Cancer Causes Control (2013) 24:1963–1972 DOI 10.1007/s10552-013-0272-3
ORIGINAL PAPER
Dietary aflatoxin B1 intake, genetic polymorphisms of CYP1A2, CYP2E1, EPHX1, GSTM1, and GSTT1, and gastric cancer risk in Korean Sang-Yong Eom • Dong-Hyuk Yim • Yanwei Zhang • Jung-Kuk Yun Sun In Moon • Hyo-Yung Yun • Young-Jin Song • Sei-Jin Youn • Taisun Hyun • Joo-Seung Park • Byung Sik Kim • Jong-Young Lee • Yong-Dae Kim • Heon Kim
•
Received: 1 April 2013 / Accepted: 31 July 2013 / Published online: 15 August 2013 Ó Springer Science+Business Media Dordrecht 2013
Abstract Purpose We investigated the effects of aflatoxin B1 (AFB1) intake, genetic polymorphisms of AFB1 metabolic enzymes, and interactions between the polymorphisms and intake of AFB1 with regard to the risk of gastric cancer in Korean. Methods The participants in the study included 477 gastric cancer patients and 477 age- and sex-matched control subjects. Direct interviews and a structured questionnaire were used to determine the level of exposure to AFB1, and the GoldenGate assay and multiplex polymerase chain reaction were used for genotypic analyses of the cytochrome P450 1A2 (CYP1A2), cytochrome P450 1E1, epoxide hydrolase 1, and glutathione S-transferase genes. Results The probable daily intake of AFB1 was significantly higher among gastric cancer patients than among control subjects (cases vs. controls: 1.91 ± 0.87 vs.
1.65 ± 0.72 ng/kg bw/day, p \ 0.0001), and increased AFB1 intake was significantly associated with an elevated risk of gastric cancer (odds ratio 1.94; 95 % confidence interval 1.43–2.63). However, genetic polymorphisms of AFB1 metabolic enzymes were not associated with gastric cancer, with the exception of CYP1A2. Moreover, there was no interaction between AFB1 intake and the genotypes of metabolic enzymes that affect gastric cancer risk. Conclusions Our results suggest that dietary AFB1 exposure might be associated with a risk of gastric cancer. However, the effect of AFB1 on gastric carcinogenesis may not be modulated by genetic polymorphisms of AFB1 metabolic enzymes.
S.-Y. Eom D.-H. Yim Y. Zhang J.-K. Yun S. I. Moon Y.-D. Kim H. Kim (&) Department of Preventive Medicine and Medical Research Institute, College of Medicine, Chungbuk National University, 52 Naesudong-ro, Heungdok-gu, Cheongju 361-763, Korea e-mail:
[email protected]
J.-S. Park Department of Surgery, College of Medicine, Eulji University, Daejon, Korea
H.-Y. Yun Y.-J. Song Department of Surgery, College of Medicine, Chungbuk National University, Cheongju, Korea
Keywords Gastric cancer Aflatoxin B1 Genetic polymorphism Cytochrome P450 1A2 Glutathione S-transferase Epoxide hydrolase
B. S. Kim Department of Surgery, Asan Medical Center, College of Medicine, Ulsan University, Seoul, Korea J.-Y. Lee Center for Genome Science, National Institute of Health, Osong, Korea
S.-J. Youn Department of Internal Medicine, College of Medicine, Chungbuk National University, Cheongju, Korea T. Hyun Department of Food and Nutrition, Chungbuk National University, Cheongju, Korea
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Introduction
Materials and methods
Gastric cancer is the second most common cancer in Korea, and it is the second leading cause of cancer death for both men and women worldwide [1, 2]. Epidemiologic studies have provided evidence that high intakes of salt and nitrite-rich foods and Helicobacter pylori infection are associated with a high incidence of gastric cancer in Korea [3–7]. Indeed, environmental factors, particularly dietary habits, may be among the important etiologic factors [4]. We previously reported that the consumption of kimchi and fermented soybean pastes is associated with increased risk of gastric cancer, and other studies have suggested that soybean paste stew consumption is a risk factor for gastric cancer [8–10]. Fermented soybean pastes are high in nitrates [11, 12] and might be a dietary source of aflatoxin B1 (AFB1) exposure in the Korean population [13]. Park et al. [14] reported that the major contributor to the dietary intake of AFB1 in Korean is rice, a staple food for Koreans. In addition, the estimated probable daily intake (PDI) of AFB1 among Koreans was higher than the tolerable daily intake [14]. Although it is known that AFB1 is a food mutagen related to cancer risk, there are no available data regarding the association between AFB1 intake and the risk of gastric cancer. Aflatoxins, mycotoxins that are derived from Aspergillus fungi, have been categorized as a group I human carcinogen by the International Agency for Research on Cancer [15]. Absorbed AFB1 is metabolically activated primarily by cytochrome P450 (CYP) (i.e., CYP3A4, CYP1A2, CYP3A5, and CYP2E1) into a reactive intermediate, AFB1-8,9-exo-epoxide (AFBO), which can lead to the formation of DNA adducts and mutations [16]. AFBO is later detoxified via conjugation with glutathione by glutathione S-transferase (GST) or hydrolysis catalyzed by microsomal epoxide hydrolase 1 (EPHX1) [17–19]. As the metabolic activation and detoxification of AFB1 are modified by the activity of enzymes involved in AFB1 metabolism, there is a possibility that genetic polymorphisms of relevant metabolizing enzymes might affect the susceptibility to cancers associated with AFB1. Several studies have shown an interactive effect between AFB1 exposure and genetic polymorphisms, though the results are inconsistent and limited to hepatocellular carcinoma (HCC) [17, 19–22]. In this case–control study, we investigated the influence of AFB1 intake, genetic polymorphism of AFB1 metabolic enzymes, and the effect of their interaction on the risk of gastric cancer.
