Optimization of clonazepam therapy adjusted to patient's CYP3A-status and NAT2 genotype.

BACKGROUND: The shortcomings of clonazepam therapy include tolerance, withdrawal symptoms and adverse effects, such as drowsiness, dizziness and confusion leading to increased risk of falls. Inter-individual variability in the incidence of adverse events in patients partly originates from the differences in clonazepam metabolism due to genetic and non-genetic factors. METHODS: Since the prominent role in clonazepam nitro-reduction and in acetylation of 7-amino-clonazepam is assigned to CYP3A and NAT2 enzymes, respectively, the association between the patients' CYP3A-status (CYP3A5 genotype, CYP3A4 expression) or NAT2 acetylator phenotype and clonazepam metabolism (plasma concentrations of clonazepam and 7-amino-clonazepam) was evaluated in 98 psychiatric patients suffering from schizophrenia or bipolar disorders. RESULTS: The patients' CYP3A4 expression was found to be the major determinant of clonazepam plasma concentrations normalized by the dose and the bodyweight (1263.5+/-482.9 and 558.5+/-202.4 ng/ml per mg/kg bw in low and normal expressers, respectively, P<0.0001). Consequently, the dose-requirement for the therapeutic concentration of clonazepam was substantially lower in low CYP3A4 expresser patients than in normal expressers (0.029+/-0.011 vs 0.058+/-0.024 mg/kg bw, P<0.0001). Furthermore, significantly higher (about 2-fold) plasma concentration ratio of 7-amino-clonazepam and clonazepam was observed in the patients displaying normal CYP3A4 expression and slow N-acetylation than all the others. CONCLUSION: Prospective assaying of CYP3A4 expression and NAT2 acetylator phenotype can better identify the patients with higher risk of adverse reactions and can facilitate the improvement of personalized clonazepam therapy and withdrawal regimen

Optimization of clonazepam therapy adjusted to patient's CYP3A-status and NAT2 genotype

BACKGROUND: The shortcomings of clonazepam therapy include tolerance, withdrawal symptoms and adverse effects, such as drowsiness, dizziness and confusion leading to increased risk of falls. Inter-individual variability in the incidence of adverse events in patients partly originates from the differences in clonazepam metabolism due to genetic and non-genetic factors. METHODS: Since the prominent role in clonazepam nitro-reduction and in acetylation of 7-amino-clonazepam is assigned to CYP3A and NAT2 enzymes, respectively, the association between the patients' CYP3A-status (CYP3A5 genotype, CYP3A4 expression) or NAT2 acetylator phenotype and clonazepam metabolism (plasma concentrations of clonazepam and 7-amino-clonazepam) was evaluated in 98 psychiatric patients suffering from schizophrenia or bipolar disorders. RESULTS: The patients' CYP3A4 expression was found to be the major determinant of clonazepam plasma concentrations normalized by the dose and the bodyweight (1263.5+/-482.9 and 558.5+/-202.4 ng/ml per mg/kg bw in low and normal expressers, respectively, P<0.0001). Consequently, the dose-requirement for the therapeutic concentration of clonazepam was substantially lower in low CYP3A4 expresser patients than in normal expressers (0.029+/-0.011 vs 0.058+/-0.024 mg/kg bw, P<0.0001). Furthermore, significantly higher (about 2-fold) plasma concentration ratio of 7-amino-clonazepam and clonazepam was observed in the patients displaying normal CYP3A4 expression and slow N-acetylation than all the others. CONCLUSION: Prospective assaying of CYP3A4 expression and NAT2 acetylator phenotype can better identify the patients with higher risk of adverse reactions and can facilitate the improvement of personalized clonazepam therapy and withdrawal regimen

An algorithm for rapid computational construction of metabolic networks: A cholesterol biosynthesis example

Alternative pathways of metabolic networks represent the escape routes that can reduce drug efficacy and can cause severe adverse effects. In this paper we introduce a mathematical algorithm and a coding system for rapid computational construction of metabolic networks. The initial data for the algorithm are the source substrate code and the enzyme/metabolite interaction tables. The major strength of the algorithm is the adaptive coding system of the enzyme-substrate interactions. A reverse application of the algorithm is also possible, when optimisation algorithm is used to compute the enzyme/metabolite rules from the reference network structure. The coding system is user-defined and must be adapted to the studied problem. The algorithm is most effective for computation of networks that consist of metabolites with similar molecular structures. The computation of the cholesterol biosynthesis metabolic network suggests that 89 intermediates can theoretically be formed between lanosterol and cholesterol, only 20 are presently considered as cholesterol intermediates. Alternative metabolites may represent links with other metabolic networks both as precursors and metabolites of cholesterol. A possible cholesterol-by-pass pathway to bile acids metabolism through cholestanol is suggested

