Introduction

Arsenic is one of the first chemicals identified as a cause of cancer. In 1879, the high rates of lung cancer in miners in Saxony were partially attributed to inhaled arsenic.1 Chronic arsenic poisoning from drinking water contamination is an emerging severe public health problem in many countries all over the world; however, the mechanisms of arsenic toxicity in human beings remained unclear.2

The metabolites of arsenic may affect its toxicity.3, 4 Inorganic arsenic (iAs) is metabolized to monomethylated arsenic (MMA) and dimethylated arsenic (DMA) in human body through the process of methylation. iAs accounts for 10–30% in the metabolism of arsenic in urine, and the proportions of MMA and DMA vary from 10 to 20%, and 60 to 70%, respectively.5 The results of recent studies indicate that the methylation of iAs is not a complete detoxification process, and the key metabolic products of the arsenic methylation may be more active and toxic. Some of the metabolic products of arsenic methylation such as monomethylarsonous acid (MMAIII) and dimethylarsinous acid (DMAIII) which are more toxic than arsenite (AsIII) have been considered as the biomarkers of arsenism.6, 7, 8, 9

Differences in disease susceptibility may due to individual variability in biotransformation of arsenic and polymorphisms in metabolic genes.5, 10 Because arsenic methylation appears to affect its toxicity, it is essential to identify factors that impact methylation capacity and to better understand risks of disease.11

Glutathione S-transferases (GST) are an enzyme super family that has pivotal roles in the detoxification step of phase II metabolism, usually by catalyzing the conjugation of glutathione (GSH) into hydrophobic and electrophilic compounds along with other Phase II enzymes.12 In vivo studies have shown that GSH serves as a reducing agent required for the reduction from arsenate to arsenite, GSH also serves as a reducing agent in the methylation of arsenic from AsIII to monomethylarsonic acid (MMAV) and from MMAIII to dimethylarsinic acid (DMAV).7 GSH has been shown to reduce pentavalent arsenicals (arsenate iAsV), methylarsonic acid (MAsV) and dimethylarsinic acid (DMAsV) in aqueous solutions.13, 14 GST theta 1 (GSTT1) and GST Mu 1 (GSTM1) are two members of GSHs family. In the studies investigating the associations between GSHs polymorphisms and disease susceptibility, researchers pay more attention to the polymorphisms of GSTT1 and GSTM1.15 Some studies indicated that the polymorphisms of GSTT1 and/or GSTM1 were associated with the methylation of arsenic,4, 11, 16, 17 while the others disagreed.18, 19, 20

In 2006, the national standard of arsenic in drinking water in China was changed from 0.05 to 0.01 mg l−1, as recommended by the World Health Organization in 2004.21, 22 However, some researchers found the standard change unnecessary, because there was not enough evidence to support the theory that 0.05 mg l−1 of arsenic in drinking water will adversely affect the health of human beings. 23, 24

The aims of this study were: (1) to determine the association between the arsenic levels in drinking water and the methylation products of arsenic in lower arsenic exposure areas (the levels of arsenic in drinking water were mainly lower than 0.05 mg l−1); and (2) to investigate whether the methylation capacity of arsenic was modified by polymorphisms of GSTM1 and GSTT1 in these areas.

Materials and methods

Sample areas

In our previous study, we found that in some villages of Xuyi County, Jiangsu Province, the levels of arsenic in drinking water ranged from 0.01 to 0.05 mg l−1.25 As the Chinese national standard of arsenic in drinking water changed from 0.05 to 0.01 mg l−1 in 2006,21 we considered these areas as the lower exposure areas of arsenic. We selected Yanhuai village among one of these villages for this study.