Study subjects
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The participants in this study included 477 newly diagnosed gastric cancer patients and 477 age (within 3 years)- and sexmatched control subjects. These patients were histologically confirmed with gastric cancer at two regional hospitals geographically located in the center of South Korea: Chungbuk National University Hospital at Cheongju (n = 251) and Eulji University Hospital at Daejeon (n = 226). These two hospitals are located within the Chungcheong Province, and no definitive difference for a regional dietary culture was known. The control individuals were selected from a pool of individuals receiving routine medical examinations in the two hospitals. After written informed consent was obtained, trained interviewers examined all of the subjects using a structured questionnaire that included questions on demographic factors, smoking habits, alcohol consumption, and dietary habits. Peripheral blood samples were collected from all of the subjects. This study was approved by the institutional review board of Chungbuk National University Hospital, Korea (IRB No. 2011-09-071). Estimation of AFB1 intake The intake of AFB1 was estimated from the dietary data collected using a semiquantitative food frequency questionnaire (FFQ) previously evaluated for validity and reliability [23]. To determine the AFB1 content in the 89 food items and six beverages included in the questionnaire, more than 10 samples of each food item were gathered from central South Korea, and the AFB1 content was measured using a commercial enzyme-linked immunosorbent assay kit (Veratox Quantitative Aflatoxin Test Kit, Neogene, Lansing, MI, USA) according to the manufacturer’s instructions. The estimated amount of AFB1 intake for each food item was calculated by multiplying the food intake amount by its mean content of AFB1, and the estimated weekly total intake of AFB1 was calculated by summing the amount of AFB1 intake for all 89 food items and six beverages. The estimated total intake of AFB1 was adjusted for body weight. Genotyping analysis Genomic DNA was isolated from peripheral blood using a DNA purification kit (DNA Extractor WB, Wako, Osaka, Japan) according to the manufacturer’s protocol; the DNA samples were stored at -70 °C until analysis. The GoldenGate assay (Illumina, San Diego, CA, USA) was used to
Cancer Causes Control (2013) 24:1963–1972
analyze the genetic polymorphisms of AFB1 metabolic enzymes, including CYP1A2, CYP2E1, CYP3A4, and EPHX1. Based on the previous reports [17, 20, 22, 24–27], we selected seven single-nucleotide polymorphisms in these four genes (rs2470890 in CYP1A2, rs8192773 in CYP2E1, rs4646438 in CYP3A4, and rs1051741, rs2234922, rs2292568, and rs3753660 in EPHX1) for genotyping. The following four single-nucleotide polymorphisms did not meet the genotyping criteria and were thus removed from the final dataset: rs1051741 and rs3753660 in EPHX1 were in disagreement with Hardy– Weinberg equilibrium, rs4646438 in CYP3A4 had a minor allele frequency of \0.01, and rs2234922 in EPHX1 had a call rate of \95 %. Genetic polymorphisms in the GST genes [glutathione S-transferase mu 1 (GSTM1) and glutathione S-transferase theta 1 (GSTT1)] were determined using the multiplex polymerase chain reaction method [28]. Data analysis The case–control genetics power was calculated using Genetic Power Calculator (http://pngu.mgh.harvard.edu/ *purcell/gpc/) [29]. The parameters were set as follows: risk allele frequency—0.15, alpha error—0.01, and disease prevalence—0.1 %. The power of a dominant model was 0.4323 when the odds ratio for a genotype with one or two risk allele(s) was taken as 1.4. The Student’s t test was used to compare continuous variables among the patients and control subjects. Associations between gastric cancer and putative risk factors were estimated by odds ratios (ORs) and their corresponding 95 % confidence intervals (95 % CI) derived from multivariate conditional logistic regression models after adjusting for potential confounding factors, such as age, sex, smoking history, amount of alcohol intake, total calorie intake, and education level. The estimated amount of AFB1 intake was categorized by the median value of the probable daily intake of AFB1 (1.56 ng/kg bw/day) among the control subjects. A stratified analysis was used to estimate the potential joint effects between the genotypes and the combined effects of those genotypes and AFB1 intake. p values for interactions between the genotypes and AFB1 exposure were assessed using the Wald test for the cross-product term in a model containing the main effects of genotype and exposure variable. All of the statistical analyses were performed using SASÒ Version 9.2 (SAS Institute, Cary, NC, USA).
