered that are responsible for several rare forms of epilepsy phenotype (Table 1) [4–79] . Epilepsy genes

While many epilepsy genes with different mutations have been identified to date (Table 1) , these only account for less than 1% of all epilepsy cases with the exception of severe myoclonic epilepsy in infancy (SMEI), benign familial neonatal convulsions (BFNCs), juvenile myoclonic epilepsy (JME) and autosomal dominant epilepsy with febrile seizure plus (ADEFS +; previously known as generalized epilepsy febrile seizure plus). The genes responsible for the common phenotypes of epilepsies are yet to be identified. Novel susceptibility loci associated with febrile seizure (FS), ADEFS + and SMEI have been found in the first phase of a two-part study on the genetic risk profile for fever-related seizure disorders [80] . There is hope that, in the future, some susceptibility/responsible genes associated with these three phenotypes may be identified. The α-subunit of Na + channel (SCN1A) mutations can account for more than 60% of SMEI [81] and 10% of ADEFS + [82] , K+ channel (KCNQ2 and KCNQ3) mutations account for approximately 60% of BFNC [83] , and those of myoclonin1/EFHC1 account for 3–9% of JME [84] . Recently, we studied 35 patients with SMEI. Previously, using direct sequencing methods, these patients had been confirmed to have no mutations in SCN1A. However, using multiplex ligation-dependent probe amplification (MLPA), we identified heterozygous multiple exonic deletions in seven of the SMEI patients (20%) [81] . Array-based comparative genomic hybridization [85] has also led to the identification of a de novo microdeletion and heterozygous missense mutations in the gene coding for syntaxin binding protein 1 (STXBP1), in a girl with early-infantile epileptic encephalopathy and suppression burst, also known as Ohtahara syndrome. Such microsomal deletions cannot be anticipated 662

by the phenotypes alone or detected by conventional methods. Therefore, genetic abnormalities in SMEI and other epilepsy phenotypes should be screened carefully by techniques that can detect microdeletions. The question arises as to why mutations in the same gene show different responses to AED treatment; for example, in the SCN1A gene, the differences can range from no need for AED treatment in patients with FS to high drug resistance in those with SMEI. These

Table 1. Epilepsy genes and epilepsy phenotypes. Epilepsy gene

Epilepsy phenotypes

Ref.

Sodium ion channel SCN1A

SMEI, SMEB, ADEFS +, FS, SIGEI, ICEGTC, GTCS and IS

SCN2A

SMEI, IGE, ADEFS +, BFNISs and MTS

SCN3A

CPE

SCN1B

ADEFS

[4–21] [22–25] [26] [27–31]

+

Potassium ion channel KCNQ2

BFNC

[32–42]

KCNQ3

BFNC

[43–45]

Calcium ion channel [46]

CACNA1A

AEA, CPS, CTS and CAE

CACNA1H

CAE

[47,48]

CACNA1G

JME and CAE

[49,50]

CACNB4

GEPSE and JME

[51]

GABA A receptor GABRA1

IGE and JME

GABRD

ADEFS

GABRG2

FS, CAE and ADEFS

[52,53] [54]

+ +

[55–59]

Neuronal nicotinic acetylcholine receptor CHRNA2

ADNFLE

[60]

CHRNA4

ADNFLE

[61–66]

CHRNA7

JME

CHRNB2

ADNFLE

[67] [68,69]

Other receptor (G-protein-coupled receptor) FS

[70]

IMPA2

FS

[71]

EFHC1

JME

[72,73]

ADPEAF and IGE

[74–79]

MASS1

Others

LGI1

ADEFS +: Autosomal dominant epilepsy with febrile seizure plus; ADNFLE: Autosomal dominant nocturnal frontal lobe epilepsy; ADPEAF: Autosomal dominant partial epilepsy with auditory features; AEA: Absence epilepsy with ataxia; BFNC: Benign familial neonatal convulsion; BFNIS: Benign familial neonatal–infantile seizures; CAE: Child absence epilepsy; CPE: Cryptogenic pediatric partial epilepsy; CPS: Complex partial seizures; CTS: Clonic–tonic seizure; FS: Febrile seizure; GEPSE: Generalized epilepsy praxis-induced seizures episodic ataxia; GTCS: Generalized tonic-clonic seizures; ICEGTC: Intractable childhood epilepsy with generalized tonic–clonic seizures; IGE: Idiopathic generalized epilepsy; IS: Infantile spasms, JAE: Juvenile absence epilepsy; JME: Juvenile myoclonic epilepsy; MTS: Mesial temporal sclerosis, SIGEI: Severe idopathic generalized epilepsy of infancy; SMEB: Severe myoclonic epilepsy of infancy borderline; SMEI: Severe myoclonic epilepsy of infancy.

Expert Rev. Clin. Pharmacol. 1(5), (2008)

Development of individualized medicine for epilepsy based on genetic information

differences may, in part, be explained by the localization of mutations in the gene coding for SCN1A [86] ; however, other important factors, such as the role of modifier genes, may also be implicated. Some of the identified genes (Table 1) were discovered in studies with only a small number of patients or in association studies. Since the clinical significance of these genes is uncertain, their identity needs to be confirmed in larger studies with patients from different ethnic groups. However, the details of patients that may be haplotype carriers, either for the same epilepsy gene or the level of significance of each (Table 1), cannot be determined at present. To better understand the genetic basis of epilepsy phenotypes showing complex inheritance pattern and genetic heterogeneity, genetic polymorphisms offer a convenient avenue. The Epilepsy Genetics Consortium in Europe examined common variations among 279 prime candidate genes in 2721 cases and 1118 control samples to search for genetic susceptibility loci in sporadic epilepsy syndrome. They found that seizure types did not identify clear common genetic risk factors that contribute to selected epilepsy subphenotypes across multiple populations, and they were not able to identify risk factors for the general allepilepsy phenotype. However, they found that numerous single nucleotide polymorphisms (SNPs) contributed to disease pre disposition in a population-specific manner and that variations in the genes KCNAB1, GABRR2, KCNMB4, SYN2 and ALDH5A were significant and warranted further study [87] . SNPs in ionchannel-related genes in generalized epilepsy, which encode ubiquitary enzymes, have been reviewed comprehensively [88] . Increases in our understanding of the genetic and molecular basis of epilepsies has raised hopes for finding effective preventions and cures; improvements in pharmacotherapy, along with individualized medicine, also hold great promise in this regard. The reader is referred to reviews by Lucarini et al. [88] , Heron et al. [89] and Dube et al. [90] that pertain to the role of genetics in epilepsy and the molecular targets reported thus far. Mechanisms of action of AEDs on ion channels & receptors

Although many molecular targets exist on which AEDs may exert an effect [91] , the common link among the proposed mechanisms of action for most AEDs is the ability of the drug to modulate excitatory and inhibitory neurotransmission through ion channels, neurotransmitter receptors and neurotransmitter metabolism. AEDs exhibit a number of pharmacological effects on molecular targets (Table 2) [92–95] , but the mechanisms of action that account for their anti-epileptic properties are not fully understood. Currently available AEDs predominantly target voltage-gated cation channels or influence GABA-mediated inhibition and glutamate-mediated excitation. Voltage-gated Na+ channels are essential for action potentials, and their mutations form the substrate for ADEFS + and benign familial neonatal-infantile seizures. Carbamazepine (CBZ), oxcarbazepine (OXC), phenytoin (PHT), lamotrigine (LTG) and felbamate (FBM) limit sustained repetitive firing through an action at the voltage-sensitive Na + channels [96–100] . Other AEDs, such as topiramate (TPM), zonisamide (ZNS) and valproate (VPA), www.expert-reviews.com

