Ethnic differences in excretion of butadiene–DNA adducts by current smokers
Abstract
1,3-Butadiene (BD) is a known human carcinogen used in the synthetic polymer industry and also found in cigarette smoke, automobile exhaust and wood burning smoke. BD is metabolically activated by cytochrome P450 monooxygenases (CYP) 2E1 and 2A6 to 3,4-epoxy-1-butene (EB), which can be detoxified by GST-catalyzed glutathione conjugation or hydrolysis. We have previously observed ethnic differences in urinary levels of EB–mercapturic acids in white, Japanese American and Native Hawaiian smokers. In the present study, similar analyses were extended to urinary BD–DNA adducts. BD-induced N7-(1-hydroxy-3-buten-2-yl) guanine (EB–GII) adducts were quantified in urine samples obtained from smokers and non-smokers belonging to three racial/ethnic groups: white, Japanese American and Native Hawaiian. After adjusting for sex, age, nicotine equivalents, body mass index and batch, we found that Japanese American smokers excreted significantly higher amounts of urinary EB–GII than whites [1.45 (95% confidence interval: 1.12–1.87) versus 0.68 (95% confidence interval: 0.52–0.85) fmol/ml urine, P = 4 × 10−5]. Levels of urinary EB–GII in Native Hawaiian smokers were not different from those in whites [0.67 (95% confidence interval: 0.51–0.84) fmol/ml urine, P = 0.938]. There were no racial/ethnic differences in urinary EB–GII adduct levels in non-smokers. Racial/ethnic differences in urinary EB–GII adduct levels in smokers could not be explained by GSTT1 gene deletion or CYP2A6 enzymatic activity. Urinary EB–GII adduct levels in smokers were significantly associated with concentrations of BD metabolite dihyroxybutyl mercapturic acid. Overall, our results reveal that urinary EB–GII adducts in smokers differ across racial/ethnic groups. Future studies are required to understand genetic and epigenetic factors that may be responsible for these differences.
1,3-Butadiene (BD) is a known human carcinogen present in tobacco smoke. In the present study, urinary BD–DNA adducts were found to differ among three racial/ethnic groups of smokers with different risks of cancer development.
Graphical Abstract
Graphical Abstract.
Introduction
Butadiene (1,3-butadiene, BD) is classified as a known carcinogen in humans (1) and is among the most potent and abundant carcinogens in tobacco smoke. There are 20–75 µg of BD per cigarette in mainstream smoke and 205–361 µg per cigarette in side stream smoke (2,3). In addition to tobacco smoke, BD is found in urban air, automobile emissions and smoke from wood burning and used in the synthetic polymer industries (4–7). BD is a known carcinogen in laboratory animals, inducing neoplasms of the lung in mice at exposures as low as 6.25 ppm (8). Occupational exposure to BD has been associated with leukemia and possibly lung cancer (9,10). In the USA, risk of many smoking-related cancers differs by racial/ethnic group (11). Studies in the Multiethnic Cohort have shown that, when accounting for risk factors including smoking, Native Hawaiians have a higher risk of lung cancer than whites and Japanese Americans (12). It is possible that these disparities, at least in part, are attributed to population differences in the metabolic activation and detoxification of tobacco smoke carcinogens such as BD, which leads to higher load of mutagenic DNA adducts in susceptible populations.
BD is metabolized to DNA-reactive epoxides 3,4-epoxy-1-butene (EB), 1,2,3,4-diepoxybutane and 1,2-dihydroxy-3,4-epoxybutane by cytochrome P450 monooxygenases (13–15). BD epoxides are detoxified by glutathione S-transferases (particularly glutathione S-transferase theta 1, GSTT1) to form monohydroxybutenyl mercapturic acid (MHBMA) and dihydroxybutyl mercapturic acid (DHBMA) from EB, trihydroxylbutyl mercapturic acid from 1,2-dihydroxy-3,4-epoxybutane and bis-butanediol mercapturic acid from 1,2,3,4-diepoxybutane, which are excreted in urine (16–19). The main metabolic pathway of BD is shown in Figure 1. BD–mercapturic acids have previously been investigated as potential urinary biomarkers of tobacco smoke exposure to BD (16–31). Urinary MHBMA levels decreased 80–90% upon smoking cessation, confirming its association with smoking status (18,31). In contrast, DHBMA levels were unchanged upon smoking cessation, suggesting that it was not associated with smoking status (18,31).
Figure 1.
Metabolic activation of BD and formation of BD–DNA adducts.
We previously reported that, after controlling for internal smoking dose as measured by nicotine equivalents [NE, the sum of total urinary nicotine (free + nicotine N-glucuronide), cotinine (free + nicotine N-glucuronide) and trans-3′-hydroxycotinine (3-HC + its glucuronide)], MHBMA levels in Japanese American smokers were significantly lower than in Native Hawaiians and whites (34). These differences are consistent with the direction of lower smoking-related lung cancer risk and are primarily a result of the higher frequency of GSTT1 gene deletion in Japanese Americans (34).
The epoxide metabolites of BD, if not detoxified, can react with nucleophilic DNA bases to form covalent BD–DNA adducts. Specifically, EB alkylates the N7 position of guanine in DNA to form N7-(1-hydroxy-3-buten-2-yl)guanine (EB–GII) adducts (32,33). Unlike BD-mercapturic acids, which represent the metabolically inactivated dose of butadiene (34), BD–DNA adducts can be considered as mechanism-based biomarkers of exposure. They can serve as useful indicators of the biologically relevant dose of carcinogens as they represent the dose of carcinogen which is available for binding to DNA (35,36). BD–DNA adducts are thought to be responsible for the carcinogenicity of BD, as they can lead to DNA polymerase errors during replication (37,38). In addition, N7-guanine lesions are hydrolytically labile and are excreted in urine as free nucleobases, making them potential biomarkers of risk associated with BD exposure (32,39–41). Workers occupationally exposed to BD (0.1–2.2 ppm of BD) excrete significantly higher concentrations of urinary EB–GII (1.25 ± 0.51 pg/mg creatinine) when compared with administrative controls (<0.01 ppm BD, 0.22 ± 0.08 pg/mg creatinine) (39).
