Predictors of Variation in CYP2A6 mRNA, Protein, and Enzyme Activity in a Human Liver Bank: Influence of Genetic and Nongenetic Factors

PharmVar GeneFocus: CYP2A6

The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the human CYP2A gene locus containing the highly polymorphic CYP2A6 gene. CYP2A6 plays a role in the metabolism of nicotine and various drugs. Thus, genetic variation can substantially contribute to the function of this enzyme and associated efficacy and safety. This GeneFocus provides an overview of the clinical significance of CYP2A6, including its genetic variation and function. We also highlight and discuss caveats in the identification and characterization of allelic variation of this complex pharmacogene, a prerequisite for accurate genotype determination and prediction of phenotype status.

Cytochrome P450 Family 4F2 and 4F11 Haplotype Mapping and Association with Hepatic Gene Expression and Vitamin K Hydroxylation Activity

This study evaluated the underlying mechanistic links between genetic variability in vitamin K metabolic pathway genes (CYP4F2 and CYP4F11) and phylloquinone hydroxylation activity using genotype- and haplotype-based approaches. Specifically, we characterized genetic variability in the CYP4F2/CYP4F11 locus and compared common single allele genotypes and common haplotypes as predictors of hepatic gene expression, enzyme abundance, and phylloquinone (VK1) ω-hydroxylation kinetics. We measured CYP4F2 and CYP4F11 mRNA levels, CYP4F2 and CYP4F11 protein abundances, and the VK1 concentration-dependent ω-hydroxylation rate in matched human liver nucleic acid and microsome samples, utilizing a novel in vitro population modeling approach. Results indicate that accounting for the CYP4F2*3 allele alone is sufficient to capture most of the genetic-derived variability in the observed phenotypes. Additionally, our findings highlight the important contribution that CYP4F11 makes toward vitamin K metabolism in the human liver.

Pharmacokinetics of Antibacterial Agents in the Elderly: The Body of Evidence

Infections are important factors contributing to the morbidity and mortality among elderly patients. High rates of consumption of antimicrobial agents by the elderly may result in increased risk of toxic reactions, deteriorating functions of various organs and systems and leading to the prolongation of hospital stay, admission to the intensive care unit, disability, and lethal outcome. Both safety and efficacy of antibiotics are determined by the values of their plasma concentrations, widely affected by physiologic and pathologic age-related changes specific for the elderly population. Drug absorption, distribution, metabolism, and excretion are altered in different extents depending on functional and morphological changes in the cardiovascular system, gastrointestinal tract, liver, and kidneys. Water and fat content, skeletal muscle mass, nutritional status, use of concomitant drugs are other determinants of pharmacokinetics changes observed in the elderly. The choice of a proper dosing regimen is essential to provide effective and safe antibiotic therapy in terms of attainment of certain pharmacodynamic targets. The objective of this review is to perform a structure of evidence on the age-related changes contributing to the alteration of pharmacokinetic parameters in the elderly.

Quantitative Proteomics in Translational Absorption, Distribution, Metabolism, and Excretion and Precision Medicine

A reliable translation of in vitro and preclinical data on drug absorption, distribution, metabolism, and excretion (ADME) to humans is important for safe and effective drug development. Precision medicine that is expected to provide the right clinical dose for the right patient at the right time requires a comprehensive understanding of population factors affecting drug disposition and response. Characterization of drug-metabolizing enzymes and transporters for the protein abundance and their interindividual as well as differential tissue and cross-species variabilities is important for translational ADME and precision medicine. This review first provides a brief overview of quantitative proteomics principles including liquid chromatography-tandem mass spectrometry tools, data acquisition approaches, proteomics sample preparation techniques, and quality controls for ensuring rigor and reproducibility in protein quantification data. Then, potential applications of quantitative proteomics in the translation of in vitro and preclinical data as well as prediction of interindividual variability are discussed in detail with tabulated examples. The applications of quantitative proteomics data in physiologically based pharmacokinetic modeling for ADME prediction are discussed with representative case examples. Finally, various considerations for reliable quantitative proteomics analysis for translational ADME and precision medicine and the future directions are discussed. SIGNIFICANCE STATEMENT: Quantitative proteomics analysis of drug-metabolizing enzymes and transporters in humans and preclinical species provides key physiological information that assists in the translation of in vitro and preclinical data to humans. This review provides the principles and applications of quantitative proteomics in characterizing in vitro, ex vivo, and preclinical models for translational research and interindividual variability prediction. Integration of these data into physiologically based pharmacokinetic modeling is proving to be critical for safe, effective, timely, and cost-effective drug development.

