Evaluation of clinical and genetic factors in the population pharmacokinetics of carbamazepine

Risk-conferring HLA variants in an epilepsy cohort: benefits of multifaceted use of whole genome sequencing in clinical practice

BACKGROUND

Whole genome sequencing is increasingly used in healthcare, particularly for diagnostics. However, its clinically multifaceted potential for individually customised diagnostic and therapeutic care remains largely unexploited. We used existing whole genome sequencing data to screen for pharmacogenomic risk factors related to antiseizure medication-induced cutaneous adverse drug reactions (cADRs), such as human leucocyte antigen HLA-B*15:02, HLA-A*31:01 variants.

METHODS

Genotyping results, generated from the Genomics England UK 100 000 Genomes Project primarily for identification of disease-causing variants, were used to additionally screen for relevant HLA variants and other pharmacogenomic variants. Medical records were retrospectively reviewed for clinical and cADR phenotypes for HLA variant carriers. Descriptive statistics and the χ2 test were used to analyse phenotype/genotype data for HLA carriers and compare frequencies of additional pharmacogenomic variants between HLA carriers with and without cADRs, respectively.

RESULTS

1043 people with epilepsy were included. Four HLA-B*15:02 and 86 HLA-A*31:01 carriers were identified. One out of the four identified HLA-B*15:02 carriers had suffered antiseizure medication-induced cADRs; the point prevalence of cADRs was 16.9% for HLA-A*31:01 carriers of European origin (n=46) and 14.4% for HLA-A*31:01 carriers irrespective of ancestry (n=83).

CONCLUSIONS

Comprehensive utilisation of genetic data spreads beyond the search for causal variants alone and can be extended to additional clinical benefits such as identifying pharmacogenomic biomarkers, which can guide pharmacotherapy for genetically-susceptible individuals.

Computer-Aided (In Silico) Modeling of Cytochrome P450-Mediated Food–Drug Interactions (FDI)

Modifications of the activity of Cytochrome 450 (CYP) enzymes by compounds in food might impair medical treatments. These CYP-mediated food–drug interactions (FDI) play a major role in drug clearance in the intestine and liver. Inter-individual variation in both CYP expression and structure is an important determinant of FDI. Traditional targeted approaches have highlighted a limited number of dietary inhibitors and single-nucleotide variations (SNVs), each determining personal CYP activity and inhibition. These approaches are costly in time, money and labor. Here, we review computational tools and databases that are already available and are relevant to predicting CYP-mediated FDIs. Computer-aided approaches such as protein–ligand interaction modeling and the virtual screening of big data narrow down hundreds of thousands of items in databanks to a few putative targets, to which the research resources could be further directed. Structure-based methods are used to explore the structural nature of the interaction between compounds and CYP enzymes. However, while collections of chemical, biochemical and genetic data are available today and call for the implementation of big-data approaches, ligand-based machine-learning approaches for virtual screening are still scarcely used for FDI studies. This review of CYP-mediated FDIs promises to attract scientists and the general public.

ABCB1 c.3435C > T and EPHX1 c.416A > G polymorphisms influence plasma carbamazepine concentration, metabolism, and pharmacoresistance in epileptic patients

The gene polymorphisms of ABCB1, EPHX1, and SCN1A were found to influence carbamazepine (CBZ) metabolism and resistance in epilepsy patients, but the relevance remains controversial. To reveal the relationships among the gene polymorphisms of ABCB1, EPHX1, SCN1A and the metabolism and resistance of CBZ, the databases of PubMed, EMBASE, Cochrane Library, Chinese National Knowledge Infrastructure, Chinese Science and Technique Journals, China Biology medicine disc and Wan Fang were retrieved for suitable studies up to April 2021. 18 studies containing 3293 epilepsy patients were included. The result revealed the gene polymorphism of ABCB1 c.3435C > T is significantly associated with altered concentration-dose ratios of CBZ (CDR_CBZ) (CC vs. CT, OR = 0.25 (95% CI: 0.08-0.42), P = 0.004), and EPHX c.416A > G gene polymorphism may also significantly adjusted the concentration-dose ratios of carbamazepine-10, 11-trans dihydrodiol (CDR_CBZD) (AA vs. GG, OR = 0.48 (95% CI: 0.01-0.96), P = 0.045; AG vs. GG, OR = 0.68 (95% CI: 0.16-1.20), P = 0.010, respectively) and the ratio of CBZD:carbamazepine-10,11-epoxide (CBZE) (CDR_CBZD:CDR_CBZE) (AG vs GG, OR = 0.83 (95% CI: 0.31-1.36), P = 0.002). Furthermore, ABCB1 c.3435C > T polymorphism was also observed to be significantly influenced CBZ resistance (CC vs TT, OR = 1.78 (95% CI: 1.17-2.72), P = 0.008; CT vs TT, OR = 1.60 (95% CI: 1.12-2.30), P = 0.01; CC + CT vs TT, OR = 1.61 (95% CI: 1.15-2.26), P = 0.006, respectively). Therefore, CBZ metabolism and resistance in patients with epilepsy may be adjusted by the gene polymorphisms of ABCB1 c.3435C > T and EPHX1 c.416A > G which provides the further scientific basis for clinical individualized therapy of epilepsy. However, larger sample size studies are still needed to provide further conclusive evidence.

