PhD Scientific Days 2019

Budapest, April 25–26, 2019

CYP3A4 expression potentially predicts metabolic side effects of clozapine in patients with schizophrenia

Menus, Ádám

Dr. Adam Menus
Semmelweis University Department of Psychiatry and Psychotherapy

Language of the presentation

Hungarian

Text of the abstract

Introduction
Clozapin is an atypical antipsychotic which is indicated in treatment resistant schizophrenia and for psychotic symptoms occuring during the course of Parkinson’s disease. Patients treated with clozapine have higher risk for rapid weight gain and developing metabolic side effects like elevated glucose levels, type 2 diabetes mellitus, and hyperlipidaemia. Clozapine is metabolised in the liver by cytochorome enzymes in consequence its plasma concentration shows high inter-individual variabilaty, therefore therapeutic drug monitoring during clozapine treatment is recommended.
Aims
The aim of our study was to investigate the association between drug metabolizing capacity and metabolic side effects of clozapine.
Method
We recruited patients with schizophrenia who were treated with clozapin. After signing the informed consent blood samples were collected in order to measure the plasma concentration of clozapin, and determining the drug metabolizing capacity with genotyping and phenotyping the relevant CYP enzymes. CYP mRNA levels were measured in peripheral leukocytes. We also evaluated the patients actual physical and mental status. Patients were on stable clozapine doses for one week in order to reach steady state concentration.
Results
In patients with low CYP3A4 expression (n=20) significant correlation was found between clozapine plasma concentrations and elevated blood glucose levels while in normal/ high CYP3A4 expressers (n=?) no correlation was observed. High clozapine levels (>600ng/ml) and severe obesity were significantly (p<0,05) more frequent in the low CYP3A4 expresser group (n=20)
Conclusion
CYP3A4 status should be taken into account before initiation of clozapine therapy because it may help in predicting the risk of metabolic side effects.

Data of the presenter

Mental Health Science Doctoral School
Psychiatry Program
Supervisor: prof. Dr. István Bitter
E-mail address: menus.adam@med.semmelweis-univ.hu