Gender Differences in Smoking Initiation and Cessation Associated with the Intergenerational Transfer of Smoking across Three Generations: The Nagahama Study

Global tobacco policies lowered overall and male smoking rates, but female smoking rates have remained unchanged. Parent-child studies revealed the effects of parental smoking, but gender differences had mixed results. We investigated the effects of long-term smoking behavior in families over three generations in order to clarify gender differences. A cross-sectional study in a community-based genome cohort was conducted using a self-reported questionnaire. A total of 8652 respondents were stratified by gender regarding smoking initiation. A logistic regression analysis was performed to analyze the family smoking history. A total of 2987 current smokers and ever-smokers were compared regarding smoking cessation. With respect to smoking initiation, women were affected by their smoking mothers (odds ratio (OR), 2.4; 95% confidence interval (CI), 1.8-3.2) and grandmothers (OR, 1.7; CI, 1.1-2.4). Women who continued smoking were affected only by their smoking mothers (OR, 1.6; CI, 1.05-2.49). In conclusion, gender differences in smoking initiation and cessation are possibly associated with family smoking history. Mothers and grandmothers were shown to have a strong influence on women with respect to both smoking initiation and cessation. Future research should focus on providing evidence for effective gender-specific intervention programs to curb long-term smoking in women.

Emerging investigator series: human CYP2A6 catalyzes the oxidation of 6:2 fluorotelomer alcohol

The biotransformation of 6:2 fluorotelomer alcohol (6:2 FTOH) results in the production of bioactive and persistent metabolites, including perfluorinated carboxylic acids (PFCAs). While the products of 6:2 FTOH metabolism have been elucidated in several animal models, the responsible cytochrome P450 (CYP) isoform(s) have not been reported. Here, we characterized the in vitro oxidation of 6:2 FTOH using human liver microsomes and recombinant human CYPs. Six major xenobiotic metabolizing CYPs were screened for their capacity to catalyze 6:2 FTOH oxidation using chemical inhibitors selective towards CYP isoforms. Of the CYP isoforms investigated, CYP2A6 was the only enzyme capable of catalyzing 6:2 FTOH in human liver microsomes, with K_M and V_max values of 4076 ng mL^-1 and 69 ng mL^-1 min^-1, respectively. We further probed the metabolic mechanism by plotting the 6:2 FTOH kinetic profile and extrapolating data to several possible kinetic models. 6:2 FTOH oxidation followed the typical one-site Michaelis-Menten kinetic model. This study also reports that 6:2 FTOH loss is associated with active CYP2A6 by incubating microsomes with the selective CYP2A6 inhibitor tranylcypromine, which bound competitively to the enzyme as determined by an increased K_M (8796 ng mL^-1) but unchanged V_max value. Collectively, these findings provide a mechanistic perspective on the potential importance of CYP2A6 in the metabolic activation and phase I elimination of 6:2 FTOH and indirect human exposure to PFCAs.

Nicotine metabolism and its association with CYP2A6 genotype among Indigenous people in Alaska who smoke

Prevalence of smoking is higher in Alaska Native and American Indian (ANAI) populations living in Alaska than the general US population. Genetic factors contribute to smoking and cessation rates. The objective of this study was to compare CYP2A6 genetic variation and CYP2A6 enzyme activity toward nicotine in an ANAI population. ANAI (N = 151) people trying to quit smoking were recruited. DNA samples were genotyped for CYP2A6 variants *1X2A, *1B, *2, *4, *9, *10, *12, and *35. Multiple nicotine metabolites were measured in plasma and urine samples, including cotinine and 3′‐hydroxycotinine used to determine CYP2A6 activity (e.g., nicotine metabolite ratio [NMR]). We calculated summary statistics for all of the genotypes and metabolites and assigned CYP2A6 activity scores based on known information. We studied the association of CYP2A6 variants with the NMR and smoking histories. The overall frequency of the CYP2A6*1B gain of function allele was high in the ANAI versus non‐ANAI populations in other studies. Both *4 null and *9 decrease of function alleles had frequencies similar to previous studies of ANAI populations. In a multivariate analysis, the genotype‐inferred CYP2A6 activity score was associated with both plasma and urine NMR (p value = 8.56E‐08 and 4.08E‐13, respectively). Plasma NMR was also associated with duration of smoking (p value < 0.01) but not urinary total nicotine equivalents uncorrected for creatinine (TNE9_uc) or biological sex. Urine NMR was significantly associated (p value < 0.01) with TNE9_uc. Variation in NMR in this ANAI population is explained in part by CYP2A6 genetic variation.

