The modifying effect of CYP2E1, GST, and mEH genotypes on the formation of hemoglobin adducts of acrylamide and glycidamide in workers exposed to acrylamide

Toxicology Letters 215 (2012) 92–99

Contents lists available at SciVerse ScienceDirect

Toxicology Letters journal homepage: www.elsevier.com/locate/toxlet

The modifying effect of CYP2E1, GST, and mEH genotypes on the formation of hemoglobin adducts of acrylamide and glycidamide in workers exposed to acrylamide夽 Yu-Fang Huang a,b , Su-Yin Chiang c , Saou-Hsing Liou b , Mei-Lien Chen d , Ming-Feng Chen b , Shi-Nian Uang e , Kuen-Yuh Wu a,∗ a

Institute of Occupational Medicine and Industrial Hygiene, National Taiwan University, College of Public Health, Taipei, Taiwan Division of Environmental Health and Occupational Medicine, National Health Research Institutes, Miaoli County, Taiwan c School of Chinese Medicine, China Medical University, Taichung, Taiwan d Institute of Environmental and Occupational Health Sciences, National Yang Ming University, Taipei, Taiwan e Division of Analytical Chemistry, Institute of Occupational Safety and Health, Council of Labor Affairs, Executive Yuan, Taiwan b

h i g h l i g h t s  Simultaneous analysis hemoglobin adducts of acrylamide and glycidamide with LC/MS/MS.  AA-Hb and GA-Hb levels in exposed workers significantly greater than those in the non-exposed.  Genetic polymorphisms of mEH associated with the formation of AA- and GA-Hb in the exposed workers.

a r t i c l e

i n f o

Article history: Received 25 June 2011 Received in revised form 11 September 2012 Accepted 5 October 2012 Available online 13 October 2012 Keywords: Acrylamide Hemoglobin adducts Genetic polymorphisms Cytochrome P450 2E1 Microsomal epoxide hydrolase Glutathione transferases

a b s t r a c t This study assesses the association of acrylamide (AA) and glycidamide (GA) hemoglobin adducts (AAVal and GAVal) and their ratios with genetic polymorphisms of the metabolic enzymes cytochrome P450 2E1 (CYP2E1), exon 3 and 4 of microsomal epoxide hydrolase (mEH3 and mEH4), glutathione transferase theta (GSTT1), and mu (GSTM1) or/and the combinations of these polymorphisms, involved in the activation and detoxification of AA in humans. Fifty-one AA-exposed workers and 34 controls were recruited and provided a post-shift blood sample. AAVal and GAVal were determined simultaneously using isotopedilution liquid chromatography-electronspray ionization/tandem mass spectrometry (LC-ESI–MS/MS). Genetic polymorphisms of CYP2E1, mEH3 and 4, GSTT1, and GSTM1 were also analyzed. Our results reveal that the GAVal/AAVal ratio, potentially reflecting the proportion of AA metabolized to GA, ranged from 0.13 to 0.45 with a mean at 0.27. Multivariate regression analysis demonstrates that the joint effect of CYP2E1, GSTM1, and mEH4 genotypes was significantly associated with AAVal and GAVal levels after adjustment for AA exposures. These results suggest that mEH4 and the combined genotypes of CYP2E1, GSTM1 and mEH4 may be associated with the formation of AAVal and GAVal. Further studies may be needed to shed light on the roles that phase I and II enzymes play in AA metabolism. © 2012 Elsevier Ireland Ltd. All rights reserved.

1. Introduction Acrylamide (AA) is an important industrial chemical widely used in the production of polyacrylamide and as an intermediate reagent

夽 Grant support: Division of Environmental Health and Occupational Medicine, National Health Research Institute Grant EO-PP-95-02, National Science Council NSC Grant 95-2314-B-400-004-MY3, and Institute of Occupational Safety and Health Grant IOSH97-A313, Taiwan. ∗ Corresponding author at: Institute of Occupational Medicine and Industrial Hygiene, National Taiwan University, Rm 721, No. 17 Shiujou Rd., Taipei 100, Taiwan. Tel.: +886 2 33668091; fax: +886 2 33668267. E-mail addresses: [email protected], [email protected] (K.-Y. Wu). 0378-4274/$ – see front matter © 2012 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.toxlet.2012.10.003

in a variety of reactions of chemical synthesis (IARC, 1994; NSC, 2006). AA is also present in tobacco smoke (Smith et al., 2000) and baked and fried carbohydrate-riched foods (Tareke et al., 2002). AA has been shown to cause neurotoxic, genotoxic, and reproductive effects to animals (IARC, 1994; Smith and Oehme, 1991), and neurotoxic effects to the exposed workers (Calleman et al., 1994; Hagmar et al., 2001; Kjuus et al., 2004). AA has been shown to induce significantly increased incidences of thyroid follicular cell tumors, scrotal sac mesotheliomas, mammary gland fibroadenomas, and lung adenomas to rodents, depending on routes of treatment (Bull et al., 1984; Johnson et al., 1986; Friedman et al., 1995). In humans, dietary AA intake in one study was found significantly associated with the risk of postmenopausal endometrial and ovarian cancers