HLA Allele-Restricted Immune-Mediated Adverse Drug Reactions: Framework for Genetic Prediction

Human leukocyte antigen (HLA) is a hallmark genetic marker for the prediction of certain immune-mediated adverse drug reactions (ADRs). Numerous basic and clinical research studies have provided the evidence base to push forward the clinical implementation of HLA testing for the prevention of such ADRs in susceptible patients. This review explores current translational progress in using HLA as a key susceptibility factor for immune ADRs and highlights gaps in our knowledge. Furthermore, relevant findings of HLA-mediated drug-specific T cell activation are covered, focusing on cellular approaches to link genetic associations to drug-HLA binding as a complementary approach to understand disease pathogenesis. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 62 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Pharmacogenetics of Carbamazepine and Valproate: Focus on Polymorphisms of Drug Metabolizing Enzymes and Transporters

Pharmacogenomics can identify polymorphisms in genes involved in drug pharmacokinetics and pharmacodynamics determining differences in efficacy and safety and causing inter-individual variability in drug response. Therefore, pharmacogenomics can help clinicians in optimizing therapy based on patient's genotype, also in psychiatric and neurological settings. However, pharmacogenetic screenings for psychotropic drugs are not routinely employed in diagnosis and monitoring of patients treated with mood stabilizers, such as carbamazepine and valproate, because their benefit in clinical practice is still controversial. In this review, we summarize the current knowledge on pharmacogenetic biomarkers of these anticonvulsant drugs.

Evaluation of clinical and genetic factors in the population pharmacokinetics of carbamazepine

Aims

Carbamazepine can cause hypersensitivity reactions in ~10% of patients. An immunogenic effect can be produced by the electrophilic 10,11‐epoxide metabolite but not by carbamazepine. Hypothetically, certain single nucleotide polymorphisms might increase the formation of immunogenic metabolites, leading ultimately to hypersensitivity reactions. This study explores the role of clinical and genetic factors in the pharmacokinetics (PK) of carbamazepine and 3 metabolites known to be chemically reactive or formed through reactive intermediates.

Methods

A combination of rich and sparse PK samples were collected from healthy volunteers and epilepsy patients. All subjects were genotyped for 20 single nucleotide polymorphisms in 11 genes known to be involved in the metabolism or transport of carbamazepine and carbamazepine 10,11‐epoxide. Nonlinear mixed effects modelling was used to build a population‐PK model.

Results

In total, 248 observations were collected from 80 subjects. A 1‐compartment PK model with first‐order absorption and elimination best described the parent carbamazepine data, with a total clearance of 1.96 L/h, central distribution volume of 164 L and absorption rate constant of 0.45 h⁻¹. Total daily dose and coadministration of phenytoin were significant covariates for total clearance of carbamazepine. EPHX1‐416G/G genotype was a significant covariate for the clearance of carbamazepine 10,11‐epoxide.

Conclusion

Our data indicate that carbamazepine clearance was affected by total dose and phenytoin coadministration, but not by genetic factors, while carbamazepine 10,11‐epoxide clearance was affected by a variant in the microsomal epoxide hydrolase gene. A much larger sample size would be required to fully evaluate the role of genetic variation in carbamazepine pharmacokinetics, and thereby predisposition to carbamazepine hypersensitivity.