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Carcinogenesis Advance Access originally published online on July 24, 2006
Carcinogenesis 2007 28(1):112-117; doi:10.1093/carcin/bgl131
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Published by Oxford University Press 2006

The influence of genetic polymorphisms in Ahr, CYP1A1, CYP1A2, CYP1B1, GST M1, GST T1 and UGT1A1 on urine 1-hydroxypyrene glucuronide concentrations in healthy subjects from Rio Grande do Sul, Brazil

Christian C. Abnet1,*, Renato B. Fagundes2, Paul T. Strickland3, Farin Kamangar1, Mark J. Roth1, Philip R. Taylor4 and Sanford M. Dawsey1

1 Nutritional Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute 6120 Executive Boulevard, EPS/320, MSC 7232, Rockville, MD 20852, USA
2 Universidade Federal de Santa Maria, Departamento de Clínica Médica, Centro de Ciências da Saúde, Campus Universitário de Camobi Santa Maria, RS, Brazil
3 Department of Environmental Health Sciences, The Johns Hopkins University Bloomberg School of Public Health Baltimore, MD, USA
4 Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute Bethesda, MD, USA

*To whom correspondence should be addressed. Tel: +1 301 594 1511; Fax: +1 301 496 6829; Email: abnetc{at}mail.nih.gov


   Abstract
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 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 References
 
Polymorphisms in genes encoding polycyclic aromatic hydrocarbon (PAH) metabolizing enzymes may alter metabolism of these carcinogens and contribute to inter-individual difference in urine concentrations. We investigated the influence of genetic polymorphism on PAH metabolism in urine from 199 healthy subjects from Southern Brazil. We measured urine 1-hydroxypyrene glucuronide (1-OHPG) concentrations using immunoaffinity chromatography and synchronous fluorescence spectroscopy and genotyped subjects using standard methods. Genetic variants in CYP1B1 (rs1056827, rs1800440, rs10012) were strongly associated with urine 1-OHPG with P-values < 0.010. Variants in aryl hydrocarbon receptor (Ahr) (rs4986826), CYP1A1 (rs1799814) and CYP1A2 (rs2069514) were also, although less strongly, associated with changes in urine 1-OHPG concentrations. These variants had P-values of 0.074, 0.040 and 0.025, respectively. The median urine 1-OHPG concentrations (pmol/ml) in the homozygous wild-type and homozygous variants for CYP1B1 (rs10012) and the Ahr, CYP1A1 and CYP1A2 variants listed above were 2.16 and 0.10, 2.16 and 0.41, 2.03 and 0.46, 2.19 and 2.79, respectively. We found no effect of deletions in GST M1 or GST T1, or different alleles of UGT1A1*28. Adjusting for age, sex, place of residence, tobacco smoke exposure, maté drinking, cachaça and barbeque preparation had only a minor impact on the associations. A model containing just exposure variables had an r2 of 0.21; a model with single genotypes for Ahr, CYP1A1, CYP1A2 and CYP1B1 had an r2 of 0.10; and a model combining both exposure and genotype information had a total r2 of 0.33. Our results suggest that CYP1B1 genotypes are strongly associated with urine 1-OHPG concentrations in this population.

Abbreviations: Ahr, aryl hydrocarbon receptor; B[a]P, benzo[a]pyrene; 1-OHPG, 1-hydroxypyrene glucuronide; IQR, interquartile range; PAH, polycyclic aromatic hydrocarbon; SNPs, single nucleotide polymorphisms


   Introduction
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 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 References
 
Exposure to polycyclic aromatic hydrocarbons (PAHs) may adversely affect human health because this class of chemicals includes toxicants and carcinogens. Human exposure routes include inhalation of smoke (tobacco, wood, coal, auto exhaust, etc.) (1), eating foods cooked at high temperature (2) or contaminated by smoke (3) and through the therapeutic use of coal-tar. Many studies use benzo[a]pyrene (B[a]P) as a prototypical PAH because it is a major component of many PAH mixtures and because it can be metabolized to a mutagenic intermediate. The urine metabolite of B[a]P, 1-hydroxypyrene glucuronide (1-OHPG), may reflect recent exposure to PAHs (4).