Functional characterization of novel rare CYP2A6 variants and potential implications for clinical outcomes

CYP2A6 activity, phenotyped by the nicotine metabolite ratio (NMR), is a predictor of several smoking behaviors, including cessation and smoking‐related disease risk. The heritability of the NMR is 60–80%, yet weighted genetic risk scores (wGRSs) based on common variants explain only 30–35%. Rare variants (minor allele frequency <1%) are hypothesized to explain some of this missing heritability. We present two targeted sequencing studies where rare protein‐coding variants are functionally characterized in vivo, in silico, and in vitro to examine this hypothesis. In a smoking cessation trial, 1687 individuals were sequenced; characterization measures included the in vivo NMR, in vitro protein expression, and metabolic activity measured from recombinant proteins. In a human liver bank, 312 human liver samples were sequenced; measures included RNA expression, protein expression, and metabolic activity from extracted liver tissue. In total, 38 of 47 rare coding variants identified were novel; characterizations ranged from gain‐of‐function to loss‐of‐function. On a population level, the portion of NMR variation explained by the rare coding variants was small (~1%). However, upon incorporation, the accuracy of the wGRS was improved for individuals with rare protein‐coding variants (i.e., the residuals were reduced), and approximately one‐third of these individuals (12/39) were re‐assigned from normal to slow metabolizer status. Rare coding variants can alter an individual’s CYP2A6 activity; their integration into wGRSs through precise functional characterization is necessary to accurately assess clinical outcomes and achieve precision medicine for all. Investigation into noncoding variants is warranted to further explain the missing heritability in the NMR.

Ontogeny of Drug-Metabolizing Enzymes

Almost 50% of prescription drugs lack age-appropriate dosing guidelines and therefore are used "off-label." Only ~10% drugs prescribed to neonates and infants have been studied for safety or efficacy. Immaturity of drug metabolism in children is often associated with drug toxicity. This chapter summarizes data on the ontogeny of major human metabolizing enzymes involved in oxidation, reduction, hydrolysis, and conjugation of drugs. The ontogeny data of individual drug-metabolizing enzymes are important for accurate prediction of drug pharmacokinetics and toxicity in children. This information is critical for designing clinical studies to appropriately test pharmacological hypotheses and develop safer pediatric drugs, and to replace the long-standing practice of body weight- or surface area-normalized drug dosing. The application of ontogeny data in physiologically based pharmacokinetic model and regulatory submission are discussed.

Mass spectrometry-based targeted proteomics method for the quantification of clinically relevant drug metabolizing enzymes in human specimens

Biotransformation by phase I and II metabolizing enzymes represents the major determinant for the oral bioavailability of many drugs. To estimate the pharmacokinetics, data on protein abundance of hepatic and extrahepatic tissues, such as the small intestine, are required. Targeted proteomics assays are nowadays state-of-the-art for absolute protein quantification and several methods for quantification of drug metabolizing enzymes have been published. However, some enzymes remain still uncovered by the analytical spectra of those methods. Therefore, we developed and validated a quantification assay for two carboxylesterases (CES-1, CES-2), 17 cytochrome P450 enzymes (CYP) (CYP1A1, CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C18, CYP2C19, CYP2D6, CYP2E1, CYP2J2, CYP3A4, CYP3A5, CYP3A7, CYP4F2, CYP4F12, CYP4A11) and five UDP-glucuronosyltransferases (UGTs) (UGT1A1, UGT1A3, UGT2B7, UGT2B15, UGT2B17). Protein quantification was performed by analyzing proteospecific surrogate peptides after tryptic digestion with stable isotope-labelled standards. Chromatographic separation was performed on a Kinetex® 2.6 µm C18 100 Å core-shell column (100 × 2.1 mm) with a gradient elution using 0.1% formic acid and acetonitrile containing 0.1% formic acid with a flow rate of 200 µl/min. Three mass transitions were simultaneously monitored with a scheduled multiple reaction monitoring (sMRM) method for each analyte and standard. The method was partly validated according to current bioanalytical guidelines and met the criteria regarding linearity (0.1-25 nmol/L), within-day and between-day accuracy and precision as well as multiple stability criteria. Finally, the developed method was successfully applied to determine the abundance of the aforementioned enzymes in human intestinal und liver microsomes. Our work offers a new fit for purpose method for the absolute quantification of CES, CYPs and UGTs in various human tissues and can be used for the acquisition of data for physiologically based pharmacokinetic modelling.

Characterization of CYP3A pharmacogenetic variation in American Indian and Alaska Native communities, targeting CYP3A4*1G allele function

The frequencies of genetic variants in the CYP3A4 and CYP3A5 genes differ greatly across global populations, leading to profound differences in the metabolic activity of these enzymes and resulting drug metabolism rates, with important consequences for therapeutic safety and efficacy. Yet, the impact of genetic variants on enzyme activity are incompletely described, particularly in American Indian and Alaska Native (AIAN) populations. To characterize genetic variation in CYP3A4 and CYP3A5 and its effect on enzyme activity, we partnered with AIAN people living in two regions of Alaska: Yup'ik Alaska Native people living in the Yukon-Kuskokwim Delta region of rural southwest Alaska and AIAN people receiving care at the Southcentral Foundation in Anchorage, Alaska. We identified low frequencies of novel and known variation in CYP3A4 and CYP3A5, including low frequencies of the CYP3A4*1G and CYP3A5*1 variants, and linkage disequilibrium patterns that differed from those we previously identified in an American Indian population in western Montana. We also identified increased activity of the CYP3A4*1G allele in vitro and in vivo. We demonstrated that the CYP3A4*1G allele confers increased protein content in human lymphoblastoid cells and both increased protein content and increased activity in human liver microsomes. We confirmed enhanced CYP3A4-mediated 4β-vitamin D hydroxylation activity in Yup'ik people with the CYP3A4*1G allele. AIAN people in Alaska and Montana who carry the CYP3A4*1G allele-coupled with low frequency of the functional CYP3A5*1 variant-may metabolize CYP3A substrates more rapidly than people with the reference CYP3A4 allele.

