Evidence map›Paper›PMID 17375979›Full record

ReviewClinical pharmacokinetics2007

The role of pharmacogenetics in the metabolism of antiepileptic drugs: pharmacokinetic and therapeutic implications.

Ulrich Klotz

Abstract readReview
PubMed Publisher
In one paragraph

Review in Clinical pharmacokinetics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
14.6field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 131 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Pharmacogenetic and pharmacogenomic discovery strategies.Cancer drug resistance (Alhambra, Calif.) · 2019
    Review
  6. Review
  7. CYP2C9 polymorphisms in epilepsy: influence on phenytoin treatment.Pharmacogenomics and personalized medicine · 2018
    Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. The effect of polymorphic metabolism enzymes on serum phenytoin level.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2015
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Ulrich KlotzDr Margarete Fischer-Bosch Institut für Klinische Pharmakologie, Stuttgart, Germany. ulrich.klotz@ikp-stuttgart.de
Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several different factors, including pharmacogenetics, contribute to interindividual variability in drug response. Like most other agents, many antiepileptic drugs (AEDs) are metabolised by a variety of enzymatic reactions, and the cytochrome P450 (CYP) superfamily has attracted considerable attention. Some of those CYPs exist in the form of genetic (allelic) variants, which may also affect the plasma concentrations or drug exposure (area under the plasma concentration-time curve [AUC]) of AEDs. With regard to the metabolism of AEDs, the polymorphic CYP2C9 and CYP2C19 are of interest. This review summarises the evidence as to whether such polymorphisms affect the clinical action of AEDs. In the case of mephenytoin, defects in its metabolism may be attributable to >10 mutated alleles (designated as *2, *3 and others) of the gene expressing CYP2C19. Consequently, poor metabolisers (PMs) and extensive metabolisers (EMs) could be differentiated, whose frequencies vary among ethnic populations. CYP2C19 contributes to the metabolism of diazepam and phenytoin, the latter drug also representing a substrate of CYP2C9, with its predominant variants being defined as *2 and *3. For both AEDs, there is maximally a 2-fold difference in the hepatic elimination rate (e.g. clearance) or the AUC between the extremes of EMs and PMs which, in the case of phenytoin (an AED with a narrow 'therapeutic window'), would suggest a dosage reduction only for patients who are carriers of mutated alleles of both CYP2C19 and CYP2C9, a subgroup that is very rare among Caucasians (about 1% of the population) but more frequent in Asians (about 10%). The minor contribution of CYP2C19 to the metabolism of phenobarbital (phenobarbitone) can be overlooked. In rare cases, valproic acid can be metabolised to the reactive (hepatotoxic) metabolite, 4-ene-valproic acid. It is not yet clear whether genetic variants of the involved enzyme (CYP2C9) are responsible for this problem. Likewise, the active metabolite of carbamazepine, carbamazepine-10,11-epoxide, is transformed by the microsomal epoxide hydrolase, an enzyme that is also highly polymorphic, but the pharmacokinetic and clinical consequences still need to be evaluated. Pharmacogenetic investigations have increased our general knowledge of drug disposition and action. As for old and especially new AEDs the pharmacogenetic influence on their metabolism is not very striking, it is not surprising that there are no treatment guidelines taking pharmacogenetic data into account. Therefore, the traditional and validated therapeutic drug monitoring approach, representing a direct 'phenotype' assessment, still remains the method of choice when an individualised dosing regimen is anticipated. Nevertheless, pharmacogenetics and pharmacogenomics can offer some novel contributions when attempts are made to maximise drug efficacy and enhance drug safety.

Indexed as

PharmacogeneticsPolymorphism, GeneticAllelesAnticonvulsantsAsian PeopleCytochrome P-450 Enzyme SystemDrug MonitoringGene ExpressionHumansMutationPractice Guidelines as TopicWhite PeopleAnticonvulsantsCytochrome P-450 Enzyme System

Identifiers

PMID17375979
OpenAlexW2205252735

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.