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have a similar effect on Na+ channels [101,102] . Voltage-gated K+ channels are essential in the repolarization and hyperpolarization that follows paroxysmal depolarization shifts (PDSs), and their mutations form the substrate for BFNC and episodic ataxia type 1. Retigabine acts by opening KCNQ2/KCNQ3 K+ channels [103,104] , which mediate the potassium M-current [105] , leading to neuronal hyperpolarization without affecting the cardiac KCNQ1 channel [106,107] . TPM may also exert an action at the K+ channels [108] . The activation of potassium currents may contribute to membrane hyperpolarization [109] . Voltage-gated Ca 2+ channels are involved in neurotransmitter release in the sustained depolarization phase of PDSs and in the generation of absence seizures. Their mutations may be a substrate for JME. Ethosuximide (ESM) inhibits thalamic T-type Ca2+ channels [110] . By preventing Ca 2+ -dependent depolarization of thalamocortical neurons, ESM is thought to block the synchronized firing associated with spike-wave discharges. ZNS and VPA also reduce voltage-dependent T-type Ca 2+ currents in cultured neurons and primary afferent neurons, respectively [111,112] . Gabapentin (GBP) binds to the two regulatory subunits of the voltage-sensitive Ca 2+ channel [113] . FBM inhibits dihydropyridine-sensitive, high-threshold, voltage-sensitive Ca 2+ currents [114] . LTG also inhibits dose-dependent high-voltage activation of Ca 2+ currents, possibly through the inhibition of presynaptic N- and P/Q-type Ca 2+ channels [114,115] . Levetiracetam (LEV) modulates a highvoltage-activated Ca 2+ current [116] and has been found to be a selective blocker of N-type Ca 2+ channels [117] . This compound also promotes inhibitory neurotransmission by reducing the negative allosteric effects of zinc and the β-carbolines on GABA A and glycine receptors [118] . Voltage-gated Cl- channels are implicated in GABA A trans mission, and mutations in these channels have been found in some families with JME, in epilepsy with grand mal seizures on awakening, and juvenile absence epilepsy. The Cl- ionophore of the GABA A receptor is responsible for the rapid post-PDS hyperpolarization and has been involved in epileptogenesis in both animals and humans, and mutations in these receptors have been found in families with JME and ADEFS +. Enhancement of GABA A inhibitory transmission is the primary mechanism of benzodiazepines (BZDs) and phenobarbital (PB). Barbiturates mainly act by increasing the mean open duration of Na+ channels without affecting channel conductance or opening frequency, whereas the binding of a BZD to its allosterically coupled GABA A binding sites increases opening frequency without affecting open or burst duration [119,120] . TPM, tiagabine (TGB) [121] , and vigabatrin (VGB) [94,122] enhance GABAergic transmission by different mechanisms. Since TPM modulates GABA-evoked currents in cortical neurons by a non-BZD mechanism [123] , it may be effective in cases of FS evolving to childhood absence epilepsy (CAE) or FS requiring AED treatment where BZD binding sites are dysfunctional owing to mutations of the α1- or d2-subunit of the GABA receptor gene [56] . Ionotropic glutamate receptors are implicated in the sustained depolarization phase of PDS and in epileptogenesis. The antiepileptic drugs FBM, PB and TPM block these receptors [124–126] . 663

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Table 2. Comparative mechanistic profile among major anti-epileptic drugs. AED

Na + channel blockade

Phenytoin

+++

+

+

Phenobarbital

++

+

+++5,6

++10

Carbamazepine

+++

+

+

+

++

Valproate

++

+

++

++

++

++

Ethosuximide

T-type Ca2+ Non-T-type Ca2+ K+ channel GABA channel blockade channel blockade mimesis

++

+

+

Antiglutamate

Monoamine release

+++

Benzodiazepines

+

Zonisamide

+

+ ++

Gabapentin

+++ 6

+ +++1

Lamotrigine

+++

++2,3

Oxcarbazepine

+++

+

++ 6 + +

2

Tiagabine

+ +++

Felbamate

+

+

Topiramate

++

+4

+

++

++11

++7 +++

++9

++

9

+

2

Retigabine

8

+7

4,5

Vigabatrin Levetiracetam

++

+++

+++: Possible major effects observed at thrapeutic levels. ++: Effects observed at therapeutic levels. +: Effects observed at supratherapeutic levels. 1 L-type Ca2+ channel (α 2δ-subunit). 2 N-type Ca2+ channel. 3 P/Q-type Ca2+ channel. 4 L-type Ca2+ channel. 5 R-type Ca2+ channel. 6 GABA A receptor allosteric modulator. 7 Increase brain GABA turnover, GABAB receptor activation. 8 GABA uptake inhibitor. 9 GABA-T blockade. 10 NMDA/kainate receptor. 11 NMDA receptor. AED: Anti-epileptic drug; NMDA: N-methyl- d -aspartate.

FBM reduces N-methyl-d-aspartate (NMDA) receptor-modulated cationic conductance [127,128] . LTG is twice as effective in inhibiting the release of glutamate compared with that of GABA [129] . Mutations in the nAChR are the substrates for nocturnal frontal lobe epilepsy (NFLE). CBZ, ZNS and BZD are efficacious for controlling the seizures of NFLE and autosomal dominant NFLE (ADNFLE). A therapeutic dose of CBZ was found to enhance acetylcholine release and synthesis in the rat striatum and hippocampus [130] . Some AEDs, such as CBZ [131,132] , ZNS [131,132] , VPA [131,133] , GBP [134] and TPM [135] , increase monoamine (MA) release within therapeutic concentrations. The effect of such AEDs on neurotransmission may explain their neuroprotective action, but the degree to which they contribute to anti-epileptic action has yet to be clarified. Although LEV does not appear in the list of mechanistic profiles shown in Table 2 , the binding site of this compound is highly homologous to synaptic vesicle protein 2A [136] , suggesting that it modifies neurotransmitter release by binding to synaptic vesicle protein, which is thought to contribute to the 664

docking and release of neurotransmitters. Studies of genes associated with epilepsy in animal models and humans have elucidated potential AED targets [91] . However, the effect of AEDs on these possible molecular targets is not yet fully understood and is sure to be the object of future studies. Currently, an understanding of the roles of ion channels and receptors in the mechanisms of action of AEDs is essential for the development of individualized treatment regimens for patients with specific mutations [92,93] . Selection of AEDs based on genetic information

Although the evidence is limited (Table 3) and further accumulation of the data is required, the selection of an AED is probably more effective when it is based on mutation identified in epilepsy genes and used in conjunction with the clinical phenotypes. Mutations of each epilepsy gene were dichotomized into two groups based on clinical response to AED treatment [137] . The responsiveness of some drugs not listed in Table 2 has been determined by clinical experience. Drug resistance has been found in most mutations of SCN1A (with the exception of del2528G) and SCN2A, identified Expert Rev. Clin. Pharmacol. 1(5), (2008)


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Table 3. Possible anti-epileptic drug selection based on mutation of epilepsy genes. Epilepsy gene Epilepsy phenotypes

Mutations

AEDs

SMEI

130 mutations

SMEB

49 mutations

Stiripentol, phenytoin, carbamazepine, lamotrigine and topiramate*

SIGEI

L433fsX499

ICEGTC

T808S

GTCS

S914fsX936, K1846fsX1856

IS

E1957G

SMEI

R102X

IGE

R1918H, (c.IVS18 +5G), (c.IVS11–12C>T)

MTS

R1918H

AED treatment resistant Sodium ion channel SCN1A

SCN2A


BFNC

K526N

Retigabine

E147K, R1820X

Lamotrigine (levetiracetam?)