Tissue-Specific Proteomics Analysis of Anti-COVID-19 Nucleoside and Nucleotide Prodrug-Activating Enzymes Provides Insights into the Optimization of Prodrug Design and Pharmacotherapy Strategy

Nucleoside and nucleotide analogs are an essential class of antivirals for COVID-19 treatment. Several nucleoside/nucleotide analogs have shown promising effects against SARS-CoV-2 in vitro; however, their in vivo efficacy is limited. Nucleoside/nucleotide analogs are often formed as ester prodrugs to improve pharmacokinetics (PK) performance. After entering cells, the prodrugs undergo several enzymatic metabolism steps to form the active metabolite triphosphate nucleoside (TP-Nuc); prodrug activation is therefore associated with the abundance and catalytic activity of the corresponding activating enzymes. Having the activation of nucleoside/nucleotide prodrugs occur at the target site of action, such as the lung, is critical for anti-SARS-CoV-2 efficacy. Herein, we conducted an absolute quantitative proteomics study to determine the expression of relevant activating enzymes in human organs related to the PK and antiviral efficacy of nucleoside/nucleotide prodrugs, including the lung, liver, intestine, and kidney. The protein levels of prodrug-activating enzymes differed significantly among the tissues. Using catalytic activity values reported previously for individual enzymes, we calculated prodrug activation profiles in these tissues. The prodrugs evaluated in this study include nine McGuigan phosphoramidate prodrugs, two cyclic monophosphate prodrugs, two l-valyl ester prodrugs, and one octanoate prodrug. Our analysis showed that most orally administered nucleoside/nucleotide prodrugs were primarily activated in the liver, suggesting that parenteral delivery routes such as inhalation and intravenous infusion could be better options when these antiviral prodrugs are used to treat COVID-19. The results also indicated that the l-valyl ester prodrug design can plausibly improve drug bioavailability and enhance effects against SARS-CoV-2 intestinal infections. This study further revealed that an octanoate prodrug could provide a long-acting antiviral effect targeting SARS-CoV-2 infections in the lung. Finally, our molecular docking analysis suggested several prodrug forms of favipiravir and GS-441524 that are likely to exhibit favorable PK features over existing prodrug forms. In sum, this study revealed the activation mechanisms of various nucleoside/nucleotide prodrugs relevant to COVID-19 treatment in different organs and shed light on the development of more effective anti-COVID-19 prodrugs.

Potential implications of DMET ontogeny on the disposition of commonly prescribed drugs in neonatal and pediatric intensive care units

Introduction: Pediatric patients, especially neonates and infants, are more susceptible to adverse drug events as compared to adults. In particular, immature small molecule drug metabolism and excretion can result in higher incidences of pediatric toxicity than adults if the pediatric dose is not adjusted.Area covered: We reviewed the top 29 small molecule drugs prescribed in neonatal and pediatric intensive care units and compiled the mechanisms of their metabolism and excretion. The ontogeny of Phase I and II drug metabolizing enzymes and transporters (DMETs), particularly relevant to these drugs, are summarized. The potential effects of DMET ontogeny on the metabolism and excretion of the top pediatric drugs were predicted. The current regulatory requirements and recommendations regarding safe and effective use of drugs in children are discussed. A few representative examples of the use of ontogeny-informed physiologically based pharmacokinetic (PBPK) models are highlighted.Expert opinion: Empirical prediction of pediatric drug dosing based on body weight or body-surface area from the adult parameters can be inaccurate because DMETs are not mature in children and the age-dependent maturation of these proteins is different. Ontogeny-informed-PBPK modeling provides a better alternative to predict the pharmacokinetics of drugs in children.

Cytochrome P450 2A6 is associated with macrophage polarization and is a potential biomarker for hepatocellular carcinoma

Cytochrome P450 2A6 (CYP2A6) is an important metabolic enzyme and is involved in the progression of hepatocellular carcinoma (HCC). However, its specific function and the mechanism of modulation remain to be elucidated. In this study, we found that CYP2A6 is dramatically downregulated in HCC. CYP2A6 expression is closely associated with pathological grading, histologic grade, hepatitis, vascular metastasis, liver inflammation, and worse prognosis. Reduced expression of CYP2A6 contributes to alternative activation of macrophage polarization and impairs macrophage maturation and phagocytosis. Mechanistically, CYP2A6 participates in arachidonic acid metabolism, initiates 20‐hydroxyeicosatetraenoic acid (HETE) generation, and inhibits epoxyeicosatrienoic acid (EET) generation. Disruption of the equilibrium between 20‐HETE and EETs can induce macrophage polarization, thereby modulating antitumor immunity.