Y.-F. Huang et al. / Toxicology Letters 215 (2012) 92–99

but not with breast cancer (Hogervorst et al., 2007). However, several epidemiological studies have been conducted, and in most of these no increased cancer incidence has been observed (Hogervorst et al., 2010). AA is classified as a probable human carcinogen by International Agency for Research on Cancer (IARC, 1994) and characterized as “likely to be carcinogenic to humans” (US EPA, 2010). Exposures to AA in workplaces and daily ingestion of AA from consumption of foods processed at high temperatures have been of great concerns. Upon absorption, AA can be metabolically activated by cytochrome P450 2E1 (CYP2E1) to glycidamide (GA) in animals and humans (Sumner et al., 1999; Ghanayem et al., 2005; Settels et al., 2008). GA is considered the active species mainly responsible for AA carcinogenicity (Doerge et al., 2005; Rice, 2005; Tareke et al., 2006). Both AA and GA can be detoxified by glutathione transferases (GSTs) to form glutathione conjugates and further metabolized to mercapturic acids (MAs), N-acetyl-S-(2-carbamoylethyl)-cysteine (AAMA), N-acetyl-S-(1carbamoyl-2-hydroxyethyl)-cysteine (GAMA2), and N-acetyl-S-(3amino-2-hydroxy-3-oxopropyl)-cysteine (GAMA3) (Sumner et al., 1992, 1997). AAMA can be oxidized to AAMA-sulfoxide (Fennell et al., 2005, 2006; Kopp and Dekant, 2009). GA can also be detoxified by microsomal epoxide hydrolase (mEH) to glyceramide (Kirman et al., 2003) and can be detected in humans in urine for the first time (Hartmann et al., 2011). Both AA and GA are also alkylating agents and can interact with valine of hemoglobin (Hb) to form N-(2-carbamoylethyl)valine (AAVal) and N-(2-carbamoyl-2hydroxyethyl)valine (GAVal). Both adducts in the blood of animals and humans were processed with the modified Edman degradation and analyzed with gas chromatography coupled with mass spectrometry (GC/MS) (Bergmark et al., 1993; Schettgen et al., 2004; Jones et al., 2006), tandem mass spectrometry (GC–MS/MS) (Paulsson et al., 2003; Schettgen et al., 2010), or liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) (Bjellaas et al., 2007; Chevolleau et al., 2007; Fennell et al., 2003; Stedingk et al., 2010; Vesper et al., 2006). Analysis of these adducts has been recommended as biomarkers for cumulative AA exposures. Since CYP2E1, GSTs, and mEH are involved in AA metabolism, genetic polymorphisms of these enzymes may predetermine their metabolic activity and affect the susceptibility of individuals to AA exposure. Recently, we reported the association between urinary AA metabolites with genetic polymorphisms of GSTM1 and mEH in 51 workers exposed to AA and high interindividual differences in metabolic activation of AA to GA (Huang et al., 2011). These results are consistent with a previous study that the GA-Hb/AA-Hb ratios for 43 subjects from dietary intake of AA were related to polymorphic differences in genes coding of metabolizing enzymes in exon 4 of mEH (mEH4), GSTM1, and GSTT1 (Duale et al., 2009). Similar study has not been reported on the gene-environment interactions by using AA- and GA-Hb adducts (AAVal and GAVal) as biomarkers for AA-exposed workers, whose exposures would be better characterized. Therefore, the objective of this study was to investigate the potential modification on the formation of AAVal and GAVal by genetic polymorphisms of CYP2E1, exon 3 of mEH (mEH3) and mEH4, GSTT1, and GSTM1 or/and by the combinations of them for the AA-exposed workers. 2. Materials and methods 2.1. Chemicals Acrylamide (>99.9%) and l-valine (>98.0%) were purchased from Sigma (St. Louis, MO, USA); 13 C3 -labeled AA (>99.0%) and 13 C5 15 N-labeled l-valine (>98.0%) from Cambridge Isotopes (Cambridge, MA, USA); both GA (>98.0%) and 13 C3 -labeled GA (>98.0%) from Toronto Research Chemicals Inc. (North York, Ontario, Canada); phenylisothiocyanate (PTH) (>99.0%) from Sigma–Aldrich (St. Louis, MO, USA). All other solvents were of HPLC grade and Milli-Q water was used throughout. The

93

AAVal-PTH, 13 C5 15 N-AAVal-PTH, GAVal-PTH, and 13 C5 15 N-GAVal-PTH were synthesized according to previously published procedures (Chevolleau et al., 2007). The synthesized chemicals were characterized by nuclear magnetic resonance (NMR) and LC–MS/MS, and their corresponding 13 C5 15 N-labeled standards were characterized by LC–MS/MS. 2.2. Subjects and sample collection This study was approved by the Ethics Committee of the National Health Research Institutes, Taiwan. Details of the study population have been described previously (Huang et al., 2011). In brief, the exposed group was comprised of 51 workers directly exposed to AA, and the control group was comprised of 34 administrative staffs. The information regarding age, gender, weight, height, smoking status, alcohol consumption, dietary status of 3 months before blood collection, and history of occupational exposure were collected by using questionnaires. After informed consent was obtained, post-shift blood samples were collected for each subject. 2.3. Personal monitoring of AA exposure and analysis Personal samples were collected to monitor the exposure to AA for the 51 workers in a full work shift between October 2006 and August 2007. Details of the AA sampling and analysis were described in our previous report (Wu et al., 2010). Briefly, airborne AA was collected using a sampling train that consisted of a 13 mm glass fiber and a standard (75/150) silica gel tube and was connected to a personal sampling pump. AA was analyzed using isotope-dilution gas chromatography–mass spectrometry in selected ion monitoring (SIM) mode. The personal exposure levels in workers ranged from 0.00437 ␮g/m3 to 113.61 ␮g/m3 with a mean of 15.36 ␮g/m3 . 2.4. Isolation of globin and quantification of hemoglobin adducts Whole blood was collected with EDTA-coated tubes and centrifuged for 10 min; serum, buffy coat, and red blood cells were separated. The erythrocytes were washed three times with 1 volume of 0.9% NaCl solution. Hemolysis was achieved by the addition of 1 volume of deionized water and stored at −80 ◦ C. Globin was isolated as described previously (Mowrer et al., 1986). In brief, 2 mL of hemolysate were added to 12 mL of 50 mM hydrochloric acid in 2-propanol. The samples were shaken vigorously and centrifuged at 3500 × g for 10 min. Eight milliliters of ethyl acetate was slowly added to the supernatant and the solution was kept at 4 ◦ C for 3 h. After centrifugation, the precipitated globin was washed two times with 5 mL ethyl acetate and 5 mL n-hexane and finally evaporated to dryness in a vacuum desiccator. Globin was stored at −80 ◦ C until used for analysis. AAVal and GAVal was analyzed with LC–MS/MS by referring to a previously reported method (Chevolleau et al., 2007), which includes a modified Edman degradation described by Fennell et al. (2003). Briefly, 20 mg of human globin were dissolved in 1.5 mL of formamide. Five microliter of NaOH (1 M) and 15 ␮L of PTH were added to the sample solution. The samples were gently rotated overnight at 37 ◦ C, and finally heated at 45 ◦ C for 1.5 h in a water bath. 13 C5 15 N-AAVal-PTH and 13 C5 15 N-GAVal-PTH were added to serve as internal standards (ISs) at levels of 502 pg and 648 pg. The samples were added with 2 mL of water and subsequently extracted twice with 4 mL tert-butyl methyl ether. The combined organic phases were evaporated to dryness in a Speed Vac. Then, the samples were raised with 2 mL of water and loaded into an Oasis HLB SPE cartridge (60 mg, 3 mL; Waters, Milford, MA) preconditioned with 2 mL of methanol and 2 mL of water, washed with 5 mL of water, and eluted with 5 mL methanol. The organic fraction was dried and dissolved in 200 ␮L of 50% methanol containing 0.1% formic acid. Supernatant (20 ␮L) was then injected for analysis. The API 3000 LC–MS/MS system was equipped with a Perkin-Elmer 200 binary pump, a degasser, and an autosampler. The column was a Purosphere Star C18 (55 mm × 4.0 mm, 3 ␮m) (Merck, Darmstadt, Germany), with a guard column. The flow rate of mobile phase was 1 mL/min and split with 25% delivered to the MS/MS. The mobile phases consisted of 0.2% acetic acid in water (A) and methanol (B). The initial conditions was set at 30% of B from 0 to 3 min, followed by a linear gradient from 30 to 50% of B between 3 and 10 min, then from 50 to 100% of B between 10 and 12 min, followed by isocratic conditions at 100% of B between 12.1 and 15 min. The MS/MS was operated under positive ion and multiple reaction mode (MRM). The ion pairs monitored for quantitation were m/z 306 → 289 for AAVal-PTH, m/z 312 → 295 for 13 C5 15 N-AAVal-PTH, m/z 322 → 305 for GAVal-PTH and m/z 328 → 311 for 13 C5 15 N-GAVal-PTH. Calibration curves were established using standards spiked in 50% methanol with concentrations ranging from 1 to 300 pg/␮L for AAVal-PTH and 1 to 100 pg/␮L for GAVal-PTH. Linear calibration curves were obtained by plotting the quotients of peak areas of AAVal-PTH or GAVal-PTH to their corresponding 13 C5 15 N-labeled ISs vs the concentrations of the standard solutions. Both correlation coefficients of these calibration curves for AAVal-PTH and GAVal-PTH exceeded 0.997. Detection limits for this method were 3.3 pg (5.5 pmol/g globin) and 3.0 pg (5.2 pmol/g globin) on-column for AAVal-PTH and GAVal-PTH, respectively. The accuracy was determined by repeated analysis of three calibration standard solutions. The accuracy range was 95.0–106.1% and the precision represented with relative standard deviation (RSD) was <3.0%. 2.5. DNA extraction and genotyping Genomic DNA was isolated from 100 ␮L of buffy coat using the PuregeneTM DNA purification kit (Gentra systems, Minneapolis, USA) by following the