Metabolism of PAHs to more hydrophilic compounds facilitates excretion (5). A major PAH biotransformation pathway follows two steps. First, functionalization by Phase I metabolizing enzymes such as cytochromes P450 followed by conjugation by Phase II metabolizing proteins to glucuronide, glutathione or other moieties, to increase water solubility. Phase I and II metabolizing enzymes exhibit distinct but overlapping substrate specificities. In humans, B[a]P is thought to be metabolized primarily by P450 1A1, 1A2 and 1B1 in Phase 1 and by glutathione-S-transferase and UDP-glucuronosyltransferase in Phase II. PAHs may also stimulate their own metabolism through feedback mechanisms. B[a]P and other similar compounds can bind and activate the aryl hydrocarbon receptor (Ahr), which subsequently upregulates transcription of some of these genes. Human genetic variation in each of these genes may play a role in inter-individual differences in the metabolism of PAHs.

The in vivo effect of human genetic variation in genes encoding PAH-metabolizing enzymes may alter the adverse health consequences of PAH exposure. Important considerations for these studies include the route of exposure, the mix of PAHs and the genetic background of the exposed individuals. To aid our understanding of the impact of genetic polymorphisms on PAH metabolism we examined the association between selected polymorphisms in a number of genes that encode PAH-metabolizing enzymes and urine 1-OHPG concentrations in a group of healthy Brazilians with elevated PAH exposures from some population-specific sources such as maté (6).


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 References
 
Subjects
Participants were volunteers from Santa Maria, a city in the central region of Rio Grande do Sul Province in Southern Brazil, an area with esophageal squamous cell carcinoma rates of ~20/100 000/year (7). Healthy subjects from the outpatient unit at the University Hospital were invited to take part; >90% of the invited individuals chose to participate. The study included 200 healthy adult subjects, half males and half females, half current smokers and half non-smokers. Informed consent was obtained from each participant. Subjects completed a brief questionnaire to elicit information about demographic variables, habits and potential exposures to PAH and also provided a buccal cell sample for DNA using the ISOCODE system (Schleicher & Schuell, Keene NH). The study was approved by the Ethical Committee on Research of the Health Sciences Center of the University of Santa Maria, RS, Brazil. The analysis of extant anonymized data and samples was exempted from review by the Office of Human Subjects Review of the National Institutes of Health, Bethesda, MD.

Urine 1-OHPG measurements
Each participant was recruited in the morning and asked to provide a 10 ml urine sample. The urine samples were collected in a sterile container, frozen at –80°C and shipped on dry ice to the National Cancer Institute. Urine samples were assayed in the laboratory of Dr Strickland at the Johns Hopkins University. Urine 1-OHPG concentrations were measured using immunoaffinity chromatography and synchronous fluorescence spectroscopy as described previously (3,8). NicAlert Strips (Jant Pharmaceutical, Encino, CA) were used to measure urine cotinine equivalents as directed by the manufacturer. This test produces categorical results ranging from 0 (<10 ng/ml cotinine equivalents) to 6 (>2000 ng/ml). Because only a small number of subjects had urine cotinine results in each of Categories 2, 3 and 4, we collapsed these three groups into a single category. We considered subjects exposed to tobacco smoke if they reported smoking cigarettes or had elevated cotinine.

DNA extraction and genotype analysis
DNA extractions and genotyping were completed by BioServe Biotechnologies (Laurel, MD). DNA was isolated from the ISOCODE cards as recommended by the manufacturer. Genetic polymorphisms were assayed using MASSCODE for all single nucleotide polymorphisms (SNPs) except GST M1 and GST T1 deletions, which were analyzed using a duplex PCR-RFLP assay (9), and the UGT1A1*28 repeat polymorphism was assayed by PCR and gel electrophoresis (10). We successfully genotyped 92–98% of samples at each polymorphic site. We tested HWE using the genhwi command in Stata with exact P-values and used P < 0.01 as the cut point for evidence of deviation (11). No deviations were detected.