Results No significant differences in age, sex, and total daily calorie intake were found between the patients and control
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subjects. The cumulative smoking amount was, however, associated with a significantly increased risk of gastric cancer. Although the alcohol intake status was not associated with gastric cancer risk, those with high alcohol intake levels ([280 g/week) had a significantly higher risk of gastric cancer than nondrinkers. In addition, higher education levels were related with reduced gastric cancer risk (Table 1). Table 2 shows the contents and the daily intake amounts of AFB1 for 89 food items and six beverages included in the FFQ. The contents of AFB1 ranged from not detected to 0.149 ng g-1. The estimated daily amount of AFB1 intake based on the AFB1 content and consumption of each food item was highest for rice in both the gastric cancer patients and control subjects. Although soybean paste stew and fermented soybean soup have relatively high AFB1 contents, the proportion of these foods in the total estimated AFB1 intake was less than 10 %. The probable daily intake (PDI) of AFB1 was significantly higher among the gastric cancer patients than control subjects, and the high AFB1 intake group had a significantly higher risk of gastric cancer compared to the low AFB1 intake group (OR 1.94; 95 % CI 1.43–2.63) (Table 3). The distributions of CYP1A2, CYP2E1, EPHX1, GSTT1, and GSTM1 genotypes among the patients with gastric cancer and control subjects are presented in Table 4. The CYP1A2 rs2470890 C/T genotype showed a significantly lower risk for gastric cancer than the C/C homozygote genotype (OR 0.72; 95 % CI 0.52–0.98). However, no statistical significance for the CYP2E1, EPHX1, GSTT1, and GSTM1 genotypes was identified (Table 4). Because the AFB1 intake levels were significantly higher for the gastric cancer patients than for control subjects, we performed stratified analyses to assess gastric cancer risk according to the AFB1 intake level. Except for the CYP1A2 rs2470890 C/T ? T/T genotype, all of the genotypes in the high AFB1 intake group had a significantly higher risk of gastric cancer than the corresponding reference genotypes in the low AFB1 intake group. Although not statistically significant, we observed a weak interaction between AFB1 intake and the GSTT1 genotype (p for interaction = 0.0783) (Table 5).
Discussion To the best of our knowledge, this study presents the first potential evidence of an association between AFB1 exposure and gastric carcinogenesis in humans; until now, the biological plausibility of AFB1 carcinogenicity in the human stomach was uncertain. Indeed, only a few in vivo
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1966 Table 1 General characteristics of the study population
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Variable
Controls (n = 477)
Cases (n = 477)
p value or OR (95 % CI)
Age, mean ± SD
57.8 ± 10.2
58.7 ± 9.9
0.1610
Males
301 (63.1)
301 (63.1)
Females
176 (36.9)
176 (36.9)
Nonsmokers
225 (47.6)
194 (41.0)
1.00 (ref.)
Smokers
248 (52.4)
279 (59.0)
1.64 (0.95, 2.84)
Gender, n (%)
1.0000
Smoking status, n (%)
Cumulative smoking amount, n (%) Nonsmokers
225 (47.6)
194 (41.0)
1.00 (ref.)
0–19 pack-years
76 (16.1)
71 (15.0)
1.49 (0.94, 2.37)
20–39 pack-years [40 pack-years
113 (23.9) 58 (12.3)
119 (25.2) 89 (18.8)
1.76 (1.13, 2.75) 2.77 (1.64, 4.67)
Nondrinkers
194 (40.7)
189 (39.6)
1.00 (ref.)
Drinkers
283 (59.3)
288 (60.4)
1.18 (0.71, 1.76)
Alcohol intake status, n (%)
Alcohol intake amount, g/week, n (%) Nondrinkers
194 (40.7)
189 (39.6)
1.00 (ref.)
[0 to B 280 g/week
217 (45.5)
180 (37.7)
0.97 (0.62, 1.54)
[280 g/week
66 (13.8)
108 (22.6)
2.05 (1.05, 3.99)
\High school
231 (48.4)
346 (72.5)
1.00 (ref.)
CHigh school
246 (51.6)
131 (27.5)
0.48 (0.32, 0.73)
Total daily calorie intake, kcal, mean ± SD
2,756 ± 1,020
2,752 ± 1,073
0.9462
Education level
studies have proposed a connection between AFB1 or a precursor of aflatoxin (i.e., sterigmatocystin) and gastric cancer or intestinal metaplasia, a precancerous lesion of gastric cancer [30–34]. Because the human stomach is exposed to AFB1 through diet and the metabolic enzymes for AFB1, such as CYP1A2, EPHX1, and GSTs, are expressed in human stomach tissue, we hypothesized that AFB1 could be a gastric carcinogen. In this study, the gastric cancer risk for the high AFB1 intake group was approximately 1.94-fold greater than that for the low AFB1 intake group. Similar to our results, some animal studies have also demonstrated the carcinogenic effects of AFB1 on the stomach [30–34]. Butler et al. [30] first observed stomach tumors after oral administration of AFB1 to rats. Ma et al. [32] reported that sterigmatocystin, which is produced by Aspergillus and is a precursor in AFB1 biosynthesis, could enhance intestinal metaplasia and increase serum gastrin levels in H. pylori-infected Mongolian gerbils. In a recent study, the long-term administration of sterigmatocystin increased the expression of proliferating cell nuclear antigen p53 and MDM2 in the gastric mucosa of aged Mongolian gerbils [34]. These results suggest that AFB1 may play a role in human stomach cancer, though the mechanism of gastric carcinogenesis by AFB1 and sterigmatocystin remains unclear.