Calcium ion channel CACNA1A

AEA


ADNFLE

S247F, S248F§ , S252F, S252L

Carbamazepine, zonisamide and benzodiazepine

Good response to AED treatment Sodium ion channel SCN1A

SCN2A

SCN1B

ADEFS +

D188W, Y780C, T875M, K1270T, V1353L, V1428A, I1656M, R1657C, D1742G, M1852T, T1067A, T875M, (c.1212G>A)

SMEI

del2528G

ADEFS +

R19K, R187W, R188W, R524Q

BFNISs

R233Q, V892L, N1001K

ADEFS +

R85C, R85H, C121W, C121T

Phenytoin, carbamazepine, lamotrigine, topiramate, vigabatrine and oxcarbazepine


BFNC

Q78fsX132, 105delS, (c.1118 +1G>A), N258S, A196V, L197P,R207W, S247W, 939insG, A294G, R333W, 2034delC, 2513delG

KCNQ3

BFNC

W309R, G263V, R330C

Retigabine, carbamazepine, zonisamide and topiramate

Calcium ion channel CACNA1A

CPS, CTS

I1710T

Carbamazepine, gabapentin, topiramate and lamotrigine (oxcarbazepine and levetiracetam?)

AED resistant. Benzodiazepine is not effective. Zonisamide is suggested instead of carbamazepine. # If treatment is needed benzodiazepines are not effective. ADEFS +: Autosomal dominant epilepsy with febrile seizure plus; ADNFLE: Autosomal dominant nocturnal frontal lobe epilepsy; ADPEAF: Autosomal dominant partial epilepsy with auditory features; AEA: Absence epilepsy with ataxia; AED: Anti-epileptic drug; BFNC: Benign familial neonatal convulsion; BFNIS: Benign familial neonatal-infantile seizures; CAE: Child absence epilepsy; CPE: Cryptogenic pediatric partial epilepsy; CPS: Complex partial seizures; CTS: Clonic–tonic seizure; FS: Febrile seizure; GEPSE: Generalized epilepsy praxis-induced seizures episodic ataxia; GTCS: Generalized tonic–clonic seizures; ICEGTC: Intractable childhood epilepsy; IGE: Idiopathic generalized epilepsy; IS: Infantile spasm; JAE: Juvenile absence epilepsy; JME: Juvenile myoclonic epilepsy; MTS: Mesial temporal sclerosis; SIGEI: Severe idopathic generalized epilepsy of infancy; SMEB: Severe myoclonic epilepsy of infancy borderline; SMEI: Severe myoclonic epilepsy of infancy. * ‡ §

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Table 3. Possible anti-epileptic drug selection based on mutation of epilepsy genes. Epilepsy gene Epilepsy phenotypes

Mutations

AEDs

Calcium ion channel CACNA1G

JME

A570V

Valproate, ethosuximide and benzodiazepines

CACNA1H

CAE

H515Y

Ethosuximide and zonisamide

CACNB4

GEPSE

C104F

– GABRA1

JME

A322D

– GABRG2

CAE

R43Q

ADEFS +

K289M, Q351X

ADEFS +

E177A, R220C, R220H

GABA A receptor:

– GABRD

Valprotate, barbiturates, benzodiazepines, tiagabine, vigabatrin and topiramate

‡

Phenobarbital, benzodiazepine, tiagabine, vigobatrin, gabapentin and topiramate


ADNFLE

I279N

CHRNB2

ADNFLE

V287L, V287M, I312M

CHRNA7

JME

(c.IVS9 +5G>A), (c.1354G>A), (c.1466C>T)

Valproate, benzodiazepines and zonisamide

– EFHC1

JME

P77T, D210N, R221H, F229L, D253Y

Valproate

– LGI1

ADPEAF

S145R, C42R, I298T, A110D

Carbamazepine, valproate, sulthiame and topiramate

Carbamazepine, zonisamide and benzodiazepines

Others:

No AED treatment is required Sodium ion channel SCN1A

FS

W1204R, R1648H, R1685V, M145T, R613X, R1525X, V1857L

FS

R43Q‡, R139G #

Usually AED is not required. If needed, benzodiazepines or barbitulates are selected

GABA A receptor: – GABRG2

Other receptor (GPCR): – MASS1

FS

S2584P, S2652X

– hSEZ6

FS

C452X

– IMPA2

FS

Others:

AED resistant. ‡ Benzodiazepine is not effective. § Zonisamide is suggested instead of carbamazepine. # If treatment is needed benzodiazepines are not effective. ADEFS +: Autosomal dominant epilepsy with febrile seizure plus; ADNFLE: Autosomal dominant nocturnal frontal lobe epilepsy; ADPEAF: Autosomal dominant partial epilepsy with auditory features; AEA: Absence epilepsy with ataxia; AED: Anti-epileptic drug; BFNC: Benign familial neonatal convulsion; BFNIS: Benign familial neonatal-infantile seizures; CAE: Child absence epilepsy; CPE: Cryptogenic pediatric partial epilepsy; CPS: Complex partial seizures; CTS: Clonic–tonic seizure; FS: Febrile seizure; GEPSE: Generalized epilepsy praxis-induced seizures episodic ataxia; GTCS: Generalized tonic–clonic seizures; ICEGTC: Intractable childhood epilepsy; IGE: Idiopathic generalized epilepsy; IS: Infantile spasm; JAE: Juvenile absence epilepsy; JME: Juvenile myoclonic epilepsy; MTS: Mesial temporal sclerosis; SIGEI: Severe idopathic generalized epilepsy of infancy; SMEB: Severe myoclonic epilepsy of infancy borderline; SMEI: Severe myoclonic epilepsy of infancy. *

in SMEI, severe myoclonic epilepsy of infancy borderline, severe idiopathic generalized epilepsy of infancy (SIGEI), generalized tonic–clonic seizures (GTCS), infantile spasms, intractable childhood epilepsy with GTCS and GTCS associated with mesial temporal sclerosis. Na+ channels and GABA A receptors are major targets of PHT, CBZ, LTG, VPA, BDZs and PB. However, with the exception of one mutation, all mutations of SCN1A and SCN2A identified in patients with SMEI are highly drug resistant to all 666

AEDs. Patients with these mutations may improve slightly with VPA and BDZs. The combination of clobazam (CLB) and stiripentol (CYP3A4, 1A2, 2C9, 2C19 and 2D6 inhibitor) has proven effective [138] , possibly because of the enhanced action of the active metabolite nor-CLB. In general, patients with KCNQ mutations respond to AEDs, but, in a rare case with mutation in the KCNQ2 gene (K526N), drug resistance has been reported, which might be influenced by acquired factors [39] . Expert Rev. Clin. Pharmacol. 1(5), (2008)


