Novel Association of Genetic Markers Affecting CYP2A6 Activity and Lung Cancer Risk

Integrating genetic and clinical data to predict lung cancer in patients with chronic obstructive pulmonary disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is closely linked to lung cancer (LC) development. The aim of this study is to identify the genetic and clinical risk factors for LC risk in COPD, according to which the prediction model for LC in COPD was constructed.

METHODS

This is a case-control study in which patientis with COPD + LC as the case group, patientis with only COPD as the control group, and patientis with only LC as the second control group. A panel of clinical variables including demographic, environmental and lifestyle factors were collected. A total of 20 single nucleotide polymorphisms (SNPs) were genotyped. The univariate analysis, candidate gene study and multivariate analysis were applied to identify the independent risk factors, as well as the prediction model was constructed. The ROC analysis was used to evaluate the predictive ability of the model.

RESULTS

A total of 503 patients were finally enrolled in this study, with 188 patients for COPD + LC group, 162 patients for COPD group and 153 patients for LC group. The univariate analysis of clincial data showed compared with the patients with COPD, the patients with COPD + LC tended to have significantly lower BMI, higher smoking pack-years, and higher prevalence of emphysema. The results of the candidate gene study showed the rs1489759 in HHIP and rs56113850 in CYP2A6 demonstrated significant differences between COPD and COPD + LC groups. By using multivariate logistic regression analysis, four variables including BMI, pack-years, emphysema and rs56113850 were identified as independent risk factors for LC in COPD and the prediction model integrating genetic and clinical data was constructed. The AUC of the prediction model for LC in COPD reached 0.712, and the AUC of the model for predicting LC in serious COPD reached up to 0.836.

CONCLUSION

The rs56113850 (risk allele C) in CYP2A6, decrease in BMI, increase in pack-years and emphysema presence were independent risk factors for LC in COPD. Integrating genetic and clinical data for predicting LC in COPD demonstrated favorable predictive performance.

Genome-wide association study of maternal plasma metabolites during pregnancy

Metabolites are key indicators of health and therapeutic targets, but their genetic underpinnings during pregnancy-a critical period for human reproduction-are largely unexplored. Using genetic data from non-invasive prenatal testing, we performed a genome-wide association study on 84 metabolites, including 37 amino acids, 24 elements, 13 hormones, and 10 vitamins, involving 34,394 pregnant Chinese women, with sample sizes ranging from 6,394 to 13,392 for specific metabolites. We identified 53 metabolite-gene associations, 23 of which are novel. Significant differences in genetic effects between pregnant and non-pregnant women were observed for 16.7%-100% of these associations, indicating gene-environment interactions. Additionally, 50.94% of genetic associations exhibited pleiotropy among metabolites and between six metabolites and eight pregnancy phenotypes. Mendelian randomization revealed potential causal relationships between seven maternal metabolites and 15 human traits and diseases. These findings provide new insights into the genetic basis of maternal plasma metabolites during pregnancy.

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.

Lung Cancer in Ever- and Never-Smokers: Findings from Multi-Population GWAS Studies

BACKGROUND

Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer.

METHODS

We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer.

RESULTS

Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P < 5 × 10-8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear > 20). Different risk patterns were observed for the variants among the different groups by smoking behavior.

CONCLUSIONS

We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies.

IMPACT

Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.

CYP2A6 Activity and Cigarette Consumption Interact in Smoking-Related Lung Cancer Susceptibility

Cigarette smoke, containing both nicotine and carcinogens, causes lung cancer. However, not all smokers develop lung cancer, highlighting the importance of the interaction between host susceptibility and environmental exposure in tumorigenesis. Here, we aimed to delineate the interaction between metabolizing ability of tobacco carcinogens and smoking intensity in mediating genetic susceptibility to smoking-related lung tumorigenesis. Single-variant and gene-based associations of 43 tobacco carcinogen-metabolizing genes with lung cancer were analyzed using summary statistics and individual-level genetic data, followed by causal inference of Mendelian randomization, mediation analysis, and structural equation modeling. Cigarette smoke-exposed cell models were used to detect gene expression patterns in relation to specific alleles. Data from the International Lung Cancer Consortium (29,266 cases and 56,450 controls) and UK Biobank (2,155 cases and 376,329 controls) indicated that the genetic variant rs56113850 C>T located in intron 4 of CYP2A6 was significantly associated with decreased lung cancer risk among smokers (OR = 0.88, 95% confidence interval = 0.85-0.91, P = 2.18 × 10-16), which might interact (Pinteraction = 0.028) with and partially be mediated (ORindirect = 0.987) by smoking status. Smoking intensity accounted for 82.3% of the effect of CYP2A6 activity on lung cancer risk but entirely mediated the genetic effect of rs56113850. Mechanistically, the rs56113850 T allele rescued the downregulation of CYP2A6 caused by cigarette smoke exposure, potentially through preferential recruitment of transcription factor helicase-like transcription factor. Together, this study provides additional insights into the interplay between host susceptibility and carcinogen exposure in smoking-related lung tumorigenesis.

SIGNIFICANCE

The causal pathway connecting CYP2A6 genetic variability and activity, cigarette consumption, and lung cancer susceptibility in smokers highlights the need for behavior modification interventions based on host susceptibility for cancer prevention.

Recurrent CYP2A6 gene mutation in biphasic hyalinizing psammomatous renal cell carcinoma: Additional support of three cases

Biphasic hyalinizing psammomatous renal cell carcinoma (BHP RCC) with NF2 gene mutations is a newly described provisional category of renal cell carcinoma (RCC). Here we described three additional cases of BHP RCC with CYP2A6 gene mutation besides NF2 gene. The carcinomas were predominantly unencapsulated, and two of them had a rounded, nodular interface with the native kidney while one had perirenal adipose tissue invasion. Histopathologically, all neoplasms had a characteristic biphasic appearance of smaller cells clustering around basement membrane material within larger acini, forming pseudorosettes or a glomeruloid pattern. The smaller cells were focally spindle-shaped in two carcinomas. Psammoma bodies were shown in two carcinomas. Cellular necrosis and perineural invasion was identified in one case. Immunohistochemically, Vimentin, EMA, P504s were extensively expressed while RCC and CD10 were only expressed in larger cells. CK7 was positive in one tumor. CYP2A6 gene mutation (CYP2A6 NM_000762.6: exon4:c.A580G:p.K194E) was revealed in three tumors by Whole-genome exome sequencing, which was further confirmed by Sanger sequencing. Only one case harbored a somatic termination mutation in NF2 gene. NF2 promoter methylation was observed in the other two cases. Clinically, one patient died of disease with widespread bone metastases confirmed by biopsy at the ninth month after surgery but the other two patients had no evidence of recurrence or metastases (follow-up period 9-90 months). Our findings validated previously described clinicopathological features and NF2 gene mutation or promoter methylation of BHP RCC. In addition, we reported different IHC pattern of BHP RCC and further revealed the recurrent CYP2A6 genetic alteration.

Evaluating the causal effect of tobacco smoking on white matter brain aging: a two-sample Mendelian randomization analysis in UK Biobank

BACKGROUND AND AIMS

Tobacco smoking is a risk factor for impaired brain function, but its causal effect on white matter brain aging remains unclear. This study aimed to measure the causal effect of tobacco smoking on white matter brain aging.

DESIGN

Mendelian randomization (MR) analysis using two non-overlapping data sets (with and without neuroimaging data) from UK Biobank (UKB). The group exposed to smoking and control group consisted of current smokers and never smokers, respectively. Our main method was generalized weighted linear regression with other methods also included as sensitivity analysis.

SETTING

United Kingdom.

PARTICIPANTS

The study cohort included 23 624 subjects [10 665 males and 12 959 females with a mean age of 54.18 years, 95% confidence interval (CI) = 54.08, 54.28].

