A quantitative systems pharmacology model of plasma kallikrein-kinin system dysregulation in hereditary angioedema.

Hereditary angioedema (HAE) due to C1-inhibitor deficiency is a rare, debilitating, genetic disorder characterized by recurrent, unpredictable, attacks of edema. The clinical symptoms of HAE arise from excess bradykinin generation due to dysregulation of the plasma kallikrein-kinin system (KKS). A quantitative systems pharmacology (QSP) model that mechanistically describes the KKS and its role in HAE pathophysiology was developed based on HAE attacks being triggered by autoactivation of factor XII (FXII) to activated FXII (FXIIa), resulting in kallikrein production from prekallikrein. A base pharmacodynamic model was constructed and parameterized from literature data and ex vivo assays measuring inhibition of kallikrein activity in plasma of HAE patients or healthy volunteers who received lanadelumab. HAE attacks were simulated using a virtual patient population, with attacks recorded when systemic bradykinin levels exceeded 20 pM. The model was validated by comparing the simulations to observations from lanadelumab and plasma-derived C1-inhibitor clinical trials. The model was then applied to analyze the impact of nonadherence to a daily oral preventive therapy; simulations showed a correlation between the number of missed doses per month and reduced drug effectiveness. The impact of reducing lanadelumab dosing frequency from 300 mg every 2 weeks (Q2W) to every 4 weeks (Q4W) was also examined and showed that while attack rates with Q4W dosing were substantially reduced, the extent of reduction was greater with Q2W dosing. Overall, the QSP model showed good agreement with clinical data and could be used for hypothesis testing and outcome predictions.

Leveraging a physiologically-based quantitative translational modeling platform for designing B cell maturation antigen-targeting bispecific T cell engagers for treatment of multiple myeloma.

Bispecific T cell engagers (TCEs) are an emerging anti-cancer modality that redirects cytotoxic T cells to tumor cells expressing tumor-associated antigens (TAAs), thereby forming immune synapses to exert anti-tumor effects. Designing pharmacokinetically acceptable TCEs and optimizing their size presents a considerable protein engineering challenge, particularly given the complexity of intercellular bridging between T cells and tumor cells. Therefore, a physiologically-relevant and clinically-verified computational modeling framework is of crucial importance to understand the protein engineering trade-offs. In this study, we developed a quantitative, physiologically-based computational framework to predict immune synapse formation for a variety of molecular formats of TCEs in tumor tissues. Our model incorporates a molecular size-dependent biodistribution using the two-pore theory, extravasation of T cells and hematologic cancer cells, mechanistic bispecific intercellular binding of TCEs, and competitive inhibitory interactions by shed targets. The biodistribution of TCEs was verified by positron emission tomography imaging of [89Zr]AMG211 (a carcinoembryonic antigen-targeting TCE) in patients. Parameter sensitivity analyses indicated that immune synapse formation was highly sensitive to TAA expression, degree of target shedding, and binding selectivity to tumor cell surface TAAs over shed targets. Notably, the model suggested a "sweet spot" for TCEs' CD3 binding affinity, which balanced the trapping of TCEs in T-cell-rich organs. The final model simulations indicated that the number of immune synapses is similar (~55/tumor cell) between two distinct clinical stage B cell maturation antigen (BCMA)-targeting TCEs, PF-06863135 in an IgG format and AMG420 in a BiTE format, at their respective efficacious doses in multiple myeloma patients. This result demonstrates the applicability of the developed computational modeling framework to molecular design optimization and clinical benchmarking for TCEs, thus suggesting that this framework can be applied to other targets to provide a quantitative means to facilitate model-informed best-in-class TCE discovery and development.

Applications of Quantitative System Pharmacology Modeling to Model-Informed Drug Development.

Significant advances in analytical technologies have dramatically improved our ability to deconvolute disease biology at molecular, cellular, and tissue levels. Quantitative system pharmacology (QSP) modeling is a computational framework to systematically integrate pharmaceutical properties of a drug candidate with scientific understanding of that deeper disease etiology, target expression, genetic variability, and human physiological processes, thus enabling more insightful drug development decisions related to efficacy and safety. In this chapter, we discuss the key attributes of QSP models in comparison to traditional models. We discuss a recommended four-step process to construct a QSP model to support drug development decisions. A number of illustrative QSP examples related to high-value drug development questions and decisions impacting target identification, lead generation and optimization, first in human studies, and clinical dose and schedule optimization are covered in the chapter. The future perspectives of QSP in the context of potential regulatory acceptance are also discussed.