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In the present study, the content of AFB1 for 89 food items and six beverages ranged from not detected to 0.149 ng g-1, which is not higher than the limit worldwide (10 ng g-1) [35]. Rice (polished and unpolished) was the main source of the estimated daily AFB1 intake in both the gastric cancer patients and control subjects, even though the relative AFB1 content of rice among the 89 food items was not high. However, the amount of estimated daily AFB1 intake through polished and unpolished rice was not significantly different between the two groups, a result that could be explained by the fact that Koreans consume a large amount of rice ([300 g/day). Ok et al. [13] reported that soybean paste and soy sauce were major dietary contributors to AFB1 intake in the Korean population, comprising 91 % of the total exposure to AFB1. We also found a high concentration of AFB1 in soybean paste (0.138–0.159 ng g-1) (data not shown). Although soybeans are abundant sources of isoflavones and antioxidants and have other antitumor effects, most studies have suggested that fermented soy foods are associated with an increased risk of gastric cancer [8–10, 36], suggesting that AFB1, a contaminant found in fermented soybean pastes, could be connected to gastric cancer. Regardless, in this study, the estimated intake value of AFB1 in this study was much lower than the PDI of highly aflatoxin-contaminated
Cancer Causes Control (2013) 24:1963–1972
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Table 2 Aflatoxin B1 content of 89 food items and daily intake of food and aflatoxin B1 Food category
Grain and grain products
Potatoes Legumes and legume products
Nuts Vegetables and vegetable products
Fruits and fruit juices
Food item
AFB content (ng/g)a
Controls Food intake (g/day)
Cases AFB intake (ng/day)
Food intake (g/day)
AFB intake (ng/day)
Sandwich bread, toast bread
0.042
3.02 ± 0.64
0.13 ± 0.03
2.30 ± 0.37
0.10 ± 0.02
Doughnut
0.035
1.01 ± 0.14
0.03 ± 0.00
1.79 ± 0.36
0.06 ± 0.01
Red bean bread Rice
0.042 0.059
4.05 ± 0.51 302.18 ± 11.43
0.17 ± 0.02 17.74 ± 0.67
4.19 ± 0.56 373.49 ± 11.47
0.17 ± 0.02 21.92 ± 0.67
Unpolished rice
0.095
178.57 ± 10.80
17.02 ± 1.03
124.82 ± 9.69
11.89 ± 0.92
Rice mixed with vegetables
0.041
22.14 ± 2.55
0.91 ± 0.11
17.84 ± 2.09
0.74 ± 0.09
Stir-fried rice with egg and vegetables
0.050
2.68 ± 0.48
0.13 ± 0.02
4.66 ± 0.61
0.23 ± 0.03
Sushi
0.052
36.14 ± 4.46
1.88 ± 0.23
23.33 ± 3.70
1.21 ± 0.19
Rice cake
0.052
4.89 ± 0.55
0.25 ± 0.03
3.03 ± 0.34
0.16 ± 0.02
Dumpling
0.034
1.33 ± 0.16
0.05 ± 0.01
1.93 ± 0.25
0.07 ± 0.01
Hand-rolled noodles soup
0.053
12.28 ± 0.96
0.65 ± 0.05
10.10 ± 0.66
0.53 ± 0.04
Cold buckwheat noodles
0.050
4.34 ± 0.40
0.22 ± 0.02
4.09 ± 0.41
0.21 ± 0.02
Stir-fried noodles with black soybean sauce
0.045
3.53 ± 0.79
0.16 ± 0.04
5.07 ± 0.51
0.23 ± 0.02
Ramen
0.054
5.00 ± 0.59
0.27 ± 0.03
10.71 ± 1.02
0.58 ± 0.06
Pizza
0.051
10.25 ± 1.33
0.52 ± 0.07
0.57 ± 0.14
0.03 ± 0.01
Sponge cake
N.D.