MEASUREMENTS

Genetic variants were selected as instrumental variables under the MR analysis assumptions: (1) associated with the exposure; (2) influenced outcome only via exposure; and (3) not associated with confounders. The exposure smoking status (current versus never smokers) was measured by questionnaires at the initial visit (2006-10). The other exposure, cigarettes per day (CPD), measured the average number of cigarettes smoked per day for current tobacco users over the life-time. The outcome was the 'brain age gap' (BAG), the difference between predicted brain age and chronological age, computed by training machine learning model on a non-overlapping set of never smokers.

FINDINGS

The estimated BAG had a mean of 0.10 (95% CI = 0.06, 0.14) years. The MR analysis showed evidence of positive causal effect of smoking behaviors on BAG: the effect of smoking is 0.21 (in years, 95% CI = 6.5 × 10-3 , 0.41; P-value = 0.04), and the effect of CPD is 0.16 year/cigarette (UKB: 95% CI = 0.06, 0.26; P-value = 1.3 × 10-3 ; GSCAN: 95% CI = 0.02, 0.31; P-value = 0.03). The sensitivity analyses showed consistent results.

CONCLUSIONS

There appears to be a significant causal effect of smoking on the brain age gap, which suggests that smoking prevention can be an effective intervention for accelerated brain aging and the age-related decline in cognitive function.

The Use of Biomarkers to Guide Precision Treatment for Tobacco Use

This review summarizes the evidence to date on the development of biomarkers for personalizing the pharmacological treatment of combustible tobacco use. First, the latest evidence on FDA-approved medications is considered, demonstrating that, while these medications offer real benefits, they do not contribute to smoking cessation in approximately two-thirds of cases. Second, the case for using biomarkers to guide tobacco treatment is made based on the potential to increase medication effectiveness and uptake and reduce side effects. Next, the FDA framework of biomarker development is presented along with the state of science on biomarkers for tobacco treatment, including a review of the nicotine metabolite ratio, electroencephalographic event-related potentials, and other biomarkers utilized for risk feedback. We conclude with a discussion of the challenges and opportunities for the translation of biomarkers to guide tobacco treatment and propose priorities for future research.

Contribution of Genetic Polymorphisms in Human Health

Human health is influenced by various factors; these include genetic inheritance, behavioral lifestyle, socioeconomic and environmental conditions, and public access to care and therapies in case of illness, with the support of the national health system. All these factors represent the starting point for the prevention and promotion of a healthy lifestyle. However, it is not yet clear to what extent these factors may actually affect the health of an entire population. The exposures to environmental and occupational factors are several, most of which might be poorly known, contributing to influencing individual health. Personal habits, including diet, smoking, alcohol, and drug consumption, together with unhealthy behaviors, may inevitably lead people to the development of chronic diseases, contributing to increasing aging and decreasing life expectancy. In this article, we highlight the role of susceptibility biomarkers, i.e., the genetic polymorphisms of individuals of different ethnicities, with particular attention to the risk factors in the response to specific exposures of Europeans. Moreover, we discuss the role of precision medicine which is representing a new way of treating and preventing diseases, taking into account the genetic variability of the individual with each own clinical history and lifestyle.

Predicting nicotine metabolism across ancestries using genotypes

BACKGROUND

There is a need to match characteristics of tobacco users with cessation treatments and risks of tobacco attributable diseases such as lung cancer. The rate in which the body metabolizes nicotine has proven an important predictor of these outcomes. Nicotine metabolism is primarily catalyzed by the enzyme cytochrone P450 (CYP2A6) and CYP2A6 activity can be measured as the ratio of two nicotine metabolites: trans-3'-hydroxycotinine to cotinine (NMR). Measurements of these metabolites are only possible in current tobacco users and vary by biofluid source, timing of collection, and protocols; unfortunately, this has limited their use in clinical practice. The NMR depends highly on genetic variation near CYP2A6 on chromosome 19 as well as ancestry, environmental, and other genetic factors. Thus, we aimed to develop prediction models of nicotine metabolism using genotypes and basic individual characteristics (age, gender, height, and weight).

RESULTS

We identified four multiethnic studies with nicotine metabolites and DNA samples. We constructed a 263 marker panel from filtering genome-wide association scans of the NMR in each study. We then applied seven machine learning techniques to train models of nicotine metabolism on the largest and most ancestrally diverse dataset (N=2239). The models were then validated using the other three studies (total N=1415). Using cross-validation, we found the correlations between the observed and predicted NMR ranged from 0.69 to 0.97 depending on the model. When predictions were averaged in an ensemble model, the correlation was 0.81. The ensemble model generalizes well in the validation studies across ancestries, despite differences in the measurements of NMR between studies, with correlations of: 0.52 for African ancestry, 0.61 for Asian ancestry, and 0.46 for European ancestry. The most influential predictors of NMR identified in more than two models were rs56113850, rs11878604, and 21 other genetic variants near CYP2A6 as well as age and ancestry.

CONCLUSIONS

We have developed an ensemble of seven models for predicting the NMR across ancestries from genotypes and age, gender and BMI. These models were validated using three datasets and associate with nicotine dosages. The knowledge of how an individual metabolizes nicotine could be used to help select the optimal path to reducing or quitting tobacco use, as well as, evaluating risks of tobacco use.

Genetic variants in CYP2B6 and HSD17B12 associated with risk of squamous cell carcinoma of the head and neck

Polycyclic aromatic hydrocarbons (PAH) and tobacco-specific nitrosamines (TSNA) metabolism-related genes play an important role in the development of cancers. We assessed the associations of genetic variants in genes involved in the metabolism of PAHs and TSNA with risk of squamous cell carcinoma of the head and neck (SCCHN) in European populations using two published genome-wide association study datasets. In the single-locus analysis, we identified two SNPs (rs145533669 and rs35246205) in CYP2B6 to be associated with risk of SCCHN (P = 1.57 × 10-4 and .004, respectively), two SNPs (EPHX1 rs117522494 and CYP2B6 rs145533669) to be associated with risk of oropharyngeal cancer (P = .001 and .004, respectively), and one SNP (rs4359199 in HSD17B12) to be associated with risk of oral cancer (P = .006). A significant interaction effect was found between rs4359199 and drinking status on risks of SCCHN and oropharyngeal cancer (P < .05). eQTL and sQTL analyzes revealed that two SNPs (CYP2B6 rs35246205 and HSD17B12 rs4359199) were correlated with alternative splicing or mRNA expression levels of the corresponding genes in liver cells (P < .05 for both). In silico functional annotation suggested that these two SNPs may regulate mRNA expression by affecting the binding of transcription factors. Results from phenome-wide association studies presented significant associations between these genes and risks of other cancers, smoking behavior and alcohol dependence (P < .05). Thus, our study provided some insight into the underlying genetic mechanism of head and neck cancer, which warrants future functional validation.

Genetic Analysis of Lung Cancer and the Germline Impact on Somatic Mutation Burden

BACKGROUND

Germline genetic variation contributes to lung cancer (LC) susceptibility. Previous genome-wide association studies (GWAS) have implicated susceptibility loci involved in smoking behaviors and DNA repair genes, but further work is required to identify susceptibility variants.

METHODS

To identify LC susceptibility loci, a family history-based genome-wide association by proxy (GWAx) of LC (48 843 European proxy LC patients, 195 387 controls) was combined with a previous LC GWAS (29 266 patients, 56 450 controls) by meta-analysis. Colocalization was used to explore candidate genes and overlap with existing traits at discovered susceptibility loci. Polygenic risk scores (PRS) were tested within an independent validation cohort (1 666 LC patients vs 6 664 controls) using variants selected from the LC susceptibility loci and a novel selection approach using published GWAS summary statistics. Finally, the effects of the LC PRS on somatic mutational burden were explored in patients whose tumor resections have been profiled by exome (n = 685) and genome sequencing (n = 61). Statistical tests were 2-sided.

RESULTS

The GWAx-GWAS meta-analysis identified 8 novel LC loci. Colocalization implicated DNA repair genes (CHEK1), metabolic genes (CYP1A1), and smoking propensity genes (CHRNA4 and CHRNB2). PRS analysis demonstrated that these variants, as well as subgenome-wide significant variants related to expression quantitative trait loci and/or smoking propensity, assisted in LC genetic risk prediction (odds ratio = 1.37, 95% confidence interval = 1.29 to 1.45; P < .001). Patients with higher genetic PRS loads of smoking-related variants tended to have higher mutation burdens in their lung tumors.

