ABCB1 C3435T polymorphism and the risk of resistance to antiepileptic drugs in epilepsy: A systematic review and meta-analysis

Haerian, Batoul Sadat; Harun, Roslan; Ali, Raymond Azman; Tan, Chong Tin; Lim, Kheng‐Seang; Zulkifli, S.Z.; Mohamed, E.H.M.; Tan, Hong-Kun; Mohamed, Zahurin

doi:10.1016/j.seizure.2010.05.004

Cited by 77 publications

(71 citation statements)

References 44 publications

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“…Several recent meta analyses of studies investigating the c.3435C>T polymorphism are listed in table 3. Digoxin pharmacokinetics were not affected by c.3435C>T [98] and the response to anticonvulsant drugs exhibited also no association with this polymorphism [99,100]. In contrast, the effects on cyclosporine pharmacokinetics are more complex: Overall, there was no effect of the c.3435C>T ABCB1 polymorphism on the pharmacokinetic parameters, although the total cyclosporine bioavailability (AUC 0-12 ) was slightly reduced (table 3) [101].…”

Section: Mdr1 (Abcb1)mentioning

confidence: 95%

Pharmacogenetics of Drug Transporters in the Enterohepatic Circulation

Stieger

Meier

2011

Pharmacogenomics

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This article summarizes the impact of the pharmacogenetics of drug transporters expressed in the enterohepatic circulation on the pharmacokinetics and pharmacodynamics of drugs. The role of pharmacogenetics in the function of drug transporter proteins in vitro is now well established and evidence is rapidly accumulating from in vivo pharmacokinetic studies, which suggests that genetic variants of drug transporter proteins can translate into clinically relevant phenotypes. However, a large amount of conflicting information on the clinical relevance of drug transporter proteins has so far precluded the emergence of a clear picture regarding the role of drug transporter pharmacogenetics in medical practice. This is very well exemplified by the case of P-glycoprotein (MDR1, ABCB1). The challenge is now to develop pharmacogenetic models with sufficient predictive power to allow for translation into drug therapy. This will require a combination of pharmacogenetics of drug transporters, drug metabolism and pharmacodynamics of the respective drugs.

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Section: Mdr1 (Abcb1)mentioning

confidence: 95%

Pharmacogenetics of Drug Transporters in the Enterohepatic Circulation

Stieger

Meier

2011

Pharmacogenomics

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“…Epilepsy patients with the CC genotype had lower levels of phenobarbital in the CSF and exhibited higher seizure activity [72]. The first study, in 2003, suggested that the 3435C > T polymorphism may explain resistance to AED therapy in epilepsy [73], but several other association studies, as well as meta-analyses, have clearly demonstrated that the impact of ABCB1 genetics on the pharmacoresistance of AEDs is inconsistent [62,74,75]. However, the concept that Pgp expression and function may be directly associated with pharmacoresistant temporal lobe epilepsy in patients has been very recently corroborated by a highly attractive approach investigating Pgp activity in patients with epilepsy using positron emission tomography technology [76].…”

Section: Role Of Drug Distribution For Pharmacoresponsementioning

confidence: 99%

Genetic Biomarkers in Epilepsy

et al. 2014

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The identification of valid biomarkers for outcome prediction of diseases and improvement of drug response, as well as avoidance of side effects is an emerging field of interest in medicine. The concept of individualized therapy is becoming increasingly important in the treatment of patients with epilepsy, as predictive markers for disease prognosis and treatment outcome are still limited. Currently, the clinical decision process for selection of an antiepileptic drug (AED) is predominately based on the patient's epileptic syndrome and side effect profiles of the AEDs, but not on effectiveness data. Although standard dosages of AEDs are used, supplemented, in part, by therapeutic monitoring, the response of an individual patient to a specific AED is generally unpredictable, and the standard care of patients in antiepileptic treatment is more or less based on trial and error. Therefore, there is an urgent need for valid predictive biomarkers to guide patient-tailored individualized treatment strategies in epilepsy, a research area that is still in its infancy. This review focuses on genomic factors as part of an individual concept for AED therapy summarizing examples that influence the prognosis of the disease and the response to AEDs, including side effects.

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“…Atorvastatin (Keskitalo et al, 2008) Carboplatin (Hamidovic et al, 2010) Digoxin (Johne et al, 2002) Docetaxel (Sissung et al, 2008) Fluvastatin, Pravastatin, Lovastatin, and Rosuvastatin, no effect (Keskitalo et al, 2009a) Paclitaxel (Sissung et al, 2006;Chang et al, 2010;Hamidovic et al, 2010) Simvastatin acid (Keskitalo et al, 2008) Various antiepileptic drugs (Sisodiya and Goldstein, 2007;Seo et al, 2008;Kwan et al, 2009;Haerian et al, 2010;Nurmohamed et al, 2010) Cisplatin (Filipski et al, 2009) Imatinib (White et al, 2007(White et al, , 2010a(White et al, , 2010bEngler et al, 2010) Metformin (Shu et al, 2007(Shu et al, , 2008Tzvetkov et al, 2009) …”

Section: Reduced Therapeutic Effectmentioning

confidence: 99%