4.24 ± 0.77
–
1.64 ± 0.28
–
Potato
0.048
8.56 ± 1.74
0.41 ± 0.08
10.24 ± 0.96
0.49 ± 0.05
Fried potato
0.047
9.18 ± 1.20
0.43 ± 0.06
1.32 ± 0.20
0.06 ± 0.01
Raw bean
0.040
12.34 ± 0.77
0.49 ± 0.03
6.78 ± 0.58
0.27 ± 0.02
Tofu
0.065
37.40 ± 1.77
2.42 ± 0.11
30.11 ± 2.14
1.94 ± 0.14
Pan-fried mung beans Soybean milk
0.067 0.038
1.90 ± 0.28 5.75 ± 0.93
0.13 ± 0.02 0.22 ± 0.04
1.19 ± 0.14 11.70 ± 2.03
0.08 ± 0.01 0.45 ± 0.08
Chestnut
0.046
5.83 ± 0.51
0.27 ± 0.02
3.28 ± 0.43
0.15 ± 0.02
Peanut
0.039
0.49 ± 0.10
0.02 ± 0.00
0.14 ± 0.02
0.01 ± 0.00
Green onion pancake
0.042
2.63 ± 0.37
0.11 ± 0.02
2.57 ± 0.33
0.11 ± 0.01
Kimchi
0.066
79.59 ± 2.56
5.25 ± 0.17
77.83 ± 2.42
5.14 ± 0.16
Kimchi without red pepper powder
0.029
14.73 ± 1.06
0.42 ± 0.03
19.41 ± 1.43
0.55 ± 0.04
Cucumber Lettuce
0.041 0.035
23.41 ± 1.28 17.86 ± 0.90
0.97 ± 0.05 0.63 ± 0.03
21.20 ± 1.11 13.28 ± 0.73
0.88 ± 0.05 0.47 ± 0.03
Green onion
0.050
15.66 ± 0.98
0.78 ± 0.05
9.57 ± 0.77
0.48 ± 0.04
Soybean sprout
0.056
18.76 ± 1.00
1.05 ± 0.06
16.15 ± 0.89
0.90 ± 0.05
Bracken
0.037
2.53 ± 0.28
0.09 ± 0.01
3.44 ± 0.40
0.13 ± 0.01
0.45 ± 0.04
3.12 ± 0.35
0.46 ± 0.05
Mugwort
0.149
2.99 ± 0.30
Seasoned dureup
N.D.
3.90 ± 0.38
Wild rocambole
0.036
3.76 ± 0.32
– 0.14 ± 0.01
3.17 ± 0.32 4.03 ± 0.33
– 0.15 ± 0.01
Mushroom
0.047
6.50 ± 0.45
0.31 ± 0.02
6.55 ± 0.59
0.31 ± 0.03
Pickled garlic
0.062
0.94 ± 0.17
0.06 ± 0.01
1.04 ± 0.12
0.06 ± 0.01
Onion
0.042
3.30 ± 0.52
0.14 ± 0.02
3.00 ± 0.34
0.12 ± 0.01
Tomato
0.039
19.00 ± 2.62
0.74 ± 0.10
37.23 ± 3.66
1.46 ± 0.14
Carrot juice
0.087
7.68 ± 1.06
0.67 ± 0.09
4.31 ± 0.94
0.38 ± 0.08
Mandarin orange
0.047
14.60 ± 1.36
0.69 ± 0.07
21.45 ± 1.75
1.01 ± 0.08
Apple
0.045
31.75 ± 2.72
1.43 ± 0.12
20.30 ± 1.34
0.92 ± 0.06
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Table 2 continued Food category
Stews
Meats
Poultry products Fishes and shellfish products
Food item
AFB content (ng/g)a
Controls Food intake (g/day)
Cases AFB intake (ng/day)
Food intake (g/day)
AFB intake (ng/day)