We recently developed a high-throughput quantitative nanoLC/ESI+-HRMS3 method for urinary EB–GII adducts in humans and validated their use as a biomarker of smoking-related exposure to BD. We showed that urinary EB–GII adducts are stable over time in human subjects (42). Additionally, we quantified urinary EB–GII in 17 individuals participating in a smoking cessation program. We found that from baseline (1.63 ± 0.64 pg/ml urine), EB–GII levels decrease by 34% (1.07 ± 0.56 pg/ml) by day 3 following smoking cessation (42). Low levels of EB–GII adducts were observed in unexposed animals and non-smokers, indicating the presence of endogenous sources of EB–GII (39). In the present study, urinary EB–GII adducts were quantified in Native Hawaiian, Japanese American and white smokers and non-smokers (N = 205–210 per ethnic group) in an attempt to identify any ethnic differences in excretion of a mechanism-based biomarker of BD-induced DNA damage.
Materials and Methods
Study population
Our study population included current cigarette smokers and non-smokers at the time of urine collections from three racial/ethnic groups. The study details for the smokers and non-smokers (34,43,44) have been previously reported. In brief, all participants were from the state of Hawaii. For the smokers, the participants were selected at random from the Hawaii component of the Multiethnic Cohort study or from the control groups of population-based case-control studies conducted in Hawaii (34,43,44). The non-smokers were selected at random from the Hawaii component of the Multiethnic Cohort study. Approximately 100 subjects in each racial/ethnic and smoking status group was selected. A total of 623 samples were analyzed for urinary EB–GII DNA adducts (207 Native Hawaiians, 205 Japanese Americans and 211 whites).
Materials
Liquid chromatography mass spectrometry (LC–MS)-grade water, methanol and acetonitrile were purchased from Fisher Scientific (Pittsburgh, PA). Strata X polymeric reversed-phase SPE cartridges (30 mg/ml) were purchased from Phenomenex (Torrance, CA). EB–GII and 15N5–EB–GII standards were prepared as previously reported (45,46). Ninety-six well plates were purchased from Analytical Sales and Services Inc. (Ledgewood, NJ). All other chemicals and solvents were obtained from Sigma–Aldrich (Millwaukee, WI; St. Louis, MO) unless otherwise specified.
Nicotine equivalents
NE were measured in the previous analysis of these subjects (44). In that study, total urinary nicotine (free + nicotine N-glucuronide), cotinine (free + nicotine N-glucuronide) and trans-3′-hydroxycotinine (3-HC + its glucuronide) were measured by gas chromatography/mass spectrometry (47,48). The sum of these metabolites (NE) was used as a measure of total nicotine uptake as it accounts for over 80% of nicotine and its metabolites (49). The phenotypic measure of cytochrome P450 2A6 (CYP2A6) activity (the primary enzyme in nicotine metabolism) was quantified as total trans-3′-hydroxycotinine (nmol/ml)/total cotinine (nmol/ml) (50).
Urine sample processing and EB–GII adduct enrichment
Urinary EB–GII concentrations were determined using the high-throughput nanoLC/ESI+-HRMS3 method previously developed in the Tretyakova laboratory (39,42). In brief, urine samples (200 μl) were centrifuged at 10 000g for 15 min to remove any particulate matter. The supernatants were spiked with 15N5-EB–GII (5 fmol, internal standard for mass spectrometry) and subjected to solid-phase extraction on Strata X cartridges (30 mg/ml; Phenomenex, Torrance, CA). Solid-phase extraction 96-well plates were conditioned with 2 ml of methanol, followed by 2 ml of Milli-Q water. Urine samples were loaded onto prepared 96-well plates, and each well was washed with 1 ml of water, followed by 1 ml of 10% methanol in water. EB–GII and its internal standard were eluted with 60% methanol in water, dried under vacuum and reconstituted with 102 μl of 0.4% formic acid in water containing 2′-deoxythymidine as a high-performance liquid chromatography (HPLC) retention time marker (2.1 nmol).
Offline HPLC purification of solid-phase extraction–enriched EB–GII and its internal standard was achieved on an Agilent 1100 series HPLC system equipped with a UV detector and an automated fraction collector (Agilent Technologies, Santa Clara, CA). A Zorbax Eclipse XDB-C18 column (4.6 × 150 mm, 5 μm; Agilent Technologies, Santa Clara, CA) was eluted at a flow rate of 1 ml/min with a gradient of 0.4% formic acid in Milli-Q water (A) and HPLC-grade acetonitrile (B). Solvent composition was maintained at 0% B for 5 min and then linearly increased to 3% B in 15 min and further to 40% B in 5 min. The solvent composition was returned to 0% acetonitrile in 5 min and held at 0% for 15 min for column equilibration. UV absorbance was monitored at 254 nm. 2′-Deoxythymidine was used as a retention time marker. Under these conditions, 2′-deoxythymidine eluted at ~17.4 min, and the retention time of EB–GII was ~15.6 min. HPLC fractions containing EB–GII and its internal standard (14.1−16.1 min) were collected into 2 ml 96-well plates (Analytical Sales and Services Inc., Ledgewood, NJ), concentrated under vacuum and reconstituted in LC/MS-grade water containing 0.01% acetic acid (30 μl) for nanoHPLC/nanoESI+-HRMS3 analysis. The injection volume was 5 μl.