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.

Does sex alter the relationship between CYP2B6 variation, hydroxybupropion concentration and bupropion-aided smoking cessation in African Americans? A moderated mediation analysis.

BACKGROUND AND AIMS: CYP2B6, a genetically variable enzyme, converts bupropion to its active metabolite hydroxybupropion. CYP2B6 activity and bupropion-aided cessation differ between women and men. The aim of this study was to determine whether genetically normal (versus reduced) CYP2B6 activity increases bupropion-aided cessation in African American smokers via higher hydroxybupropion concentration, and whether this differs by sex. DESIGN AND SETTING: Secondary analysis of a smoking cessation clinical trial (NCT00666978). PARTICIPANTS/CASES: African American light smokers (≤ 10 cigarettes/day). INTERVENTIONS: Participants were treated with bupropion for 7 weeks. MEASUREMENTS: Participants with detectable bupropion and/or hydroxybupropion concentrations were divided into normal (n = 64) and reduced (n = 109) CYP2B6 activity groups based on the presence of decreased-function CYP2B6*6 and CYP2B6*18 alleles. Biochemically verified smoking cessation was assessed at week 3, end of treatment (7 weeks) and follow-up (26 weeks). FINDINGS: Normal (versus reduced) CYP2B6 activity was associated with increased cessation at week 7, which was mediated by higher hydroxybupropion concentration [odds ratio (OR) = 1.25, 95% confidence interval (CI) = 1.03, 1.78]; this mediation effect persisted at week 26 (OR = 1.23, 95% CI = 1.02, 1.70). The mediation effect was similar in women (n = 116; OR = 1.33, 95% CI = 1.01, 2.30) and men (n = 57; OR = 1.33, 95% CI = 0.92, 3.87). Moreover, sex did not appear to moderate the mediation effect, although this should be tested in a larger sample. CONCLUSIONS: In African American light smokers with verified early bupropion use, genetically normal CYP2B6 activity appears to be indirectly associated with greater smoking cessation success in a relationship mediated by higher hydroxybupropion concentration. The mediating effect of higher hydroxybupropion concentration on smoking cessation persists beyond the active treatment phase and does not appear to differ by sex.

Physiologically-Based Pharmacokinetic Modeling in Renal and Hepatic Impairment Populations: A Pharmaceutical Industry Perspective.

The predictive performance of physiologically-based pharmacokinetics (PBPK) models for pharmacokinetics (PK) in renal impairment (RI) and hepatic impairment (HI) populations was evaluated using clinical data from 29 compounds with 106 organ impairment study arms were collected from 19 member companies of the International Consortium for Innovation and Quality in Pharmaceutical Development. Fifty RI and 56 HI study arms with varying degrees of organ insufficiency along with control populations were evaluated. For RI, the area under the curve (AUC) ratios of RI to healthy control were predicted within twofold of the observed ratios for > 90% (N = 47/50 arms). For HI, > 70% (N = 43/56 arms) of the hepatically impaired to healthy control AUC ratios were predicted within twofold. Inaccuracies, typically overestimation of AUC ratios, occurred more in moderate and severe HI. PBPK predictions can help determine the need and timing of organ impairment study. It may be suitable for predicting the impact of RI on PK of drugs predominantly cleared by metabolism with varying contribution of renal clearance. PBPK modeling may be used to support mild impairment study waivers or clinical study design.

Quantitative Systems Pharmacology Approaches for Immuno-Oncology: Adding Virtual Patients to the Development Paradigm.

Drug development in oncology commonly exploits the tools of molecular biology to gain therapeutic benefit through reprograming of cellular responses. In immuno-oncology (IO) the aim is to direct the patient's own immune system to fight cancer. After remarkable successes of antibodies targeting PD1/PD-L1 and CTLA4 receptors in targeted patient populations, the focus of further development has shifted toward combination therapies. However, the current drug-development approach of exploiting a vast number of possible combination targets and dosing regimens has proven to be challenging and is arguably inefficient. In particular, the unprecedented number of clinical trials testing different combinations may no longer be sustainable by the population of available patients. Further development in IO requires a step change in selection and validation of candidate therapies to decrease development attrition rate and limit the number of clinical trials. Quantitative systems pharmacology (QSP) proposes to tackle this challenge through mechanistic modeling and simulation. Compounds' pharmacokinetics, target binding, and mechanisms of action as well as existing knowledge on the underlying tumor and immune system biology are described by quantitative, dynamic models aiming to predict clinical results for novel combinations. Here, we review the current QSP approaches, the legacy of mathematical models available to quantitative clinical pharmacologists describing interaction between tumor and immune system, and the recent development of IO QSP platform models. We argue that QSP and virtual patients can be integrated as a new tool in existing IO drug development approaches to increase the efficiency and effectiveness of the search for novel combination therapies.