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Various voltage-gated Ca 2+ channel sub1 units and auxiliary proteins are targets of ESM, VPA, lamotrigine, ZNS, levetiracetam, CBZ, OXC, GBP and TPM, which 5 are AEDs selected for patients with mutaC N tions of Ca 2+ channels. Since barbiturates, BDZs, VPA, GBP, TGB, TPM and VGB show GABA mimesis, these AEDs can be 2 prescribed for idiopathic generalized epilepsy, JME and CAE. However, mutation I II III IV R43Q in the gene coding for GABRG2 results in the disturbance of BZD binding sites of the GABA receptor, leading to 4 insensitivity to BZDs (Figure 1) [52,55–57,59] . In such a case, TPM may be selected for treatment because it enhances GABAevoked currents in clonazepam-insensitive cortical neurons, indicating that GABA A-receptor sensitivity to TPM is not dependent on the presence of BZD sensitivity [123] . As illustrated in Figure 1, three 3 missense mutations (R43Q, K289M and Expert Rev. Clin. Pharmacol. © Future Science Group Ltd (2008) R139G) and one truncation mutation (Q351X) of GABRG2 were identified in Figure 1. Mutations identified in GABRA1/GABRG2. The GABA A receptor contains cases of FS-evolving CAE, FS or FS plus, four membrane-spanning segments (I–IV), and segment II is a voltage sensor. Three missense mutations (1: R43Q; 2: K289M; 5: R139G) and one truncation mutation and SMEI, respectively [55–57,59] . One mis(3: Q351X) of GABRG2 were identified in cases of Febrile seizure (FS)-evolving child sense mutation (A322D) of GABRA1 was absence epilepsy, FS or FS plus, and severe myoclonic epilepsy of infancy, respectively reported to be associated with JME [52] . For [55–57,59] . One missense mutation (4: A322D) was reported to be associated with juvenile patients with K289M, R139G or A322D, myoclonic epilepsy [52] . VPA or AEDs with the action of GABA A mimesis were selected. Patients with Q351X are drug resistant, in dissociated rat hippocampal granule neurons in the pilocarpine and stiripentol may be suggested (as mentioned previously). For model of chronic epilepsy and reported that the reduced pharpatients with R34Q, AEDs act as GABA agonists, but BZDs are macosensitivity of Na+ channels might contribute to the developnot recommended. ment of drug resistance, as seen in the reduced effects of PHT In general, CBZ, BZD and ZNS are considered for patients with and, to a lesser extent, LTG in chronic epilepsy [142] . C121W in CHRNA4 or CHRNB2 mutations; however, in most cases, CBZ SCN1B identified in patients with ADEFS + may change voltageis preferred since ADNFLE mutations are sensitive to CBZ [139] . dependent gating but does not directly affect drug receptors, sugHowever, in patients with S284F mutation in CHRNA4, which gesting that a Na+ channel mutation responsible for epilepsy can was recently identified in ADNFLE and isolated cases of NFLE, also alter channel response to AEDs [143] . In a study using human ZNS was more effective than CBZ [139] . Patients with mutation hippocampal slices, a loss of Na+ channel drug sensitivity to CBZ of I279N in CHRNA2 are reported to be drug resistant [60] . Most have was reported to contribute to drug resistance in epilepsy often, patients with FS do not require AED treatment, but in treatment, indicating the importance of this channel to pharmaextreme cases – possibly owing to frequent seizures with high fever coresistance [142] . These findings are interesting but confirmation caused by various etiologies – barbiturates or BZDs are selected, of their results is needed. except in the case of patients with R43Q mutation lacking BZD Some AEDs, including CBZ, often result in cutaneous adverse binding sites (as mentioned previously). drug reactions, such as Stevens–Johnson syndrome (SJS) and In addition to mutations in epilepsy genes, polymorphisms of toxic epidermal necrolysis (TEN). Chung et al. reported that molecular targets in the brain, such as those of SCN1A, are likely SJS/TEN caused by CBZ was strongly associated with the to be involved in the drug response. In a cohort of patients with HLA‑B*1502 in the Han Chinese [144] . They further studied chronic epilepsy, AA genotype was associated with patients who the implication of this polymorphism for cutaneous adverse drug were prescribed higher maximum doses of CBZ and PHT than reactions, including maculopapular eruption and hypersensitivthose with SCN1A intron 5 (IVS5–91) GG genotype [140] . A sig- ity syndrome (HSS), and found that HLA-B*1502 was not assonificant association between AA genotype and CBZ resistance ciated with maculopapular eruption or HSS. However, macuhas been confirmed in Japanese patients with epilepsy [141] . Remy lopapular exanthema was associated with SNPs in the HLA-E et al. analyzed the effects of PHT, LTG and VPA on Na + current region and a nearby allele, HLA-A+3101, and HSS with SNPs in www.expert-reviews.com

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Table 4. Anti-epileptic drug substrate for presumed cytochrome P450s and drug transporters. AEDs

CYPs

Drug-transporter genes

Carbamazepine

3A4, 2D6, 2C8

MDR1 and MRP2

Valproate

2C9, 2C19, 1A2, 2B1,2B2, 2B4, 2E1, 4B1 MRP2 MDR1 and LNAA

Gabapentin Phenobarbital

3A4, 2D6, 2C9, 2B1, 4A1

MDR1

Phenytoin

3A4, 2C8, 2C9, 2C10, 2C19

MDR1, MRP2 and RLIP76

Topiramate

2C19

MDR1

Levetiracetam

MDR1

Lamotrigine

MDR1*

that contributes to the pharmacokinetics of drugs that are Pgp substrates, has been studied extensively. Table 4 summarizes commonly used AEDs that are substrates for various CYPs and transporters [93,147,148] . Among these, CYP3A4/5, CYP2C9, CYP2C19 and MDR1 are the most relevant to AED pharmacokinetics and, to a lesser extent, pharmacodynamics. Analysis of phenotype–genotype relationships that regulate drug concentration at target sites provides crucial data for the creation of personalized medicine. AED-related CYPs

Most AEDs, except for GBP [149] and LEV [150] , are metabolized by at least one CYP enzyme. TPM is a partial substrate for * Diazepam 3A4, 2C19, 1A2 MDR1 CYP2C19, and 60% of TPM is excreted in Clobazam 3A4 urine. Similarly, TGB, viabatrin and ZNS are also partially excreted in urine [147] . For AED Felbamate 2C19 metabolism, analysis of CYP2C9, CYP2C19 Mephobarbital 2C19 and CYP3A4/5 variants is most relevant. CYP2C9 and CYP2C19 variants affect the Oxcarbazepine 3A4, 2C19 hydroxylation capacity of PHT, and mutaN-desmethyl 2C19 tions of these genes reduce the dose of PHT clobazam needed to achieve the therapeutic drug con* Results using dog P-glycoprotein (MDR1). centration range. This has been observed AED: Antiepileptic drug; CYP: Cytochrome P450; LNAA: Large neutral amino acid transporter. in a wide range of ethnic populations studthe motilin gene located in the major histocompatibility complex ied [140,151–153] . While CYP2C9 variants have more impact on PHT class II genes. These evidences strongly suggest the importance metabolism than CYP2C19 [153,154] , CYP2C polymorphisms did not of HLA genotyping. correlate with the degree of gingival hyperplasia [155] , although ginHowever, replication of the Chung et al. study in Europe found gival overgrowth might depend on PHT serum concentrations [156] . that in 12 patients with CBZ-induced SJS, only four patients Patients with two poor metabolizer (PM) alleles of CYP2C19*2 or had the HLA-B*1502 allele. These patients had an Asian ances- *3 or a combination of the two, showed reduced clearance of PB try [145] . Another study in Europe reported that HLA-B*1502 compared with those without mutation [157] . The total clearance was not a marker for all forms of CBZ-induced hypersensitivity of PB decreased by 48% in patients with CYP2C9*1*3 genotype in Caucasians [146] . These results suggest that the HLA region, compared with those with CYP2C9*1*1 genotype; however, no which may contain relevant genes for SJS, is not a universal effect of CYP2C19 was reported [158] . VPA and CBZ metabolisms marker, but rather, is linked to ethnicity. Therefore, further are influenced by CYP2C9 mutations [140,159] . VPA competitively investigation is required to delineate the exact role of the HLA inhibits CYP2C9, and slightly inhibits CYP2C19 and CYP3A4 region in adverse reactions. activities [148] . CYP2C9*1 is the predominant catalyst in the formation of 4-ene-VPA (toxic metabolite of VPA), 4-OH-VPA, Relevance of CYP & transporter genotypes to and 5-OH-VPA. CYP2A6 contributes partially to 3-OH-VPA optimize dosage formation [160] . CBZ and OXC are inducers of drug metabolism Our understanding of the mechanisms of AED concentrations via CYP3A4. The inductive effect of CBZ is approximately 46% at target sites in the brain has progressed greatly in the last two higher than that of OXC [161] and both compounds have clinidecades. Throughout the literature, studies report the identi- cal significance. The clearance of ZNS is affected by CYP2C19 fication of genes that are implicated in the variability among genotypes, and it was lower in heterozygous extensive metabolizers patients in drug response and metabolism and/or transport of (EMs) and PMs by 16 and 30%, respectively. A combination of AEDs. CYP is the collective term for a superfamily of heme- enzyme-inductive AEDs, such as CBZ, PHT or PB, increased the containing membrane proteins, responsible for the metabolism clearance of ZNS by 24–29% [162] . of approximately 70–80% of clinically used drugs. The MDR1 N-desmethylclobazam (N-CLB), the major metabolite of CLB gene product, the ATP-binding cassette (ABC) transporter with a long half-life, exerts great influence on therapeutic and ABCB1 or P-glycoprotein (Pgp), is an ATP-driven efflux pump adverse effects of CLB. The degree of elevation in the serum Zonisamide

