Browsing by Subject "CYP2D6"

Pharmacogenetics is the study of variations in DNA sequence as related to drug response, i.e. pharmacokinetics, drug efficacy and adverse effects. The literature review of the thesis covers pharmacogenetics of analgesics. The most studied genetic variations affecting the analgesics response are the 118A>G variant of µ-opioid receptor gene (OPRM1) and several variations in the genes coding for cytochrome (CYP) P450 enzymes. Also variations in the COMT gene and the ABCB1 gene coding for P-glycoprotein have been shown to modify the response to analgesics. Genetic polymorphism of CYP2D6, CYP3A4 and CYP3A5 enzymes was studied in the experimental part of the thesis. The aim of the study was to determine if the allele and haplotype frequencies of the CYP2D6, CYP3A4 and CYP3A5 gene variations are different between Finnish breast cancer patients and healthy volunteers. The results will be further used to explore whether the genetic polymorphism of these metabolic enzymes affects the response to a certain drug substance. The study population consisted of 996 Finnish breast cancer patients. Common genetic variants affecting the enzymatic activity of CYP2D6, CYP3A4 and CYP3A5 were studied. In addition to gene copy number, ten single nucleotide polymorphisms (SNP) of the CYP2D6 gene were genotyped. For CYP3A4 gene, genotyping was done for intron 6 SNP rs35599367 shown to decrease CYP3A4 gene expression. CYP3A5 SNP 6986A>G leading to splicing defect and premature STOP codon was also genotyped. Genotyping and copy number determination was done using PCR-based TaqMan® 5'-nuclease method. CYP2D6 haplotype analysis and phenotype predictions were derived based on genotype data. According to CYP2D6 enzyme activity individuals are commonly classified as poor metabolizers (PM), intermediate metabolizers (IM), extensive metabolizers (EM) or ultra-rapid metabolizers (UM). The frequencies of CYP2D6 phenotypic classes in our study population were the following: PM, 2.8%; IM 2.0 %; EM 87.7% and UM 7.6%. The haplotype and phenotype frequencies determined for breast cancer patients coincide with the values observed earlier for Finnish healthy volunteers. In our study population, the minor allele frequency (MAF) of the CYP3A4 rs35599367 SNP was 2.7% and the MAF of the CYP3A5 6986G>A SNP 7.6%. The MAF of CYP3A5 6986G>A SNP found in our study is in line with the previous findings for Finnish healthy volunteers. There are no previous publications on the frequency of CYP3A4 rs35599367 SNP in Finnish population. In conclusion, no differences were detected in the frequency of the studied CYP2D6 and CYP3A5 genetic variations between Finnish breast cancer patients and healthy volunteers. Frequency of CYP3A4 rs35599367 SNP in Finnish healthy volunteers should be determined in order to compare it with our findings in the population comprising of breast cancer patients. The results of this study can be further used to explore the effects of CYP2D6, CYP3A4 and CYP3A5 genetic polymorphism on drug response.

Interindividual variability in drug responses can complicate the determination of drug doses and increase drug-related risks. The variability can be caused by pharmacokinetics or pharmacodynamics of drug. One significant factor giving rise to the variability in the pharmacokinetics is the genetic polymorphism of cytochrome P450 (CYP) enzymes. CYP2C19 and CYP2D6 are highly polymorphic enzymes and many of their polymorphisms are well-known. For both genes there exist null alleles producing the enzyme with complete lack of function and alleles producing increased enzyme activity. Additionally there are alleles of CYP2D6 leading to partially deficient enzyme function. Based on the genotype of the CYP gene individuals can be divided into four phenotype groups describing the enzyme activity: poor, intermediate, extensive and ultrarapid metabolizers. According to the clinical observations the pharmacokinetics of CYP2C19 and CYP2D6 substrates in the individuals genotyped as poor metabolizers often significantly differentiates from the pharmacokinetics in the individuals belonging to other phenotype groups. Between the other phenotype groups the pharmacokinetic variability caused by the genotype seems to be often covered by other reasons causing variability in the pharmacokinetics. The pharmaceutical industry could benefit from methods that could predict the interindividual variability in the drug responses before the clinical studies. The pharmacokinetic variability caused by the genetic polymorphism of CYP enzymes has been predicted with different kinds of static and dynamic physiologically based pharmacokinetic simulation models. The models have taken the CYP genotype into account by non-substratespesific or substratespesific methods. The models have succeeded to predict the clinically observed interindividual variability in the pharmacokinetics of substrates. The goal of this study was to find out if in vitro metabolism data obtained with human liver microsomes genotyped for CYP2C19 or CYP2D6 could be used to predict the interindividual variability in the pharmacokinetics of drugs. The effect of polymorphism on metabolism was examined by incubating the substrates with microsomes with different CYP2C19 or CYP2D6 genotypes. S-mephenytoin, omeprazole and Y1 (compound developed by the pharmaceutical company Orion Oyj) were used as substrates for CYP2C19. Neither the rate of metabolism of S-mephenytoin nor omeprazole appeared to be dependent on the CYP2C19 genotype, with the exception of the poor metabolizer genotype. Use of microsomes genotyped for the other CYP2C19 phenotypes to obtain predictive in vitro metabolism data might therefore not be reasonable. More significant dependence of the Y1 metabolism on the CYP2C19 genotype could not be completely excluded. When examining the effect of polymorphism on non-selective metabolic reactions, the activity of metabolizing enzymes other than the polymorphic enzyme should always be taken into consideration: in this study, CYP3A4 activity biased the results initially achieved with omeprazole and Y1. Dextromethorphan and bufuralol were used as substrates for CYP2D6 and their rates of metabolism correlated well with the CYP2D6 genotype. So microsomes genotyped for CYP2D6 could possibly be used to obtain predictive in vitro metabolism data. If genotyped microsomes are to be used in the pharmaceutical industry to predict the interindividual variability in the pharmacokinetics, factors increasing reliability of the results should be considered first and more studies should be conducted.