A Minimal Physiologically-Based Pharmacokinetic Model Demonstrates Role of the Neonatal Fc Receptor (FcRn) Competition in Drug-Disease Interactions With Antibody Therapy.

Disease trajectories following antibody therapy can have a significant impact on the pharmacokinetics of the antibody. Although this phenomenon can often be explained by reduced target-expressing cells, other mechanisms may play a role. We use a novel minimal physiologically-based pharmacokinetic model to evaluate an alternative drug-disease interaction mechanism involving competitive inhibition of neonatal Fc receptor (FcRn)-mediated Immunoglobulin G recycling by paraproteins. The model is validated with clinical data from the anti-FcRn antibody M281 and is used to conduct a scenario test to quantify the interaction among M-protein, the characteristic paraprotein of multiple myeloma (MM), and the anti-CD38 antibody daratumumab indicated for MM treatment. Simulations predict up to a 3.6-fold increase in daratumumab half-life following M-protein reduction, which lends credence to the hypothesis that FcRn competition in MM can manifest as time-dependent reduction of clearance for daratumumab. This model can inform optimal dosing strategies for antibodies in MM and other pathologies of paraprotein excess.

A Citrulline-Based Translational Population System Toxicology Model for Gastrointestinal-Related Adverse Events Associated With Anticancer Treatments.

Gastrointestinal (GI)-related adverse events (AEs) are commonly observed in the clinic during cancer treatments. Citrulline is a potentially translatable biomarker of GI AEs. In this study, irinotecan-induced citrulline changes were studied for a range of doses and schedules in rats. A translational system toxicology model for GI AEs using citrulline was then developed based on new experimental data and parameters from a literature intestinal cell dynamic model. With the addition of feedback-development and tolerance-development mechanisms, the model well captured the plasma citrulline profiles after irinotecan treatment in rats. Subsequently, the model was translated to humans and predicted the observed GI AE dynamics in humans including dose-scheduling effect using the cytotoxic and feedback parameters estimated in rats with slight calibrations. This translational toxicology model could be used for other antineoplastic drugs to simulate various clinical dosing scenarios before human studies and mitigate potential GI AEs.

C57BL/6 Substrain Differences in Pharmacological Effects after Acute and Repeated Nicotine Administration.

Tobacco smoking is the major cause of disability and death in the United States and around the world. In addition, tobacco dependence and addiction express themselves as complex behaviors involving an interplay of genetics, environment, and psychological state. Mouse genetic studies could potentially elucidate the novel genes and/or gene networks regulating various aspects of nicotine dependence. Using the closely related C57BL/6 (B6) mice substrains, recent reports have noted phenotypic differences within C57BL/6J (B6J) and C57BL/6N (B6N) mice for some drugs of abuse: alcohol, opiates, and cocaine. However, the differences in nicotine's effects have not yet been described in these substrains. We examined the phenotypic differences in these substrains following the acute and repeated administration of nicotine in several pharmacological measures, including locomotion (after acute and repeated exposure), body temperature, nociception, and anxiety-like behaviors. We report substrain differences in the pharmacological effects of acute and repeated nicotine administration in the B6 substrains. Overall, we show enhanced nicotine sensitivity to locomotion, hypothermia, antinociception, and anxiety-like behaviors in the B6J mouse substrain compared to B6N. In the repeated administration paradigm, both the B6N and B6J substrains showed no sensitized locomotor responses after repeated exposure to nicotine at the two doses tested. This study thus provides evidence that the B6 mouse substrains may be useful for genetic studies to elucidate some of the genetic variants involved in tobacco dependence and addiction.

Recommendations for the Design of Clinical Drug-Drug Interaction Studies With Itraconazole Using a Mechanistic Physiologically-Based Pharmacokinetic Model.