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Review

Table 5. Ethnic variability in frequency of cytochrome P450 genotypes. Gene

Genotypes

Number of genotypes Myrand et al.§

Yasui-Furukori et al.

‡

N CYP3A4

Korean (%)

Caucasian (%)

618

100

101

100

143

137

(22.2)

5

(5.0)

7

(7.0)

6

(6.0)

0

(0)

*

1/ 3

229

(37.1)

34

(34.0)

41

(41.0)

37

(37.0)

21

(14.8)

3/*3

252

(40.8)

61

(61.0)

53

(52.0)

57

(57.0)

122

(85.2)

N

611

100

100

99

139

1/ 1

572

(93.6)

93

(93.0)

95

(95.0)

92

(93.0)

93

(65.0)

1/ 2

0

(0)

0

(0)

0

(0)

0

(0)

27

(19.1)

1/ 3

39

(6.4)

7

(7.0)

5

(5.0)

7

(7.0)

12

(8.2)

*

2/ 2

0

(0)

0

(0)

0

(0)

0

(0)

4

(2.7)

2/*3

0

(0)

0

(0)

0

(0)

0

(0)

2

(1.4)

3/*3

0

(0)

0

(0)

0

(0)

0

(0)

1

(0.7)

* * * *

* * *

* *

N

1190

100

98

93

143

*

1/ 1

386

(32.4)

31

(31.0)

42

(43.0)

37

(40.0)

57

(40.1)

1/ 2

413

(34.7)

39

(39.0)

42

(43.0)

33

(36.0)

27

(19.0)

* *

*

1/ 3

174

(14.6)

10

(10.0)

4

(4.0)

11

(12.0)

0

(0.0)

1/*17

0

(0)

1

(1.0)

1

(1.0)

3

(3.0)

46

(32.4)

2/*2

107

(9.0)

13

(13.0)

6

(6.0)

5

(5.0)

2

(1.4)

2/ 3

92

(7.7)

4

(4.0)

3

(3.0)

4

(4.0)

0

(0)

2/ 17

0

(0)

0

(0)

0

(0)

0

(0)

8

(5.6)

3/*3

18

(1.5)

2

(2.0)

0

(0.0)

0

(0.0)

0

(0.0)

4/*17

0

(0)

0

(0)

0

(0)

0

(0)

1

(0.7)

17/ 17

0

(0)

0

(0)

0

(0)

0

(0)

1

(0.7)

*

*

* * * *

* *

* * *

*

N CYP2D6

Chinese (%)

1/ 1

*

CYP2C19

Japanese (%)

*

* *

CYP2C9

Japanese (%)

982

100

101

100

142

1/ 1

164

(16.7)

15

(15.0)

7

(7.0)

6

(6.0)

26

(18.2)

1/ 1×2

4

(0.4)

1

(1.0)

0

(0)

1

(1.0)

0

(0)

1/*2

99

(10.1)

8

(8.0)

9

(9.0)

10

(10.0)

38

(26.6)

*

1/ 2×2

1

(0.1)

1

(1.0)

0

(0)

1

(1.0)

0

(0)

*

1/ 3

0

(0)

0

(0)

0

(0)

0

(0)

3

(2.1)

1/ 4

1

(0.1)

1

(1.0)

0

(0)

0

(0)

16

(11.2)

1/*4×2

0

(0)

0

(0)

0

(0)

0

(0)

10

(7.0)

1/*5

39

(4.0)

5

(5.0)

4

(4.0)

4

(4.0)

2

(1.4)

1/ 6

0

(0)

0

(0)

0

(0)

0

(0)

3

(2.1)

1/ 10

294

(29.9)

27

(27.0)

28

(28.0)

30

(30.0)

1

(0.7)

*

1/ 10×2

1

(0.1)

2

(2.0)

0

(0)

1

(1.0)

0

(0)

*

1/ 14

3

(0.3)

0

(0)

0

(0)

0

(0)

0

(0)

1/*21

0

(0)

1

(1.0)

0

(0)

0

(0)

0

(0)

* *

* *

* * * *

*

* * * * * *

* *

*

‡ §

Data sampled from four regions in Japan (Hirosaki, Asaka, Kinki and Mie) [170, Yasui-Furukori et al. Unpublished Data]. From [169].


669

Review


Table 5. Ethnic variability in frequency of cytochrome P450 genotypes. Gene

Genotypes

Number of genotypes Myrand et al.§

Yasui-Furukori et al.

‡

N CYP2D6

Japanese (%)

Japanese (%)

Chinese (%)

Korean (%)

Caucasian (%)

982

100

101

100

142

1/ 36

2

(0.2)

0

(0)

0

(0)

1

(1.0)

0

(0)

1/ 41

16

(1.6)

0

(0)

0

(0)

0

(0)

0

(0)

1×2/*2

1

(0.1)

0

(0)

0

(0)

0

(0)

0

(0)

1×2/ 5

0

(0)

0

(0)

1

(1.0)

0

(0)

0

(0)

1×2/ 10

1

(0.1)

0

(0)

0

(0)

0

(0)

0

(0)

2/ 2

19

(1.9)

0

(0)

2

(2.0)

1

(1.0)

11

(7.7)

2/*3

0

(0)

0

(0)

0

(0)

0

(0)

2

(1.4)

2/*4

1

(0.1)

0

(0)

0

(0)

0

(0)

17

(11.8)

2/ 1×2

1

(0.1)

0

(0)

0

(0)

0

(0)

0

(0)

2/ 2×2

1

(0.1)

0

(0)

0

(0)

0

(0)

0

(0)

* *

* *

* *

*

* *

*

*

* * * *

* *

2/ 4×2

0

(0)

0

(0)

0

(0)

0

(0)

10

(7.0)

2/*5

14

(1.4)

3

(3.0)

2

(2.0)

3

(3.0)

3

(2.1)

2/*6

0

(0)

0

(0)

0

(0)

0

(0)

3

(2.1)

2/ 10

89

(9.1)

11

(11.0)

12

(12.0)

10

(10.0)

1

(0.7)

*

2/ 10×2

4

(0.4)

0

(0)

0

(0)

0

(0)

0

(0)

*

2/ 14

1

(0.1)

0

(0)

0

(0)

3

(3.0)

0

(0)

2/*21

0

(0)

0

(0)

1

(1.0)

0

(0)

0

(0)

2/*41

2

(0.2)

0

(0)

0

(0)

0

(0)

0

(0)

2×2/ 4

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

2×2/ 5

2

(0.2)

1

(1.0)

0

(0)

0

(0)