94

Y.-F. Huang et al. / Toxicology Letters 215 (2012) 92–99

Table 1 AA- and GA-Hb adducts levels in this study. GA-Hb/AA-Hb

n* > LOD

GM (GSD)

Range

nb > LODa

GM (GSD)

Range

22

0.27 ± 0.07 (0.13–0.45) 0.27 ± 0.08 (0.13–0.45) 0.28 ± 0.06 (0.19–0.36)

51

316.3 (4.0) 357.3 (4.0) 275.9 (3.9)

54.9–7416.4

22

28.3–2010.1

80.1–7416.4

12

54.9–6513.6

10

294.8 (3.6) 308.8 (3.8) 278.9 (3.5)

0

–

34

13.5–113.4

0

<5.2

<5.2

Smoker (n = 4)

0

–

4

52.2–81.7

0

<5.2

<5.2

Non-smoker (n = 30)

0

–

30

49.2 (1.6) 67.1 (1.3) 47.2 (1.6)

13.5–113.4

0

<5.2

<5.2

Smoker (n = 27)

12

Non-smoker (n = 24)

10

Control Total (n = 34)

a

GA-Hb (pmol/g globin)

Mean ± SD (range)

Exposed Total (n = 51)

b

AA-Hb (pmol/g globin)

n* > LOD

27 24

28.3–1659.4 37.1–2010.1

LOD: the limit of detection (below 5.2 pmol/g globin). The numbers of blood samples were positively detected for AA- and GA-Hb adducts.

manufacturer’s instructions. CYP2E1, mEH3 and 4, GSTM1, and GSTT1 polymorphisms were all analyzed in our previous study (Huang et al., 2011). Subjects were classified into three groups according to the expected mEH enzyme activity (Sarmanova et al., 2000). The carriers with combinations of His/His-His/His, His/His-His/Arg, Tyr/HisHis/His, and His/His-Arg/Arg were classified as low mEH activity; combinations of Tyr/Tyr-His/His, Tyr/His-His/Arg, and Tyr/His-Arg/Arg were classified as medium activity, and combinations of Tyr/Tyr-Arg/Arg and Tyr/Tyr-His/Arg were classified as high activity. For quality control, 10% of the samples were genotyped twice and the consistency of results was 100%. 2.6. Statistical analysis The AA- and GA-Hb levels were natural-logarithm transformed before statistical analysis. The Mann–Whitney U test was used to compare differences between study groups (exposed vs nonexposed workers) in AA- and GA-Hb levels. Correlations between personal AA exposure level, smoking status, or preference for fried food and AA- and GA-Hb levels were evaluated with the Spearman correlation coefficients. The Kruskal–Wallis test was used to testify the differences between polymorphic genotypes or/and combinations of these polymorphisms and Hb adducts levels. Multivariate regression analyses were used to analyze AA- and GA-Hb levels and the GA-Hb/AA-Hb ratios as the dependent variables to adjust for covariates such as personal AA exposures, smoking status, preferred fried-food, and polymorphic genotypes. To explore the relationships between AA exposures, genotypes and Hb adducts, for GA-Hb level below the detection limit, the content was designated as one-half of the limit of detection (LOD). All p-values were two-sided. Statistical analyses were conducted using the Statistical Package for the Social Sciences (SPSS) version 11.0 (SPSS Inc., Chicago, IL, USA).

3. Results 3.1. General demographic data The demographic information and the overall distribution of CYP2E1, mEH3 and 4, GSTT1, and GSTM1 genotypes for our study population were described in detail previously (Huang et al., 2011). In brief, the distributions of age, body mass index (BMI), working years, alcohol consumption, and preference for fried-food did not differ significantly between exposed and the control groups, except gender and smoking status did. The frequency of our study subjects with CYP2E1, mEH4, GSTM1, and GSTT1 allele are similar to those reported elsewhere for Taiwanese and Chinese populations, except for mEH3 (Stephens et al., 1994; Hildesheim et al., 1995; Lin et al., 2000; Yin et al., 2001; Lei et al., 2002; Wu et al., 2002). 3.2. Analysis of AA- and GA-Hb adducts in exposed workers and controls An LC–MS/MS method was successfully established to simultaneously analyze AA- and GA-Hb adducts in blood samples collected from our study subjects. Fig. 1 shows representative chromatograms generated from analysis of AA- and GA-Hb adducts in

an exposed sample. Analysis of all samples shows that AAVal and GAVal were detectable in 51 and 22 of exposed samples, 34 of the control samples for AAVal while GAVal was all below LODs in the control samples. The natural-logarithm adducts levels showed skewed patterns with AAVal levels having maximal frequency at 2.01 and 2.17 (103.2 and 146.7 pmol/g globin) and GAVal levels having maximal at <5.2 pmol/g globin in the exposed group (Fig. 2). Data are summarized in Table 1 with detectable numbers of AAVal and GAVal, and their geometric mean (GM) and ranges of AAexposed workers and controls. The GM (range) of AAVal levels for AA-exposed workers was 316.3 (54.9–7416.4) pmol/g globin, and that of GAVal levels were 294.8 (28.3–2010.1) pmol/g globin, which appeared significantly greater than 49.2 (13.5–113.4) pmol/g and <5.2 pmol/g globin for controls (p < 0.001). The mean GAVal/AAVal ratio, which potentially representing the proportion of AA metabolized to GA, was 0.27 (range, 0.13–0.45) in the exposed group. 3.3. Association between genotypes and Hb adducts The GAVal/AAVal ratios, AAVal levels, and GAVal levels were stratified by CYP2E1, mEH3 and 4, mEH activity, and GST genotypes, as shown in Table 2. Both the GAVal/AAVal ratios and the GAVal levels of the exposed workers with the Tyr/His genotype of mEH3 significantly exceeded those of workers with the Tyr/Tyr and the His/His genotypes. The GAVal/AAVal ratios, AAVal levels, and GAVal levels of the exposed workers with the His/Arg genotype of mEH4 significantly exceeded those of workers with the His/His genotype. For the GSTM1 genotype, the GAVal/AAVal ratio, the AAVal level, and the GAVal level differed significantly between subjects with positive and deficient genotypes. The joint effect of genetic polymorphisms of CYP2E1, GSTM1, GSTT1, and mEH genotypes in relation to the GAVal/AAVal ratios, AAVal, and GAVal levels were also analyzed and summarized in Table 3. There were significant associations of the combination of CYP2E1 (c1/c1) and GSTM1deficient with the AAVal levels, which mean that individuals with these combined genotypes had significantly lower levels of AAVal when compared with those who did not carry these genotypes. The combined CYP2E1 (c1/c1), GSTM1-deficient, and mEH4 (His/His) genotypes were also significantly associated with the decreased levels of AAVal and GAVal. 3.4. Association between AA exposures and Hb adducts The association of AA- and GA-Hb levels with AA exposures (personal AA exposures), smoking status, and preferred

