Optimization of Clonazepam Therapy Adjusted to Patient’s CYP3A Status andNAT2Genotype

Abstract

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 nongenetic factors.Methods:Since the prominent role in clonazepam nitro-reduction and acetylation of 7-amino-clonazepam is assigned to CYP3A and N-acetyl transferase 2 enzymes, respectively, the association between the patients’ CYP3A status (CYP3A5 genotype, CYP3A4 expression) or N-acetyl transferase 2 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 bodyweight (1263.5±482.9 and 558.5±202.4ng/mL per mg/kg bodyweight in low and normal expressers, respectively, P<.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±0.024mg/kg bodyweight, P<.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 slower N-acetylation than all the others.Conclusion:Prospective assaying of CYP3A4 expression and N-acetyl transferase 2 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.

Variations in Dysbindin-1 are associated with cognitive response to antipsychotic drug treatment

“…All antipsychotic drugs interact with dopamine D2 receptors 13 , with variable ranges of D2 occupacy suggested to be important for optimal clinical and cognitive responses 13 – 15 . From a pharmacokinetic perspective, genetic variations such as those in CYP2D6 , CYP3A4/5 , and ABCB1 might impact the metabolism and distribution of antipsychotic drugs, potentially affecting the margin between the dosages that are required for efficacy and those associated with side effects 16 , 17 . Shifting to a pharmacodynamic perspective, genetic variations influencing D2 receptors could in principle also influence the efficacy of antipsychotic drugs 13 .…”

Phenoconversion of CYP2D6 by inhibitors modifies aripiprazole exposure

“…The non-genetic factors, such as age, hormonal status or transcriptional induction by CYP3A-inducers, such as carbamazepine or valproic acid, can mask the effect of genetic factors on CYP3A4 expression [2,46]; therefore, for the categorization of the patients regarding CYP3A4 expression, more useful information can be obtained from CYP3A4 mRNA levels than from CYP3A4-genotyping. CYP3A-metabolizing capacity determined by CYP3A4 expression in leukocytes was demonstrated to inform about the hepatic activity towards CYP3A substrates, such as ciclosporin, tacrolimus or clonazepam [43,47].…”

Refined Prediction of Pharmacokinetic Kratom-Drug Interactions: Time-Dependent Inhibition Considerations

“…5.3 Citalopram CYP3A, CYP2C19, CYP2D6 (von Moltke et al, 2001) 7 3.5 Furanyl-fentanyl NA NA 8 2.5 Temazepam, olanzapine, sertraline, clonazepam CYP3A, CYP2C9, CYP2C19, CYP2D6, UGT2B7 (Kobayashi et al, 1999;Urichuk et al, 2008;Tóth et al, 2016) 9 0.42 3,4-Dimethoxy-Nmethylamphetamine NA NA 10 6.7 Etizolam, nordiazepam, mirtazapine CYP3A, CYP2D6, CYP1A2 (Onof et al, 1996;Störmer et al, 2000;Niwa et al, 2005) 11 12 2,4,5-Trimethoxyamphetamine CYP2D6 (Ewald and Maurer, 2008) 12 0.62 Oxycodone CYP3A, CYP2D6 (Lalovic et al, 2004) 13 1.9 Oxycodone, fentanyl, cocaine CYP3A, CYP2D6, esterases (Kamendulis et al, 1996;Guitton et al, 1997;Kanamori et al, 2019) 14 Table 3. Prediction of CYP3A-mediated kratom-drug interactions via a mechanistic static model.…”