A significant inter-individual variability can be found in clinical response during antipsychotic drug therapy. In the United Kingdom, up to 30 percent of patients respond inadequately to treatment for chemical imbalances in the brain. Some of the poor response can be can be attributed to poor patient compliance in taking the prescribed medication. However, alterations in genes encoding mediators of drug efficacy may be particularly important. This includes drug metabolizing enzymes, receptor targets, and transporters. These alterations may also be important for treatment-induced side effects
Clozapine (trade name clozaril) is one of the newer antipsychotic medicines used to treat people with schizophrenia. Although clozapine is often more effective than other antipsychotic medicines, it is not suitable for everybody. Clozapine can cause a problem with the white blood cells of some people, and therefore patients take scheduled blood tests. When clozapine is first prescribed, recipients generally go into the hospital so that their reaction (which may include severe side effects) to the drug can be monitored. The amount of time people need to stay in the hospital varies, from several days to three or four weeks.
Does an individual's genetic make up determine how effective Clozapine is as a treatment and the nature of its side effects? A British research team is engaging pharmacogenetics, or how genes affect the way people respond to medicines, including antidepressants, chemotherapy treatments, asthma drugs, and many others. The ultimate goal of pharmacogenetics research is to help doctors select the most suitable form of drug therapy from the outset.
A presentation concerning "Applications of Pharmacogenetics: Genetics of Clozapine Response as a Model" is being conducted by Dalu Mancama, from the Clinical Neuropharmacology, Institute of Psychiatry, London at the 54th Annual Meeting of the American Association for Clinical Chemistry (AACC). AACC (http://www.
Dr. Mancama's presentation will highlight the following from the teams current research:
- Drug metabolizing enzymes: Antipsychotic medication metabolism is primarily mediated by the cytochrome P450 (CYP) isoenzymes. Currently more than 30 distinct subtypes have been identified (enzymes CYP1A2, CYP3A4, CYP2D6 and CYP2C19 of particular importance).
- Drug enzyme interaction: The metabolic relationship between antipsychotic medications Haloperidol, Ziprasidone, Risperidone, Olanzapine, Quetiapine, Sertindole, and Clozapine to enzymes CYP1A2, CYP2D6, CYP3A4, CYP2D6, CYP3A4, CYP1A2,CYP2D6, CYP3A4, CYP2D6, CYP1A2, and CYP3A4.
- Genetic variation and enzyme function: That the influence of genetic polymorphisms of CYP enzyme activity is well established and is extensively demonstrated for the CYP2D6 subtype. Essentially, the polymorphisms confer certain types of differences in drug metabolism for clozapine, which results in extensive metabolizers (EM) for 75-85 percent of the population, poor metabolizers (PM) is for 10-l5 percent of the population, and ultra-metabolizers (UM) is between one and ten percent of the population.
- Assessment of the enzyme variants and drug efficacy: The evidence of association between CYP polymorphisms and drug efficacy is presently unclear due to conflicting findings for the influence of CYP2D6 variants on the steady-state plasma concentrations of haloperiodol.
- CYP enzyme variants and side effects: There is evidence demonstrating possible genetic contribution to antipsychotic treatment related side effects. Specifically, the CYP1A2 polymorphism phenotype may be more susceptible to clozapine- induced side effects, especially sedation and seizures.
- Drug receptor targets: CYP variants do not appear to solely determine patient outcome to antipsychotic treatment.
- Their research has found that current response- general response prediction for Clozapine genotypic data from four key genes (5-HT2A, 5HT2C, 5-HTT and H2) can successfully predict treatment outcome in approximately 77 percent of cases. Polymorphisms in the 5-HT2A, 5-HT2C, 5-HTT, 5HT-6 and D3 genes demonstrate similar potential for response prediction relevant polymorphisms in novel targets.
The British experience finds that future clinical applications rely on development of kit- based protocols for individualized treatment based on genetic profile. This would result in different anti-psychotics with pertinent predictor variables for optimal drug selection resulting in improved clinical management of patients and a significant reduction in treatment costs.
Editor's Note: To interview Dr. Mancama , please contact Donna Krupa at 703.527.7357 (direct dial), 703.967.2751 (cell) or email@example.com.
Or contact the AACC Newsroom at: 407.685.4215.