Y.-F. Huang et al. / Toxicology Letters 215 (2012) 92–99

95

Table 2 Blood GA-Hb/AA-Hb ratio, AA-Hb, and GA-Hb adducts levels stratified by genotype polymorphism. Genotype CYP2E1 C1/C1 C1/C2 C2/C2 p mEH3a (Tyr113His) Tyr/Tyr Tyr/His His/His p mEH4a (His139Arg) His/His His/Arg p mEH activity Low Median High p GSTM1 Deficient Positive p GSTT1 Deficient Positive p

n

AA (mg/m3 ) Mean ± SD

GA-Hb/AA-Hb Mean ± SD

27 22 2

0.033 ± 0.108 0.022 ± 0.031 0.008 ± 0.011

0.12 ± 0.14 0.14 ± 0.13 0.17 ± 0.20 0.665

43 5 3

0.029 ± 0.088 0.019 ± 0.008 0.011 ± 0.002

0.11 ± 0.13 0.28 ± 0.04 0.14 ± 0.19 0.043*

276.84 (3.73) 1086.33 (4.08) 273.56 (5.22) 0.127

14.82 (11.12) 299.84 (4.61) 16.31 (24.06) 0.038*

44 7

0.029 ± 0.087 0.015 ± 0.011

0.11 ± 0.12 0.25 ± 0.13 0.023*

270.01 (3.89) 855.56 (3.03) 0.037*

14.27 (11.35) 167.94 (7.22) 0.021*

5 42 4

0.012 ± 0.002 0.030 ± 0.088 0.007 ± 0.005

0.19 ± 0.16 0.12 ± 0.02 0.17 ± 0.09 0.251

472.15 (6.59) 279.24 (3.72) 710.06 (3.94) 0.420

50.35 (21.57) 15.33 (11.14) 103.76 (13.16) 0.226

27 24

0.003 ± 0.005 0.050 ± 0.109

0.09 ± 0.13 0.18 ± 0.12 0.030*

197.21 (3.20) 538.24 (4.16) 0.009*

5.75 (8.78) 58.17 (11.75) 0.004*

25 26

0.016 ± 0.026 0.039 ± 0.115

0.14 ± 0.15 0.12 ± 0.12 0.925

353.71 (3.84) 284.10 (4.14) 0.522

22.48 (13.23) 17.89 (11.89) 0.786

AA-Hb (pmol/g globin) GM (GSD)

GA-Hb (pmol/g globin) GM (GSD)

285.94 (4.03) 332.15 (3.49) 722.55 (22.41) 0.783

16.51 (12.60) 22.55 (10.96) 72.29 (110.23) 0.680

For GA-Hb level below the limit of detection (LOD, 5.2 pmol/g globin), the content was designated as 1/2 LOD. a Exon 3 of mEH: mEH3; exon 4 of mEH: mEH4. * p < 0.05. Table 3 Association of combined genotypes and blood GA-Hb/AA-Hb ratio, AA-Hb, and GA-Hb adducts levels. Joint effects

n

CYP2E1 and GSTM1 Reference CYP2E1(c1/c1) + GSTM1-deficient p CYP2E1 and GSTT1 Reference CYP2E1(c1/c1) + GSTT1-deficient p CYP2E1, GSTM1 and GSTT1 Reference CYP2E1(c1/c1) + GSTM1-deficient + GSTT1-deficient p CYP2E1, GSTM1 and Exon4 Reference CYP2E1(c1/c1) + GSTM1-deficient + mEH4 (His/His) p CYP2E1, GSTM1, Exin3 and Exon4 Reference CYP2E1(c1/c1) + GSTM1-deficient + mEH3 (Tyr/His + His/His) + mEH4(His/His) p

GA-Hb/AA-Hb

AA-Hb (pmol/g globin)

GA-Hb (pmol/g globin)

Mean ± SD

GM

GSD

GM

GSD

36 15

0.15 ± 0.13 0.09 ± 0.14 0.321

409.33 170.40

4.14 2.90 0.028*

30.81 7.10

12.89 8.26 0.058

38 13

0.12 ± 0.12 0.16 ± 0.16 0.713

292.09 399.32

4.03 3.85 0.424

17.80 28.19

11.69 15.04 0.615

45 6

0.12 ± 0.12 0.19 ± 0.19 0.431

309.51 372.40

4.04 3.72 0.700

18.79 32.07

12.06 16.74 0.658

38 13

0.16 ± 0.13 0.05 ± 0.09 0.054

426.02 132.49

4.06 2.36 0.005*

34.80 3.97

12.79 4.61 0.007*

48 3

0.13 ± 0.13 0.14 ± 0.19 0.836

319.21 273.56

3.96 5.22 0.777

20.27 16.31

12.18 24.06 0.925

For GA-Hb level below the limit of detection (LOD, 5.2 pmol/g globin), the content was designated as 1/2 LOD. * p < 0.05. Table 4 Spearman correlations in 51 AA-exposed workers.

a

8 h TWA AA Smoking Preferred fried-food AA-Hb GA-Hb

8 h TWA AA (mg/m3 )

Smoking

Preferred fried-food

AA-Hb (pmol/g globin)

GA-Hb (pmol/g globin)

1.000 −0.093 0.258 0.637** 0.789**

1.000 0.044 0.124 0.020

1.000 0.107 0.250

1.000 0.879**

1.000

For GA-Hb level below the limit of detection (LOD, 5.2 pmol/g globin), the content was designated as 1/2 LOD. a 8 h TWA AA: eight hour time-weighted average (TWA) AA. ** Correlation is significant at the 0.0001 level (2-tailed).