Additional file 3: of Transcriptome study and identification of potential marker genes related to the stable expression of recombinant proteins in CHO clones

Names and biological functions of the 14 potential marker genes. Short and full gene names including biological functions of the 14 potential marker genes. (XLSX 13 kb

Dehydroepiandrosterone post-transcriptionally modifies CYP1A2 induction involving androgen receptor.

The pharmacological dosage of dehydroepiandrosterone (DHEA) protects against chemically induced carcinogenesis. The chemoprotective activity of DHEA is attributed to its inhibitory potential for the expression of CYP1A enzymes, which are highly responsible for metabolic activation of several mutagenic and carcinogenic chemicals. The present work investigated whether the chemoprevention by DHEA was due to diminished transcriptional activation of CYP1A genes or to the post-transcriptional modulation of CYP1A expression. In primary human hepatocytes, DHEA diminished the increase in CYP1A activities (7-ethoxyresorufin O-dealkylation and phenacetin O-dealkylation) and in CYP1A2 mRNA level induced by 3-methylcholanthrene, but did not alter the amount of CYP1A1 and CYP1B1 mRNA. The androgen receptor seemed to be involved in DHEA-mediated diminishment of CYP1A2 induction, which was attenuated in the presence of bicalutamide, the androgen receptor antagonist. The potential role of the glucocorticoid receptor and estrogen receptor in DHEA-mediated decrease in CYP1A2 induction was excluded. The developed computational model of CYP1A2 induction kinetics and CYP1A2 mRNA degradation proposed that a posttranscriptional mechanism was likely to be the primary mechanism of the DHEA-mediated diminishment of CYP1A2 induction. The hypothesis was confirmed by the results of actinomycin D-chase experiments in MCF-7 and LNCaP cells, displaying that the degradation rates of CYP1A2 mRNA were significantly higher in the cells exposed to DHEA. The novel findings on DHEA-mediated modulation of CYP1A2 mRNA stability may account for the beneficial effects of DHEA by decreasing the metabolic activation of procarcinogenic compounds

Phenoconversion of CYP2D6 by inhibitors modifies aripiprazole exposure

The efficacy of aripiprazole therapy and the risk of adverse reactions are influenced by substantial inter-individual variability in aripiprazole metabolizing capacity. In vitro studies assigned the potential role in aripiprazole metabolism to CYP2D6 and CYP3A enzymes; therefore, the association between the steady-state aripiprazole plasma concentrations and patients' CYP2D6 and CYP3A statuses (CYP2D6, CYP3A4, and CYP3A5 genotypes, and CYP3A4 expression) and/or co-medication with CYP function modifying medications has been investigated in 93 psychiatric patients on stable aripiprazole therapy. The patients' CYP2D6 genotype had a major effect on aripiprazole plasma concentrations, whereas contribution of CYP3A genotypes and CYP3A4 expression to aripiprazole clearance were considered to be minor or negligible. The role of CYP3A4 expression in aripiprazole metabolism did not predominate even in the patients with nonfunctional CYP2D6 alleles. Furthermore, dehydroaripiprazole exposure was also CYP2D6 genotype-dependent. Dehydroaripiprazole concentrations were comparable with aripiprazole levels in patients with functional CYP2D6 alleles, and 35% or 22% of aripiprazole concentrations in patients with one or two non-functional CYP2D6 alleles, respectively. The concomitant intake of CYP2D6 inhibitors, risperidone, metoprolol, or propranolol was found to increase aripiprazole concentrations in patients with at least one wild-type CYP2D6*1 allele. Risperidone and 9-hydroxy-risperidone inhibited both dehydrogenation and hydroxylation of aripiprazole, whereas metoprolol and propranolol blocked merely the formation of the active dehydroaripiprazole metabolite, switching towards the inactivation pathways. Patients' CYP2D6 genotype and co-medication with CYP2D6 inhibitors can be considered to be the major determinants of aripiprazole pharmacokinetics. Taking into account CYP2D6 genotype and co-medication with CYP2D6 inhibitors may improve the outcomes of aripiprazole therapy