How Can Drug Metabolism and Transporter Genetics Inform Psychotropic Prescribing?

Many genetic variants in drug metabolizing enzymes and transporters have been shown to be relevant for treating psychiatric disorders. Associations are strong enough to feature on drug labels and for prescribing guidelines based on such data. A range of commercial tests are available; however, there is variability in included genetic variants, methodology, and interpretation. We herein provide relevant background for understanding clinical associations with specific variants, other factors that are relevant to consider when interpreting such data (such as age, gender, drug-drug interactions), and summarize the data relevant to clinical utility of pharmacogenetic testing in psychiatry and the available prescribing guidelines. We also highlight areas for future research focus in this field.

Characterization of Differential Tissue Abundance of Major Non-CYP Enzymes in Human

The availability of assays that predict the contribution of cytochrome P450 (CYP) metabolism allows for the design of new chemical entities (NCEs) with minimal oxidative metabolism. These NCEs are often substrates of non-CYP drug-metabolizing enzymes (DMEs), such as UDP-glucuronosyltransferases (UGTs), sulfotransferases (SULTs), carboxylesterases (CESs), and aldehyde oxidase (AO). Nearly 30% of clinically approved drugs are metabolized by non-CYP enzymes. However, knowledge about the differential hepatic versus extrahepatic abundance of non-CYP DMEs is limited. In this study, we detected and quantified the protein abundance of eighteen non-CYP DMEs (AO, CES1 and 2, ten UGTs, and five SULTs) across five different human tissues. AO was most abundantly expressed in the liver and to a lesser extent in the kidney; however, it was not detected in the intestine, heart, or lung. CESs were ubiquitously expressed with CES1 being predominant in the liver, while CES2 was enriched in the small intestine. Consistent with the literature, UGT1A4, UGT2B4, and UGT2B15 demonstrated liver-specific expression, whereas UGT1A10 expression was specific to the intestine. UGT1A1 and UGT1A3 were expressed in both the liver and intestine; UGT1A9 was expressed in the liver and kidney; and UGT2B17 levels were significantly higher in the intestine than in the liver. All five SULTs were detected in the liver and intestine, and SULT1A1 and 1A3 were detected in the lung. Kidney abundance was the most variable among the studied tissues, and overall, high interindividual variability (>15-fold) was observed for UGT2B17, CES2 (intestine), SULT1A1 (liver), UGT1A9, UGT2B7, and CES1 (kidney). These differential tissue abundance data can be integrated into physiologically based pharmacokinetic (PBPK) models for the prediction of non-CYP drug metabolism and toxicity in hepatic and extrahepatic tissues.

Genetic polymorphisms of pharmacogenomic VIP variants in the Dai population from Yunnan province

Background

Pharmacogenomics plays a crucial role in individualized therapy, but the variant information of pharmacogenomics in the Dai population is limited. We therefore aimed to screen very important pharmacogenetic (VIP) in the Dai population and compared differences between Dai and other 25 populations.

Methods

In this study, we genotyped 73 VIP variants from the PharmGKB and compared genotype distribution of variants in Dai with other 25 populations by χ2 test. To assess the genetic relationship among 26 populations, we performed the structure analysis. In addition, pair‐wise F‐statistics (Fst) was calculated to measure the population differentiation.

Results

We found 12, 10, 13, 17, 11, 39, 46, 46, 45, 43, 49, 46, 46, 46, 49, 45, 41, 42, 48, 53, 45, 50, 50, 51, 47, and 50 significantly different variants in Dai compared with other 25 populations. Genetic structure analysis showed Dai had close relationships with CDX (Chinese Dai in Xishuangbanna), CHB (Han Chinese in Beijing), JPT (Japanese in Tokyo), and KHV (Kinh in Ho Chi Minh City, Vietnam). Moreover, Dai is the most similar to KHV according to Fst analysis.

Conclusions

Our study complement the pharmacogenomics information of Dai population from Yunnan province and provide a theoretical basis for personalized medicine.

From Genotype to Phenotype: Content and Activities of Cytochromes P450 2A6 in Human Liver In Vitro and Predicted In Vivo