96

Y.-F. Huang et al. / Toxicology Letters 215 (2012) 92–99

Fig. 1. Representative LC–MS/MS chromatograms generated from analysis of AA- and GA-Hb adducts in a blood sample collected from an AA-exposed worker. AAValPTH, GAVal-PTH, and the 13 C5 15 N-labeled internal standards were monitored in the MRM by monitoring the following ion mass transitions as follows: (A) AAVal-PTH, m/z 306 → 289; (B) 13 C5 15 N-AAVal-PTH, m/z 312 → 295; (C) GAVal-PTH, m/z 322 → 305; (D) 13 C5 15 N-GAVal-PTH, m/z 328 → 311.

fried-food was analyzed using Spearman correlation coefficients. As shown in Table 4, there were significant correlations between exposures (8 h time-weighted average (TWA) AA level) and AAVal levels (r = 0.637, p < 0.0001) and GAVal levels (r = 0.789, p < 0.0001). There were insignificant correlations between AAVal (or GAVal) and self-reported smoking or preference for fried-food. Our results showed that the GMs (geometric standard deviation; GSD) of AAVal and GAVal levels in exposed smokers were 357.3 (4.0) pmol/g and 308.8 (3.8) pmol/g globin, which appeared insignificantly greater than 275.9 (3.9) pmol/g and 278.9 (3.5) pmol/g globin in nonsmoking workers.

3.5. Effects of genotypes and AA exposures on Hb adducts The results regarding to the effects between AAVal and GAVal and potential covariates such as personal AA exposure, genetic polymorphisms, joint effect of genotypes, and preference for friedfood as well as smoking status are shown in Table 5. Personal AA exposure (p = 0.001) and mEH4 (p = 0.02) were found to be significant predictors for AAVal levels after adjusting for potential confounding factors. AA exposures (p = 0.003) and mEH4 (p = 0.03) were also significant predictors for GAVal levels after adjustments for other factors. mEH4 (p = 0.02) was a significant predictor for the GAVal/AAVal ratio after adjustments for other factors

Y.-F. Huang et al. / Toxicology Letters 215 (2012) 92–99

97

Table 5 Multivariate regression analysis: predictors of blood AA-Hb, GA-Hb, and ratio of GA-Hb/AA-Hb in 51 AA-exposed workers. Predictors

(A) Intercept 8-h TWA AA (mg/m3 ) CYP2E1 (c1/c1 vs c1/c2 + c2/c2) GSTM1 (positive vs deficient) mEH4b (His/His vs His/Arg) Smoking (yes vs no) Preferred fried-food (yes vs no) (B) Intercept 8-h TWA AA (mg/m3 ) CYP2E1 + GSTM1 + mEH4a Smoking (yes vs no) Preferred fried-food (yes vs no)

GA-Hb/AA-Hb

Log AA-Hb (pmol/g globin)

Log GA-Hb (pmol/g globin)

B

SE

p-Value

B

SE

p-Value

B

SE

p-Value

0.18 0.36 −0.02 0.05 −0.12 −0.01 0.05

0.07 0.24 0.04 0.04 0.06 0.04 0.03

0.02* 0.14 0.69 0.20 0.04* 0.72 0.10

2.90 3.77 −0.17 0.16 −0.58 0.06 −0.003

0.31 0.99 0.16 0.16 0.24 0.16 0.13

<0.001* 0.001* 0.30 0.34 0.02* 0.71 0.98

1.80 5.59 −0.22 0.44 −0.99 −0.06 0.24

0.56 1.79 0.29 0.29 0.43 0.28 0.23

0.003* 0.003* 0.45 0.15 0.03* 0.83 0.31

0.04 0.35 0.08 −0.03 0.06

0.04 0.23 0.04 0.04 0.03

0.31 0.14 0.08 0.42 0.07

2.11 3.49 0.39 −0.03 0.04

0.17 0.97 0.19 0.16 0.13

<0.001* 0.001* 0.04* 0.86 0.78

0.55 5.44 0.69 −0.19 0.29

0.31 1.78 0.34 0.29 0.23

0.08 0.004* 0.05* 0.51 0.22

For GA-Hb level below the limit of detection (LOD, 5.2 pmol/g globin), the content was designated as 1/2 LOD. a CYP2E1(c1/c1) + GSTM1-deficient + mEH4 (His/His) vs CYP2E1(c1/c2 + c2/c2) + GSTM1-positive + mEH4 (His/Arg). b Exon 4 of mEH: mEH4. * p < 0.05.

(Table 5A). Furthermore, as shown in Table 5B, we also found significant associations between the triple combination CYP2E1 (c1/c1), GSTM1-deficient, and mEH4 (His/His) with the AAVal (p = 0.04) and GAVal (p = 0.05) levels. However, the given combination of genotypes was marginally associated with the GAVal/AAVal ratio (p = 0.08). 4. Discussion Several LC–MS/MS methods have been developed to quantify AAVal and GAVal (Bjellaas et al., 2007; Chevolleau et al., 2007; Fennell et al., 2003; Stedingk et al., 2010; Vesper et al., 2006). Compared with their LODs in the range from 0.2 to 3 pmol/g globin for AAVal, and from 0.4 to 7 pmol/g globin for GAVal, our method with LODs at 5.5 pmol/g globin for AAVal, and 5.2 pmol/g globin for GAVal is comparable with the previous method. Only 45% of the exposed samples with detectable GAVal levels suggested that AA exposures for most of our study subjects were relatively low. These observations are consistent with their personal exposure data with a mean at 15.4 ␮g/m3 and only 17.6% of the personal exposure were greater than the current TWA at 30 ␮g/m3 (Wu et al., 2010). Most studies had investigated AAVal and GAVal levels in animal (Chevolleau et al., 2007; Fennell et al., 2003; Sumner et al., 2003) and humans exposed to AA through food consumption and tobacco smoke (Bergmark et al., 1997; Bjellaas et al., 2007; Chevolleau et al., 2007; Duale et al., 2009; Schettgen et al., 2004; Urban et al., 2006; Vesper et al., 2010) as well as with occupational exposures (Bergmark et al., 1993, 1997; Hagmar et al., 2001; Jones et al., 2006; Perez et al., 1999). Results from this study show that the GMs of AAVal and GAVal levels in exposed workers were 316.3 pmol/g and 294.8 pmol/g globin, and these values were significantly greater than those in the control group since GAVal was not detectable for all control samples (Table 1). The GM of AAVal and GAVal levels in our control group were consistent with previous studies, which reported the mean AAVal and GAVal levels in the range of 19–51 pmol/g and 17–51 pmol/g globin for nonsmokers, and 53–154 pmol/g and 34–93 pmol/g globin for smokers, respectively (Bergmark et al., 1997; Bjellaas et al., 2007; Chevolleau et al., 2007; Duale et al., 2009; Schettgen et al., 2004; Urban et al., 2006; Vesper et al., 2010). These results showed that AA occupational exposures could dominate the formation of AAVal and GAVal when compared with those contributed by tobacco smoke and consumption of high-temperature processed foods. Although several studies have reported that AAVal and GAVal levels in smokers were around 3–8

