Abstract:
The Cytochrome P450 family of enzymes is responsible for the majority of Phase I
metabolism, and has been identified as an important source of pharmacokinetic variation in therapeutic responses. CYP2C19 and CYP2D6, metabolising >35% of commonly prescribed medications, are two of the most important pharmacogenetic markers that have been studied with the aim of improving treatment response and reducing adverse drug reactions.
The Food and Drug Administration (FDA) approved AmpliChip CYP450 Test (AmpliChip)
was compared to a previously developed PCR-RFLP platform and a newly developed XLPCR+ Sequencing platform for the ability to identifying genotype and predicting phenotype for CYP2C19 and CYP2D6 respectively. The AmpliChip was found not to be genotypically comprehensive enough for evaluating CYP2C19 genotype, not robust enough for determining CYP2D6 genotype and inaccurate in predicting phenotype for both. The XLPCR+ Sequencing method identified three novel alleles and one sub-variant.
Advances in online column-switching solid phase extraction generated a rapid and robust LCMS/ MS method for simultaneously quantifying the probe drugs omeprazole (CYP2C19 substrate), dextromethorphan (CYP2D6 substrate) and their metabolites. Antimodes were identified for phenotypic cut-offs which offered measured phenotype for comparison to predicted phenotype.
Omeprazole metabolism by CYP2C19 correlated well with predicted phenotype in a
demographically representative South African cohort. There are concerns regarding the use of omeprazole as a probe drug as participants predicted to be ultrarapid metabolisers for CYP2C19 had similar rates to extensive metabolisers. Regardless of this concern, decreased metabolism was assigned to the CYP2C19*15 for the first time.
CYP2D6 predicted phenotype correlated very well with measured phenotype, validating the suitability of dextromethorphan use for measuring CYP2D6 metabolism. Substrate modified activity score using 0.5 to predict intermediate metabolisers fine-tuned the XLPCR+ Sequencing platform for phenotype prediction. This finding, along with observations in CYP2C19 metabolism of omeprazole, highlights the importance of substrate specific phenotype prediction strategies. Controversially, attempts to associate CYP2D6 phenotype prediction with risperidone-related
adverse drug reactions has yielded conflicting results. The XL-PCR+Sequencing platform was able to discount this association by predicting a variety of metabolisers in a pilot cohort selected to be experiencing risperidone-related adverse drug reactions. The comprehensive capability of the XL-PCR+Sequencing allowed for the identification of an additional novel allele in this cohort.
The data presented in thisthesis has provided insight into the relationship between predicted and measured phenotype for CYP2C19 and CYP2D6 in the South African population. The XL-PCR+Sequencing platform can be used for future research or can be applied to improve treatment outcome. The LC-MS/MS method developed could be used for future evaluations of predicted and measured phenotype with the ability to be adjusted for therapeutic drug monitoring. This thesis advances pharmacogenetics of CYP2C19 and CYP2D6 for use in the South African population.