0

(0)

*

*

* * * * *

*

* * *

*

*

*

3/ 4

0

(0)

0

(0)

0

(0)

0

(0)

1

(0.7)

4/*4

0

(0)

0

(0)

0

(0)

0

(0)

7

(4.9)

4/*10

2

(0.2)

0

(0)

0

(0)

0

(0)

2

(1.4)

*

4/ 10×2

1

(0.1)

0

(0)

0

(0)

0

(0)

0

(0)

4/ 36

0

(0)

0

(0)

0

(0)

1

(1.0)

0

(0)

5/ 5

2

(0.2)

0

(0)

0

(0)

0

(0)

0

(0)

5/*10

50

(5.1)

4

(4.0)

6

(6.0)

6

(6.0)

0

(0)

5/*14

0

(0)

1

(1.0)

0

(0.0)

2

(2.0)

0

(0)

*

5/ 36

1

(0.1)

0

(0)

0

(0)

0

(0)

0

(0)

*

*

* * * * *

*

*

* * *

5/ 41

1

(0.1)

0

(0)

0

(0)

0

(0)

0

(0)

10/*10

149

(15.2)

18

(18.0)

26

(26.0)

19

(19.0)

0

(0)

10/*10×2

5

(0.5)

0

(0)

0

(0)

0

(0)

0

(0)

*

10/ 14

4

(0.4)

0

(0)

1

(1.0)

0

(0.0)

0

(0)

*

10/ 35

1

(0.1)

0

(0)

0

(0)

0

(0)

0

(0)

10/ 36

0

(0)

0

(0)

0

(0)

2

(2.0)

0

(0)

10/*41

7

(0.7)

0

(0)

0

(0)

0

(0)

0

(0)

*

*

* * * * * *

*

‡ §

Data sampled from four regions in Japan (Hirosaki, Asaka, Kinki and Mie) [170, Yasui-Furukori et al. Unpublished Data]. From [169].

670



Review

N-CLB–CLB concentration ratio is depenTable 6. Human drug-metabolizing cytochrome P450 isoforms dent on the number of mutated alleles of identified in the brain. CYP2C19 (gene–dose effect). This ratio in Cell type Ref. patients with two mutated alleles was more CYP isoform Brain region than sixfold higher than in patients with CYP1A1 [174] Brain cortex Neurons wild-type alleles [163] . [175] CYP1B1 Temporal lobe Neurons Although the development of tolerance [176] Cerebellum and hippocampus Astrocytes and neurons was not affected by genotype, the responder CYP2B6 [177] Cortex, hippocampus and cerebellum Neurons rate was greater in PMs and heterozygous CYP2D6 EMs than in homozygous EMs with a CYP2E1 [178] Cerebellum Neurons gene–dose effect [164] . Thus, gene testing [179] CYP3A4 Neurons of CYP2C19 is a valuable parameter for Brain barriers Endothelial and epithelial [180] screening patients at risk for side effects and CYP4×1 for predicting the effects of drugs at various CYP: Cytochrome P450. dosages. This is particularly important in Asian populations, where mutant allele frequency is high. The affected the activity of CYP1A2, CYP2E1 and CYP3A4/5. The overall effect of CYP3A4 inducer on N-CLB metabolism is small, authors of this important study conclude that equivalent plasma indicating that the CYP2C19 genotype is the major determinant drug concentrations and metabolic profiles can be expected for of N-CLB concentration. native Japanese, first- and third-generation Japanese, Koreans and The AEDs CBZ, PB and PHT are inducers of CYP3A (Table 4) Chinese for compounds handled through these six CYP enzymes. and are, in turn, metabolized by the induced CYP3A enzymes. The study did not find any subjects with CYP3A4*1B in Asian This feedback regulation influences drug response. The induc- populations but did find this allele in Caucasian populations. tion affects the efficacy of coadministered AEDs and the inhibi- This is a comprehensive and informative study but the major tion, for instance, by ingestion of pomegranate juice, may cause setback was that study population was small (82–143 subjects). unwanted effects of CYP3A substrate CBZ [165] . Further studies with a larger number of subjects are needed to The antithetical effects of CYP3A5 genotypes have been identify the precise incidence of genetic variance and metabolic reported. Mouly et al. reported that the CYP3A5*1 genotype profile (Table 5) [169,170] . was associated with increased mean apparent oral clearance Regarding CYP3A5, there were cases with *1B, *1C or *6 in * of saquinavir [166] . In another study, CYP3A5 3 genotype did Caucasians, but not in Asians, and unreported variants of not affect the pharmacokinetics of intravenous midazolam in CYP3A4/5 may exist (Yasui-Furukori N et al., Unpublished Data) . A difKorean subjects [167] . The CYP3A5*3 allele was found to contrib- ference in the expression levels of CYP3A4, CYP3A5 and CYP3A7 ute only slightly to the large interindividual variation of CBZ mRNA was observed in the livers of Japanese and Caucasian pharmacokinetics [168] . subjects. Moreover, these levels were higher in the Japanese popuStudies of the impact of CYP genotypes on AED pharmaco lation compared with Caucasians. The levels of CYP3A4 mRNA kinetics have not yet been conducted on the full range of AEDs in the livers of Caucasians did not correlate with those of CYP3A5 that are used in the clinical setting. After identification of the mRNAs in Japanese, in contrast to coregulatory expression of genes that code for CYPs or other enzymes responsible for metab- CYP3A4, CYP3A5 and CYP3A7 in the livers of Caucasians, indiolism, the genetic variation that distinguishes the PM from the cating the existence of ethnic differences in the expression levels rapid metabolizer will become a significant factor in adjusting of liver CYP3A mRNAs between Japanese and Caucasians adults. AED dose to a level that could account for the predicted metabo- It is possible that the mechanism(s) regulating hepatic CYP3A lism. Drug monitoring may be especially useful for personal- expression may be different between these ethnic groups [171] . The izing pharmacotherapy for the intermediate metabolizer, since significance of CYP3A5 coding variants has been reported but it is unclear how the intermediate metabolizer phenotype affects they occur at relatively low allelic frequencies and their functional drug and dose selection. significance has not yet been established. The allele frequency of CYP2C9*2 and that of CYP2C9*3 are Ethnic differences in frequency of CYP variants higher in Caucasians than those in Asians. Conversely, the allele The data accumulated to date clearly implicate ethnicity as a fac- frequencies of CYP2C19*2 and CYP2C19*3 are high in Asian tor that influences drug response and disease state. The nature of populations in comparison with those of Caucasians [153,169–173] . the association of pharmacokinetics and genotypes in major CYP Recently, genotyping of CYPs and transporters has been conenzymes has been determined in Japanese, Korean, Chinese and ducted to determine whether or not differences in the frequency Caucasian populations by Myrand et al. [169] . They reported that exist among Japanese people (n = 1002) sampled from four differthe mean metabolic ratios (MRs) for these four ethnic groups ent regions in Japan. No substantial difference in the frequency of were similar, except for a lower activity of CYP2D6 in Caucasians genotypes was found that would justify a nationwide collection of and CYP2C19 in Asians. Genotype, not ethnicity, impacted the samples. The frequency of CYP alleles that resulted in homozyMRs for CYP2C9, CYP2C19 and CYP2D6; neither of them gote PM status in Japanese was less than 1% for CYP2C9*2 and www.expert-reviews.com

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Table 7. Ethnic variability in frequency of MDR1 and MRP2 genotypes. Gene

Polymorphism Genotypes

Frequency of MDR1 and MRP2 genotypes (%)* Japanese Chinese European Nigerian

MDR1 (ABCB1)

A61G (rs9289564)

T129C (rs1202183)

C3435T (rs1045642)