times and 2–5 times higher, respectively, than those of nonsmokers (Bergmark et al., 1997; Bjellaas et al., 2007; Chevolleau et al., 2007; Duale et al., 2009; Schettgen et al., 2004; Urban et al., 2006; Vesper et al., 2010), the effect of AA exposures from tobacco smoke on the formation of AAVal and GAVal could not be studied because the small sample size of smokers in the control group (Tables 4 and 5). In addition, analysis of data using both Spearman correlation and multivariate linear regression analyses showed that the airborne AA exposure was a dominant predictor of AAVal and GAVal levels after adjustments for other confounding variables (Tables 4 and 5); these results demonstrate that AAVal and GAVal could serve as biomarkers for cumulative AA exposures. In this study, personal AA exposures were assessed for the first time to explore gene–environment interactions by using AAVal and GAVal as biomarkers for the exposed workers. Since GA is the active metabolite of AA, the GAVal/AAVal ratio could be used as an indicator of the fraction of absorbed AA metabolized to GA, we analyzed the associations between genetic polymorphisms of CYP2E1, mEH 3 and 4, GSTM1, and GSTT1 with the GAVal/AAVal ratios, AAVal and GAVal levels. mEH4 and GSTM1 genotypes have significantly modified effects on the formation of AAVal and GAVal and the GAVal/AAVal ratios, and mEH3 was significantly associated with GAVal levels and GAVal/AAVal ratios (Table 2). Further multivariate regression analyses showed that only mEH4 was a significant predictor for the GAVal/AAVal ratios, AAVal and GAVal levels, but GSTM1 and mEH3 were not after adjustments for other covariates (Table 5A). Our results show that exposed workers with the mEH4 (His/His) genotype have significantly lower GAVal/AAVal ratios, AAVal and GAVal levels. This finding is in agreement with our recent study (Huang et al., 2011), where mEH4 genetic polymorphism was significantly modified the excretion of urinary GAMAs (the summation of GAMA2 and GAMA3) after adjustment for personal AA exposures. Although we did not observe the influence of CYP2E1, GSTM1 or GSTT1 on the formation of AAVal and GAVal, compared with the findings of Doroshyenko et al. (2009) and Duale et al. (2009), the lack of effect in CYP2E1 might be attributed to the fact that CYP2E1 probably accounts for one fourth of the primary AA metabolism in humans. Our results also revealed that the predicted mEH activity had insignificant effect on both adducts and might be explained by the fact that the relatively small sample size in the low and high mEH activity. An in vitro study reported that the polymorphisms in the GSTM1 or GSTT1 enzymes did not affect the levels of Hb adduct after exposure of human blood to AA and GA (Paulsson

98

Y.-F. Huang et al. / Toxicology Letters 215 (2012) 92–99

genotypes is assumed to cause an increased GA and GAVal level. Moreover, multivariate regression analyses also shows that the joint effect of CYP2E1 (c1/c1), GSTM1-deficient, and mEH4 (His/His) genotypes was a significant predictor for the AAVal and GAVal level after adjusting for confounding factors. These results indicate that the combination of CYP2E1, GSTM1, and mEH4 genetic polymorphisms may play important roles in metabolism of AA. Although this study was limited by the facts that the sample size was not large enough, and the activity of mEH enzymes was predicted without measurement, a very detailed AA exposure assessment for each study subject might have gained some advantages in statistical resolution power (Wu et al., 2010). We could still detect the potential modifying effects of mEH4 genetic polymorphism on the levels of AAVal and GAVal and the GAVal/AAVal ratio, and also the joint effect of CYP2E1, GSTM1, and mEH4 genotypes on the levels of AAVal and GAVal. In conclusion, this study explored the associations between AA exposures and genetic polymorphisms of some phase I and II genes or/and the combinations of these polymorphisms in the formation of AAVal and GAVal. Statistical analysis of data reveals that genetic polymorphism of mEH4 significantly influences the formation of AAVal and GAVal and the GAVal/AAVal ratio. There are also significant associations between combined CYP2E1, GSTM1, and mEH4 genotypes and the levels of AAVal and GAVal after adjustment for other covariates, such as smoking status, and preferred fried-food. Personal AA exposure is the dominant factor on the formation of both adducts. These observations are somewhat in concordance with the results of Duale et al. (2009). Further studies are needed to shed light on the mechanisms and the roles played by CYP2E1, mEH4 and GSTM1 on AA metabolisms in humans. Conflict of interest statement None. References

Fig. 2. Frequency distribution of AA- and GA-Hb adducts levels after logarithmic conversion in the exposed group.

et al., 2005). A previous study concluded that GSTP1, GSTM1, and GSTT1 enzymes played no major roles in the AA and GA conjugation with glutathione in humans (Doroshyenko et al., 2009). Because the AA is metabolized by phase I and II enzymes, the formation of AAVal and GAVal summarized the effects of metabolism and detoxification. We therefore assessed the influence of combined genetic polymorphisms of CYP2E1, GSTM1, GSTT1, mEH3 and 4 on the formation of AAVal and GAVal. Theoretically, an individual with a combination of the most efficient CYP2E1 genotype, the least efficient genotypes of GSTM1, GSTT1, and the least efficient genotype of mEH could lead to the maximum formation of GAVal given the same AA exposure. Results from this study show that individuals with double (CYP2E1 (c1/c1) and GSTM1-deficient) or triple (CYP2E1 (c1/c1), GSTM1-deficient and mEH4 (His/His)) genotypes had significantly decreased levels of AAVal and GAVal (Table 3). The decreased level of GAVal was unexpected because the combination of CYP2E1 (c1/c1), GSTM1-deficient, and mEH4 (His/His)

Bergmark, E., Calleman, C.J., He, F.S., Costa, L.G., 1993. Determination of hemoglobin adducts in humans occupationally exposed to acrylamide. Toxicology and Applied Pharmacology 120, 45–54. Bergmark, E., 1997. Haemoglobin adducts of acrylamide and acrylonitrile in laboratory workers, smokers and non-smokers. Chemical Research in Toxicology 10, 78–84. Bjellaas, T., Olesen, P.T., Frandsen, H., Haugen, M., Stolen, L.H., Paulsen, J.E., Alexander, J., Lundanes, E., Becher, G., 2007. Comparison of estimated dietary intake of acrylamide with hemoglobin adducts of acrylamide and glycidamide. Toxicological Sciences 98 (1), 110–117. Bull, R.J., Robinson, M., Laurie, R.D., Stoner, G.D., Greisiger, E., Meier, J.R., Stober, J., 1984. Carcinogenic effects of acrylamide in sencar and A/J mice. Cancer Research 44, 107–111. Calleman, C.J., Wu, Y., He, F., Tian, G., Bergmark, E., Zhang, S., Deng, H., Wang, Y., Crofton, K.M., Fennell, T., Costa, L.G., 1994. Relationships between biomarkers of exposure and neurological effects in a group of workers exposed to acrylamide. Toxicology and Applied Pharmacology 126 (2), 361–371. Chevolleau, S., Jacques, C., Canlet, C., Tulliez, J., Debrauwer, L., 2007. Analysis of hemoglobin adducts of acrylamide and glycidamide by liquid chromatographyelectronspray ionization tandem mass spectrometry, as exposure biomarkers in French population. Journal of Chromatography A 1167 (2), 125–134. Doerge, D.R., Young, J.F., McDaniel, P., Twaddle, N.C., Churchwell, M.I., 2005. Toxicokinetics of acrylamide and glycidamide in Fischer 344 rats. Toxicology and Applied Pharmacology 208, 199–209. Doroshyenko, O., Fuhr, U., Kunz, D., Frank, D., Kinzig, M., Jetter, A., Reith, Y., Lazar, A., Taubert, D., Kirchheiner, J., Baum, M., Eisenbrand, G., Berger, F.I., Bertow, D., Berkessel, A., Sorgel, F., Schomig, E., Tomalik-Scharte, D., 2009. In vivo role of cytochrome P450 2E1 and glutathione-S-transferase activity for acrylamide toxicokinetics in humans. Cancer Epidemiology, Biomarkers and Prevention 18 (2), 433–443. Duale, N., Bjellaas, T., Alexander, J., Becher, G., Haugen, M., Paulsen, J.E., Frandsen, H., Olesen, P.T., Brunborg, G., 2009. Biomarkers of human exposure to acrylamide and relation to polymorphisms in metabolizing genes. Toxicological Sciences 108 (1), 90–99. Fennell, T.R., Snyder, R.W., Krol, W.L., Sumner, S.C.J., 2003. Comparison of the hemoglobin adducts formed by administration of N-methylolacrylamide and acrylamide to rats. Toxicological Sciences 71, 164–175.