CONCLUSIONS

This study has expanded the number of LC susceptibility loci and provided insights into the molecular mechanisms by which these susceptibility variants contribute to LC development.

Accuracy and applications of sequencing and genotyping approaches for CYP2A6 and homologous genes

OBJECTIVES

We evaluated multiple genotyping/sequencing approaches in a homologous region of chromosome 19, and investigated associations of two common 3'-UTR CYP2A6 variants with activity in vivo.

METHODS

Individuals (n = 1704) of European and African ancestry were phenotyped for the nicotine metabolite ratio (NMR), an index of CYP2A6 activity, and genotyped/sequenced using deep amplicon exon sequencing, SNP array, genotype imputation and targeted capture sequencing. Amplicon exon sequencing was the gold standard to which other methods were compared within-individual for CYP2A6, CYP2A7, CYP2A13, and CYP2B6 exons to identify highly discordant positions. Linear regression models evaluated the association of CYP2A6*1B and rs8192733 genotypes (coded additively) with logNMR.

RESULTS

All approaches were ≤2.6% discordant with the gold standard; discordant calls were concentrated at few positions. Fifteen positions were discordant in >10% of individuals, with 12 appearing in regions of high identity between homologous genes (e.g. CYP2A6 and CYP2A7). For six, allele frequencies in our study and online databases were discrepant, suggesting errors in online sources. In the European-ancestry group (n = 935), CYP2A6*1B and rs8192733 were associated with logNMR (P < 0.001). A combined model found main effects of both variants on increasing logNMR. Similar trends were found in those of African ancestry (n = 506).

CONCLUSION

Multiple genotyping/sequencing approaches used in this chromosome 19 region contain genotyping/sequencing errors, as do online databases. Gene-specific primers and SNP array probes must consider gene homology; short-read sequencing of related genes in a single reaction should be avoided. Using improved sequencing approaches, we characterized two gain-of-function 3'-UTR variants, including the relatively understudied rs8192733.

Association between early gestation passive smoke exposure and neonatal size among self-reported non-smoking women by race/ethnicity: A cohort study

Understanding implications of passive smoke exposure during pregnancy is an important public health issue under the Developmental Origins of Health and Disease paradigm. In a prospective cohort of low-risk non-smoking pregnant women (NICHD Fetal Growth Studies—Singletons, 2009–2013, N = 2055), the association between first trimester passive smoke exposure and neonatal size was assessed by race/ethnicity. Plasma biomarker concentrations (cotinine, nicotine) assessed passive smoke exposure. Neonatal anthropometric measures included weight, 8 non-skeletal, and 2 skeletal measures. Linear regression evaluated associations between continuous biomarker concentrations and neonatal anthropometric measures by race/ethnicity. Cotinine concentrations were low and the percent above limit of quantification varied by maternal race/ethnicity (10% Whites; 14% Asians; 15% Hispanics; 49% Blacks). The association between cotinine concentration and infant weight differed by race/ethnicity (P_interaction = 0.034); compared to women of the same race/ethnicity, per 1 log-unit increase in cotinine, weight increased 48g (95%CI -44, 139) in White and 51g (95%CI -81, 183) in Hispanic women, but decreased -90g (95%CI -490, 309) in Asian and -93g (95%CI -151, -35) in Black women. Consistent racial/ethnic differences and patterns were found for associations between biomarker concentrations and multiple non-skeletal measures for White and Black women (P_interaction<0.1). Among Black women, an inverse association between cotinine concentration and head circumference was observed (−0.20g; 95%CI −0.38, −0.02). Associations between plasma cotinine concentration and neonatal size differed by maternal race/ethnicity, with increasing concentrations associated with decreasing infant size among Black women, who had the greatest biomarker concentrations. Public health campaigns should advocate for reducing pregnancy exposure, particularly for vulnerable populations.

Multiethnic Prediction of Nicotine Biomarkers and Association With Nicotine Dependence

INTRODUCTION

The nicotine metabolite ratio and nicotine equivalents are measures of metabolism rate and intake. Genome-wide prediction of these nicotine biomarkers in multiethnic samples will enable tobacco-related biomarker, behavioral, and exposure research in studies without measured biomarkers.

AIMS AND METHODS

We screened genetic variants genome-wide using marginal scans and applied statistical learning algorithms on top-ranked genetic variants, age, ethnicity and sex, and, in additional modeling, cigarettes per day (CPD), (in additional modeling) to build prediction models for the urinary nicotine metabolite ratio (uNMR) and creatinine-standardized total nicotine equivalents (TNE) in 2239 current cigarette smokers in five ethnic groups. We predicted these nicotine biomarkers using model ensembles and evaluated external validity using dependence measures in 1864 treatment-seeking smokers in two ethnic groups.

RESULTS

The genomic regions with the most selected and included variants for measured biomarkers were chr19q13.2 (uNMR, without and with CPD) and chr15q25.1 and chr10q25.3 (TNE, without and with CPD). We observed ensemble correlations between measured and predicted biomarker values for the uNMR and TNE without (with CPD) of 0.67 (0.68) and 0.65 (0.72) in the training sample. We observed inconsistency in penalized regression models of TNE (with CPD) with fewer variants at chr15q25.1 selected and included. In treatment-seeking smokers, predicted uNMR (without CPD) was significantly associated with CPD and predicted TNE (without CPD) with CPD, time-to-first-cigarette, and Fagerström total score.

CONCLUSIONS

Nicotine metabolites, genome-wide data, and statistical learning approaches developed novel robust predictive models for urinary nicotine biomarkers in multiple ethnic groups. Predicted biomarker associations helped define genetically influenced components of nicotine dependence.

IMPLICATIONS

We demonstrate development of robust models and multiethnic prediction of the uNMR and TNE using statistical and machine learning approaches. Variants included in trained models for nicotine biomarkers include top-ranked variants in multiethnic genome-wide studies of smoking behavior, nicotine metabolites, and related disease. Association of the two predicted nicotine biomarkers with Fagerström Test for Nicotine Dependence items supports models of nicotine biomarkers as predictors of physical dependence and nicotine exposure. Predicted nicotine biomarkers may facilitate tobacco-related disease and treatment research in samples with genomic data and limited nicotine metabolite or tobacco exposure data.

Polymorphism in cytochrome P4502A6 reduces the risk to head and neck cancer and modifies the treatment outcome

The present case-control study consisting of 1300 cases of head and neck squamous cell carcinoma (HNSCC) and the equal number of controls aimed to investigate the association of functionally important polymorphisms in cytochrome P4502A6 (CYP2A6*1B, CYP2A6*4C, CYP2A6*9-rs28399433) with HNSCC and the treatment response in cases receiving a combination of chemotherapy/radiotherapy (CT/RT). A significant decrease in risk to HNSCC was observed in the cases with deletion (CYP2A6*4B and CYP2A6*4C) or reduced activity genotypes (CYP2A6*9) of CYP2A6. This risk to HNSCC was further reduced significantly in tobacco users among the cases when compared to nontobacco users among the cases. The risk was also reduced to a slightly greater extent in alcohol users among the cases when compared to nonalcohol users among the cases. In contrast with decreased risk to HNSCC, almost half of the cases with variant genotypes of CYP2A6 (CYP2A6*1A/*4C+*1B/*4C+*4C/*4C and *9/*9) did not respond to the treatment. Likewise, the survival rate in cases receiving the treatment, after 55 months of follow-up was significantly lower in cases with deletion (6.3%) or reduced activity (11.9%) allele than in the cases with common alleles (41%). The present study has shown that CYP2A6 polymorphism significantly reduces the risk to HNSCC. Our data further suggested that CYP2A6 polymorphism may worsen the treatment outcome in the cases receiving CT/RT.