Subjects chosen and information collection

The study was conducted from January 2008 to December 2009. We chose 230 out of 432 families in Yanhuai village, by using random digit function in Excel 2000 (Microsoft Corporation, Redmond, USA). One subject, over 30 years old, was selected by using the method of KISH Grid from each family.26, 27 In total, there were 230 subjects in our study. Information of subjects were collected through questionnaires with regard to demography (for example age, gender, family income, education, occupation, disease history, height and weight), diet, residential history including identification of the primary water source (tube well), period of water source and so on. We received 229 valid questionnaires in total, with response rate of 99.57%. All recruited subjects have no endemic arsenism symptom.

Before investigation, a written informed consent was obtained from each subject. The study was approved by Jiangsu Provincial Center for Disease Control and Prevention, and School of Public Health in South East University, Nanjing, China.

Sampling and testing

The drinking water samples, collected from the household shallow wells of each subject, were kept in clean plastic bottles and analyzed within 6 days. The urina sanguinis sample (first time urine in the morning) was collected in clean plastic bottles and kept in a refrigerator (–40 °C), which were analyzed within 4 weeks. The bottles were soaked in 10% nitric acid for 48 h, and washed with tap water for three times and distilled water for two times before used to collect drinking water and urine sample. A fasting venous blood sample (5 ml) was obtained from each subject in two underpressure plastic tubes (with or without ethylene diamine tetraacetic acid (EDTA)) (manufactured by Becton, Dickinson and Company, Shanghai, China). Each plastic tube contains 2.5-ml blood sample. The blood samples with EDTA were reversed 8–10 times slightly and kept in refrigerator (–40 °C). The blood samples without EDTA were immediately centrifuged at 3000 r.p.m for 10 min, and the serum was removed to another clean plastic tube and kept in refrigerator (–40 °C) for subsequent analysis within 4 weeks. The total valid urina sanguinis samples were 210 (of the 229 subjects, 9 subjects refused to collect urine samples and 10 samples were invalid). The total valid blood samples were 207 (of the 229 subjects, 19 subjects refused to collect blood samples and three samples were not sufficient for analysis).

The arsenic in drinking water was detected by atomic fluorescence spectrophotometer (AFS-230E, manufactured by Beijing Haiguang Instrument Company, Beijing, China). The arsenic and its metabolite in urine, such as total arsenic (TAs), inorganic arsenic (iAs), MMA and DMA were analyzed and quantified by cold trap hydride generation-atomic absorption spectrometry (HG-AFS, manufactured by Shimadzu International Co., Ltd, Kyoto, Japan) with an arsenic speciation pretreatment system ASA-2sp (Shimadzu) in China Medical University, Shenyang, China. Arsenic speciation was based on the well-established hydride generation of volatile arsines, followed by cryogenic separation in liquid nitrogen.28 The detection limit of the hydride generation and atomic absorption spectrometry method for arsenic species was 1 ng. For standard reference material with certified concentration values for arsenic (480±100 μg l−1), the average value measured in our laboratory was 464±21 μg l−1. Furthermore, the recoveries of added arsenic species ranged 85–98%, 84–92% and 90–105% for Urine iAs (UiAs), Urine MMA (UMMA) and Urine DMA (UDMA), respectively.

The blood samples with EDTA were melted at room temperature, and DNA was extracted by using the QIAGEN kits manufactured by QIAGEN Company (Shanghai, China). The genotypes of GSTM1 and GSTT1 were detected by the method of multiple polymerase chain reactions (PCR). The primers of GSTM1, GSTT1 and β-globin (reference gene) were as follows synthesized by Sangon Biotech Co., Ltd, Shangai, China:

The PCR products were separated by agarose gel electrophoresis under voltage of 100 V for 30 min, and then visualized under ultraviolet lamp. The β-globin with 268 bp in size was used as control for the PCR reaction. DNA samples from subjects with different levels of arsenic exposure were analyzed in the same PCR reaction. Furthermore, 10% of genotyping samples were randomly chosen to repeat the assay blindly for consistency check.