Y.-F. Huang et al. / Toxicology Letters 215 (2012) 92–99 Fennell, T.R., Sumner, S.C.J., Snyder, R.W., Burgess, J., Spicer, R., Bridson, W.E., Friedman, M.A., 2005. Metabolism and hemoglobin adduct formation of acrylamide in humans. Toxicological Sciences 85 (1), 447–459. Fennell, T.R., Sumner, S.C.J., Snyder, R.W., Burgess, J., Friedman, M.A., 2006. Kinetics of elimination of urinary metabolites of acrylamide in humans. Toxicological Sciences 93 (2), 256–267. Friedman, M.A., Dulak, L.H., Stedham, M.A., 1995. A lifetime oncogenicity study in rats with acrylamide. Fundamental and Applied Toxicology 27, 95–105. Ghanayem, B.I., McDaniel, L.P., Churchwell, M.I., Twaddle, N.C., Snyder, R., Fennell, T.R., Doerge, D.R., 2005. Role of CYP2E1 in the epoxidation of acrylamide to glycidamide and formation of DNA and hemoglobin adducts. Toxicological Sciences 88 (2), 311–318. Hagmar, L., Törnqvist, M., Nordaner, C., Rosen, I., Bruze, M., Kautianinen, A., Magnusson, A.L., Malmberg, B., Aprea, P., Granath, F., Axmon, A., 2001. Health effects of occupational exposure to acrylamide using haemoglobin adducts as biomarkers of internal dose. Scandinavian Journal of Work, Environment and Health 27 (4), 219–226. Hartmann, E.C., Latzin, J.M., Schindler, B.K., Koch, H.M., Angerer, J., 2011. Excretion of 2,3-dihydroxy-propionamide (OH-PA), the hydrolysis product of glycidamide, in human urine after single oral dose of deuterium-labeled acrylamide. Archives of Toxicology 85, 601–606. Hildesheim, A., Chen, C.J., Caporaso, N.E., Cheng, Y.J., Hoover, R.N., Hsu, M.M., Levine, P.H., Chen, I.H., Chen, J.Y., Yang, C.S., 1995. Cytochrome P4502E1 genetic polymorphisms and risk of nasopharyngeal carcinoma: results from a case–control study conducted in Taiwan. Cancer Epidemiology, Biomarkers and Prevention 4 (6), 607–610. Hogervorst, J.G., Schouten, L.J., Konings, E.J., Goldbohm, R.A., Brandt, P.A., 2007. A prospective study of dietary acrylamide intake and the risk of endometrial, ovarian, and breast cancer. Cancer Epidemiology, Biomarkers and Prevention 16 (11), 2304–2313. Hogervorst, J.G., Baars, B.J., Schouten, L.J., Konings, E.J., Goldbohm, R.A., van den Brandt, P.A., 2010. The carcinogenicity of dietary acrylamide intake: a comparative discussion of epidemiological and experimental animal research. Critical Reviews in Toxicology 40, 485–512. Huang, Y.F., Chen, M.L., Liou, S.H., Chen, M.F., Uang, S.N., Wu, K.Y., 2011. Association of CYP2E1, GST and mEH genetic polymorphisms with urinary acrylamide metabolites in workers exposed to acrylamide. Toxicology Letters 203 (2), 118–126. IARC, 1994. Acrylamide. In: IARC Monographs on the Evaluation of Carcinogen Risk to Humans: Some Industrial Chemicals, vol. 60. International Agency for Research on Cancer, Lyon, pp. 389–433. Johnson, K.A., Gorzinski, S.J., Bodner, K.M., Campbell, R.A., Wolf, C.H., Friedman, M.A., Mast, R.W., 1986. Chronic toxicity and oncogenicity study on acrylamide incorporated in the drinking water of Fischer 344 rats. Toxicology and Applied Pharmacology 85, 154–168. Jones, K., Garfitt, S., Emms, V., Warren, N., Cocker, J., Farmer, P., 2006. Correlation of haemoglobin-acrylamide adducts with airborne exposure: an occupational survey. Toxicology Letters 162, 174–180. Kjuus, H., Goffeng, L.O., Heier, M.S., Sjoholm, H., Ovrebo, S., Skaug, V., Paulsson, B., Törnqvist, M., Brudal, S., 2004. Effects on the peripheral nervous system of tunnel workers exposed to acrylamide and N-methylolacrylamide. Scandinavian Journal of Work, Environment and Health 30, 21–29. Kirman, C.R., Gargas, M.L., Deskin, R., Tonner-Navarro, L., Andersen, M.E., 2003. A physiologically based pharmacokinetic model for acrylamide and its metabolites, glycidamide, in the rat. Journal of Toxicology and Environmental Health: Part A 66 (3), 253–274. Kopp, E.K., Dekant, W., 2009. Toxicokinetics of acrylamide in rats and humans following single oral administration of low doses. Toxicology and Applied Pharmacology 235, 135–142. Lei, Y.C., Hwang, S.J., Chang, C.C., Kuo, H.W., Luo, J.C., Chang, M.J., Cheng, T.J., 2002. Effects on sister chromatid exchange frequency of polymorphisms in DNA repair gene XRCC1 in smokers. Mutation Research 519 (1–2), 93–101. Lin, P., Wang, S.L., Wang, H.J., Chen, K.W., Lee, H.S., Tsai, K.J., Chen, C.Y., Lee, H., 2000. Association of CYP1A1 and microsomal epoxide hydrolase polymorphisms with lung squamous cell carcinoma. British Journal of Cancer 82 (4), 852–857. Mowrer, J., Törnqvist, M., Jensen, S., Ehrenberg, L., 1986. Modified Edman degradation applied to hemoglobin for monitoring occupational exposure to alkylating agents. Toxicological and Environmental Chemistry 11, 215–231. NSC, 2006. Chemical Backgrounders Index: Acrylamide. Available at http:// www.environmentwriter.org/resources/backissues/chemicals/acrylamide.htm (accessed on 22 June 2009). Paulsson, B., Athanassiadis, I., Rydberg, P., Törnqvist, M., 2003. Hemoglobin adducts from glycidamide: acetonization of hydrophilic groups for reproducible gas chromatography/tandem mass spectrometric analysis. Rapid Communications in Mass Spectrometry 17, 1859–1865. Paulsson, B., Rannug, A., Henderson, A.P., Golding, B.T., Törnqvist, M., Warholm, M., 2005. In vitro studies of the influence of glutathione transferases and epoxide hydrolase on the detoxification of acrylamide and glycidamide in blood. Mutation Research 580 (1–2), 53–59.