Analyses of nicotine metabolism biomarker genetics stratified by sex in African and European Americans

Nicotine is inactivated by the polymorphic CYP2A6 enzyme to cotinine and then to 3'hydroxycotinine. The Nicotine Metabolite Ratio (NMR; 3'hydroxycotinine/cotinine) is a heritable nicotine metabolism biomarker, varies with sex and ancestry, and influences smoking cessation and disease risk. We conducted sex-stratified genome-wide association studies of the NMR in European American (EA) and African American (AA) smokers (NCT01314001, NCT00666978). In EA females (n = 389) and males (n = 541), one significant (P < 5e-8) chromosome 19 locus was found (top variant: rs56113850, CYP2A6 (intronic), for C vs. T: females: beta = 0.67, P = 7.5e-22, 21.8% variation explained; males: beta = 0.75, P = 1.2e-37, 26.1% variation explained). In AA females (n = 503) and males (n = 352), the top variant was found on chromosome 19 but differed by sex (females: rs11878604, CYP2A6 (~ 16 kb 3'), for C vs. T: beta = - 0.71, P = 6.6e-26, 16.2% variation explained; males: rs3865454, CYP2A6 (~ 7 kb 3'), for G vs. T: beta = 0.64, P = 1.9e-19, 18.9% variation explained). In AA females, a significant region was found on chromosome 12 (top variant: rs12425845: P = 5.0e-9, TMEM132C (~ 1 Mb 5'), 6.1% variation explained) which was not significant in AA males. In AA males, significant regions were found on chromosomes 6 (top variant: rs9379805: P = 4.8e-9, SLC17A2 (~ 8 kb 5'), 8.0% variation explained) and 16 (top variant: rs77368288: P = 3.5e-8, ZNF469 (~ 92 kb 5'), 7.1% variation explained) which were not significant in AA females. Further investigation of these associations outside of chromosome 19 is required, as they did not replicate. Understanding how sex and ancestry influence nicotine metabolism genetics may improve personalized approaches for smoking cessation and risk prediction for tobacco-related diseases.

Population-specific reference panels are crucial for genetic analyses: an example of the CREBRF locus in Native Hawaiians

Statistical imputation applied to genome-wide array data is the most cost-effective approach to complete the catalog of genetic variation in a study population. However, imputed genotypes in underrepresented populations incur greater inaccuracies due to ascertainment bias and a lack of representation among reference individuals, further contributing to the obstacles to study these populations. Here we examined the consequences due to the lack of representation by genotyping in a large number of self-reported Native Hawaiians (N = 3693) a functionally important, Polynesian-specific variant in the CREBRF gene, rs373863828. We found the derived allele was significantly associated with several adiposity traits with large effects (e.g. ~ 1.28 kg/m2 per allele in body mass index as the most significant; P = 7.5 × 10-5), consistent with the original findings in Samoans. Due to the current absence of Polynesian representation in publicly accessible reference sequences, rs373863828 or its proxies could not be tested through imputation using these existing resources. Moreover, the association signals at the entire CREBRF locus could not be captured by alternative approaches, such as admixture mapping. In contrast, highly accurate imputation can be achieved even if a small number (<200) of internally constructed Polynesian reference individuals were available; this would increase sample size and improve the statistical evidence of associations. Taken together, our results suggest the alarming possibility that lack of representation in reference panels could inhibit discovery of functionally important loci such as CREBRF. Yet, they could be easily detected and prioritized with improved representation of diverse populations in sequencing studies.

Genome-wide association study of letrozole plasma concentrations identifies non-exonic variants that may affect CYP2A6 metabolic activity

OBJECTIVES

Letrozole is a nonsteroidal aromatase inhibitor used to treat hormone-receptor-positive breast cancer. Variability in letrozole efficacy and toxicity may be partially attributable to variable systemic drug exposure, which may be influenced by germline variants in the enzymes responsible for letrozole metabolism, including cytochrome P450 2A6 (CYP2A6). The objective of this genome-wide association study (GWAS) was to identify polymorphisms associated with steady-state letrozole concentrations.

METHODS

The Exemestane and Letrozole Pharmacogenetics (ELPh) Study randomized postmenopausal patients with hormone-receptor-positive nonmetastatic breast cancer to letrozole or exemestane treatment. Germline DNA was collected pretreatment and blood samples were collected after 1 or 3 months of treatment to measure steady-state letrozole (and exemestane) plasma concentrations via HPLC/MS. Genome-wide genotyping was conducted on the Infinium Global Screening Array (>650 000 variants) followed by imputation. The association of each germline variant with age- and BMI-adjusted letrozole concentrations was tested in self-reported white patients via linear regression assuming an additive genetic model.

RESULTS

There were 228 patients who met the study-specific inclusion criteria and had both DNA and letrozole concentration data for this GWAS. The association for one genotyped polymorphism (rs7937) with letrozole concentration surpassed genome-wide significance (P = 5.26 × 10-10), explaining 13% of the variability in untransformed steady-state letrozole concentrations. Imputation around rs7937 and in silico analyses identified rs56113850, a variant in the CYP2A6 intron that may affect CYP2A6 expression and activity. rs7937 was associated with age- and BMI-adjusted letrozole levels even after adjusting for genotype-predicted CYP2A6 metabolic phenotype (P = 3.86 × 10-10).

CONCLUSION

Our GWAS findings confirm that steady-state letrozole plasma concentrations are partially determined by germline polymorphisms that affect CYP2A6 activity, including variants near rs7937 such as the intronic rs56113850 variant. Further research is needed to confirm whether rs56113850 directly affects CYP2A6 activity and to integrate nonexonic variants into CYP2A6 phenotypic activity prediction systems.

Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

BACKGROUND

Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field.

RESULTS

Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels.

CONCLUSION

This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

Genome-wide association meta-analysis of nicotine metabolism and cigarette consumption measures in smokers of European descent

Smoking behaviors, including amount smoked, smoking cessation, and tobacco-related diseases, are altered by the rate of nicotine clearance. Nicotine clearance can be estimated using the nicotine metabolite ratio (NMR) (ratio of 3'hydroxycotinine/cotinine), but only in current smokers. Advancing the genomics of this highly heritable biomarker of CYP2A6, the main metabolic enzyme for nicotine, will also enable investigation of never and former smokers. We performed the largest genome-wide association study (GWAS) to date of the NMR in European ancestry current smokers (n = 5185), found 1255 genome-wide significant variants, and replicated the chromosome 19 locus. Fine-mapping of chromosome 19 revealed 13 putatively causal variants, with nine of these being highly putatively causal and mapping to CYP2A6, MAP3K10, ADCK4, and CYP2B6. We also identified a putatively causal variant on chromosome 4 mapping to TMPRSS11E and demonstrated an association between TMPRSS11E variation and a UGT2B17 activity phenotype. Together the 14 putatively causal SNPs explained ~38% of NMR variation, a substantial increase from the ~20 to 30% previously explained. Our additional GWASs of nicotine intake biomarkers showed that cotinine and smoking intensity (cotinine/cigarettes per day (CPD)) shared chromosome 19 and chromosome 4 loci with the NMR, and that cotinine and a more accurate biomarker, cotinine + 3'hydroxycotinine, shared a chromosome 15 locus near CHRNA5 with CPD and Pack-Years (i.e., cumulative exposure). Understanding the genetic factors influencing smoking-related traits facilitates epidemiological studies of smoking and disease, as well as assists in optimizing smoking cessation support, which in turn will reduce the enormous personal and societal costs associated with smoking.

Low expression of developing brain homeobox 2 (Dbx2) may serve as a biomarker to predict poor prognosis in endometrial cancer

OBJECTIVE

For investigating Dbx2's expression in endometrial cancer (EC) and its effect on prognosis of patients with EC.

METHODS

A comparison was performed in the Cancer Genome Atlas (TCGA) database in terms of the expression profiling of EC and the survival data. To obtain differential expression genes (DEGs), Volcano plot and Venn analysis were adopted. DEGs function was performed by carrying out the GO annotation analysis (GO) and gene set enrichment analysis (GSEA). In clinical EC samples, PCR was applied to the verification of Dbx2's expression.