Peach
0.051
18.13 ± 1.69
0.93 ± 0.09
9.00 ± 0.74
0.46 ± 0.04
Pear
0.046
8.20 ± 1.01
0.38 ± 0.05
14.8 ± 1.41
0.69 ± 0.07
Korean melon
0.039
12.75 ± 1.00
0.50 ± 0.04
7.78 ± 0.56
0.31 ± 0.02
Water melon Strawberry
0.047 N.D.
15.05 ± 1.47 2.44 ± 0.29
0.70 ± 0.07 –
28.75 ± 1.90 3.83 ± 0.29
1.35 ± 0.09 –
Grape
0.036
3.58 ± 0.39
0.13 ± 0.02
5.23 ± 0.44
0.19 ± 0.02
Dried persimmons
0.039
3.78 ± 0.26
0.15 ± 0.01
0.45 ± 0.07
0.02 ± 0.00
Orange juice
0.051
14.6 ± 1.36
0.69 ± 0.07
21.45 ± 1.75
1.01 ± 0.08
Kimchi stew
0.062
29.10 ± 1.35
1.80 ± 0.08
41.57 ± 2.08
2.57 ± 0.13
Soybean paste stew
0.111
62.20 ± 2.44
6.89 ± 0.27
67.98 ± 3.24
7.52 ± 0.36
Fermented soybeans soup
0.105
26.02 ± 1.50
2.72 ± 0.16
23.53 ± 1.65
2.46 ± 0.17
Beef
0.048
9.40 ± 0.85
0.45 ± 0.04
14.14 ± 1.86
0.68 ± 0.09
Ox bone soup
0.045
4.91 ± 0.51
0.22 ± 0.02
4.86 ± 0.40
0.22 ± 0.02
Hangover soup
0.055
9.07 ± 0.69
0.50 ± 0.04
10.26 ± 0.80
0.57 ± 0.04
Grilled pork loin
0.028
16.23 ± 1.12
0.45 ± 0.03
21.37 ± 1.59
0.60 ± 0.04
Pork
0.033
18.38 ± 1.23
0.61 ± 0.04
10.26 ± 1.05
0.34 ± 0.03
Bacon
0.048
0.66 ± 0.07
0.03 ± 0.00
0.20 ± 0.08
0.01 ± 0.00
Dog meat
0.044
3.46 ± 0.82
0.15 ± 0.04
6.02 ± 0.61
0.27 ± 0.03
Pork liver
0.073
0.85 ± 0.09
0.06 ± 0.01
0.18 ± 0.05
0.01 ± 0.00
Sausage Chicken ginseng soup
0.041 0.047
0.24 ± 0.07 2.57 ± 0.26
0.01 ± 0.00 0.12 ± 0.01
0.40 ± 0.14 5.92 ± 0.42
0.02 ± 0.01 0.28 ± 0.02
Fried chicken
0.039
4.14 ± 0.31
0.16 ± 0.01
1.94 ± 0.37
0.07 ± 0.01
Raw fish
0.031
3.03 ± 0.29
0.09 ± 0.01
2.17 ± 0.21
0.07 ± 0.01
Grilled mackerel
0.046
7.86 ± 0.49
0.36 ± 0.02
7.23 ± 0.54
0.34 ± 0.02
Pollack stew
0.057
4.43 ± 0.32
0.25 ± 0.02
5.17 ± 0.47
0.29 ± 0.03
Grilled hairtail fish
0.056
1.18 ± 0.14
0.07 ± 0.01
2.38 ± 0.28
0.13 ± 0.02
Broiled eel
0.029
2.12 ± 0.22
0.06 ± 0.01
2.04 ± 0.21
0.06 ± 0.01
Dried pollack
0.038
3.28 ± 0.33
0.12 ± 0.01
3.34 ± 0.34
0.13 ± 0.01
Canned mackerel
0.043
0.41 ± 0.10
0.02 ± 0.00
0.33 ± 0.08
0.01 ± 0.00
Canned tuna
0.024
0.69 ± 0.19
0.02 ± 0.00
0.92 ± 0.17
0.02 ± 0.00
Boiled fish paste Squid
0.041 0.042
0.92 ± 0.11 5.14 ± 0.71
0.04 ± 0.00 0.21 ± 0.03
2.39 ± 0.42 3.28 ± 0.26
0.10 ± 0.02 0.14 ± 0.01
Shrimp
0.042
2.34 ± 0.26
0.10 ± 0.01
1.76 ± 0.29
0.07 ± 0.01
Shellfish
0.051
1.37 ± 0.13
0.07 ± 0.01
1.28 ± 0.13
0.07 ± 0.01
Salted and fermented squid
0.050
0.49 ± 0.06
0.02 ± 0.00
0.79 ± 0.09
0.04 ± 0.00
Seaweeds
Brown seaweed
0.047
8.27 ± 0.46
0.38 ± 0.02
7.91 ± 0.48
0.37 ± 0.02
Laver
0.033
4.89 ± 0.30
0.16 ± 0.01
4.37 ± 0.28
0.14 ± 0.01
Dairy and Egg products
Egg
0.030
7.05 ± 0.46
0.21 ± 0.01
7.74 ± 0.59
0.23 ± 0.02
Yogurt
N.D.
7.30 ± 1.25
–
7.59 ± 1.00
Milk
N.D.
33.61 ± 3.36
–
41.09 ± 3.82
–
Cheese
N.D.
2.80 ± 0.33
–
0.03 ± 0.01
–
Fat and oils Sweets
123
–
Butter
N.D.
0.04 ± 0.02
–
0.04 ± 0.01
Margarine
0.099
0.01 ± 0.01
0.00 ± 0.00
0.03 ± 0.01
0.00 ± 0.00
–
Strawberry jam
0.049
0.13 ± 0.03
0.01 ± 0.00
0.14 ± 0.06
0.01 ± 0.00
Cancer Causes Control (2013) 24:1963–1972
1969
Table 2 continued Food category
Beverages
Alcoholic beverages
Food item
AFB content (ng/g)a
Controls Food intake (g/day)
Cases AFB intake (ng/day)
Food intake (g/day)
AFB intake (ng/day)
Ice cream
N.D.
10.87 ± 1.47
–
7.72 ± 1.25
–
Chocolate
N.D.