99

Perez, M.L., Cheong, H.K., Yang, J.S., Osterman-Golkar, S., 1999. Simultaneous analysis of haemoglobin adducts of acrylamide and glycidamide by GC–MS. Analytical Biochemistry 274, 59–68. Rice, J.M., 2005. The carcinogenicity of acrylamide. Mutation Research 580 (1–2), 3–20. Sarmanova, J., Tynkova, L., Susova, S., Gut, I., Soucek, P., 2000. Genetic polymorphisms of biotransformation enzymes: allele frequencies in the population of the Czech Republic. Pharmacogenetics 10 (9), 781–788. Schettgen, T., Rossbach, B., Kutting, B., Letzel, S., Drexler, H., Angerer, J., 2004. Determination of haemoglobin adducts of acrylamide and glycidamide in smoking and non-smoking persons of the general population. International Journal of Hygiene and Environmental Health 207, 531–539. Schettgen, T., Müller, J., Fromme, H., Angerer, J., 2010. Simultaneous quantification of haemoglobin adducts of ethylene oxide, propylene oxide, acrylonitrile, acrylamide and glycidamide in human blood by isotope-dilution GC/NCI-MS/MS. Journal of Chromatography B 878 (27), 2467–2473. Settels, E., Bernauer, U., Palavinskas, R., Klaffke, H.S., Gundert-Remy, U., Appel, K.E., 2008. Human CYP2E1 mediates the formation of glycidamide from acrylamide. Archives of Toxicology 82 (10), 717–727. Smith, E.A., Oehme, F.W., 1991. Acrylamide and polyacrylamide: a review of production, use, environmental fate and neurotoxicity. Reviews on Environmental Health 9 (4), 215–228. Smith, C.J., Perfetti, T.A., Rumple, M.A., Rodgman, A., Doolittle, D.J., 2000. “IARC Group 2A Carcinogens” reported in cigarette mainstream smoke. Food and Chemical Toxicology 38, 371–383. Stedingk, H.V., Rydberg, P., Törnqvist, M., 2010. A new modified Edman procedure for analysis of N-terminal valine adducts in hemoglobin by LC–MS/MS. Journal of Chromatography B 878 (27), 2483–2490. Stephens, E.A., Taylor, J.A., Kaplan, N., Yang, C.H., Hsieh, L.L., Lucier, G.W., Bell, D.A., 1994. Ethnic variation in the CYP2E1 gene: polymorphism analysis of AfricanAmericans, European-Americans and Taiwanese. Pharmacogenetics 4, 185–192. Sumner, S.C., MacNeela, J.P., Fennell, T.R., 1992. Characterization and quantitation of urinary metabolites of [1,2,3-13C]acrylamide in rats and mice using 13C nuclear magnetic resonance spectroscopy. Chemical Research in Toxicology 5 (1), 81–89. Sumner, S.C., Selvaraj, L., Nauhaus, S.K., Fennell, T.R., 1997. Urinary metabolites from F344 rats and B6C3F1 mice coadministered acrylamide and acrylonitrile for 1 or 5 days. Chemical Research in Toxicology 10 (10), 1152–1160. Sumner, S.C., Fennell, T.R., Moore, T.A., Chanas, B., Gonzalez, F., Ghanayem, B.I., 1999. Role of cytochrome P450 2E1 in the metabolism of acrylamide and acrylonitrile in mice. Chemical Research in Toxicology 12, 1110–1116. Sumner, S.C., Williams, C.C., Snyder, R.W., Krol, W.L., Asgharian, B., Fennell, T.R., 2003. Acrylamide: a comparison of metabolism and hemoglobin adducts in rodents following dermal, intraperitoneal, oral, or inhalation exposure. Toxicological Sciences 75, 260–270. Tareke, E., Rydberg, P., Karlsson, P., Eriksson, S., Törnqvist, M., 2002. Analysis of acrylamide, a carcinogen formed in heated foodstuffs. Journal of Agricultural and Food Chemistry 50 (17), 4998–5006. Tareke, E., Twaddle, N.C., McDaniel, P., Churchwell, M.I., Young, J.F., Doerge, D.R., 2006. Relationships between biomarkers of exposure and toxicokinetics in Fischer 344 rats and B6C3F1 mice administered single doses of acrylamide and glycidamide and multiple doses of acrylamide. Toxicology and Applied Pharmacology 217, 63–75. Urban, M., Kavvadias, D., Riedel, K., Scherer, G., Tricker, A.R., 2006. Urinary mercapturic acids and a hemoglobin adduct for the dosimetry of acrylamide exposure in smokers and nonsmokers. Inhalation Toxicology 18 (10), 831–839. US EPA, 2010. Acrylamide (CASRN 79-06-1), Integrated Risk Information System. Available at http://www.epa.gov/iris/subst/0286.htm (accessed on 19 January 2011). Vesper, H.W., Ospina, M., Meyers, T., Ingham, L., Smith, A., Gray, J.G., Myers, G.L., 2006. Automated method for measuring globin adducts of acrylamide and glycidamide at optimized Edman reaction conditions. Rapid Communications in Mass Spectrometry 20 (6), 959–964. Vesper, H.W., Caudill, S.P., Osterloh, J.D., Meyers, T., Scott, D., Myers, G.L., 2010. Exposure of the U.S. population to acrylamide in the National Health and Nutrition Examination Survey 2003–2004. Environmental Health Perspectives 118 (2), 278–283. Wu, M.S., Chen, C.J., Lin, M.T., Wang, H.P., Shun, C.T., Sheu, J.C., Lin, J.T., 2002. Genetic polymorphisms of cytochrome P450 2E1, glutathione S-transferase M1 and T1, and susceptibility to gastric carcinoma in Taiwan. International Journal of Colorectal Disease 17 (5), 338–343. Wu, K.Y., Huang, Y.F., Chen, M.F., Shih, T.S., Uang, S.N., Mao, I.F., Chen, M.L., 2010. Exposure assessment of airborne acrylamide for occupationally-exposed workers by using an isotope-dilution gas chromatography coupled with mass spectrometry. Annals of Occupational Hygiene 54 (5), 575–583. Yin, L., Pu, Y., Liu, T.Y., Tung, Y.H., Chen, K.W., Lin, P., 2001. Genetic polymorphisms of NAD(P)H quinone oxidoreductase, CYP1A1 and microsomal epoxide hydrolase and lung cancer risk in Nanjing China. Lung Cancer 33 (2–3), 133–141.