Unraveling the molecular mechanisms by which genetic variants of cytochrome P450 2A6 lead to different metabolic phenotypes remains a long-standing but important challenge. CYP2A6 is an enzyme involved in the metabolism of several clinical drugs as well as the metabolic activation of carcinogenic nitrosamines. Herein, CYP2A6 genotypes and phenotypes, as indicated by protein content [by liquid chromatography-mass spectrometry (MS)/MS] and metabolic activities [Vmax, clearance (CL)], were determined for 90 human liver samples. We determined the median, range, and interindividual and intraindividual variation of CYP2A6 content and activity at the microsomal, liver tissue, and whole liver level and predicted hepatic in vivo clearance by in vitro-in vivo extrapolation based on CYP2A6-mediated coumarin metabolism by each CYP2A6 genotype. These results reveal how different CYP2A6 genotypes yield different phenotypic traits in protein content and enzyme activity. For relative Vmax, CL, and protein content, the intraindividual percentage coefficients of variation (ICVs) were 41.0% (18.8%-125.1%), 28.5% (2.39%-133.5%), and 27.8% (2.68%-88.0%), respectively. The high ICVs implied large intraindividual variation at different levels, sometimes in a genotype-dependent manner. Intergenotype analysis revealed that the CYP2A6*4 allele demonstrated the most obvious effect on phenotypic outcomes, both in protein content and in metabolic activity. Indeed, decreased CYP2A6 protein content with the CYP2A6*4 genotype might explain the decreased metabolic activity from the molecular to the organismal level. These findings may allow useful predictions for CYP2A6-mediated drug metabolism on an individual patient basis in accord with the goal of achieving personalized medicine. SIGNIFICANCE STATEMENT: We provide the median, range, and interindividual and intraindividual variation in CYP2A6 content at the microsomal, liver tissue, and whole liver level by liquid chromatography-mass spectrometry (MS)/MS as well as activities at the protein, microsomal, liver tissue, and whole liver level both in vitro and at the organismal level based on CYP2A6-mediated coumarin metabolism with each CYP2A6 genotype, thereby allowing us to elucidate how different CYP2A6 genotypes yield differing phenotypic traits (protein content and enzyme activity), facilitating the development of personalized medicine.

Cancer Hazard Identification Integrating Human Variability: The Case of Coumarin

Coumarin is a naturally occurring sweet-smelling benzopyrone that may be extracted from plants or synthesized for commercial uses. Its uses include as a flavoring agent, fragrance enhancer, and odor-masking additive. We reviewed and evaluated the scientific evidence on the carcinogenicity of coumarin, integrating information from carcinogenicity studies in animals with mechanistic and other relevant data, including data from toxicogenomic, genotoxicity, and metabolism studies, and studies of human variability of a key enzyme, CYP2A6. Increases in tumors were observed in multiple studies in rats and mice in multiple tissues. Our functional pathway analysis identified several common cancer-related biological processes/pathways affected by coumarin in rat liver following in vivo exposure and in human primary hepatocytes exposed in vitro. When coumarin 7-hydroxylation by CYP2A6 is compromised, this can lead to a shift in metabolism to the 3,4-epoxidation pathway and increased generation of electrophilic metabolites. Mechanistic data align with 3 key characteristics of carcinogens, namely formation of electrophilic metabolites, genotoxicity, and induction of oxidative stress. Considerations of metabolism, human variability in CYP2A6 activity, and coumarin hepatotoxicity in susceptible individuals provide additional support for carcinogenicity concern. Our analysis illustrates the importance of integrating information on human variability in the cancer hazard identification process.

Interrogation of CYP2D6 Structural Variant Alleles Improves the Correlation Between CYP2D6 Genotype and CYP2D6-Mediated Metabolic Activity

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.

Tobacco Smoke Exposure, Urban and Environmental Factors as Respiratory Disease Predictors in Italian Adolescents

Risk monitoring in childhood is useful to estimate harmful health effects at later stages of life. Thus, here we have assessed the effects of tobacco smoke exposure and environmental pollution on the respiratory health of Italian children and adolescents using spirometry and the forced oscillation technique (FOT). For this purpose, we recruited 188 students aged 6–19 years living in Chivasso, Italy, and collected from them the following data: (1) one filled out questionnaire; (2) two respiratory measurements (i.e., spirometry and FOT); and (3) two urine tests for Cotinine (Cot) and 15-F_2t-Isoprostane (15-F_2t-IsoP) levels. We found a V-shape distribution for both Cotinine and 15-F_2t-IsoP values, according to age groups, as well as a direct correlation (p = 0.000) between Cotinine and tobacco smoke exposure. These models demonstrate that tobacco smoke exposure, traffic, and the living environment play a fundamental role in the modulation of asthma-like symptoms (p = 0.020) and respiratory function (p = 0.007). Furthermore, the results from the 11–15-year group indicate that the growth process is a protective factor against the risk of respiratory disease later in life. Lastly, the FOT findings highlight the detrimental effects of tobacco smoke exposure and urbanization and traffic on respiratory health and asthma-like symptoms, respectively. Overall, monitoring environmental and behavioral factors in childhood can provide valuable information for preventing respiratory diseases in adulthood.

Differences in the rate of nicotine metabolism among smokers with and without HIV

OBJECTIVE

HIV-infected smokers lose more life years to tobacco use than to HIV infection. The nicotine metabolite ratio (NMR), a biomarker of CYP2A6, represents individual variation in the rate at which nicotine is metabolized and is associated with response to smoking cessation treatments. We evaluated whether HIV-infected smokers metabolize nicotine faster than HIV-uninfected smokers, which may contribute to the disproportionate smoking burden and may have important treatment implications.