Statistical analysis
Statistical analyses were carried out using SAS 9.1 for Windows (SAS institute, Cary, NC) and STATA/SE 8.0 for Windows (Stata, College Station, TX). We tabulated the median and interquartile range (IQR) of 1-OHPG by genotypes for comparison. Next we examined the association between individual genetic polymorphisms and urine 1-OHPG concentration using linear regression models. First, we examined 1-OHPG concentrations in a crude model, with no covariates other than indicator variables for genotypes, and then with the addition of personal covariates previously shown to be associated with urine 1-OHPG concentration (6). These covariates included age, sex, rural versus urban residence, consumption of maté, cachaça, tobacco smoke exposure and the frequency of preparing barbeque.


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 References
 
We measured urine 1-OHPG in 199 healthy subjects from Rio Grand do Sul, Brazil.

We genotyped subjects for polymorphisms in seven genes potentially involved in B[a]P metabolism. We examined the genetic linkage between polymorphisms within and between these genes (Table II). We found good evidence of linkage between some of the polymorphisms within each gene. Several SNP pairs had D's > 0.9 and high r2. Two genes located in tandem on chromosome 15, Cyp1A1 and Cyp1A2, also showed linkage between some of the polymorphisms.


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  		Table I Subject characteristics

 


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  		Table II Polymorphism names, RS numbers, location and disequilibrium

 
Table III presents the median (IQR) urinary 1-OHPG concentration for each of the genetic polymorphisms examined in this study. Several of the polymorphisms show strong differences in the median. To better show the crude associations, we plotted the individual urine 1-OHPG values by genotype for selected variants in Ahr, CYP1A1, CYP1A2 and CYP1B1 (Figure 1).


Figure 1
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  		Fig. 1 Dot plots of urine 1-OHPG concentrations for four genetic variants in healthy subjects from Rio Grande do Sul, Brazil. For each polymorphism the individual concentrations were plotted by genotype and the data were jittered to improve clarity. Only one subject was AA for Cyp1A1 C461A so that subject's data point was plotted with the heterozygotes. Horizontal bars indicate the median concentration.

 


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  		Table III Median (25th–75th percentile) urine 1-OHPG concentration and regression coefficients and P-values for crude and adjusted modelsa by genotype

 
We tested the association between each polymorphism and the measured concentration of urinary 1-OHPG (Table III) and found significant crude associations for each of the polymorphisms in Cyp1B1 and one of the SNPs in Ahr. Adjustment for factors known to influence urine 1-OHPG concentration did not alter the associations with Cyp1B1 polymorphisms, while the Ahr association was substantially attenuated. The adjusted model also showed significant associations for one SNP in Cyp1A1 and one SNP in Cyp1A2. These two SNPs are not linked (D' = –0.47, r2 = –0.0021). The Cyp1A1 C461A association appeared to be slightly confounded by smoking. Subjects carrying the variant allele were non-significantly less likely to smoke than those with homozygous CC. The Cyp1A2 A3860G association showed no single strong confounder; the association became stronger overall after the addition of all adjusting variables.

To examine the joint effects of different polymorphisms we selected the single SNPs from Ahr, Cyp1A1 and Cyp1A2 that were associated with urine 1-OHPG concentration and the Cyp1B1 SNP with the strongest association. Using an indicator variable for the homozygous variant genotype we fit models for each variant alone, for comparison, and all four in a single model (Table IV). The combined model had no effect on the Cyp1B1 polymorphism association, reduced the modeled effect of the Cyp1A1 polymorphism and strengthened the effect and significance of the other two polymorphisms. A model containing just the exposure variables had a total r2 of 0.21. Adding the four genotype variables improved the total r2 to 0.33. Therefore, adding these four genetic variants explained 12% more of the total variation in urine 1-OHPG concentrations, which is a 57% increase in the explanatory power of the model.


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  		Table IV Adjusted single and multi-gene regression modelsa for the association between selected homozygous variant genotypes and urine 1-OHPG concentration

 

   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
References
 
Using data collected in this study, we previously demonstrated that healthy subjects, even non-smokers, from Rio Grande do Sul were exposed to moderately elevated levels of PAHs, as measured by urine 1-OHPG concentration, and that smoking tobacco and drinking maté were important predictors of exposure (6). To further investigate the variation of PAH metabolism in these subjects, we examined whether genetic variation in PAH-metabolizing enzyme genes demonstrated phenotypic changes in 1-OHPG excretion.