The electrophoretogram of the PCR products is shown in Figure 1. The specific band of 219 bp indicated the presence of GSTM1 and the genotype was labeled as GSTM1(+), while the 480-bp band indicated the presence of GSTT1 and labeled as GSTT1(+). On the contrary, the samples with absent of those two bands were identified as genotypes GSTT1(−) or GSTM1(−), respectively. Among the 207 blood samples, we got 203 valid PCR products.

Figure 1
figure 1

Electropherogram of PCR products of GSTT1 and GSTM1. The electrophoretogram of the PCR products is shown in Figure 1. The specific band of 219 bp indicated the presence of GSTM1 and the genotype was labeled as GSTM1(+), while the 480-bp band indicated the presence of GSTT1 and labeled as GSTT1(+). On the contrary, the samples with absent of those two bands were identified as genotypes GSTT1(−) or GSTM1(−), respectively. Among the 207 blood samples, we got 203 valid PCR products.

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Statistical analysis

The EPIDATA Software 3.0 (http://www.epidata.dk/download.php) was used to build up the database. The analyses were performed using STATA software (version 9; StataCorp, College Station, TX, USA) and SAS software (version 8.2; SAS Institute Inc., Cary, NC, USA). In addition, for comparing urinary arsenic concentrations and the distribution of arsenic species, we also analyzed two methylation rates indices, the primary methylation index [PMI=(MMA+DMA)/total As (TAs)] and the secondary methylation index [SMI=DMA/(MMA+DMA)] as previous report.9 Arithmetic mean (AM) or geometric means (GM) was used to describe the data of normal distribution or transformed normal distribution respectively. Comparison between two groups was performed by using Mann–Whitney U test, while comparison among multiple groups by Kruskal–Wallis H Test. Multiple regression analysis was used to analyze the data of multiplicity.

Results

Two hundred and twenty-nine subjects were recruited in this study, among them, 115 subjects are male (average age was 49.91±9.09 years) and 143 are female (average age was 50.79±8.00 years). Based on the arsenic concentration of drinking water (WAs) in their household shallow well, the subjects were divided into four subgroups used the quartiles method: 0-1.00 μg l−1 (group A), 1.01–4.07 μg l−1 (group B), 4.08–31.88 μg l−1 (group C) and 31.89–64.36 μg l−1 (group D) (in group D, only 12 samples are with the arsenic level of over 50 μg l−1). There were no significant differences in the demographic characteristics such as age, gender, body mass index and family income, among the four subgroups ( Table 1).

Table 1 Demographic characteristics of the subjects
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The distributions of WAs, UiAs, UDMA, UMMA and UTAs were not normal, with Kolmogorov–Smirnov Z values of 3.281, 3.520, 4.144, 3.530, 3.822, respectively (P<0.001). Therefore, we used the geometric mean and its 95% confidence interval to describe the distributions and compare the differences. Because of 10 water samples with the level of arsenic under the detective limitation of the atomic fluorescence spectrophotometer in group A, we used arithmetic mean to describe the distribution of water arsenic.

The MMA, DMA, iAs and TAs in urine gradually elevated with the increased levels of arsenic in household shallow well. The levels of UiAs, UMMA, UDMA and UTAs in males were higher than that in females, and the differences were significant between males and females in the level of UiAs in subgroup B and C, and UTAs in subgroup C but not in subgroup A. The SMI significantly decreased when the level of arsenic in drinking water increased, with significant differences between females in subgroup B, C, D and subgroup A. By contrast, the PMI had no differences among the subgroups (Table 2).

Table 2 The results of As in drinking water and the methylation products in urine in the subjects in Yanhuai village
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Among the 207 blood samples, we got 203 valid PCR products (103 male which accounted for 50.74%, and 100 female which accounted for 49.26%). Genotyping results showed that the genotype frequencies of GSTT1(−) accounted for 43.84%, and GSTM1(−) accounted for 54.68%, which consistent with the report of Ren et al.29 in Hebei Province in China (the genotype frequencies of GSTT1(−) and GSTM1(−) 48.6 and 59.0%). There were no significant differences in genotype distributions of GSTT1 and GSTM1 between the genders and among the different subgroups (Table 3).