NanoLC/ESI+-HRMS3 analysis of urinary EB–GII
All nanoLC/ESI+-HRMS3 analyses were conducted on an LTQ Orbitrap Velos instrument equipped with a nanospray source (Thermo Fisher Scientific Corp., Waltham, MA) interfaced with a Dionex UltiMate 3000 RSLCnano HPLC system (Thermo Fisher Scientific Corp., Waltham, MA) using previously described methodology (39,42). Gradient elution was achieved using LC/MS-grade water containing 0.01% acetic acid (A) and LC/MS-grade acetonitrile containing 0.02% acetic acid (B). Samples were loaded onto a nanoLC column (0.075 × 200 mm) manually packed with Synergi Hydro-RP 80 Å (4 μm) chromatographic packing (Phenomenex, Torrance, CA). Initial HPLC flow rate was maintained at 1 μl/min at 2% B for 5 min to enable sample loading onto the nano column, followed by a flow rate decrease to 300 nl/min at 2% B for 1 min. The percentage of solvent B was linearly increased to 25% B in 9 min and further to 50% B in 10 min at a flow rate of 300 nl/min. The HPLC flow rate was increased to 1 μl/min, and solvent composition was returned to 2% B in 1 min, followed by 5 min column equilibration. Under these conditions, EB–GII eluted as a sharp peak at 13 min.
Tandem mass spectrometry analysis was performed by fragmenting the [M + H]+ ions of EB–GII (m/z 222.1) via collision-induced dissociation in the linear ion trap portion of the instrument using the collision energy at 25 and an isolation width of 1.0 amu. MS/MS fragment ions at m/z 152.1 [Gua + H]+ were subjected to further fragmentation in the high collision dissociation cell of the instrument using nitrogen as a collision gas (collision energy = 75 units, isolation width = 1.0 amu). The resulting MS3 fragment ions at m/z 135.0301 ([Gua−NH3] +) and m/z 153.0411 ([Gua−NH3 + H2O]+) were detected in the mass range of m/z 50−270 using the Orbitrap mass analyzer (HRMS) at a resolution of 25 000. The 15N5 labeled internal standard ([15N5]–EB–GII) was detected using an analogous MS3 scan event consisting of fragmentation of m/z 227.1 ([M + H]+) to m/z 157.1 ([15N5–Gua + H]+) and further to m/z 139.0183 ([15N5–Gua–NH3] +) and m/z 157.0283 ([15N5–Gua–NH3 + H2O]+). Extracted ion chromatograms corresponding to the sum of m/z 135.0301 ([Gua−NH3] +) and m/z 153.0411 ([Gua−NH3 + H2O]+) were used for quantitation of EB–GII, whereas m/z 139.0183 ([15N5-Gua − NH3] +) and m/z 157.0283 ([15N5-Gua−NH3 + H2O]+) were used for quantitation of [15N5]–EB–GII. Mass accuracy was 5 ppm. A full scan event was also performed over the mass range of m/z 100−500 at a resolution of 15,000 to monitor for any co-eluting matrix components. EB–GII amounts were determined by comparing the areas of the nanoLC/ESI+-HRMS3 peaks corresponding to the analyte and its internal standard using standard curves generated by analyzing known analyte amounts. Method limit of detection and limit of quantification values were determined from the analysis of spiked non-smoker urine samples to be 0.25 fmol/ml and 0.5 fmol/ml urine, respectively. Intra- and interday precision was 13.1 and 10.6%, respectively. Method accuracy was between 83.9–115.4% for quantification of EB–GII through the dynamic range of the assay (0.1–10 fmol) (39,42).
Genotyping
Genotyping methods for GSTT1 gene deletion was achieved using the TaqMan copy number assay as previously reported (34). In brief, DNA was extracted from blood leukocytes using a QiaAmp DNA Blood extraction kit (Qiagen, Germantown MD). The samples were genotyped using a predesigned TaqMan GSTT1 copy number assay (Hs00010004_cn) and run on the 7900HT Fast Real-Time System (Life Technologies, Foster City, CA). Copy number counts were calculated using Life Technologies CopyCaller v2.0 software. Approximately 5% of blind duplicates were included for quality control. Test for Hardy Weinberg Equilibrium was met for all three populations (P > > 0.05).
Statistical methods
EB–GII adduct levels were expressed as fmol/ml urine. Spearman’s partial correlation coefficients, adjusting for age, sex and race/ethnicity (for overall), were computed to examine the correlation between EB adducts, NE, MHBMA, DHBMA and BD metabolite ratio MHBMA/(MHBMA+DHBMA), which were previously measured using an HPLC–ESI–MS/MS method developed in the Tretyakova laboratory (34). Multivariable linear models regressed the urinary levels of EB–GII adducts on the following predictors: age at time of urine collection (continuous), race/ethnicity (when results were not stratified by race/ethnicity), smoking status (when results were not stratified by smoking status), body mass index (BMI), batch and NE (natural log). To better meet model assumptions, all metabolite concentrations were transformed by taking the natural log. If large numbers of EB–GII values were at a detection limit (0.125 fmol/ml) in a given analysis, so that approximate lognormality was not achieved by transformation, we performed two supplementary analyses. The first was a logistic regression of a yes/no variable indicating whether the recorded EB–GII values were above or below the detection limit and the second a (log) linear regression model restricted to those with detectable levels. Both analyses used the same set of predictor variables as above. Consistency between these three analyses was assessed by checking that regression parameter estimates were in the same direction and whether they were statistically significant (P < 0.05).