DESIGN

We analysed baseline data from two clinical trials (NCT01710137; NCT01314001) to compare the NMR in HIV-infected smokers (N = 131) to HIV-uninfected smokers (N = 199).

METHODS

Propensity scores were used to match the groups 2 : 1 on characteristics that influence NMR: sex, race, BMI and smoking rate. Nicotine metabolites were assessed via liquid chromatography-tandem mass spectrometry methods and the ratio of 3-hydroxycotinine:cotinine was used to compute the NMR.

RESULTS

HIV-infected smokers had significantly higher NMR (mean = 0.47, SEM = 0.02) and were more likely to be in the highest NMR quartile compared with HIV-uninfected smokers (mean = 0.34, SEM = 0.02; Ps < 0.001).

CONCLUSION

The higher NMR observed among HIV-infected smokers may partially explain higher smoking rates and lower response to transdermal nicotine therapy. Understanding the mechanisms by which HIV and/or ART contribute to faster nicotine metabolism may guide the use of the NMR to personalize tobacco cessation strategies in this underserved population.

Hepatic Abundance and Activity of Androgen- and Drug-Metabolizing Enzyme UGT2B17 Are Associated with Genotype, Age, and Sex

The major objective of this study was to investigate the association of genetic and nongenetic factors with variability in protein abundance and in vitro activity of the androgen-metabolizing enzyme UGT2B17 in human liver microsomes (n = 455). UGT2B17 abundance was quantified by liquid chromatography-tandem mass spectrometry proteomics, and enzyme activity was determined by using testosterone and dihydrotestosterone as in vitro probe substrates. Genotyping or gene resequencing and mRNA expression were also evaluated. Multivariate analysis was used to test the association of UGT2B17 copy number variation, single nucleotide polymorphisms (SNPs), age, and sex with its mRNA expression, abundance, and activity. UGT2B17 gene copy number and SNPs (rs7436962, rs9996186, rs28374627, and rs4860305) were associated with gene expression, protein levels, and androgen glucuronidation rates in a gene dose-dependent manner. UGT2B17 protein (mean ± S.D. picomoles per milligram of microsomal protein) is sparsely expressed in children younger than 9 years (0.12 ± 0.24 years) but profoundly increases from age 9 years to adults (∼10-fold) with ∼2.6-fold greater abundance in males than in females (1.2 vs. 0.47). Association of androgen glucuronidation with UGT2B15 abundance was observed only in the low UGT2B17 expressers. These data can be used to predict variability in the metabolism of UGT2B17 substrates. Drug companies should include UGT2B17 in early phenotyping assays during drug discovery to avoid late clinical failures.

Biosignature Discovery for Substance Use Disorders Using Statistical Learning

There are limited biomarkers for substance use disorders (SUDs). Traditional statistical approaches are identifying simple biomarkers in large samples, but clinical use cases are still being established. High-throughput clinical, imaging, and 'omic' technologies are generating data from SUD studies and may lead to more sophisticated and clinically useful models. However, analytic strategies suited for high-dimensional data are not regularly used. We review strategies for identifying biomarkers and biosignatures from high-dimensional data types. Focusing on penalized regression and Bayesian approaches, we address how to leverage evidence from existing studies and knowledge bases, using nicotine metabolism as an example. We posit that big data and machine learning approaches will considerably advance SUD biomarker discovery. However, translation to clinical practice, will require integrated scientific efforts.

Novel CYP2A6 diplotypes identified through next-generation sequencing are associated with in-vitro and in-vivo nicotine metabolism

OBJECTIVES

Smoking patterns and cessation rates vary widely across smokers and can be influenced by variation in rates of nicotine metabolism [i.e. cytochrome P450 2A6 (CYP2A6), enzyme activity]. There is high heritability of CYP2A6-mediated nicotine metabolism (60-80%) owing to known and unidentified genetic variation in the CYP2A6 gene. We aimed to identify and characterize additional genetic variants at the CYP2A6 gene locus.

METHODS

A new CYP2A6-specific sequencing method was used to investigate genetic variation in CYP2A6. Novel variants were characterized in a White human liver bank that has been extensively phenotyped for CYP2A6. Linkage and haplotype structure for the novel single nucleotide polymorphisms (SNPs) were assessed. The association between novel five-SNP diplotypes and nicotine metabolism rate was investigated.

RESULTS

Seven high-frequency (minor allele frequencies ≥6%) noncoding SNPs were identified as important contributors to CYP2A6 phenotypes in a White human liver bank (rs57837628, rs7260629, rs7259706, rs150298687 (also denoted rs4803381), rs56113850, rs28399453, and rs8192733), accounting for two times more variation in in-vitro CYP2A6 activity relative to the four established functional CYP2A6 variants that are frequently tested in Whites (CYP2A6*2, *4, *9, and *12). Two pairs of novel SNPs were in high linkage disequilibrium, allowing us to establish five-SNP diplotypes that were associated with CYP2A6 enzyme activity (rate of nicotine metabolism) in-vitro in the liver bank and in-vivo among smokers.

