dextrorphan and alpha-hydroxymetoprolol

The cytochrome P450 2D6 (CYP2D6) gene locus is challenging to accurately genotype due to numerous single nucleotide variants and complex structural variation. Our goal was to determine whether the CYP2D6 genotype-phenotype correlation is improved when diplotype assignments incorporate structural variation, identified by the bioinformatics tool Stargazer, with next-generation sequencing data. Using CYP2D6 activity measured with substrates dextromethorphan and metoprolol, activity score explained 40% and 34% of variability in metabolite formation rates, respectively, when diplotype calls incorporated structural variation, increasing from 36% and 31%, respectively, when diplotypes did not incorporate structural variation. We also investigated whether the revised Clinical Pharmacogenetics Implementation Consortium (CPIC) recommendations for translating genotype to phenotype improve CYP2D6 activity predictions over the current system. Although the revised recommendations do not improve the correlation between activity score and CYP2D6 activity, perhaps because of low frequency of the CYP2D6*10 allele, the correlation with metabolizer phenotype group was significantly improved for both substrates. We also measured the function of seven rare coding variants: one (A449D) exhibited decreased (44%) and another (R474Q) increased (127%) activity compared with reference CYP2D6.1 protein. Allele-specific analysis found that A449D is part of a novel CYP2D6*4 suballele, CYP2D6*4.028. The novel haplotype containing R474Q was designated CYP2D6*138 by PharmVar; another novel haplotype containing R365H was designated CYP2D6*139. Accuracy of CYP2D6 phenotype prediction is improved when the CYP2D6 gene locus is interrogated using next-generation sequencing coupled with structural variation analysis. Additionally, revised CPIC genotype to phenotype translation recommendations provides an improvement in assigning CYP2D6 activity.

Topics: Alleles; Computational Biology; Cytochrome P-450 CYP2D6; Dextromethorphan; Dextrorphan; Genetic Association Studies; Genetic Loci; Haplotypes; High-Throughput Nucleotide Sequencing; Humans; Metoprolol; Microsomes, Liver; Pharmacogenomic Testing; Polymorphism, Genetic; Practice Guidelines as Topic

The effects of gender, time variables, menstrual cycle phases, plasma sex hormone concentrations and physiologic urinary pH on CYP2D6 phenotyping were studied using two widely employed CYP2D6 probe drugs, namely dextromethorphan and metoprolol. Phenotyping on a single occasion of 150 young, healthy, drug-free women and men revealed that the dextromethorphan: dextrorphan metabolic ratio (MR) was significantly lower (P < 0.0001) in 56 female extensive metabolizers (0.008+/-0.021) compared to 86 male extensive metabolizers (0.020 +/-0.040). Urinary pH was a significant predictor of dextromethorphan: dextrorphan MRs in men and women (P < 0.001). Once-a-month phenotyping with dextromethorphan of 12 healthy young men (eight extensive metabolizers and four poor metabolizers) over a 1-year period, as well as every-other-day phenotyping with dextromethorphan of healthy, pre-menopausal women (10 extensive metabolizers and 2 poor metabolizers) during a complete menstrual cycle, did not follow a particular pattern and showed similar intrasubject variability ranging from 24.1% to 74.5% (mean 50.9%) in men and from 20.5% to 96.2% (mean 52.0%) in women, independent of the CYP2D6 phenotype (P = 0.342). Using metoprolol as a probe drug, considerable intrasubject variability (38.6+/- 12.0%) but no correlation between metoprolol: alpha-hydroxymetoprolol MRs and pre-ovulatory, ovulatory and luteal phases (mean +/- SD metoprolol: a-hydroxymetoprolol MRs: 1.086+/- 1.137 pre-ovulatory; 1.159+/-1.158 ovulatory and 1.002+/-1.405 luteal phase; P> 0.9) or 17beta-oestradiol, progesterone or testosterone plasma concentrations was observed. There was a significant inverse relationship between physiologic urinary pH and sequential dextromethorphan: dextrorphan MRs as well as metoprolol: alpha-hydroxymetoprolol MRs in men and women, with metabolic ratios varying up to six-fold with metoprolol and up to 20-fold with dextromethorphan (ANCOVA P < 0.001). We conclude that apparent CYP2D6 activity is highly variable, independent of menstrual cycle phases, sex hormones, time variables or phenotype. Up to 80% of the observed variability can be explained by variations of urinary pH within the physiological range. An apparent phenotype shift as a result of variations in urinary pH may be observed in individuals who have metabolic ratios close to the population antimode.

Topics: Administration, Oral; Adult; Analysis of Variance; Biomarkers; Cytochrome P-450 CYP2D6; Dextromethorphan; Dextrorphan; Enzyme Activation; Female; Gonadal Steroid Hormones; Humans; Hydrogen-Ion Concentration; Male; Menstrual Cycle; Metoprolol; Sex Characteristics; Sex Factors; Substrate Specificity; Time Factors; Urine

A reverse-phase High Performance Liquid Chromatographic (HPLC) method was developed for the analysis of metoprolol in the large number of human plasma samples obtained in in vitro-in vivo correlations (IVIVC) and bioavailability studies of extended release formulations of metoprolol tartrate. The metabolite, alpha-hydroxy metoprolol (OH-met), could also be quantified. The analytes were extracted from the plasma using solid phase columns, separated on a C-4 analytical column followed by fluorimetric detection. The linearity, precision, accuracy, stability, selectivity and ruggedness were validated for the concentration ranges of 1-400 ng ml-1 for metoprolol and 0.5-200 ng ml-1 for OH-met. The same chromatographic conditions were slightly modified to quantify dextromethorphan and its metabolite dextrorphan in urine in the concentration range 0.052-0.05 microgram ml-1 as a method for screening for fast metabolizers.

Topics: Adrenergic beta-Antagonists; Antitussive Agents; Chromatography, High Pressure Liquid; Dextromethorphan; Dextrorphan; Humans; Indicators and Reagents; Metoprolol; Neuroprotective Agents; Quality Control; Reference Standards; Reproducibility of Results; Spectrometry, Fluorescence