To examine ethnic/racial differences of EB–GII adducts in smokers, covariate-adjusted geometric means were computed for each ethnic/racial group at the mean covariate vector using the LS means procedure in SAS. We also examined whether the geometric means of BD adducts differed according to nicotine metabolism or GSTT1 gene deletion. Here, nicotine metabolism was quantified by the urinary CYP2A6 enzymatic activity ratio [measured by total trans-3′-hydroxycotinine (nmol/ml)/total cotinine (nmol/ml)]. This biomarker was stratified by tertile based on the overall population. GSTT1 gene deletion was modeled by the number of gene copies (2, 1 or 0), where 0 was the equivalent to no copies of the gene (i.e. gene deletion resulting in no enzymatic activity).
Results
Study population
Baseline demographic characteristics of the study population are presented in Table 1. Among 623 participants, 292 were non-smokers and 331 were current smokers at time of urine collection. The three racial/ethnic groups included were Native Hawaiian, white and Japanese American. Racial/ethnic groups were approximately evenly distributed across each smoking status group. For smokers, additional measures including smoking frequency and measures of BD metabolites are also included.
Table 1.
Demographic characteristics of study participants
| Japanese Americans | Native Hawaiians | Whites | |
|---|---|---|---|
| N | 205 | 207 | 211 |
| Age, mean (SD) | 63.30 (7.26) | 60.32 (9.85) | 62.74 (7.36) |
| Gender | |||
| Males (%) | 106 (51.71) | 94 (45.41) | 100 (47.39) |
| Females (%) | 99 (48.29) | 113 (54.59) | 111 (52.61) |
| Smoking status | |||
| Smokers (%) | 108 (52.68) | 110 (53.14) | 113 (53.55) |
| Non-smokers (%) | 97 (47.32) | 97 (46.86) | 98 (46.45) |
| EB–GII DNA adducts (fmol/ml), mean (SD) | 1.61 (3.20) | 0.98 (1.50) | 1.17 (2.19) |
| BMI, mean (SD) (kg/m2) | 24.81 (4.14) | 28.04 (5.87) | 26.92 (5.78) |
| NE, mean (SD) (nmol/ml), Smokers only | 30.65 (22.02) | 47.91 (34.18) | 54.97 (49.24) |
| Cigarettes per day, mean (SD), Smokers only | 20.02 (7.06) | 19.36 (9.26) | 25.80 (11.41) |
| CYP2A6 activity, mean (SD), Smokers only | 0.86 (1.80) | 1.02 (0.84) | 1.32 (1.30) |
| MHBMA, mean (SD) (ng/ml), Smokers onlya | 3.45 (3.12) | 7.22 (7.56) | 7.13 (8.68) |
| DHBMA, mean (SD) (ng/ml), Smokers onlya | 342.68 (268.84) | 448.49 (405.41) | 437.25 (455.13) |
| Metabolic Ratio: MHBMA/(MHBMA + DHBMA)a | 0.012 (0.010) | 0.017 (0.012) | 0.018 (0.015) |
Native Hawaiian smokers (n = 110) were the heaviest (median BMI = 28.04 ± 5.87 kg/m2), followed by whites and Japanese Americans (26.92 ± 5.78 kg/m2 and 24.81 ± 4.14 kg/m2, respectively). Native Hawaiians and Japanese Americans reported smoking fewer cigarettes per day (mean cigarettes per day = 19.36 ± 9.26 and 20.02 ± 7.06, respectively) than whites (cigarettes per day = 25.8 ± 11.41). Japanese Americans had the lowest CYP2A6 activity enzymatic ratio (0.86 ± 1.8) when compared with Native Hawaiians and whites (1.02 ± 0.84 and 1.32 ± 1.30, respectively). As previously reported for a larger group of smokers, half of whom were included in this current study (34), urinary MHBMA levels were higher in whites and Native Hawaiians [6.7 (95% confidence interval {CI}: 5.8–7.8) ng/mg Cr and 5.3 (95% CI: 4.6–6.2) ng/mg Cr, respectively], when compared with Japanese Americans [4.4 (95% CI: 3.8–5.1) ng/mg Cr] (Table 1) after adjusting for age, sex BMI and NE. DHBMA levels did not differ between the three ethnic groups (P > 0.15). The Pearson’s partial correlation (in smokers) between NE and MHBMA was statistically significant (r = 0.532, P < 0.001). A depiction of the univariate distribution of NE, EB–GII, MHBMA and DHBMA is given in Supplementary Figures S1a, b and S2a–c, available at Carcinogenesis Online.
Urinary excretion of EB–GII adducts of BD
To compare BD–DNA adduct load among the three ethnic groups, EB–GII levels were quantified in urine of Native Hawaiian, white and Japanese American smokers and non-smokers. We found that when adjusting for sex, age, BMI, batch and race/ethnicity, smokers excreted significantly higher levels of EB–GII adducts [0.98 (95% CI: 0.84–1.12) fmol/ml] than non-smokers [0.19 (95% CI: 0.15–0.22) fmol/ml] (P = 5.8 × 10−34) (Table 2). This is consistent with our earlier study revealing a strong association of urinary EB–GII with smoking and a decline in urinary adduct levels upon smoking cessation (42).
Table 2.
