Cytochrome P450 enzymes in drug metabolism: regulation of gene expression, enzyme activities, and impact of genetic variation. Pharmacol Ther. 2013;138:103-141. [PMID: 23333322 DOI: 10.1016/j.pharmthera.2012.12.007]

Genetic variation of platelet function and pharmacology: an update of current knowledge

Platelets are critically involved in atherosclerosis and acute thrombosis. The platelet phenotype shows a wide variability documented by the inherited difference of platelet reactivity, platelet volume and count and function of platelet surface receptors. Several candidate genes have been put into focus and investigated for their functional and prognostic role in healthy individuals and patients with cardiovascular (CV) disease treated with antiplatelet agents. In addition to genetic variation, other clinical, disease-related and demographic factors are important so-called non-genetic factors. Due to the small effect sizes of single nucleotide polymorphisms (SNP) in candidate genes and due to the low allele frequencies of functional relevant candidate SNPs, the identification of genetic risk factors with high predictive values generally depends on the sample size of study cohorts. In the post-genome era new array and bioinformatic technologies facilitate high throughput genome-wide association studies (GWAS) for the identification of novel candidate genes in large cardiovascular cohorts. One of the crucial aspects of platelet genomic studies is the precise definition of a specific clinical phenotype (e.g. stent thrombosis) as this will impact importantly the findings of genomic studies like GWAS. Here, we provide an update on genetic variation of platelet receptors and drug metabolising enzymes under specific consideration of data derived by GWAS. The potential impact of this information and the role in personalised therapeutic concepts will be discussed.

A meta-analysis of CYP2D6 metabolizer phenotype and metoprolol pharmacokinetics

Metoprolol, a commonly prescribed beta-blocker, is primarily metabolized by cytochrome P450 2D6 (CYP2D6), an enzyme with substantial genetic heterogeneity. Several smaller studies have shown that metoprolol pharmacokinetics is influenced by CYP2D6 genotype and metabolizer phenotype. To increase robustness of metoprolol pharmacokinetic estimates, a systematic review and meta-analysis of pharmacokinetic studies that administered a single oral dose of immediate release metoprolol was performed. Pooled analysis (n= 264) demonstrated differences in peak plasma metoprolol concentration, area under the concentration-time curve, elimination half-life, and apparent oral clearance that were 2.3-, 4.9-, 2.3-, and 5.9-fold between extensive and poor metabolizers, respectively, and 5.3-, 13-, 2.6-, and 15-fold between ultra-rapid and poor metabolizers (all p<0.001). Enantiomer-specific analysis revealed genotype-dependent enantio-selective metabolism, with nearly 40% greater R- vs S-metoprolol metabolism in ultra-rapid and extensive metabolizers. This study demonstrates a marked effect of CYP2D6 metabolizer phenotype on metoprolol pharmacokinetics and confirms enantiomer specific metabolism of metoprolol.

Gene expression variability in human hepatic drug metabolizing enzymes and transporters

Interindividual variability in the expression of drug-metabolizing enzymes and transporters (DMETs) in human liver may contribute to interindividual differences in drug efficacy and adverse reactions. Published studies that analyzed variability in the expression of DMET genes were limited by sample sizes and the number of genes profiled. We systematically analyzed the expression of 374 DMETs from a microarray data set consisting of gene expression profiles derived from 427 human liver samples. The standard deviation of interindividual expression for DMET genes was much higher than that for non-DMET genes. The 20 DMET genes with the largest variability in the expression provided examples of the interindividual variation. Gene expression data were also analyzed using network analysis methods, which delineates the similarities of biological functionalities and regulation mechanisms for these highly variable DMET genes. Expression variability of human hepatic DMET genes may affect drug-gene interactions and disease susceptibility, with concomitant clinical implications.

Direct transcriptional regulation of human hepatic cytochrome P450 3A4 (CYP3A4) by peroxisome proliferator-activated receptor alpha (PPARα)

The nuclear receptor peroxisome proliferator-activated receptor (PPAR)α is known primarily as a regulator of fatty acid metabolism, energy balance, and inflammation, but evidence suggests a wider role in regulating the biotransformation of drugs and other lipophilic chemicals. We investigated whether PPARα directly regulates the transcription of cytochrome P450 3A4, the major human drug-metabolizing enzyme. Using chromatin immunoprecipitation in human primary hepatocytes as well as electrophoretic mobility shift and luciferase reporter-gene assays, we identified three functional PPARα-binding regions (PBR-I, -II, and -III) within ∼12 kb of the CYP3A4 upstream sequence. Furthermore, a humanized CYP3A4/3A7 mouse model showed in vivo induction of CYP3A4 mRNA and protein by [4-chloro-6-(2,3-xylidino)-2-pyrimidinylthio]acetic acid (WY14,643) in liver but not in intestine, whereas hepatic occupancy of PBRs by PPARα was ligand independent. Using lentiviral gene knock-down and treatment with WY14,643 in primary human hepatocytes, PPARα was further shown to affect the expression of a distinct set of CYPs, including 1A1, 1A2, 2B6, 2C8, 3A4, and 7A1, but not 2C9, 2C19, 2D6, or 2E1. Interestingly, the common phospholipid 1-palmitoyl-2-oleoyl-sn-glycerol-3-phosphocholine (16:0/18:1-PC), previously proposed to reflect nutritional status and shown to be a specific endogenous ligand of PPARα, induced CYP3A4 (up to 4-fold) and other biotransformation genes in hepatocytes with similar selectivity and potency as WY14,643. These data establish PPARα as a direct transcriptional regulator of hepatic CYP3A4. This finding warrants investigation of both known and newly developed PPARα-targeted drugs for their drug-drug interaction potential. Furthermore, our data suggest that nutritional status can influence drug biotransformation capacity via endogenous phospholipid signaling.