C1236T (rs1128503)

A/A

100

100

80.0

100

A/G

0

0

20.0

0

G/G

0

0

0

0

T/T

100

100

100

100

T/C

0

0

0

0

C/C

0

0

0

0

T/T

20.5

20.0

24.1

1.7

T/C

54.5

40.0

60.3

18.6

C/C

25.0

40.0

15.5

79.7

T/T

33.3

48.9

13.3

1.8

T/C

48.9

40.0

51.7

21.1

C/C

17.8

11.1

35.0

77.2

32.2

100

The identification of the genotype of patients prior to AED treatment can prevent unwanted effects of AEDs, such as SJS [144] , and shorten periods for titration. Unfortunately, no large clinical association studies have been conducted that can provide relevant data and only a few reports are available on the newer AEDs. The usefulness of most published reports on epilepsy is limited by the lack of information regarding the concomitant use of drug by the subjects in the study, comorbidities, ethnic origin, medications and seizure phenotype, along with a lack of dose information for the AEDs. Therefore, greater effort is needed to accumulate drug–response data used for each AED-related CYP(s), regardless of whether or not they have an impact on treatment efficacy. Functions of CYPs in the brain

The main site for CYP-dependent drug metabolism in humans and mammals is G/T 55.9 0 the liver; however, several CYP isoforms occur in defined cellular populations of T/T 11.9 0 the brain. Table 6 summarizes the CYPs G/G reported in the human brain [174–180] . The G/A cerebral isoforms CYP2B1, CYP2B10, CYP2C29, CYP3A11 and CYPsA13 are A/A inducible by AEDs. Although the funcC3435T T/T 20.5 20.0 24.1 1.7 tion of these CYPs in the brain is poorly (rs1045642) T/C 54.5 40.0 60.3 18.6 understood, it is hypothesized that CYPs C/C 25.0 40.0 15.5 79.7 in the brain may have functions other than drug metabolism and may be regulated difrs13233308 T/T 18.2 33.3 13.3 0 ferently than the liver enzymes [181] . CYPs T/C 56.8 46.7 60.0 0 most probably play an important role in C/C 25.0 20.0 26.7 100 the biosynthesis of neurosteroids and in MRP2 G1249A G/G 82.2 84.4 58.3 60.0 neurotransmission [182] . Recently, CYP3A2 (ABCC2) (rs2273697) and CYP3A11 have been reported to be G/A 17.8 15.6 36.7 36.7 crucial mediators of androgen receptor A/A 0 0 5.0 3.3 expression and signaling after AED treatC3972T C/C 52.3 51.1 40.0 51.7 ment [183] . Treatment of epilepsy with a (rs3740066) C/T 38.6 44.4 51.7 41.7 CYP-inducing AED is associated with negative mood state, menstrual disorders, T/T 9.1 4.4 8.3 6.7 infertility, impotency and obesity. These G4544A G/G 100 100 88.1 78.3 conditions are thought to originate from (rs8187710) G/A 0 0 11.9 21.7 reduced testosterone levels, most probably A/A 0 0 0 0 by its enhanced catabolism within the brain * [184] . In specified regions of the brain, such Data obtained from HapMap Phase II [301]. as the hypothalamus, hippocampus and 2–5% for CYP2C9*3, 32% for 2C19*2, 5–10% for 2C19*3 and striatum, CYPs provide signaling molecules, such as steroids and 75.6% for CYP3A4/5*3 [169] . Such prospective studies involving fatty acids, necessary for neuronal outgrowth and maintenance. a large number of subjects and genotype–phenotype analysis in Induction of these CYPs by neuroactive drugs, such as AEDs, can each ethnic group would establish a firm basis for the development alter steroid hormone signaling directly in drug target cells, which of individualized medicine. may cause clinically relevant side effects, as mentioned previously. G2677 T/A (rs2032582)

672

G/G



Thus, the understanding of brain CYP function appears to be of major interest in long-term drug-mediated therapy of neurological diseases such as epilepsy [185] . Transporters

A number of AED efflux transporters, such as Pgp and multidrug-resistance-associated proteins (MRPs), have been identified (Table 4) . They are expressed in the brain and intestine. In the brain, they are located in the apical membrane of capillary endothelial cells that form the blood–brain barrier (BBB). Since breast cancer-resistance protein is also normally located at the BBB (mainly at the luminal surface of microvessel endothelium) it is possible that it acts as an additional barrier for the drug to access the brain [191] . Pathologically elevated expression of Pgp has been found in the region of experimentally induced seizure foci and in spatial association with a number of clinical neuropathologies associated with uncontrolled seizures [186] . This was supported by Vogelgesang’s study, where the expression of Pgp was predominantly observed in endothelial cells of brain capillaries and in process-bearing astrocytes in dysembryoplastic neuroepithelial tumor samples, which are often associated with AED-resistant epilepsy [187] . MRP2, MRP5 and BCRP were also overexpressed and localized in the endothelium of brain capillaries, together with reactive astrocytic processes and epileptogenic tissue (tumor and peritumoral tissues), respectively [187] . Numerous studies have been conducted on relationships between phenotypes (drug resistant or not) and genotypes (polymorphism of transporters) that regulate AED concentrations at target sites in the brain, which are based on the premise that the majority of AEDs are substrates for active efflux by one or more drug-transport proteins. However, there is significant disagreement in the literature as to whether or not AEDs are all substrates of transporters. For example, PHT and LEV were directionally transported by mouse but not human Pgp, while CBZ was not transported by Pgp [188] . None of these three AEDs were transported by MRP2 [188] . VPA is not a substrate for Pgp nor MRP1 and MRP2 in several in vivo and in vitro transport assays [189] . The effects of MDR1 polymorphisms on drug responsiveness and pharmacokinetics of CBZ have been analyzed in clinical settings in the Japanese population. Patients with CBZ-resistant epilepsy (n = 210) were more likely to have the T allele and the TT genotype at C3435T, and the TT genotype at G2677T/A (odds ratio vs the GG genotype) was observed frequently. The frequency of the T–T–T haplotype at C1236T and C3435T was significantly higher, and the CC–GG–CC diplotype was lower in the drug-resistant patients than in the drug-responsive patients. None of the MDR1 influenced the plasma CBZ levels [190] . These results were the inverse of previous findings in European patients with epilepsy [191,192] , which suggests that the influence of MDR1 polymorphisms on Pgp activity may differ among races. However, since no evidence has been presented that accounts for these discrepancies, the possibility still remains that they can be simply explained by the ethnic variability in the frequency of transporter genotypes (Table 7) [301] . www.expert-reviews.com

Review

Table 8. Mutations of nicotinic acetylcholine receptor and drug response. AED

ZNS

CBZ

BZP

S284L

+++

±

++

S280L

++

++

++

T293I

++

±

++

Ins259L

++

+++

++

V287M

++

±

++

V287L

++

+++

++

I312M

++

+++

++

CHRNA4

CHRNB2

The responsiveness of AEDs has been determined by clinical experience. S284L-TG rat shows similar AED response to humans. AED: Anti-epileptic drug; BZP: Benzodiazepine; CBZ: Carbamazepine; ZNS: Zonisamide.