Table 3 The genotype distribution of GSTT1 and GSTM1 in four subgroups
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In the subjects with genotype of GSTT1(+), the SMI was significantly higher than that with GSTT1(−). The levels of UDMA, UiAs and UTAs in the subjects of GSTT1(+) were higher than that in the subjects of GSTT1(−), although the differences were not significant. In the subjects with genotype of GSTM1(+), the levels of UiAs, UTAs were significantly higher than that with GSTM1(−). The levels of UMMA and UDMA in GSTM1(+) subjects were higher than that in GSTM1(−) subjects; however, the differences were not significant. When we compared the metabolism products between the genders in the different genotype of GSTT1(−/+) and GSTM1(−/+), the levels of UMMA, UDMA, UiAs and total UTAs in male were higher than that in female; and UMMA in GSTM1(+) group, UMMA, UiAs and UTAs in GSTT1(+) group had significant difference between the gender (Table 4).

Table 4 Compared the metabolism products and methylation ratios of arsenic [GM(95%CI)]a in urine among the different genotype of GSTT1(−/+) and GSTM1(−/+)
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Multiple regression analysis was used to see whether the factors, including gender, age, UTAs, genotype of GSTT1 and GSTM1, and the interaction of genotype and UTAs, had an impact on the arsenic methylation products of UMMA and UDMA (Table 5). The result showed that polymorphisms of GSTT1 and GSTM1 had no significant effects on the levels of UMMA (P>0.05). UMMA levels increased with the raised UTAs (P<0.01), and decreased as the interactions of genotype (GSTT1 or GSTM1) and increased UTAs (P=0.04 and P<0.01 respectively). The levels of UDMA in the subjects with the genotype of GSTT1(+) or GSTM1(+) were significantly higher than that in the subjects without (P=0.03 and P<0.01, respectively). The levels of UDMA increased with the increased UTAs (P<0.01), and decreased with the interactions of genotype and UTAs (P<0.01).

Table 5 Multiple regression analysis of the sex, age, TAs, GSTT1/GSTM1 and interaction of the genotypes and TAs together with UMMA and UDMA
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Discussion

In China, some of endemic arsenism areas, the arsenic levels in household shallow well water ranged from 0.2 to 2.0 mg l−1.25, 30 Our previous study screened 3556 wells in Xuyi County, and the results showed that 11.75% of them (418 wells) with over 0.01 mg l−1 levels of arsenic. Among these wells, the highest arsenic level was 0.296 mg l−1.31 In this research, Yanhuai village (the arsenic levels ranged from 0 to 0.064 mg l−1) was selected as low exposure areas.

In this study, we found that the levels of iAs, TAs, MMA, and DMA in urine samples significantly increased with the arsenic levels in drinking water. This result is consistent with some previous reports.9, 32, 33, 34 We found that the levels of iAs, MMA, DMA, and TAs in male urine samples were higher than that in female samples from the same subgroup, especially the iAs level in subgroups B and C, and the TAs level in subgroup C. However, the previous research works of Sun et al.9, Xu et al.34, and Li et al.32 did not find differences in the capacity to methylate arsenic between males and females. The studies of Wang et al.33 and Tseng et al.35 found that females had a greater ability to methylate arsenic than males. Our results indicated that PMI had no differences among males, females and different subgroups, but SMI in females was significantly decreased with the increase of the arsenic levels in drinking water. The results of Sun et al.9 indicated that the values of PMI and SMI in adults and children significantly decreased in the groups exposed to 90 μg l−1 and 160 μg l−1 arsenic compared with the control group; Li et al.32 reported that, in the exposure group, PMI increased significantly, while SMI decreased significantly compared with control group. The reasons for the inconsistent results among these studies could be: (1) the differences in subject numbers, age, and gender; and (2) the differences in arsenic exposure levels and arsenic valence states (trivalent or pentavalent) in drinking water.