Regulatory agencies currently recommend itraconazole (ITZ) as a strong cytochrome P450 3A (CYP3A) inhibitor for clinical drug-drug interaction (DDI) studies. This work by an International Consortium for Innovation and Quality in Pharmaceutical Development working group (WG) is to develop and verify a mechanistic ITZ physiologically-based pharmacokinetic model and provide recommendations for optimal DDI study design based on model simulations. To support model development and verification, in vitro and clinical PK data for ITZ and its metabolites were collected from WG member companies. The model predictions of ITZ DDIs with seven different CYP3A substrates were within the guest criteria for 92% of area under the concentration-time curve ratios and 95% of maximum plasma concentration ratios, thus verifying the model for DDI predictions. The verified model was used to simulate various clinical DDI study scenarios considering formulation, duration of dosing, dose regimen, and food status to recommend the optimal design for maximal inhibitory effect by ITZ.

Application of unbound liver-to-plasma concentration ratio to quantitative projection of cytochrome P450-mediated drug-drug interactions using physiologically based pharmacokinetic modelling approach.

1. This study evaluated the prediction accuracy of cytochrome P450 (CYP)-mediated drug-drug interaction (DDI) using minimal physiologically-based pharmacokinetic (PBPK) modelling incorporating the hepatic accumulation factor of an inhibitor (i.e. unbound liver/unbound plasma concentration ratio [Kp,uu,liver]) based on 22 clinical DDI studies. 2. Kp,uu,liver values were estimated using three methods: (1) ratio of cell-to-medium ratio in human cryopreserved hepatocytes (C/Mu) at 37 °C to that on ice (Kp,uu,C/M), (2) multiplication of total liver/unbound plasma concentration ratio (Kp,u,liver) estimated from C/Mu at 37 °C with unbound fraction in human liver homogenate (Kp,uu,cell) and (3) observed Kp,uu,liver in rats after intravenous infusion (Kp,uu,rat). 3. PBPK model using each Kp,uu,liver projected the area under the curve (AUC) increase of substrates more accurately than the model assuming a Kp,uu,liver of 1 for the average fold error and root mean square error did. Particularly, the model with a Kp,uu,liver of 1 underestimated the AUC increase of triazolam following co-administration with CYP3A4 inhibitor itraconazole by five-fold, whereas the AUC increase projected using the model incorporating the Kp,uu,C/M, Kp,uu,cell, or Kp,uu,rat of itraconazole and hydroxyitraconazole was within approximately two-fold of the actual value. 4. The results indicated that incorporating Kp,uu,liver into the PBPK model improved the accuracy of DDI projection.

Genome-wide association study of a nicotine metabolism biomarker in African American smokers: impact of chromosome 19 genetic influences.

BACKGROUND AND AIMS: The activity of CYP2A6, the major nicotine-inactivating enzyme, is measurable in smokers using the nicotine metabolite ratio (NMR; 3'hydroxycotinine/cotinine). Due to its role in nicotine clearance, the NMR is associated with smoking behaviours and response to pharmacotherapies. The NMR is highly heritable (~80%), and on average lower in African Americans (AA) versus whites. We previously identified several reduce and loss-of-function CYP2A6 variants common in individuals of African descent. Our current aim was to identify novel genetic influences on the NMR in AA smokers using genome-wide approaches. DESIGN: Genome-wide association study (GWAS). SETTING: Multiple sites within Canada and the United States. PARTICIPANTS: AA smokers from two clinical trials: Pharmacogenetics of Nicotine Addiction Treatment (PNAT)-2 (NCT01314001; n = 504) and Kick-it-at-Swope (KIS)-3 (NCT00666978; n = 450). MEASUREMENTS: Genome-wide SNP genotyping, the NMR (phenotype) and population substructure and NMR covariates. FINDINGS: Meta-analysis revealed three independent chromosome 19 signals (rs12459249, rs111645190 and rs185430475) associated with the NMR. The top overall hit, rs12459249 (P = 1.47e-39; beta = 0.59 per C (versus T) allele, SE = 0.045), located ~9.5 kb 3' of CYP2A6, remained genome-wide significant after controlling for the common (~10% in AA) non-functional CYP2A6*17 allele. In contrast, rs111645190 and rs185430475 were not genome-wide significant when controlling for CYP2A6*17. In total, 96 signals associated with the NMR were identified; many were not found in prior NMR GWASs in individuals of European descent. The top hits were also associated with the NMR in a third cohort of AA (KIS2; n = 480). None of the hits were in UGT or OCT2 genes. CONCLUSIONS: Three independent chromosome 19 signals account for ~20% of the variability in the nicotine metabolite ratio in African American smokers. The hits identified may contribute to inter-ethnic variability in nicotine metabolism, smoking behaviours and tobacco-related disease risk.