Geometric means (95% confidence limits) for EB–GII (fmol/ml) by race/ethnicity and smoking status
| N | Geometric mean | β d | P-value | N g | Geometric mean | β d,g | P-valueg | |
|---|---|---|---|---|---|---|---|---|
| (95% CI) | (95% CI)g | |||||||
| Non-smokersa | ||||||||
| Overall | 290 | 0.19 (0.15–0.22)e | 122 | 0.37 (0.28–0.46)h | ||||
| Native Hawaiians | 97 | 0.21 (0.17–0.24) | 0.098 | 0.355 | 42 | 0.44 (0.34–0.56) | 0.047 | 0.789 |
| Japanese Americans | 96 | 0.21 (0.17–0.23) | 0.084 | 0.435 | 45 | 0.35 (0.26–0.43) | −0.203 | 0.271 |
| Whites | 97 | 0.19 (0.16–0.22) | Reference | 35 | 0.42 (0.32–0.54) | Reference | ||
| Smokersb | ||||||||
| Overall | 331 | 0.98 (0.84–1.12)e | 266 | 1.66 (1.39–1.95)h | ||||
| Native Hawaiians | 110 | 0.68 (0.52–0.86) | −0.071 | 0.664 | 79 | 1.39 (1.08–1.78) | 0.066 | 0.664 |
| Japanese Americans | 108 | 1.35 (1.04–1.72) | 0.618 | 7.8 × 10−4 | 95 | 2.10 (1.65–2.65) | 0.477 | 0.0034 |
| Whites | 113 | 0.73 (0.56–0.91) | Reference | 92 | 1.31 (1.02–1.65) | Reference | ||
| Smokersc | ||||||||
| Overall | 331 | 0.90 (0.76–1.03)f | 266 | 1.60 (1.34–1.89)i | ||||
| Native Hawaiians | 110 | 0.67 (0.51–0.84) | −0.013 | 0.938 | 79 | 1.39 (1.07–1.76) | 0.108 | 0.481 |
| Japanese Americans | 108 | 1.45 (1.12–1.87) | 0.766 | 4.8 × 10−5 | 95 | 2.22 (1.74–2.80) | 0.578 | 6.8 × 10−4 |
| Whites | 113 | 0.68 (0.52–0.85) | Reference | 92 | 1.24 (0.97–1.57) | Reference |
Among smokers, the highest concentration of urinary EB–GII adducts was found in Japanese Americans [1.35 (95% CI: 1.04–1.72) fmol/ml], with significantly lower levels in Native Hawaiians [0.68 (95% CI: 0.52–0.86) fmol/ml] and whites [0.73 (95% CI: 0.56–0.91) fmol/ml], after adjusting for sex, age, BMI, batch and NE (Table 2). Urinary EB–GII adduct concentrations were significantly higher in Japanese American smokers than in white smokers (P = 4.8 × 10−5), whereas the amounts of urinary EB–GII in Native Hawaiian smokers were not significantly different from white smokers (P = 0.938). This pattern was not observed in non-smokers, instead, urinary EB–GII adduct levels were fairly consistent across the racial/ethnic groups (ranging from 0.19 to 0.21 fmol/ml). These results reveal ethic differences in EB–GII adducts in current smokers, but not in non-smokers.
Variation in urinary EB–GII by GSTT1 gene deletion or CYP2A6 enzymatic activity ratio
We next investigated whether population’s variation of urinary EB–GII levels can be explained by metabolic enzymes involved in BD biotransformation. As GSTT1-catalyzed glutathione conjugation is the major metabolic detoxification pathway for butadiene epoxides including EB (16–18), we first investigated the relationship for GSTT1 gene deletion status with urinary EB–GII adduct levels overall and by racial/ethnic groups. The geometric means of urinary EB–GII adduct levels did not differ by GSTT1 genotype (P = 0.2689, Table 3). This is different from our previous results for MHBMA, which was strongly correlated with GSTT1 copy number (34).
Table 3.
Geometric means (95% confidence limits) for EB–GII (fmol/ml) stratified by GSTT1 CNV and race/ethnicity among smokers
| GSTT1 gene deletion genotypea | N | Geometric mean (95% CI) | P-value |
|---|---|---|---|
| Allb | 323 | ||
| 1/1 | 70 | 0.92 (0.68–1.22) | 0.2689 |
| 1/0 | 157 | 0.80 (0.65–0.96) | |
| 0/0 | 96 | 1.02 (0.79–1.30) | |
| Whitesc | 109 | ||
| 1/1 | 32 | 0.81 (0.52–1.22) | 0.2385 |
| 1/0 | 46 | 0.67 (0.45–0.97) | |
| 0/0 | 31 | 1.09 (0.68–1.70) | |
| Native Hawaiiansc | 109 | ||
| 1/1 | 27 | 0.96 (0.59–1.54) | 0.1537 |
| 1/0 | 59 | 0.66 (0.47–0.88) | |
| 0/0 | 23 | 1.06 (0.63–1.77) | |
| Japanese Americansc | 105 | ||
| 1/1 | 11 | 1.28 (0.55–2.90) | 0.9537 |
| 1/0 | 52 | 1.42 (0.93–2.15) | |
| 0/0 | 42 | 1.33 (0.84–2.07) |
As CYP2A6 monooxygenase along with CYP2E1 is involved in epoxidation of butadiene to form EB (13–15), we additionally investigated the association of CYP2A6 enzymatic activity ratio with urinary EB–GII adduct levels overall and within each race/ethnicity. EB–GII adduct levels were not affected by CYP2A6 activity, although there was a suggestive positive increase of EB–GII adduct levels among Japanese Americans with higher CYP2A6 enzymatic activity (Table 4). This could be explained by CYP2E1 compensating for any deficiency of CYP2A6 activity.