In a multivariate model in the study of McCarty et al.11, 12, a 10-fold increase in primary methylation ratio was associated with a 1.5-fold increase in skin lesions (95% CI, 1.001–2.26); for individuals with the GSTT1 wild-type genotype (GSTT1(+)), a 10-fold increase in primary methylation ratio was associated with a 1.67-fold increased in skin lesions (95% CI, 1.06–2.64), and a 10-fold increase in secondary methylation ratio was associated with 0.87 odds of skin lesions (odds ratio (OR)=0.87, 95% CI, 0.76–0.99), compared with GSTT1 null [GSTT1(−)]; they also found GSTT1 homozygous wild-type status was associated with increased odds of skin lesions compared with the null status (OR 1.56 95% CI 1.10–2.19). Individuals with GSTM1 null genotype had significantly increase urothelial carcinoma risk.37 These results suggested that the polymorphisms of GSTT1 and GSTM1 may be correlated with the methylation of As, thus affect the outcome of arsenism. In this study, the results of single factor analysis indicated that the levels of iAs, DMA and TAs in urine samples of the subjects with genotypes of GSTT1(+) and GSTM1(+) were higher than that in the subjects with GSTT1(−) and GSTM1(−), and were higher in male than that in female. The levels of iAs and TAs were significantly different between the two genotypes GSTM1(+) and GSTM1(−). The level of SMI in this study was significantly higher in the subjects with GSTT1(+) than that with GSTT1(−), which was consistent with the report of Kile et al.38 The results of these studies (included our study) indicated that the polymorphisms of GSTT1 and GSTM1 may affect the methylation of arsenic before they were excreted from urine, and UMMA has been associated with adverse effects, UDMA has the lowest body retention of the metabolites.38, 39

The results of multiple regression analysis in this study indicated that the TAs levels in urine, together with the genotypes of GSTT1 and GSTM1 with urinary TAs, and the difference in gender were associated with the urinary MMA levels. The genotypes of GSTT1 and GSTM1, the TAs levels in urine, together with the genotypes of GSTT1 and GSTM1 with urine TAs were significantly associated with the urinary DMA levels. These results suggested that the genotypes of GSTT1 and GSTM1 may affect the methylation of arsenic, especially the levels of DMA and SMI.

The limitations of this study were as following: (1) the sample size may not be sufficient for evaluating the gene–environment interactions, it may take benefit to expand the population size; (2) the main iAs (iAsIII and iAsV) was the type in the natural water in China. The toxicity of iAsIII was significantly higher than that of iAsV, and the distributions of iAsIII and iAsV in water varied in different areas depending on the pH value and the presence of oxidizing and reducing substances40, 41 which may affect the methylation of arsenic. However, we did not include related investigation and analysis in this study; (3) smoking, sea food and other factors may also affect the methylation of arsenic.9, 42 In our study, the smoking factor was simplified to a binary choice (yes or no), the detailed information such as numbers of cigarette per day, types of tobacco products, how long of the smoking period, was not included. Furthermore, sea food was rare in the diet of the studied subjects because of isolation from sea, we just ignored this information in our study.

In conclusion, our results showed that the levels of iAs, MMA, DMA, TAs in urine significantly increased when exposure levels of arsenic in drinking water increased in the low exposure areas of arsenic, and the polymorphisms of GSTT1 and GSTM1 may modify arsenic methylation in these areas, especially for the secondary methylation index. The capacity of arsenic methylation of GSTT1 and GSTM1 may be considered as the biomarkers of arsenism. Whether the Subjects with the genotype of GSTT1(−/+) and GSTM1(−/+) likely to develop the arsenism or not need to be further study.