Fasiglifam (TAK-875) Alters Bile Acid Homeostasis in Rats and Dogs: A Potential Cause of Drug Induced Liver Injury.

Fasiglifam (TAK-875), a Free Fatty Acid Receptor 1 (FFAR1) agonist in development for the treatment of type 2 diabetes, was voluntarily terminated in phase 3 due to adverse liver effects. A mechanistic investigation described in this manuscript focused on the inhibition of bile acid (BA) transporters as a driver of the liver findings. TAK-875 was an in vitro inhibitor of multiple influx (NTCP and OATPs) and efflux (BSEP and MRPs) hepatobiliary BA transporters at micromolar concentrations. Repeat dose studies determined that TAK-875 caused a dose-dependent increase in serum total BA in rats and dogs. Additionally, there were dose-dependent increases in both unconjugated and conjugated individual BAs in both species. Rats had an increase in serum markers of liver injury without correlative microscopic signs of tissue damage. Two of 6 dogs that received the highest dose of TAK-875 developed liver injury with clinical pathology changes, and by microscopic analysis had portal granulomatous inflammation with neutrophils around a crystalline deposition. The BA composition of dog bile also significantly changed in a dose-dependent manner following TAK-875 administration. At the highest dose, levels of taurocholic acid were 50% greater than in controls with a corresponding 50% decrease in taurochenodeoxycholic acid. Transporter inhibition by TAK-875 may cause liver injury in dogs through altered bile BA composition characteristics, as evidenced by crystalline deposition, likely composed of test article, in the bile duct. In conclusion, a combination of in vitro and in vivo evidence suggests that BA transporter inhibition could contribute to TAK-875-mediated liver injury in dogs.

The discriminative stimulus effects of i.v. nicotine in rhesus monkeys: Pharmacokinetics and apparent pA2 analysis with dihydro-ß-erythroidine.

Quantitative analysis of antagonism is infrequently used to identify nAChRs mediating behavioral effects. Here, nicotine (0.032 mg/kg i.v.) was established as a discriminative stimulus in rhesus monkeys responding under a fixed ratio 5 schedule; pharmacokinetics and underlying nAChR mechanism(s) were examined. When measured up to 4 h in venous blood, the training dose resulted in the following mean pharmacokinetic parameters: nicotine Cmax = 71.7 ng/ml, t1/2 = 116 min, and clearance = 6.25 ml/min/kg; cotinine Cmax = 191 ng/ml; and 3OH-cotinine Cmax = 63 ng/ml. The ED50 value of nicotine to produce discriminative stimulus effects was 0.013 mg/kg. Epibatidine and varenicline increased drug-lever responding to 97% and 95%, respectively (ED50 values = 0.00015 and 0.031 mg/kg, respectively), whereas cocaine, midazolam, and morphine produced no more than 28% drug-appropriate responding. Mecamylamine and dihydro-ß-erythroidine (DHßE) dose-dependently attenuated the discriminative stimulus effects of the nicotine training dose, whereas methyllycaconitine (MLA) did not. DHßE (0.1 and 0.32) produced rightward shifts of the nicotine and varenicline dose-response functions; Schild plots fitted through individual data resulted in slopes that were not different from unity; the apparent pA2 calculated for DHßE did not significantly differ in the presence of nicotine (6.58) or varenicline (6.45). Compared to human cigarette smoking, nicotine blood levels after 0.032 mg/kg nicotine i.v. took a similar time to reach maximal concentration, levels at Cmax were similar to smoking 2-3 cigarettes, while average nicotine levels were comparable to smoking 5-6 cigarettes. Apparent pA2 analysis with DHßE under these conditions is consistent with nicotine and varenicline acting through the same nAChRs to produce discriminative stimulus effects.

Utilizing In Vitro Dissolution-Permeation Chamber for the Quantitative Prediction of pH-Dependent Drug-Drug Interactions with Acid-Reducing Agents: a Comparison with Physiologically Based Pharmacokinetic Modeling.