RESULTS

Dbx2 was a downregulated expression in tumor tissues. Dbx2 can have a poor prognosis role in EC by regulating the apoptotic signaling pathway and the immune pathway. Lower expression of Dbx2 was related to lymph node metastasis and FIGO stage.

CONCLUSION

Dbx2 is downregulated in endometrial cancer, which serves as a biomarker to predict poor prognosis.

Biochemistry of nicotine metabolism and its relevance to lung cancer

Nicotine is the key addictive constituent of tobacco. It is not a carcinogen, but it drives smoking and the continued exposure to the many carcinogens present in tobacco. The investigation into nicotine biotransformation has been ongoing for more than 60 years. The dominant pathway of nicotine metabolism in humans is the formation of cotinine, which occurs in two steps. The first step is cytochrome P450 (P450, CYP) 2A6–catalyzed 5′-oxidation to an iminium ion, and the second step is oxidation of the iminium ion to cotinine. The half-life of nicotine is longer in individuals with low P450 2A6 activity, and smokers with low activity often decrease either the intensity of their smoking or the number of cigarettes they use compared with those with “normal” activity. The effect of P450 2A6 activity on smoking may influence one's tobacco-related disease risk. This review provides an overview of nicotine metabolism and a summary of the use of nicotine metabolite biomarkers to define smoking dose. Some more recent findings, for example, the identification of uridine 5′-diphosphoglucuronosyltransferase 2B10 as the catalyst of nicotine N-glucuronidation, are discussed. We also describe epidemiology studies that establish the contribution of nicotine metabolism and CYP2A6 genotype to lung cancer risk, particularly with respect to specific racial/ethnic groups, such as those with Japanese, African, or European ancestry. We conclude that a model of nicotine metabolism and smoking dose could be combined with other lung cancer risk variables to more accurately identify former smokers at the highest risk of lung cancer and to intervene accordingly.

Pharmacogenetics factors influencing smoking cessation success; the importance of nicotine metabolism

Introduction: Smoking remains a worldwide epidemic, and despite an increase in public acceptance of the harms of tobacco use, it remains the leading cause of preventable death. It is estimated that up to 70% of all smokers express a desire to quit, but only 3-5% of them are successful.Areas covered: The goal of this review was to evaluate the current status of smoking cessation treatments and the feasibility of implementing personalized-medicine approaches to these pharmacotherapies. We evaluated the genetics associated with higher levels of nicotine addiction and follow with an analysis of the genetic variants that affect the nicotine metabolic ratio (NMR) and the FDA approved treatments for smoking cessation. We also highlighted the gaps in the process of translating current laboratory understanding into clinical practice, and the benefits of personalized treatment approaches for a successful smoking cessation strategy.Expert opinion: Evidence supports the use of tailored therapies to ensure that the most efficient treatments are utilized in an individual's smoking cessation efforts. An understanding of the genetic effects on the efficacy of individualized smoking cessation pharmacotherapies is key to smoking cessation, ideally utilizing a polygenetic risk score that considers all genetic variation.

Coffee consumption and risk of breast cancer: A Mendelian randomization study

BACKGROUND

Observational studies have reported either null or weak protective associations for coffee consumption and risk of breast cancer.

METHODS

We conducted a two-sample Mendelian randomization (MR) analysis to evaluate the relationship between coffee consumption and breast cancer risk using 33 single-nucleotide polymorphisms (SNPs) associated with coffee consumption from a genome-wide association (GWA) study on 212,119 female UK Biobank participants of White British ancestry. Risk estimates for breast cancer were retrieved from publicly available GWA summary statistics from the Breast Cancer Association Consortium (BCAC) on 122,977 cases (of which 69,501 were estrogen receptor (ER)-positive, 21,468 ER-negative) and 105,974 controls of European ancestry. Random-effects inverse variance weighted (IVW) MR analyses were performed along with several sensitivity analyses to assess the impact of potential MR assumption violations.

RESULTS

One cup per day increase in genetically predicted coffee consumption in women was not associated with risk of total (IVW random-effects; odds ratio (OR): 0.91, 95% confidence intervals (CI): 0.80-1.02, P: 0.12, P for instrument heterogeneity: 7.17e-13), ER-positive (OR = 0.90, 95% CI: 0.79-1.02, P: 0.09) and ER-negative breast cancer (OR: 0.88, 95% CI: 0.75-1.03, P: 0.12). Null associations were also found in the sensitivity analyses using MR-Egger (total breast cancer; OR: 1.00, 95% CI: 0.80-1.25), weighted median (OR: 0.97, 95% CI: 0.89-1.05) and weighted mode (OR: 1.00, CI: 0.93-1.07).

CONCLUSIONS

The results of this large MR study do not support an association of genetically predicted coffee consumption on breast cancer risk, but we cannot rule out existence of a weak association.

Recommendations to researchers for aiding in increasing American Indian representation in genetic research and personalized medicine

Increasing American Indian/Alaska Native (AI/AN) representation in genetic research is critical to ensuring that personalized medicine discoveries do not widen AI/AN health disparities by only benefiting well-represented populations. One reason for the under-representation of AIs/ANs in research is warranted research distrust due to abuse of some AI/AN communities in research. An approach to easing the tension between protecting AI/AN communities and increasing the representation of AI/AN persons in genetic research is community-based participatory research. This approach was used in a collaboration between a tribe and academic researchers in efforts to increase AI/AN participation in genetic research. From the lessons learned, the authors propose recommendations to researchers that may aid in conducting collaborative and respectful research with AI/AN tribes/communities and ultimately assist in increasing representation of AIs/ANs in personalized medicine discoveries.

Transferability of Ancestry-Specific and Cross-Ancestry CYP2A6 Activity Genetic Risk Scores in African and European Populations

The Nicotine Metabolite Ratio (NMR; 3-hydroxycotinine/cotinine), a highly heritable index of nicotine metabolic inactivation by the CYP2A6 enzyme, is associated with numerous smoking behaviors and diseases, as well as unique cessation outcomes. However, the NMR cannot be measured in nonsmokers, former smokers, or intermittent smokers, for example, in evaluating tobacco-related disease risk. Traditional pharmacogenetic groupings based on CYP2A6 * alleles capture a modest portion of NMR variation. We previously created a CYP2A6 weighted genetic risk score (wGRS) for European (EUR)-ancestry populations by incorporating independent signals from genome-wide association studies to capture a larger proportion of NMR variation. However, CYP2A6 genetic architecture is unique to ancestral populations. In this study, we developed and replicated an African-ancestry (AFR) wGRS, which captured 30-35% of the variation in NMR. We demonstrated model robustness against known environmental sources of NMR variation. Furthermore, despite the vast diversity within AFR populations, we showed that the AFR wGRS was consistent between different US geographical regions and unaltered by fine AFR population substructure. The AFR and EUR wGRSs can distinguish slow from normal metabolizers in their respective populations, and were able to reflect unique smoking cessation pharmacotherapy outcomes previously observed for the NMR. Additionally, we evaluated the utility of a cross-ancestry wGRS, and the capacity of EUR, AFR, and cross-ancestry wGRSs to predict the NMR within stratified or admixed AFR-EUR populations. Overall, our findings establish the clinical benefit of applying ancestry-specific wGRSs, demonstrating superiority of the AFR wGRS in AFRs.

Applying Tobacco, Environmental, and Dietary-Related Biomarkers to Understand Cancer Etiology and Evaluate Prevention Strategies

Many human cancers are caused by environmental and lifestyle factors. Biomarkers of exposure and risk developed by our team have provided critical data on internal exposure to toxic and genotoxic chemicals and their connection to cancer in humans. This review highlights our research using biomarkers to identify key factors influencing cancer risk as well as their application to assess the effectiveness of exposure intervention and chemoprevention protocols. The use of these biomarkers to understand individual susceptibility to the harmful effects of tobacco products is a powerful example of the value of this type of research and has provided key data confirming the link between tobacco smoke exposure and cancer risk. Furthermore, this information has led to policy changes that have reduced tobacco use and consequently, the tobacco-related cancer burden. Recent technological advances in mass spectrometry led to the ability to detect DNA damage in human tissues as well as the development of adductomic approaches. These new methods allowed for the detection of DNA adducts in tissues from patients with cancer, providing key evidence that exposure to carcinogens leads to DNA damage in the target tissue. These advances will provide valuable insights into the etiologic causes of cancer that are not tobacco-related.See all articles in this CEBP Focus section, "Environmental Carcinogenesis: Pathways to Prevention."

