Developmental Changes in Human Liver CYP2D6 Expression

BACKGROUND The use of opioids to alleviate pain is complicated by the risk of severe adverse events and the large variability in dose requirements. Pharmacogenetics (PGx) could possibly be used to tailor pain medication based on an individual's genetic background. Many potential genetic markers have been described, and the importance of genetic predisposition in opioid efficacy and toxicity has been demonstrated in knockout mouse models and human twin studies. Such predictors are especially of value for neonates and young children, in whom the assessment of efficacy or side effects is complicated by the inability of the patient to communicate this properly. The current problem is determining which of the many potential candidates to focus on for clinical implementation. CONTENT We systematically searched publications on PGx for opioids in 5 databases, aiming to identify PGx markers with sufficient robust data and high enough occurrence for potential clinical application. The initial search yielded 4257 unique citations, eventually resulting in 852 relevant articles covering 24 genes. From these genes, we evaluated the evidence and selected the most promising 10 markers: cytochrome P450 family 2 subfamily D member 6 (CYP2D6), cytochrome P450 family 3 subfamily A member 4 (CYP3A4), cytochrome P450 family 3 subfamily A member 5 (CYP3A5), UDP glucuronosyltransferase family 2 member B7 (UGT2B7), ATP binding cassette subfamily B member 1 (ABCB1), ATP binding cassette subfamily C member 3 (ABCC3), solute carrier family 22 member 1 (SLC22A1), opioid receptor kappa 1 (OPRM1), catechol-O-methyltransferase (COMT), and potassium voltage-gated channel subfamily J member 6 (KCNJ6). Treatment guidelines based on genotype are already available only for CYP2D6. SUMMARY The application of PGx in the management of pain with opioids has the potential to improve therapy. We provide a shortlist of 10 genes that are the most promising markers for clinical use in this context.

Liver cytochrome P450s (P450s) play critical roles in drug metabolism, toxicology, and metabolic processes. Despite rapid progress in the understanding of these enzymes, a systematic investigation of the full spectrum of functionality of individual P450s, the interrelationship or networks connecting them, and the genetic control of each gene/enzyme is lacking. To this end, we genotyped, expression-profiled, and measured P450 activities of 466 human liver samples and applied a systems biology approach via the integration of genetics, gene expression, and enzyme activity measurements. We found that most P450s were positively correlated among themselves and were highly correlated with known regulators as well as thousands of other genes enriched for pathways relevant to the metabolism of drugs, fatty acids, amino acids, and steroids. Genome-wide association analyses between genetic polymorphisms and P450 expression or enzyme activities revealed sets of SNPs associated with P450 traits, and suggested the existence of both cis-regulation of P450 expression (especially for CYP2D6) and more complex trans-regulation of P450 activity. Several novel SNPs associated with CYP2D6 expression and enzyme activity were validated in an independent human cohort. By constructing a weighted coexpression network and a Bayesian regulatory network, we defined the human liver transcriptional network structure, uncovered subnetworks representative of the P450 regulatory system, and identified novel candidate regulatory genes, namely, EHHADH, SLC10A1, and AKR1D1. The P450 subnetworks were then validated using gene signatures responsive to ligands of known P450 regulators in mouse and rat. This systematic survey provides a comprehensive view of the functionality, genetic control, and interactions of P450s.

Atomoxetine (ATX) is a second-line nonstimulant medication used to control symptoms of attention deficit hyperactivity disorder (ADHD). Inconsistent therapeutic efficacy has been reported with ATX, which may be related to variable CYP2D6-mediated drug clearance. We characterized ATX metabolism in a panel of human liver samples as a basis for a bottom-up PBPK model to aid in ATX exposure prediction and control. K m , V max , and Cl int values in pooled human liver microsomes (HLMs) were 2.4 mM, 479 pmol/min/mg protein, and 202 ml/min/mg protein, respectively. Mean population values of kinetic parameters are not adequate to describe variability in a population, given that K m , V max , and Cl int values from single-donor HLMs ranged from 0.93 to 79.2 mM, 20.0 to 1600 pmol/min/mg protein, and 0.3 to 936 ml/min/mg protein. All kinetic parameters were calculated from 4-hydroxyatomoxetine (4-OH-ATX) formation. CYP2E1 and CYP3A contributed to 4-OH-ATX formation in livers with CYP2D6 intermediate and poor metabolizer status. In HLMs with lower CYP2D6 activity levels, 2-hydroxymethylatomoxetine (2-CH 2 OH-ATX) formation became a more predominant pathway of metabolism, which appeared to be catalyzed by CYP2B6. ATX biotransformation at clinically relevant plasma concentrations was characterized in a panel of pediatric HLM (n = 116) samples by evaluating primary metabolites. Competing pathways of ATX metabolism [N-desmethylatomoxetine (NDM-ATX) and 2-CH 2 OH-ATX formation] had increasing importance in livers with lesser CYP2D6 activity, but, overall ATX clearance was still compromised. Modeling ATX exposure to individualize therapy would require comprehensive knowledge of factors that affect CYP2D6 activity as well as an understanding of competing pathways, particularly for individuals with lower CYP2D6 activity.