Table 4.
Geometric means (95% confidence limits) for EB–GII (fmol/ml) stratified by tertiles of CYP2A6 activity and race/ethnicity among smokers
| Values of CYP2A6 by tertilese | N | Geometric mean (95% CI)a,b | β a,b | P-valuea,b | P-trenda,b,c | Geometric mean (95% CI)d | β d | P-valued | P-trendd |
|---|---|---|---|---|---|---|---|---|---|
| Alla | 331 | ||||||||
| Tertile 1 | 110 | 0.71 (0.55–0.90) | Reference | 0.081 | 0.75 (0.57–0.95) | Reference | 0.245 | ||
| Tertile 2 | 111 | 1.00 (0.78–1.26) | 0.340 | 0.056 | 1.00 (0.78–1.25) | 0.290 | 0.101 | ||
| Tertile 3 | 110 | 0.99 (0.76–1.25) | 0.327 | 0.073 | 0.93 (0.72–1.18) | 0.223 | 0.227 | ||
| Whitesb | 113 | ||||||||
| Tertile 1 | 16 | 0.74 (0.37–1.42) | Reference | 0.856 | 0.87 (0.44–1.67) | Reference | 0.616 | ||
| Tertile 2 | 44 | 0.85 (0.56–1.25) | 0.140 | 0.722 | 0.88 (0.58–1.28) | 0.009 | 0.981 | ||
| Tertile 3 | 53 | 0.82 (0.37–1.42) | 0.108 | 0.776 | 0.75 (0.51–1.08) | −0.140 | 0.718 | ||
| Native Hawaiiansb | 110 | ||||||||
| Tertile 1 | 36 | 0.58 (0.38–0.86) | Reference | 0.281 | 0.61 (0.40–0.91) | Reference | 0.465 | ||
| Tertile 2 | 39 | 0.71 (0.47–1.04) | 0.201 | 0.481 | 0.70 (0.46–1.02) | 0.135 | 0.640 | ||
| Tertile 3 | 35 | 0.79 (0.51–1.18) | 0.312 | 0.284 | 0.76 (0.49–1.14) | 0.216 | 0.467 | ||
| Japanese Americansb | 108 | ||||||||
| Tertile 1 | 58 | 0.98 (0.69–1.37) | Reference | 0.084 | 0.99 (0.70–1.38) | Reference | 0.100 | ||
| Tertile 2 | 28 | 1.80 (1.10–2.90) | 0.601 | 0.048 | 1.79 (1.09–2.89) | 0.589 | 0.054 | ||
| Tertile 3 | 22 | 1.56 (0.90–2.68) | 0.464 | 0.156 | 1.54(0.89–2.65) | 0.443 | 0.178 |
Relationship between urinary EB–GII and BD metabolites
To compare the results for EB-derived urinary metabolites and DNA adducts in smokers, we evaluated the relationship between urinary EB–GII adducts quantified in this study and BD-mercapturic acids (MHBMA and DHBMA) among the subjects with the available data previously reported by our group (34) (Table 5). After adjusting for age, sex, BMI and batch, urinary MHBMA and DHBMA levels were significantly associated with EB–GII adduct concentrations. Specifically, for MHBMA, a 1 log-unit increase (approximately a 2.7-fold increase) was associated with a 0.20 log-unit increase (approximately a 1.2-fold increase) of EB–GII adduct levels (P = 4.1 × 10−3). This association was statistically significant in Native Hawaiians (P = 0.03) and whites (P = 0.02), but not in Japanese Americans (P = 0.28). For DHBMA, a 1 log-unit increase (approximately a 2.7-fold increase) was associated with a 0.68 log-unit increase (approximately a 2.0-fold increase) of EB–GII adduct levels (P = 8.4 × 10−12), and this association was statistically significant in all three populations. When adjusting for internal smoking dose, measured by NE, the association was found no longer statistically significant for MHBMA (r = 0.07, P = 0.22), but remained for DHBMA, overall (P = 7.2 × 10−10). By race/ethnicity, this relationship was most significant in whites, followed by Native Hawaiians and Japanese Americans (P’s = 5.4 × 10−6, 3.6 × 10−4 and 7.2 × 10−3, respectively, Table 5). These results indicate that urinary levels of BD-mercapturic acids are not predictive of the extent of BD–DNA damage. We also examined potential association between urinary adducts and NE. For all smokers as a whole, urinary EB–GII adducts were not correlated with NE (r = 0.09, P = 0.10). By race/ethnicity, EB–GII adducts were found to be correlated with NE only in whites (r = 0.25, P = 0.009) and not the other racial/ethnic groups (P’s > 0.14). This indicates that in addition to smoking amounts, the levels of urinary EB–GII adducts could be affected by other biological factors such as DNA repair, adduct excretion and further metabolism (51).
Table 5.