Dissecting the genetic overlap of smoking behaviors, lung cancer, and chronic obstructive pulmonary disease: A focus on nicotinic receptors and nicotine metabolizing enzyme

Smoking is a major contributor to lung cancer and chronic obstructive pulmonary disease (COPD). Two of the strongest genetic associations of smoking-related phenotypes are the chromosomal regions 15q25.1, encompassing the nicotinic acetylcholine receptor subunit genes CHRNA5-CHRNA3-CHRNB4, and 19q13.2, encompassing the nicotine metabolizing gene CYP2A6. In this study, we examined genetic relations between cigarettes smoked per day, smoking cessation, lung cancer, and COPD. Data consisted of genome-wide association study summary results. Genetic correlations were estimated using linkage disequilibrium score regression software. For each pair of outcomes, z-score-z-score (ZZ) plots were generated. Overall, heavier smoking and decreased smoking cessation showed positive genetic associations with increased lung cancer and COPD risk. The chromosomal region 19q13.2, however, showed a different correlational pattern. For example, the effect allele-C of the sentinel SNP (rs56113850) within CYP2A6 was associated with an increased risk of heavier smoking (z-score = 19.2; p = 1.10 × 10-81 ), lung cancer (z-score = 8.91; p = 5.02 × 10-19 ), and COPD (z-score = 4.04; p = 5.40 × 10-5 ). Surprisingly, this allele-C (rs56113850) was associated with increased smoking cessation (z-score = -8.17; p = 2.52 × 10-26 ). This inverse relationship highlights the need for additional investigation to determine how CYP2A6 variation could increase smoking cessation while also increasing the risk of lung cancer and COPD likely through increased cigarettes smoked per day.

Metabolomics Profiles of Smokers from Two Ethnic Groups with Differing Lung Cancer Risk

African American (AA) smokers are at a higher risk of developing lung cancer compared to whites. The variations in the metabolism of nicotine and tobacco-derived carcinogens in these groups were reported previously with the levels of nicotine metabolites and carcinogen-derived metabolites measured using targeted approaches. While useful, these targeted strategies are not able to detect global metabolic changes for use in predicting the detrimental effects of tobacco use and ultimately lung cancer susceptibility among smokers. To address this limitation, we have performed global untargeted metabolomics profiling in urine of AA and white smokers to characterize the pattern of metabolites, identify differentially regulated pathways, and correlate these profiles with the observed variations in lung cancer risk between these two populations. Urine samples from AA (n = 30) and white (n = 30) smokers were used for metabolomics analysis acquired in both positive and negative electrospray ionization modes. LC-MS data were uploaded onto the cloud-based XCMS online (http://xcmsonline.scripps.edu) platform for retention time correction, alignment, feature detection, annotation, statistical analysis, data visualization, and automated systems biology pathway analysis. The latter identified global differences in the metabolic pathways in the two groups including the metabolism of carbohydrates, amino acids, nucleotides, fatty acids, and nicotine. Significant differences in the nicotine degradation pathway (cotinine glucuronidation) in the two groups were observed and confirmed using a targeted LC-MS/MS approach. These results are consistent with previous studies demonstrating AA smokers with lower glucuronidation capacity compared to whites. Furthermore, the d-glucuronate degradation pathway was found to be significantly different between the two populations, with lower amounts of the putative metabolites detected in AA compared to whites. We hypothesize that the differential regulation of the d-glucuronate degradation pathway is a consequence of the variations in the glucuronidation capacity observed in the two groups. Other pathways including the metabolism of amino acids, nucleic acids, and fatty acids were also identified, however, the biological relevance and implications of these differences across ethnic groups need further investigation. Overall, the applied metabolomics approach revealed global differences in the metabolic networks and endogenous metabolites in AA and whites, which could be used and validated as a new potential panel of biomarkers that could be used to predict lung cancer susceptibility among smokers in population-based studies.

Systematic analyses of regulatory variants in DNase I hypersensitive sites identified two novel lung cancer susceptibility loci

DNase I hypersensitive sites (DHS) are abundant in regulatory elements, such as promoter, enhancer and transcription factor binding sites. Many studies have revealed that disease-associated variants were concentrated in DHS-related regions. However, limited studies are available on the roles of DHS-related variants in lung cancer. In this study, we performed a large-scale case-control study with 20 871 lung cancer cases and 15 971 controls to evaluate the associations between regulatory genetic variants in DHS and lung cancer susceptibility. The expression quantitative trait loci (eQTL) analysis and pathway-enrichment analysis were performed to identify the possible target genes and pathways. In addition, we performed motif-based analysis to explore the lung-cancer-related motifs using sequence kernel association test. Two novel variants, rs186332 in 20q13.3 (C>T, odds ratio [OR] = 1.17, 95% confidence interval [95% CI]: 1.10-1.24, P = 8.45 × 10-7) and rs4839323 in 1p13.2 (T>C, OR = 0.92, 95% CI: 0.89-0.95, P = 1.02 × 10-6) showed significant association with lung cancer risk. The eQTL analysis suggested that these two SNPs might regulate the expression of MRGBP and SLC16A1, respectively. What's more, the expression of both MRGBP and SLC16A1 was aberrantly elevated in lung tumor tissues. The motif-based analysis identified 10 motifs related to the risk of lung cancer (P < 1.71 × 10-4). Our findings suggested that variants in DHS might modify lung cancer susceptibility through regulating the expression of surrounding genes. This study provided us a deeper insight into the roles of DHS-related genetic variants for lung cancer.

Evaluation of a weighted genetic risk score for the prediction of biomarkers of CYP2A6 activity

The nicotine metabolite ratio (NMR; 3-hydroxycotinine/cotinine) is an index of CYP2A6 activity. CYP2A6 is responsible for nicotine's metabolic inactivation and variation in the NMR/CYP2A6 is associated with several smoking behaviors. Our aim was to integrate established alleles and novel genome-wide association studies (GWAS) signals to create a weighted genetic risk score (wGRS) for the CYP2A6 gene for European-ancestry populations. The wGRS was compared with a previous CYP2A6 gene scoring approach designed for an alternative phenotype (C2/N2; cotinine-d2/(nicotine-d2 + cotinine-d2)). CYP2A6 genotypes and the NMR were assessed in European-ancestry participants. The wGRS training set included N = 933 smokers recruited to the Pharmacogenetics of Nicotine Addiction and Treatment clinical trial [NCT01314001]. The replication cohort included N = 196 smokers recruited to the Quit 2 Live clinical trial [NCT01836276]. Comparisons between the two CYP2A6 phenotypes and with fractional clearance were made in a laboratory-based pharmacokinetic study (N = 92 participants). In both the training and replication sets, the wGRS, which included seven CYP2A6 variants, explained 33.8% (P < 0.001) of the variance in NMR, providing improved predictive power to the NMR phenotype when compared with other CYP2A6 gene scoring approaches. NMR and C2/N2 were strongly correlated to nicotine clearance (ρ = 0.70 and ρ = 0.79, respectively; P < 0.001), and to one another (ρ = 0.82; P < 0.001); however reduced function genotypes occurred in slow NMR but throughout C2/N2. The wGRS was able to predict smoking quantity and nicotine intake, to discriminate between NMR slow and normal metabolizers (AUC = 0.79; P < 0.001), and to replicate previous NMR-stratified cessation outcomes showing unique treatment outcomes between metabolizer groups.