0.92 ± 0.14
–
1.90 ± 0.31
–
Cola Coffee
0.079 0.125
49.66 ± 5.54 51.26 ± 4.84
3.94 ± 0.44 6.39 ± 0.60
12.96 ± 1.83 121.26 ± 7.11
1.03 ± 0.15 15.12 ± 0.89
Black tea
0.060
1.87 ± 0.60
0.11 ± 0.04
2.46 ± 0.77
0.15 ± 0.05
Green tea
0.075
9.88 ± 1.54
0.74 ± 0.12
17.70 ± 2.67
1.32 ± 0.20
Korean raw rice wine
0.037
1.49 ± 0.44
0.05 ± 0.02
9.61 ± 2.08
0.35 ± 0.08
Korean distilled liquor
0.077
16.65 ± 1.68
1.28 ± 0.13
26.31 ± 3.14
2.03 ± 0.24
Total
100.41 ± 44.87
106.19 ± 49.86
N.D. not detected a
Mean value
Table 3 Dietary AFB1 intake and risk of gastric cancer Variable
Probable daily intake, ng/kg bw/day, mean ± SD
Controls
1.65 ± 0.72
Cases
p value or OR (95 % CI)
1.91 ± 0.87 \0.0001
Table 4 Distributions of the CYP1A2, CYP2E1, EPHX1, GSTT1, and GSTM1 genotypes and risk of gastric cancer Genotype
Controls
240 (50.3)
High ([1.56 ng/kg bw/ day)
237 (49.7)
186 (39.0)
p value
Cases
CYP1A2 rs2470890
Dietary AFB1 intake level, n (%)a Low (B1.56 ng/kg bw/ day)
OR (95 % CI)a
No. (%)
1.00 (ref.)
C/C
308 (65.3)
335 (70.8)
1.00 (ref.)
C/T T/T
150 (31.8) 14 (3.0)
122 (25.8) 16 (3.4)
0.72 (0.52, 0.98) 1.00 (0.45, 2.21)
0.0365 0.9903
C/T ? T/T
164 (34.8)
138 (29.2)
0.74 (0.55, 1.00)
0.0504
1.00 (ref.)
CYP2E1 rs8192773 291 (61.0)
1.94 (1.43, 2.63)
a
Categorized by the median aflatoxin B1 probable daily intake value (1.56 ng/kg bw/day) among the control subjects
areas in China (3.68 lg/kg of body weight per day) [37], and the ORs of AFB1 exposure for HCC risk were much greater than those for gastric cancer [21, 38]. These facts show that the amount of AFB1 intake in the subjects of the present study is lower than that in areas of high aflatoxin contamination. Additionally, as aflatoxins are more rapidly transformed into biologically active metabolites in the liver, producing DNA adducts or directly damaging DNA [16], aflatoxins are more carcinogenic to the liver than the stomach. Larsson et al. [26] reported that AFBO, a reactive metabolite of AFB1, accumulated in the glandular stomach in a state of glutathione depletion, suggesting that the possible mechanism of AFB1 carcinogenicity might be related to an imbalance between the capacity for bioactivation and detoxification in gastric tissue. We hypothesized that genetic polymorphisms in AFB1-metabolizing enzymes may influence the susceptibility to gastric cancer. CYP1A2 is known to cause the metabolic activation of
T/T
421 (88.6)
422 (88.7)
T/G
54 (11.4)
52 (10.9)
G/G
0 (0.0)
2 (0.4)
54 (11.4)
54 (11.3)
T/G ? G/G
0.96 (0.54, 1.73)
0.8962
–
–
0.99 (0.55, 1.76)
0.9585
EPHX1 rs2292568 C/C
349 (73.9)
347 (73.2)
1.00 (ref.)
C/T
113 (23.9)
114 (24.1)
1.09 (0.79, 1.50)
T/T C/T ? T/T
0.6120
10 (2.1)
13 (2.7)
1.50 (0.56, 3.83)
0.4430
123 (26.1)
127 (26.8)
1.12 (0.82, 1.53)
0.4937
GSTT1 Present Null GSTM1
265 (55.7)
267 (56.0)
1.00 (ref.)
211 (44.3)
210 (44.0)
0.96 (0.73, 1.26)
Present
217 (45.6)
214 (44.9)
1.00 (ref.)
Null
259 (54.4)
263 (55.1)
0.96 (0.73, 1.27)
0.7556
0.7891
a
Adjusted for smoking history, alcohol intake, total calorie intake, and education level
various carcinogens, such as AFB1, aromatic amines, heterocyclic aromatic amines, nitroaromatic amines, and polycyclic aromatic hydrocarbons [39, 40]. Although CYP1A2 is expressed primarily in the liver, it is also
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1970
Cancer Causes Control (2013) 24:1963–1972
Table 5 Gastric cancer risk based on genotypes of CYP1A2, EPHX1, GSTT1, and GSTM1 and AFB1 intake level Genotype
AFB1 intake levela
p for interaction
Low
High
Controls/cases
ORb (95 % CI)
Controls/cases
ORb (95 % CI)
160/132
1.00 (ref.)
148/203
1.98 (1.38, 2.84)
78/53
0.72 (0.46, 1.15)
86/85
1.37 (0.89, 2.10)
T/T
210/164
1.00 (ref.)