Association between urinary BD adducts (EB–GII, fmol/ml) and BD metabolites (MHBMA and DHBMA), overall and by race/ethnicity among smokers
| Overalla | Native Hawaiiansb | Japanese Americansb | Whitesb | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| n | β | P-value | n | β | P-value | n | β | P-value | n | β | P-value | P-hetd | |
| MHBMA (ng/ml) | 330 | 0.200 | 4.12E-03 | 110 | 0.265 | 0.03 | 108 | 0.124 | 0.284 | 113 | 0.311 | 0.022 | 0.199 |
| DHBMA (ng/ml) | 329 | 0.682 | 8.44E-12 | 110 | 0.659 | 1.03E-04 | 108 | 0.489 | 9.28E-03 | 112 | 0.853 | 3.22E-07 | 0.200 |
| Metabolic ratio: MHBMA/(MHBMA + DHBMA) | 323 | −0.154 | 0.049 | 109 | −0.062 | 0.645 | 105 | −0.086 | 0.494 | 109 | −0.311 | 0.060 | 0.511 |
| MHBMA (ng/ml)c | 330 | 0.126 | 0.112 | 110 | 0.227 | 0.127 | 108 | 0.104 | 0.397 | 113 | 0.179 | 0.290 | 0.449 |
| DHBMA (ng/ml)c | 329 | 0.749 | 7.18E-10 | 110 | 0.731 | 3.64E-04 | 108 | 0.654 | 7.20E-03 | 112 | 0.956 | 5.37E-06 | 0.108 |
| Metabolic ratio: MHBMA/(MHBMA + DHBMA)c | 323 | −0.175 | 0.024 | 109 | −0.113 | 0.413 | 105 | −0.082 | 0.515 | 109 | −0.348 | 0.031 | 0.496 |
Discussion
BD is one of the most abundant carcinogens in tobacco smoke (2,3) and has a relatively high cancer risk index when compared with other tobacco smoke carcinogens (3). Our laboratory has developed quantitative mass spectrometry methods for butadiene metabolites (18,19,27) and DNA adducts in humans (39,52–54). These advanced methodologies have been previously used to investigate interindividual differences in butadiene metabolism (55,56), to establish the correlation of these biomarkers with smoking (42) and ethnicity/genetic polymorphisms (29,34). We found that GSTT1 copy number influenced BD metabolism and toxicity in human HAPMAP cells and could explain some of the ethnic differences in excretion of BD-mercapturic acid MHBMA (29,55,56). Furthermore, the chemopreventive agent present in cruciferous vegetables (phenylethylisothiocyanate, PEITC) influenced the levels of BD-mercapturic acids in a nested study of current smokers by inducing glutathione S-transferases (57).
The present study was focused on quantifying urinary EB–GII, butadiene-DNA adducts formed from butadiene monoepoxide (EB), in a multiethnic group of smokers and non-smokers. Unlike BD metabolites MHBMA and DHBMA, which can be considered as biomarkers of exposure to butadiene (16–31), urinary DNA adducts represent the biologically relevant dose of butadiene bound to genomic DNA and subsequently released through DNA repair and/or spontaneous hydrolysis (Figure 1) (40,58).Therefore, BD–DNA adducts are considered a better biomarker of BD-associated cancer risk than previously employed BD-mercapturic acids (which represent detoxified butadiene). EB–GII adducts have a half-life of 2.20 ± 0.12 days, due to their spontaneous depurination (40,41). We previously reported the detection of urinary EB–GII adducts in laboratory animals treated with BD by inhalation and in current and former smokers, showing their association with smoking (39,42).
Our new results reported here confirm the association of BD–DNA damage with smoking: EB–GII adducts levels were significantly higher in urine of smokers than non-smokers [0.98 (95% CI: 0.84–1.12) fmol/ml versus 0.19 (95% CI: 0.15–0.22) fmol/ml, P = 5.8 × 10−34, Table 2]. This is consistent with previous reports that suggest that smoking is an important source of butadiene exposure and BD–DNA adduct formation (18,29,31,34,39,42). We have previously shown that urinary EB–GII adduct levels decrease upon smoking cessation and are significantly higher in smokers when compared with non-smokers (39,42). Butadiene metabolites MHBMA and trihydroxylbutyl mercapturic acid have also been shown to decrease upon smoking cessation (18,31).
The main goal of our study was to investigate racial/ethnic differences in butadiene metabolism and DNA adduct formation in Japanese American, Native Hawaiian and white smokers and non-smokers residing in Hawaii. Although similar studies have been carried out in large multiethnic samples for butadiene metabolites (29,34), this is the first attempt to quantify butadiene–DNA adducts among these racial/ethnic groups and to evaluate the relationship of these adducts with butadiene metabolites across populations. Among smokers, Japanese Americans had the highest levels of urinary BD–DNA adducts (EB–GII), compared with white and Native Hawaiians (Table 2). In contrast, our earlier study of urinary BD metabolites (MHBMA and DHBMA) using the same population found that white smokers excreted the highest concentrations of BD-mercapturic acids MHBMA, while Japanese American smokers excreted the lowest amounts of MHBMA (34). However, it should be noted that although BD-mercapturic acids are a measure of carcinogen exposure, urinary EB–GII adduct levels represent the amount of butadiene metabolite bound to DNA and subsequently excreted due to spontaneous hydrolysis and active repair of the resulting DNA lesions. More efficient repair of genomic butadiene–DNA adducts by Japanese American smokers may help explain higher levels of EB–GII adducts in their urine, despite their overall lower risk of lung cancer due to smoking. This possibility will be investigated in our future studies by correlating the levels of genomic and urinary EB–GII adducts and identifying DNA repair mechanisms involved in their removal.
Non-smokers from all three ethnic groups excreted low, but detectable levels of urinary EB–GII adducts (Table 2). These levels did not vary by racial/ethnic group. Although tobacco smoke is one of the major sources of BD exposure, lower levels of BD are present in automobile exhaust, wood burning smoke and urban air (4–7). Furthermore, in addition to DNA adducts forming from these environmental exposures to BD, EB–GII adducts may form endogenously. The contributions of endogenous EB–GII adducts to the overall adduct load are being examined in our ongoing laboratory animal studies utilizing stable isotope-labeling experiments to distinguish between endogenous and exogenous adducts. Additional analyses in cell culture are being conducted to identify potential metabolic and dietary sources of endogenous BD–DNA adducts.