Individual Differences in the Response of Human β-Lymphoblastoid Cells to the Cytotoxic, Mutagenic, and DNA-Damaging Effects of a DNA Methylating Agent, N-Methylnitrosourethane

Metabolic activation of many carcinogens leads to formation of reactive intermediates that form DNA adducts. These adducts are cytotoxic when they interfere with cell division. They can also cause mutations by miscoding during DNA replication. Therefore, an individual's risk of developing cancer will depend on the balance between these processes as well as their ability to repair the DNA damage. Our hypothesis is that variations of genes participating in DNA damage repair and response pathways play significant roles in an individual's risk of developing tobacco-related cancers. To test this hypothesis, 61 human B-lymphocyte cell lines from the International HapMap project were phenotyped for their sensitivity to the cytotoxic and genotoxic properties of a model methylating agent, N-nitroso-N-methylurethane (NMUr). Cell viability was measured using a luciferase-based assay. Repair of the mutagenic and toxic DNA adduct, O⁶-methylguanine (O⁶-mG), was monitored by LC-MS/MS analysis. Genotoxic potential of NMUr was assessed employing a flow-cytometry based in vitro mutagenesis assay in the phosphatidylinositol-glycan biosynthesis class-A (PIG-A) gene. A wide distribution of responses to NMUr was observed with no correlation to gender or ethnicity. While the rate of O⁶-mG repair partially influenced the toxicity of NMUr, it did not appear to be the major factor affecting individual susceptibility to the mutagenic effects of NMUr. Genome-wide analysis identified several novel single nucleotide polymorphisms to be explored in future functional validation studies for a number of the toxicological end points.

GWAS of smoking behaviour in 165,436 Japanese people reveals seven new loci and shared genetic architecture

Cigarette smoking is a risk factor for a wide range of human diseases¹. To investigate the genetic components associated with smoking behaviours in the Japanese population, we conducted a genome-wide association study of four smoking-related traits using up to 165,436 individuals. In total, we identified seven new loci, including three loci associated with the number of cigarettes per day (EPHX2-CLU, RET and CUX2-ALDH2), three loci associated with smoking initiation (DLC1, CXCL12-TMEM72-AS1 and GALR1-SALL3) and LINC01793-MIR4432HG, associated with the age of smoking initiation. Of these, three loci (LINC01793-MIR4432HG, CXCL12-TMEM72-AS1 and GALR1-SALL3) were found by conducting an additional sex-stratified genome-wide association study. This additional analysis showed heterogeneity of effects between sexes. The cross-sex linkage disequilibrium score regression^2,3 analysis also indicated that the genetic component of smoking initiation was significantly different between the sexes. Cross-trait linkage disequilibrium score regression analysis and trait-relevant tissue analysis showed that the number of cigarettes per day has a specific genetic background distinct from those of the other three smoking behaviours. We also report 11 diseases that share genetic basis with smoking behaviours. Although the current study should be carefully considered owing to the lack of replication samples, our findings characterized the genetic architecture of smoking behaviours. Further studies in East Asian populations are warranted to confirm our findings.

A decade in psychiatric GWAS research

After more than 10 years of accumulated efforts, genome-wide association studies (GWAS) have led to many findings, most of which have been deposited into the GWAS Catalog. Between GWAS's inception and March 2017, the GWAS Catalog has collected 2429 studies, 1818 phenotypes, and 28,462 associated SNPs. We reclassified the psychology-related phenotypes into 217 reclassified phenotypes, which accounted for 514 studies and 7052 SNPs. In total, 1223 of the SNPs reached genome-wide significance. Of these, 147 were replicated for the same psychological trait in different studies. Another 305 SNPs were replicated within one original study. The SNPs rs2075650 and rs4420638 were linked to the most replications within a single reclassified phenotype or very similar reclassified phenotypes; both were associated with Alzheimer's disease (AD). Schizophrenia was associated with 74 within-phenotype SNPs reported in independents studies. Alzheimer's disease and schizophrenia were both linked to some physical phenotypes, including cholesterol and body mass index, through common GWAS signals. Alzheimer's disease also shared risk SNPs with age-related phenotypes such as age-related macular degeneration and longevity. Smoking-related SNPs were linked to lung cancer and respiratory function. Alcohol-related SNPs were associated with cardiovascular and digestive system phenotypes and disorders. Two separate studies also identified a shared risk SNP for bipolar disorder and educational attainment. This review revealed a list of reproducible SNPs worthy of future functional investigation. Additionally, by identifying SNPs associated with multiple phenotypes, we illustrated the importance of studying the relationships among phenotypes to resolve the nature of their causal links. The insights within this review will hopefully pave the way for future evidence-based genetic studies.

Lung cancer health disparities

Compared with all other racial and ethnic groups in the United States, African Americans are disproportionally affected by lung cancer, both in terms of incidence and survival. It is likely that smoking, as the main etiological factor associated with lung cancer, contributes to these disparities, but the precise mechanism is still unclear. This paper seeks to explore the history of lung cancer disparities and review to the literature regarding the various factors that contribute to them.

Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder

Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.

Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder

Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.

Tobacco biomarkers and genetic/epigenetic analysis to investigate ethnic/racial differences in lung cancer risk among smokers

The Multiethnic Cohort Study has demonstrated that African Americans and Native Hawaiians have a higher risk for lung cancer due to cigarette smoking than Whites while Latinos and Japanese Americans have a lower risk. These findings are consistent with other epidemiologic studies in the literature. In this review, we summarize tobacco carcinogen and toxicant biomarker studies and genetic analyses which partially explain these differences. As determined by measurement of total nicotine equivalents in urine, which account for about 85% of the nicotine dose, African Americans take up greater amounts of nicotine than Whites per cigarette while Japanese Americans take up less. There are corresponding differences in the uptake of tobacco smoke carcinogens such as tobacco-specific nitrosamines, polycyclic aromatic hydrocarbons, 1,3-butadiene, and other toxic volatiles. The lower nicotine uptake of Japanese Americans is clearly linked to the preponderance of low activity forms of the primary nicotine metabolizing enzyme CYP2A6 in this ethnic group, leading to more unchanged nicotine in the body and thus lower smoking intensity. But the relatively high risk of Native Hawaiians and the low risk of Latino smokers for lung cancer are not explained by these factors. The possible role of epigenetics in modifying lung cancer risk among smokers is also discussed here. The results of these published studies may lead to a better understanding of susceptibility factors for lung cancer in cigarette smokers thus potentially identifying biomarkers that can detect those individuals at highest risk so that preventive approaches can be initiated at an early stage of the lung cancer development process.

Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression

Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

The Value of Biosamples in Smoking Cessation Trials: A Review of Genetic, Metabolomic, and Epigenetic Findings

Introduction

Human genetic research has succeeded in definitively identifying multiple genetic variants associated with risk for nicotine dependence and heavy smoking. To build on these advances, and to aid in reducing the prevalence of smoking and its consequent health harms, the next frontier is to identify genetic predictors of successful smoking cessation and also of the efficacy of smoking cessation treatments ("pharmacogenomics"). More broadly, additional biomarkers that can be quantified from biosamples also promise to aid "Precision Medicine" and the personalization of treatment, both pharmacological and behavioral.

Aims and Methods

To motivate ongoing and future efforts, here we review several compelling genetic and biomarker findings related to smoking cessation and treatment.

Results

These Key results involve genetic variants in the nicotinic receptor subunit gene CHRNA5, variants in the nicotine metabolism gene CYP2A6, and the nicotine metabolite ratio. We also summarize reports of epigenetic changes related to smoking behavior.

Conclusions

The results to date demonstrate the value and utility of data generated from biosamples in clinical treatment trial settings. This article cross-references a companion paper in this issue that provides practical guidance on how to incorporate biosample collection into a planned clinical trial and discusses avenues for harmonizing data and fostering consortium-based, collaborative research on the pharmacogenomics of smoking cessation.

Implications

Evidence is emerging that certain genotypes and biomarkers are associated with smoking cessation success and efficacy of smoking cessation treatments. We review key findings that open potential avenues for personalizing smoking cessation treatment according to an individual's genetic or metabolic profile. These results provide important incentive for smoking cessation researchers to collect biosamples and perform genotyping in research studies and clinical trials.

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.

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.