We found strong associations between three different Cyp1B1 polymorphisms and 1-OHPG concentration. Two of these polymorphisms were in very strong linkage disequilibrium and therefore produced very similar results. The third polymorphism showed some linkage disequilibrium with the other two (D' = –0.76 and r2 = 0.18). We also found modest but significant associations with one variant in each of the Ahr, Cyp1A1 and Cyp1A2 genes. In general, adjustment for variables associated with higher urine 1-OHPG concentration (age, smoking, maté, etc) had modest effects on the regression coefficients.

The biological differences for the tightly linked Cyp1B1 polymorphisms have been examined in vitro and were found to show no major differences in the catalytic activity for two important substrates, ethoxyresorufin and 17ß-estradiaol, nor did the variants produce proteins with different stabilities when expressed in COS-1 cells (12). Despite this lack of difference in cell culture, we have found statistically significant differences in urine 1-OHPG concentrations in humans. The polymorphisms are non-synonymous and are thought to occur in areas of the protein that may be critical to enzyme activity (12). The polymorphism in Cyp1A2 that we found to be significantly associated with urine 1-OHPG is in the gene promoter and is thought to effect enzyme activity by reducing the inducibility of the gene. An early study reported that subjects with the polymorphism have decreased P4501A2 activity in caffeine metabolism (13), but other studies have failed to confirm this result (14,15).

Previous studies of genetic variation in PAH-metabolizing genes that have examined urine 1-OHPG or 1-hydroxypyrene concentrations have also produced inconsistent results for most of the genes studied, including Cyp1A1 (16,17), Cyp1A2 (18,19), GSTM1 (20,21) and GSTT1 (20,22). The strongest evidence of a phenotypic effect in our study was for polymorphisms in Cyp1B1. Two other studies that examined the association between Cyp1B1 variants and urinary 1-hydroxypyrene did not find an association (16,18). Population- and exposure-specific effects may help explain the inconsistencies. For example, the cited studies have included occupationally and non-occupationally exposed subjects. The exposures to B[a]P and co-occurring PAHs are probably very different in coke-oven workers versus subjects exposed to B[a]P through tobacco smoke and food. Also, the different ethnic background of the subjects under study may result in other genetic variants that impact PAH metabolism, which have not been measured in the relatively small number of polymorphisms studied to date. On the other hand, inconsistencies in results among free-living individuals from different ethnic backgrounds with different sources of exposure may not be surprising considering the inconsistencies cited using controlled experiments in the metabolism of caffeine or other probes.

Our study has several strengths and weaknesses. Since our study used free-living healthy volunteers, our results may accurately reflect the general population of Southern Brazil. We found that modeling the effect of polymorphisms using a multi-gene model sharpened the associations between genetic polymorphisms and urine 1-OHPG concentrations. And this procedure might improve reproducibility between studies. We demonstrated that the contributions to inter-individual variability in urine 1-OHPG concentrations from lifestyle and genetic sources are essentially independent and additive.

Our study only examined the association between genotypes and urine 1-OHPG at a single point in time for only one level of exposure, which may limit the understanding of the association. That is, the association between certain genotypes and urine 1-OHPG concentration may be different if the same individuals had substantially higher or lower PAH exposure or other unknown co-exposures. Also, we picked a small number of polymorphism in each gene rather than using a comprehensive approach taking into account the linkage disequilibrium blocks for each gene. Essentially all published studies share this limitation and this may contribute to the overall inconsistency in the literature.

In conclusion, we found evidence that Cyp1B1 genotypes were strongly associated with urine 1-OHPG concentrations. We also found some evidence that genotypes of Ahr, Cyp1A1 and Cyp1A2 were associated with 1-OHPG concentration. Finally, we showed that models including information on personal characteristics, sources of PAH exposure and genetic variation explained considerably more of the variation in urinary 1-OHPG concentrations than models that include only one of these types of data.


   Acknowledgments
 
This research was supported in part by the Intramural Research Program of the NIH, National Cancer Institute, Division of Cancer Epidemiology and Genetics and by NIH grant P01-ES06052 to Dr P.T.S.

Conflict of Interest Statement: None declared.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

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Received April 7, 2006; revised July 10, 2006; accepted July 11, 2006.


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