Unlike EB–mercapturic acids (MHBMA) (34), urinary EB–GII levels in smokers were not associated with GSTT1 gene deletion (Table 3). Conjugation of butadiene epoxides to glutathione through GSTT1 is a major metabolic detoxification pathway for EB, and previous studies reported that GSTT1 gene deletion partially explains ethnic differences in butadiene metabolite excretion (29,34). In an earlier study of Japanese Americans, whites and Native Hawaiian smokers, GSTT1 gene deletion was significantly associated with MHBMA levels (P < 0.0001) (34). Another study among African American, white and Native Hawaiian smokers utilized a genome wide association to identify genetic determinants of BD metabolism and found that GSTT1 gene deletion explained 7.3% of the variability in MHBMA levels (29). The observed lack of correlation between GSTT1 status and urinary EB–GII adduct excretion can be explained by the greater influences of other factors such as DNA repair and nucleotide metabolism (see below).
Additionally, urinary EB–GII levels in current smokers were not influenced by variation in CYP2A6 enzymatic activity (Table 4). CYP2A6 enzymatic activity is associated with lung cancer risk (59) and is partially responsible for the epoxidation of butadiene (14). CYP2A6 enzymatic activity is highest among whites, followed by Native Hawaiians and lowest in Japanese Americans (60). The observed lack of correlation between urinary EB–GII and GSTT1 gene deletion or CYP2A6 enzymatic activity ratio is not surprising because CYP2E1 plays a much more important role in metabolism of BD, and polymorphisms in the CYP2E1 gene are less common (14,61). Furthermore, other genetic factors such as polymorphisms in DNA repair genes might have a stronger influence on urinary EB–GII adduct levels. For example, our cell culture studies revealed that NEIL1 glycosylase plays a role in the removal of EB–GII adducts via the base excision repair pathway (52). In mouse embryonic fibroblasts deficient in base excision repair protein NEIL1−/−, EB–GII adduct levels were nearly 3-fold higher than in the isogenic strain (NEIL1+/+) (52). A genome wide association study for the three ethnic groups is now in progress to identify additional genes that may be contributing to the racial/ethnic differences observed in urinary EB−GII.
Urinary levels of butadiene metabolites and butadiene-DNA adducts represent total BD exposure and the biologically relevant dose of butadiene bound to DNA, respectively. We found that BD metabolite DHBMA levels were significantly associated with urinary EB−GII adduct levels, whereas MHBMA levels were not associated with urinary EB–GII adduct levels if values were adjusted to smoking levels as defined by NE (Table 5). Our earlier study observed no association between GSTT1 gene deletion and DHBMA in Native Hawaiians, whites and Japanese American smokers (34). It should be noted that although DHBMA levels correlate with occupational exposure to BD (62), they do not decrease significantly upon smoking cessation (31) and are only 1.4-fold higher in smokers when compared with non-smokers (63). Therefore, human exposure to BD in cigarette smoke does not fully explain DHBMA levels, although the latter is significantly associated with urinary EB–GII adducts. Unlike DHBMA, MHBMA is strongly affected by smoking status as revealed in a smoking cessation study (31). The observed lack of correlation between BD–mercapturic acids and urinary BD–DNA adducts indicates that they are influenced by different genetic factors and provide distinct information in population studies.
The main limitation of our study is the use of urinary adducts rather than adducts in genomic DNA to determine biologically relevant dose of BD bound to DNA. Although our mass spectrometry methods for detection and quantitation of DNA adducts can be applied to genomic DNA, only urine samples were available in the present study. Unlike genomic EB–GII adducts quantified in blood or oral DNA, urinary EB–GII adduct levels represent the amount of DNA lesions that are removed from the DNA backbone, either through active repair or via spontaneous hydrolysis. Therefore, urinary EB–GII adduct levels can be affected by the efficiency of EB–GII DNA adduct repair and their further metabolism, potentially leading to the lack of association between urinary EB–GII adduct levels and MHBMA, GSTT1 gene deletion and CYP2A6 activity. We are currently developing a method for the quantification of EB–GII in oral DNA to investigate genomic levels of EB–GII in smokers.
In conclusion, we found that urinary EB–GII adduct levels are greater in smokers than non-smokers across all racial/ethnic groups and, among smokers, Japanese Americans had the highest urinary adduct levels. These findings warrant further investigation to quantify EB–GII adducts in genomic DNA and urine samples in the same smokers to investigate the relationship between excreted and persistent EB–GII adducts. Additional ongoing studies will utilize a genome wide association study to elucidate the role of DNA repair in EB–GII removal and to identify the potential genetic polymorphisms in DNA repair genes that could affect urinary EB–GII adduct levels.
Supplementary Material
bgab020_suppl_Supporting_Information
Glossary
Abbreviations
-
BD
1,3-butadiene
BMI
body mass index
CI
confidence interval
CYP
cytochrome P450 monooxygenases
DHBMA
dihydroxybutyl mercapturic acid
EB
3,4-epoxy-1-butene
GSTT1
glutathione S-transferase theta 1
HPLC
high-performance liquid chromatography
LC–MS
liquid chromatography mass spectrometry
MHBMA
monohydroxybutenyl mercapturic acid
NE
nicotine equivalents
Funding
This work was supported the National Cancer Institute (P01-CA-138338). Mass spectrometry was carried out in the Analytical Biochemistry Shared Resource of the Masonic Cancer Center, supported in part by Cancer Center Support Grant P30-CA-077598.
Conflict of Interest Statement: None declared.
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Supplementary Materials
bgab020_suppl_Supporting_Information