For many orally administered basic drugs with pH-dependent solubility, concurrent administration with acid-reducing agents (ARAs) can significantly impair their absorption and exposure. In this study, pH-dependent drug-drug interaction (DDI) prediction methods, including in vitro dissolution-permeation chamber (IVDP) and physiologically based pharmacokinetic (PBPK) modeling, were evaluated for their ability to quantitatively predict the clinical DDI observations using 11 drugs with known clinical pH-dependent DDI data. The data generated by IVDP, which consists of a gastrointestinal compartment and a systemic compartment separated by a biomimic membrane, significantly correlated with the clinical DDI observations. The gastrointestinal compartment AUC ratio showed strong correlation with clinical AUC ratio (R=0.72 and P=0.0056), and systemic compartment AUC ratio showed strong correlation with clinical Cmax ratio (R=0.91 and P=0.0003). PBPK models were also developed for the 11 test compounds. The simulations showed that the predictions from PBPK model with experimentally measured parameters significantly correlated with the clinical DDI observations. Future studies are needed to evaluate predictability of Z-factor-based PBPK models for pH-dependent DDI. Overall, these data suggested that the severity of pH-dependent DDI can be predicted by in vitro and in silico methods. Proper utilization of these methods before clinical DDI studies could allow adequate anticipation of pH-dependent DDI, which helps with minimizing pharmacokinetic variation in clinical studies and ensuring every patient with life-threatening diseases receives full benefit of the therapy.

Genome-Wide Meta-Analysis of Cotinine Levels in Cigarette Smokers Identifies Locus at 4q13.2.

Genome-wide association studies (GWAS) of complex behavioural phenotypes such as cigarette smoking typically employ self-report phenotypes. However, precise biomarker phenotypes may afford greater statistical power and identify novel variants. Here we report the results of a GWAS meta-analysis of levels of cotinine, the primary metabolite of nicotine, in 4,548 daily smokers of European ancestry. We identified a locus close to UGT2B10 at 4q13.2 (minimum p = 5.89 × 10(-10) for rs114612145), which was consequently replicated. This variant is in high linkage disequilibrium with a known functional variant in the UGT2B10 gene which is associated with reduced nicotine and cotinine glucuronidation activity, but intriguingly is not associated with nicotine intake. Additionally, we observed association between multiple variants within the 15q25.1 region and cotinine levels, all located within the CHRNA5-A3-B4 gene cluster or adjacent genes, consistent with previous much larger GWAS using self-report measures of smoking quantity. These results clearly illustrate the increase in power afforded by using precise biomarker measures in GWAS. Perhaps more importantly however, they also highlight that biomarkers do not always mark the phenotype of interest. The use of metabolite data as a proxy for environmental exposures should be carefully considered in the context of individual differences in metabolic pathways.

Effects of Menthol on Nicotine Pharmacokinetic, Pharmacology and Dependence in Mice.

Although menthol, a common flavoring additive to cigarettes, has been found to impact the addictive properties of nicotine cigarettes in smokers little is known about its pharmacological and molecular actions in the brain. Studies were undertaken to examine whether the systemic administration of menthol would modulate nicotine pharmacokinetics, acute pharmacological effects (antinociception and hypothermia) and withdrawal in male ICR mice. In addition, we examined changes in the brain levels of nicotinic receptors of rodents exposed to nicotine and menthol. Administration of i.p. menthol significantly decreased nicotine's clearance (2-fold decrease) and increased its AUC compared to i.p. vehicle treatment. In addition, menthol pretreatment prolonged the duration of nicotine-induced antinociception and hypothermia (2.5 mg/kg, s.c.) for periods up to 180 min post-nicotine administration. Repeated administration of menthol with nicotine increased the intensity of mecamylamine-precipitated withdrawal signs in mice exposed chronically to nicotine. The potentiation of withdrawal intensity by menthol was accompanied by a significant increase in nicotine plasma levels in these mice. Western blot analyses of α4 and ß2 nAChR subunit expression suggests that chronic menthol impacts the levels and distribution of these nicotinic subunits in various brain regions. In particular, co-administration of menthol and nicotine appears to promote significant increase in ß2 and α4 nAChR subunit expression in the hippocampus, prefrontal cortex and striatum of mice. Surprisingly, chronic injections of menthol alone to mice caused an upregulation of ß2 and α4 nAChR subunit levels in these brain regions. Because the addition of menthol to tobacco products has been suggested to augment their addictive potential, the current findings reveal several new pharmacological molecular adaptations that may contribute to its unique addictive profile.