Simon et al. observed that low CBZ plasma levels showed a trend towards higher intestinal MDR1 expression and that CBZ dose correlated positively with MRP2 expression [193] . MDR1 expression and the CBZ and PHT dose requirement were found to be influenced by the genotype in positions 2677 and 3435 of the MDR1 gene. Based on these results, the authors suggested that the difference in intestinal MDR1 and MRP2 expression might influence CBZ and PHT disposition and account for inter-individual pharmacokinetic variability. In a study using mdr1a-knockout mice, no increase in brain uptake of PB, PHT, CBZ, VGP, LTG or GBP was observed between knockout mice and control wild-type mice. Among the AEDs studied, only TPM showed a twofold increase [194] . A recent study failed to find a significant association between MRP2 haplotype and drug resistance in 279 Japanese epilepsy patients, although the delGCGC haplotype at G-a774delG, C-24T, G1249A and C3972T was overrepresented among patients with mental retardation in comparison with patients who did not have this condition [195] . Despite the great efforts that have been expended, the association of MRPs and MDR1 genetic variations with clinical phenotype are not yet understood. In specific experimental models, both seizures and AED treatment can induce MDR1 expression, thus amplifying the effect of MDR1 genotype on Pgp quantity and function [196] . Genetic variation within MDR1 affects the structure and transport function of the encoded Pgp [197] , indicating not only that the transport function of Pgp depends on genotype at specific loci within MDR1, but also that differences in transport function are exaggerated when the transcription machinery is put under stress such as increased gene expression [198] . Therefore, to evaluate the impact of polymorphisms of transporters on individualized medicine for epilepsy, a definition of the degree of drug response must be established and it must be determined whether or not the epilepsy phenotype affects the drug response. It is only then that the following issues can be resolved: • Whether major AEDs are substrates for Pgp, MRPs or both • The impact of allelic variants of transporters on efflux efficacy 673

Review


• The degree that the ethnic difference of transporters has on efflux efficacy • The difference between species and tissue in expression at the BBB A greater understanding of the properties of these transporters will further the development of individualized medicine to a greater degree. Recently, a novel mechanism of epilepsy multidrug resistance has been described. Ral-binding protein 1 (RLIP76), a protein that catalyzes the ATP-dependent transport of glutathione conjugates, has been proposed as an alternative mechanism of drug resistance in epilepsy [199–201] . However, in a retrospective cohort study, Soranzo et al. demonstrated that no association exists between common genetic variants in the RLIP76 gene and drug resistance [202] . Leschziner et al. were also unable to find evidence supporting the suggestion that RLIP76 polymorphisms have a role in drug resistance in epilepsy [203] . Thus, it is unlikely that common variants in RLIP76 contribute to drug response in epilepsy. Tools to assist analysis of drug response

In the context of true individualized medicine, pharmacodynamic analysis is key for evaluating therapeutic response, and the pathomechanisms of epileptogenesis must be considered. Clinical data that enable the prediction/estimation of drug response by each mutation of a responsible gene in patients are required. However, this is almost impossible in reality, since numerous unknown responsible genes and/or susceptible genes may exist. Animal models can help speed up the data collection, provided that they are similar to clinical cases in terms of etiology, biochemistry, symptomatology and treatment. An epilepsy animal model must conform to three validation criteria: face validity, construct validity and predictive validity. Face validity is the ability to fundamentally mimic the seizure characteristics of epilepsy. Construct validity conforms to a theoretical rationale for epilepsy. Predictive validity is the ability to predict unknown aspects of behavior, genetics and neurobiology of epilepsy from the model [204] . Recently, a series of transgenic animal models bearing human epilepsy genes, such as ADNFLE (S284L-TG of CHRNA4), has been generated for use as an evaluative tool for determining the therapeutic efficacy of AEDs [205,206] . S284L-TG fulfilled the criteria for animal models, and the therapeutic response of the rats to ZNS, CBZ

and diazepam was quite similar to that of epileptic patients with this mutation, namely that S284L-TG responded to ZNS and diazepam, but not to CBZ (Table 8) [139] . The response of AEDs to epilepsy genes will be evaluated effectively by mutations by developing this kind of animal model that, when used in combination with clinical data, may lead to more accurate selection of AEDs. Expert commentary

Development of the system for true individualized medicine of epilepsy will be difficult without the inclusion of data from animal models that fulfill the criteria for the transgenic animal model. These data are critical for the following reasons: • Many new drugs await introduction into the market; • There are profound ethnic differences in genotype frequencies of CYP and transporters, even in polymorphisms at target sites of AEDs; • The response of AEDs differs greatly among mutations found in epilepsy patients and even within the same epilepsy phenotype; • For better understanding of drug response, monopharmacy cases must be analyzed with a large number of subjects in each ethnic group where stratification by seizure type or epilepsy syndrome is crucial. For these reasons, the inclusion of animal data and the introduction of tools such as the DNA chip for genetic testing are essential for the rapid development of a system of individualized medicine. The collaboration of research institutions worldwide would make individualized medicine a reality in the treatment of epilepsy. In the coming years, new genes and susceptible genes for epilepsy will be identified at a rapid pace, in keeping with the continual advances in mutation-detection technologies. Already, more new tools, such as the animal model for epilepsy and DNA chips, are rapidly becoming available. Ultimately, by combining these innovative technologies, selection of the most effective AEDs and optimized dosage for patients can be established based on the mechanisms of action of AEDs in the future. Five-year view

Over the next 5 years, much advancement with regard to the targets of AEDs – epilepsy genes and gene families associated with common phenotypes of epilepsy – might be achieved

Key issues • Pharmacogenetic studies are yet to explain why 20–25% of patients do not respond to anti-epileptic drugs (AEDs). • There is no convincing clinical evidence that P-glycoprotein at the blood–brain barrier limits the uptake of AEDs into the brains of epileptic patients and contributes to drug-resistance phenotype. Much more research is needed to establish the transporters that have a clinical impact on AED response. The definition of drug responsiveness should take into account current discrepancies in association studies between genetic variations in transporters and cytochrome P450s and the clinical phenotype of drug response. • The pharmacokinetic and clinical consequences still need to be evaluated for most AEDs. Most of the data currently available in the literature are based on observations of epileptic patients treated with polypharmacy, ignoring stratification by epilepsy seizure type or epilepsy syndrome. In future studies, the phenotype–genotype relationship must be examined in monopharmacy cases and stratification by epilepsy phenotype must be taken into account to exclude confounding factors.

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Financial & competing interests disclosure

This study was supported by grants from the Ministry of Education, Science and Culture of Japan (No. 16109006), the Epilepsy Research Foundation, Japan, a Research Grant for Nervous and Mental Disorders from the Ministry of Health and Welfare, the Hirosaki Research Institute for Neurosciences, and Hirosaki University. The authors are indebted to all members for their helpful cooperation of the Genetic Study Group, Japan (Chair person: S Kaneko). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.

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Review

Affiliations •

Sunao Kaneko Department of Neuropsychiatry, Hirosaki, University Graduate School of Medicine, Zaifu-cho 5, Hirosaki, 036‑8562, Japan Tel.: +81 172 395 066 Fax: +81 172 395 067 [email protected]

•

Shuichi Yoshida Department of Neuropsychiatry, Hirosaki, University Graduate School of Medicine, Zaifu-cho 5, Hirosaki, 036‑8562, Japan Tel.: +81 172 395 066 Fax: +81 172 395 067 [email protected]

•

Kazuaki Kanai Department of Neurology, Graduate School of Medicine, Chiba University, Chu Ooku 1–8–1, Chiba, 260-8670, Japan Tel.: +81 432 227 171; ext 5414 Fax: +81 432 262 160 [email protected]

•

Norio Yasui-Furukori Department of Neuropsychiatry, Hirosaki, University Graduate School of Medicine, Zaifu-cho 5, Hirosaki, 036‑8562, Japan Tel.: +81 172 395 066 Fax: +81 172 395 067 [email protected]

•

Hiroto Iwasa Department of Neuropsychiatry, Hirosaki, University Graduate School of Medicine, Zaifu-cho 5, Hirosaki, 036-8562, Japan Tel.: +81 172 395 066 Fax: +81 172 395 067 [email protected]

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