211/258
1.92 (1.39, 2.65)
T/G ? G/G
28/22
1.00 (0.52, 1.91)
26/32
2.02 (1.03, 3.99)
CYP1A2 rs2470890 C/C C/T ? T/T CYP2E1 rs8192773
0.9046
0.9302
EPHX1 rs2292568
0.6685
C/C
180/137
1.00 (ref.)
169/210
2.13 (1.48, 3.06)
C/T ? T/T
58/46
1.33 (0.80, 2.21)
65/81
2.06 (1.31, 3.22)
Present
120/103
1.00 (ref.)
145/164
1.54 (1.03, 2.31)
Null
119/83
0.77 (0.50, 1.17)
92/127
1.92 (1.25, 2.95)
GSTT1
0.0783
GSTM1
0.8176
Present
104/76
1.00 (ref.)
113/138
1.81 (1.16, 2.81)
Null
135/110
0.94 (0.61, 1.45)
124/153
1.92 (1.25, 2.97)
a
Categorized by the median AFB1 intake value (1.56 ng/kg bw/day) among the control subjects
b
Adjusted for smoking history, alcohol intake, total calorie intake, and education level
observed in the epithelial cells of the gastrointestinal tract in the small intestine, glandular stomach, and gastric mucosa in the form of intestinal metaplasia [41]. Several studies have reported an association between CYP1A2 genetic polymorphisms and gastric cancer risk [42–44]; however, the results of these studies were inconsistent due to the heterogeneity of CYP1A2 enzyme activity based on ethnicity and altered inducibility of CYP1A2 expression by environmental chemicals [45, 46]. In the present study, although the CYP1A2 rs2470890 C/T genotype was significantly associated with gastric cancer risk (OR 0.72; 95 % CI 0.52–0.98), the effect of AFB1 intake on gastric carcinogenesis was not modified by genetic polymorphisms of CYP1A2. Guengerich et al. [16] reported that CYP3A4 is directly involved in the activation of AFB1, whereas CYP1A2 plays a small role in the formation of reactive products. EPHX1 usually catalyzes the hydrolysis of AFBO, which is the critical electrophilic substance for DNA adduct formation: AFBO is converted to water-soluble dihydrodiols by EPHX1 and then excreted in the urine. However, some dihydrodiols derived from polycyclic aromatic hydrocarbons may be subjected to additional metabolic activation to become more reactive diol-epoxides [17, 20, 42]. Ikeda et al. [43] reported that EPHX1 rs2292568 C[T polymorphism is associated with gastric cancer risk, yet our study did not reveal any statistical significance. Some epidemiologic studies have been performed on the association between GSTs, genetic polymorphisms, and
123
gastric cancer risk, but the results have been inconclusive to date. The absence of GST activity due to deletion was expected to increase the risk of various cancers because GSTs are involved in the detoxification of potential carcinogens. However, in the present study, no GSTT1 and GSTM1 genotypes were associated with gastric cancer risk, confirming the results of previous studies [47–51]. Although not statistically significant, we observed an interaction between AFB1 intake and the GSTT1 genotype (p for interaction = 0.0783). Similarly, it has been reported that a homozygous deletion in GSTM1 modifies the relationship between aflatoxin exposure and HCC [21], and Nan et al. [8] also proposed that GSTM1 polymorphism could modify the effects of some environmental factors on the risk of gastric cancer. These results indicate that although GST polymorphism alone may not be important in gastric carcinogenesis, it may modulate xenobiotic-induced gastric cancer risk. This study has some limitations. First, it was nearly impossible to measure the patients’ actual AFB1 intake prior to cancer development; thus, we estimated those amounts using a highly reproducible semiquantitative FFQ. Clearly, potential misclassification may occur in this process, though all of the information used in this study was obtained by interviewing each subject directly rather than using self-reported data. Additionally, all of the cases and matched controls were from the same populations, and thus, the likelihood of population stratification and observational bias would be attenuated. Second, we did not assess H. pylori infection status or history, though it is the
Cancer Causes Control (2013) 24:1963–1972
most important risk factor for gastric cancer. Third, we tested only nine SNPs in AFB1 metabolic enzymes and did not find any evidence that genetic polymorphisms of these AFB1 metabolic enzymes influence the effect of AFB1 intake on the risk of gastric cancer. It is plausible that other genetic polymorphisms not examined in this study modify the AFB1 effect or that the bioactivation of AFB1 may not be an essential element for AFB1-induced gastric cancer. In addition, our study may have insufficient statistical power to identify certain associations between AFB1metabolizing polymorphisms and gastric cancer. In conclusion, the results of this study suggest that dietary AFB1 intake may increase the risk of gastric cancer. The effect of dietary AFB1 exposure on gastric carcinogenesis may not be modulated by genetic polymorphisms of AFB1 metabolic enzymes, such as CYP1A2, CYP2E1, EPHX1, GSTT1, and GSTM1. Acknowledgments This study was supported by a grant from the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (1120330). Conflict of interest
None.
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