Association of CYP2A6 activity with lung cancer incidence in smokers: The multiethnic cohort study

While smoking is the primary cause of lung cancer, only 11-24% of smokers develop the malignancy over their lifetime. The primary addictive agent in tobacco smoke is nicotine and variation in nicotine metabolism may influence the smoking levels of an individual. Therefore, inter-individual variation in lung cancer risk among smokers may be due in part to differences in the activity of enzymes involved in nicotine metabolism. In most smokers, cytochrome P450 2A6 (CYP2A6)-catalyzed C-oxidation accounts for >75% of nicotine metabolism, and the activity of this enzyme has been shown to correlate with the amount of nicotine and carcinogens drawn from cigarettes. We prospectively evaluated the association of urinary biomarkers of nicotine uptake (total nicotine equivalents [TNE]) and CYP2A6 activity (ratio of urinary total trans-3'-hydroxycotinine to cotinine) with lung cancer risk among 2,309 Multiethnic Cohort Study participants who were current smokers at time of urine collection; 92 cases were diagnosed during a mean follow-up of 9.5 years. We found that higher CYP2A6 activity and TNE was associated with increased lung cancer risk after adjusting for age, sex, race/ethnicity, body mass index, smoking duration, and urinary creatinine (p's = 0.002). The association for CYP2A6 activity remained even after adjusting for self-reported cigarettes per day (CPD) (Hazard Ratio [HR] per unit increase in log-CYP2A6 activity = 1.52; p = 0.005) and after adjusting for TNE (HR = 1.46; p = 0.01). In contrast, the association between TNE and lung cancer risk was of borderline statistical significance when adjusted for CPD (HR = 1.53; p = 0.06) and not statistically significant when further adjusted for CYP2A6 activity (HR = 1.30; p = 0.22). These findings suggest that CYP2A6 activity provides information on lung cancer risk that is not captured by smoking history or a (short-term) biomarker of dose. CYP2A6 activity should be further studied as a risk biomarker for smoking-related lung cancer.

Phenome-wide association study for CYP2A6 alleles: rs113288603 is associated with hearing loss symptoms in elderly smokers

To identify novel phenotypic associations related to Cytochrome P450 Family 2 Subfamily A Member 6 (CYP2A6), we investigated the human phenome in a total of 11,271 individuals. Initially, we conducted a phenome-wide association study in 3,401 nicotine-exposed elderly subjects considering 358 phenotypic traits. We identified a significant association between CYP2A6 rs113288603 and hearing loss symptoms (p = 5.75 × 10⁻⁵). No association was observed in a sample of 3,245 nicotine-unexposed individuals from the same discovery cohort, consistent with the conclusion that the finding is related to CYP2A6 involvement in nicotine metabolism. Consistent results were obtained (p < 0.1) in an independent sample of 2,077 nicotine-exposed elderly subjects, and similarly, no significance was observed in the nicotine-unexposed sample (n = 2,548) of the replication cohort. Additional supporting evidence for this association was provided by gene expression data: rs113288603 is associated with increased CYP2A6 expression in cerebellar hemispheres (p = 7.8 × 10⁻⁴). There is a well-known correlation between smoking and age-related hearing loss. Cigarette smoking is associated with structural changes in the brain and CYP2A6 mediates these changes. In this context, the regulatory role of rs113288603 in cerebellum appears to be consistent with the known involvement of this brain region in auditory function.

CYP2A6 genetic polymorphisms and biomarkers of tobacco smoke constituents in relation to risk of lung cancer in the Singapore Chinese Health Study

Cytochrome P450 2A6 (CYP2A6) catalyzes the metabolism of nicotine and the tobacco-specific lung carcinogen, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). Genetic variation in CYP2A6 may affect smoking behavior and contribute to lung cancer risk. A nested case-control study of 197 lung cancer cases and 197 matched controls was conducted within a prospective cohort of 63 257 Chinese men and women in Singapore. Quantified were five genetic variants of CYP2A6 (*1A, *4, *7, *9 and *12) and urinary metabolites of nicotine [total nicotine, total cotinine, total trans-3'-hydroxycotinine (3HC)] and NNK (total NNAL, free NNAL, NNAL-glucuronide, NNAL-N-glucuronide, and NNAL-O-glucuronide). Higher urinary metabolites of nicotine and NNK were significantly associated with a 2- to 3-fold increased risk of lung cancer after adjustment for smoking intensity and duration. Lower CYP2A6-determined nicotine metabolizer status was significantly associated with a lower ratio of total 3HC over total cotinine, lower total nicotine equivalent and reduced risk of developing lung cancer (all Ptrend < 0.001). Compared with normal metabolizers, odds ratios (95% confidence intervals) of developing lung cancer for intermediate, slow and poor metabolizers determined by CYP2A6 genotypes were 0.85 (0.41-1.77), 0.55 (0.28-1.08) and 0.32 (0.15-0.70), respectively, after adjustment for smoking intensity and duration and urinary total nicotine equivalents. Thus the reduced risk of lung cancer in smokers with lower CYP2A6 activity may be explained by lower consumption of cigarettes, less intense smoking and reduced CYP2A6-catalyzed activation of the tobacco-specific lung carcinogen NNK.

Functional Characterization of 34 CYP2A6 Allelic Variants by Assessment of Nicotine C-Oxidation and Coumarin 7-Hydroxylation Activities

CYP2A6, a member of the cytochrome P450 (P450) family, is one of the enzymes responsible for the metabolism of therapeutic drugs and such tobacco components as nicotine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, and N-nitrosodiethylamine. Genetic polymorphisms in CYP2A6 are associated with individual variation in smoking behavior, drug toxicities, and the risk of developing several cancers. In this study, we conducted an in vitro analysis of 34 allelic variants of CYP2A6 using nicotine and coumarin as representative CYP2A6 substrates. These variant CYP2A6 proteins were heterologously expressed in 293FT cells, and their enzymatic activities were assessed on the basis of nicotine C-oxidation and coumarin 7-hydroxylation activities. Among the 34 CYP2A6 variants, CYP2A6.2, CYP2A6.5, CYP2A6.6, CYP2A6.10, CYP2A6.26, CYP2A6.36, and CYP2A6.37 exhibited no enzymatic activity, whereas 14 other variants exhibited markedly reduced activity toward both nicotine and coumarin. These comprehensive in vitro findings may provide useful insight into individual differences in smoking behavior, drug efficacy, and cancer susceptibility.

Differences in Toxicological and Pharmacological Responses Mediated by Polymorphic Cytochromes P450 and Related Drug-Metabolizing Enzymes

Research over the past 30 years has elucidated the roles of polymorphic human liver cytochrome P450 (P450) enzymes associated with toxicological and/or pharmacological actions. Thalidomide exerts its various pharmacological and toxic actions in primates through multiple mechanisms, including nonspecific modification of many protein networks after bioactivation by autoinduced human P450 enzymes. To overcome species differences between rodents, currently, nonhuman primates and/or mouse models with transplanted human hepatocytes are used. Interindividual variability of P450-dependent drug clearances in cynomolgus monkeys and common marmosets is partly accounted for by polymorphic P450 variants and/or aging, just as it is in humans with increased prevalence of polypharmacy. Genotyping of P450 genes in nonhuman primates would be beneficial before and/or after drug metabolism and toxicity testing and evaluation as well in humans. Genome-wide association studies in humans have been rapidly advanced; however, unique whole-gene deletion of P450 2A6 was subsequently developed to cover nicotine-related lung cancer risk study. Regarding polypharmacy, toxicological research should generally be aimed at identifying the risk of adverse drug events following specific potential drug exposures by examining single or multiple metabolic pathways involving single or multiple drug-metabolizing enzymes. Current and next-generation research of drug metabolism and disposition resulting in drug toxicity would be addressed under advanced knowledge of polymorphic and age-related intra- and/or interspecies differences of drug-metabolizing enzymes. In the near future, humanized animal models combining transplanted hepatocytes and a humanized immune system may be available to study human immune reactions caused by human-type drug metabolites. Such sophisticated models should provide preclinical predictions of human drug metabolism and potential toxicity.