CONCLUSION

The novel five-SNP diplotype may be useful to incorporate into CYP2A6 genotype models for personalized prediction of nicotine metabolism rate, cessation success, and response to pharmacotherapies.

Variation in CYP2A6 Activity and Personalized Medicine

The cytochrome P450 2A6 (CYP2A6) enzyme metabolizes several clinically relevant substrates, including nicotine-the primary psychoactive component in cigarette smoke. The gene that encodes the CYP2A6 enzyme is highly polymorphic, resulting in extensive interindividual variation in CYP2A6 enzyme activity and the rate of metabolism of nicotine and other CYP2A6 substrates including cotinine, tegafur, letrozole, efavirenz, valproic acid, pilocarpine, artemisinin, artesunate, SM-12502, caffeine, and tyrosol. CYP2A6 expression and activity are also impacted by non-genetic factors, including induction or inhibition by pharmacological, endogenous, and dietary substances, as well as age-related changes, or interactions with other hepatic enzymes, co-enzymes, and co-factors. As variation in CYP2A6 activity is associated with smoking behavior, smoking cessation, tobacco-related lung cancer risk, and with altered metabolism and resulting clinical responses for several therapeutics, CYP2A6 expression and enzyme activity is an important clinical consideration. This review will discuss sources of variation in CYP2A6 enzyme activity, with a focus on the impact of CYP2A6 genetic variation on metabolism of the CYP2A6 substrates.

Genetic and Nongenetic Factors Associated with Protein Abundance of Flavin-Containing Monooxygenase 3 in Human Liver

Hepatic flavin-containing mono-oxygenase 3 (FMO3) metabolizes a broad array of nucleophilic heteroatom (e.g., N or S)-containing xenobiotics (e.g., amphetamine, sulindac, benzydamine, ranitidine, tamoxifen, nicotine, and ethionamide), as well as endogenous compounds (e.g., catecholamine and trimethylamine). To predict the effect of genetic and nongenetic factors on the hepatic metabolism of FMO3 substrates, we quantified FMO3 protein abundance in human liver microsomes (HLMs; n = 445) by liquid chromatography-tandem mass chromatography proteomics. Genotyping/gene resequencing, mRNA expression, and functional activity (with benzydamine as probe substrate) of FMO3 were also evaluated. FMO3 abundance increased 2.2-fold (13.0 ± 11.4 pmol/mg protein vs. 28.0 ± 11.8 pmol/mg protein) from neonates to adults. After 6 years of age, no significant difference in FMO3 abundance was found between children and adults. Female donors exhibited modestly higher mRNA fragments per kilobase per million reads values (139.9 ± 76.9 vs. 105.1 ± 73.1; P < 0.001) and protein FMO3 abundance (26.7 ± 12.0 pmol/mg protein vs. 24.1 ± 12.1 pmol/mg protein; P < 0.05) compared with males. Six single nucleotide polymorphisms (SNPs), including rs2064074, rs28363536, rs2266782 (E158K), rs909530 (N285N), rs2266780 (E308G), and rs909531, were associated with significantly decreased protein abundance. FMO3 abundance in individuals homozygous and heterozygous for haplotype 3 (H3), representing variant alleles for all these SNPs (except rs2066534), were 50.8% (P < 0.001) and 79.5% (P < 0.01), respectively, of those with the reference homozygous haplotype (H1, representing wild-type). In summary, FMO3 protein abundance is significantly associated with age, gender, and genotype. These data are important in predicting FMO3-mediated heteroatom-oxidation of xenobiotics and endogenous biomolecules in the human liver.

The Promises of Quantitative Proteomics in Precision Medicine

Precision medicine approach has a potential to ensure optimum efficacy and safety of drugs at individual patient level. Physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models could play a significant role in precision medicine by predicting interindividual variability in drug disposition and response. In order to develop robust PBPK/PD models, it is imperative that the critical physiological parameters affecting drug disposition and response and their variability are precisely characterized. Currently used PBPK/PD modeling software, for example, Simcyp and Gastroplus, encompass information such as organ volumes, blood flows to organs, body fat composition, glomerular filtration rate, etc. However, the information on the interindividual variability of the majority of the proteins associated with PK and PD, for example, drug metabolizing enzymes, transporters, and receptors, are not fully incorporated into these PBPK modeling platforms. Such information is significant because the population factors such as age, genotype, disease, and gender can affect abundance or activity of these proteins. To fill this critical knowledge gap, mass spectrometry-based quantitative proteomics has emerged as an important technique to characterize interindividual variability in the protein abundance of drug metabolizing enzymes, transporters, and receptors. Integration of these quantitative proteomics data into in silico PBPK/PD modeling tools will be crucial toward precision medicine.