Drug Metabolizing Enzyme and Transporter Gene Variation, Nicotine Metabolism, Prospective Abstinence, and Cigarette Consumption.

The Nicotine Metabolite Ratio (NMR, ratio of trans-3'-hydroxycotinine and cotinine), has previously been associated with CYP2A6 activity, response to smoking cessation treatments, and cigarette consumption. We searched for drug metabolizing enzyme and transporter (DMET) gene variation associated with the NMR and prospective abstinence in 2,946 participants of laboratory studies of nicotine metabolism and of clinical trials of smoking cessation therapies. Stage I was a meta-analysis of the association of 507 common single nucleotide polymorphisms (SNPs) at 173 DMET genes with the NMR in 449 participants of two laboratory studies. Nominally significant associations were identified in ten genes after adjustment for intragenic SNPs; CYP2A6 and two CYP2A6 SNPs attained experiment-wide significance adjusted for correlated SNPs (CYP2A6 PACT=4.1E-7, rs4803381 PACT=4.5E-5, rs1137115, PACT=1.2E-3). Stage II was mega-regression analyses of 10 DMET SNPs with pretreatment NMR and prospective abstinence in up to 2,497 participants from eight trials. rs4803381 and rs1137115 SNPs were associated with pretreatment NMR at genome-wide significance. In post-hoc analyses of CYP2A6 SNPs, we observed nominally significant association with: abstinence in one pharmacotherapy arm; cigarette consumption among all trial participants; and lung cancer in four case:control studies. CYP2A6 minor alleles were associated with reduced NMR, CPD, and lung cancer risk. We confirmed the major role that CYP2A6 plays in nicotine metabolism, and made novel findings with respect to genome-wide significance and associations with CPD, abstinence and lung cancer risk. Additional multivariate analyses with patient variables and genetic modeling will improve prediction of nicotine metabolism, disease risk and smoking cessation treatment prognosis.

Lack of Associations of CHRNA5-A3-B4 Genetic Variants with Smoking Cessation Treatment Outcomes in Caucasian Smokers despite Associations with Baseline Smoking.

CHRNA5-A3-B4 variants, rs16969968, rs588765 and rs578776, are consistently associated with tobacco consumption among smokers, but the association with smoking cessation is less consistent. Among the studies that reported significant associations with cessation, the effects were observed in smokers treated with placebo treatment in some studies and conversely in those receiving active pharmacological therapy (bupropion and nicotine replacement therapies) in others. Thus, it remains unclear whether CHRNA5-A3-B4 is a useful marker for optimizing smoking cessation. Using data from 654 Caucasian smokers treated with placebo, nicotine patch or varenicline, we investigated whether CHRNA5-A3-B4 variants were associated with smoking cessation outcomes, and whether there were significant genotype-by-treatment or haplotype-by-treatment interactions. We observed no significant associations between CHRNA5-A3-B4 variants and smoking cessation, despite replicating previous associations with baseline tobacco consumption. At end of treatment the effect size on smoking cessation in the placebo, patch and varenicline groups for rs16969968 [GG vs. GA+AA] was OR = 0.66 (P = 0.23), OR = 1.01 (P = 0.99), and OR = 1.30 (P = 0.36) respectively, of rs588765 [CC vs. CT+TT] was OR = 0.96 (P = 0.90), OR = 0.84 (P = 0.58), and OR = 0.74 (P = 0.29) respectively, and for rs578776 [GG vs. GA+AA] on smoking cessation was OR = 1.02 (P = 0.95), OR = 0.75 (P = 0.35), and OR = 1.20 (P = 0.51) respectively. Furthermore, we observed no associations with cessation using the CHRNA5-A3-B4 haplotype (constructed using rs16969968 and rs588765), nor did we observe any significant genotype-by-treatment interactions, with or without adjusting for the rate of nicotine metabolism (all P>0.05). We also observed no significant genetic associations with 6 month or 12 month smoking abstinence. In conclusion, we found no association between CHRNA5-A3-B4 variants and smoking cessation rates in this clinical trial; however, as expected, significant associations with baseline tobacco consumption were replicated. Our data suggest that CHRNA5-A3-B4 gene variants do not exhibit a robust association with smoking cessation and are unlikely to be useful for clinically optimizing smoking cessation pharmacotherapy for Caucasian smokers.