The effects of diet on DNA bulky adduct levels are strongly modified by GSTM1 genotype: a study on 634 subjects

Domenico Palli7, Giovanna Masala1, Marco Peluso1, Laura Gaspari2, Vittorio Krogh3, Armelle Munnia1, Salvatore Panico4, Calogero Saieva1, Rosario Tumino5, Paolo Vineis6 and Seymour Garte2

1 Molecular and Nutritional Epidemiology Unit and Cancer Risk Factor Branch, Molecular Biology Laboratory—CSPO, Scientific Institute of Tuscany, Florence, 2 Genetics Research Institute, Milan, 3 Epidemiology Unit, INT, Milan, 4 Department of Clinical and Experimental Medicine, Federico II University, Naples, 5 Registro Tumori, A.O. ‘Civile-M.P. Arezzo’, Ragusa and 6 Cancer Epidemiology Unit, CPO, Turin, Italy


    Abstract
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Frequent consumption of fresh fruit and vegetables, and polymorphisms in the detoxifying enzyme glutathione S-transferase M1 (GSTM1) and other metabolic genes have been shown to modulate cancer risk at some sites. We have shown recently that DNA adducts, a reliable indicator of genotoxic damage and, possibly, of cancer risk, are modulated by plasma levels of selected micronutrients. Here we further investigate the association between DNA adduct levels and consumption of major food groups and foods, and the estimated dietary intake of nutrients, taking into account the possible modifying effect of metabolic polymorphisms, in a larger sample of 634 healthy adults enrolled in a prospective study in Italy. DNA adducts and five polymorphic metabolic genotypes (GSTM1, GSTT1, NAT2, CYP1A1 and MTHFR) were determined in peripheral leukocytes by using 32P-postlabeling technique and PCR methods. DNA bulky adducts (mean: 7.82 ± 0.40/109 nt) were detected in 482/634 samples (76.0%). Overall, DNA adduct levels were significantly and inversely associated with the intake of raw leafy vegetables (P = 0.02), non-citrus fruits (P = 0.04), potassium (P = 0.01) and ß-carotene (P = 0.05). No association was evident with the five genotypes. Stratification by GSTM1 genotype showed strong inverse associations of DNA adduct levels with increasing consumption of all vegetables combined (P = 0.04), leafy vegetables (P = 0.004), raw leafy vegetables (P = 0.002) and fish (P = 0.03) among 307 GSTM1-null subjects; strong inverse associations also emerged with estimated dietary intakes of ß-carotene (P = 0.004), vitamin E (P = 0.004), niacin (P = 0.02) and potassium (P = 0.01). In contrast, no association emerged among 295 subjects with a GSTM1-wild genotype. Overall, statistically significant interactions in predicting DNA adduct levels were observed between the GSTM1-null genotype and consumption of leafy vegetables (P = 0.01), white meat (P = 0.04), and intake of vitamin C (P = 0.04), vitamin E (P = 0.05) and ß-carotene (P = 0.02). Our results suggest that the role of a diet rich in antioxidants in preventing or reducing DNA adduct formation is restricted to subjects lacking the detoxifying activity of GSTM1 isoenzyme (~50% of the general population).

Abbreviations: BMI, body mass index; CYP1A1, human cytocrome P450 1A1 gene; GSTM1, glutathione S-transferase M1; MTHFR, methylene-tetra-hydrofolate reductase; NAT, N-acetyl-transferase 2; PAH, polycyclic aromatic hydrocarbons


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Several epidemiological studies suggest that polymorphic genes controlling the metabolism of carcinogens and nutritional status are both associated with cancer risk. Dietary habits characterized by frequent consumption of fresh fruit and vegetables have been associated with a reduced risk of cancer at several sites (13). Results are particularly consistent for cancer of the gastrointestinal tract and for lung cancer even if the results of some large prospective studies have not confirmed these associations (46). Similar protective associations emerged when the dietary intakes of selected micronutrients were considered, although less consistently, possibly due to the well known difficulties in the assessment of nutrient intake. Genetic polymorphisms of several phase I (activation) and phase II (detoxification) enzymes have been shown to play a role in the modulation of cancer risk, although with contrasting results. Among the detoxification systems, the GST (glutathione S-transferase) enzyme polymorphisms have been studied particularly in smoke-related cancers. Polymorphisms in these metabolic genes have been linked to increased risk of cancer in several case-control studies (7). The genetic deficiency in the detoxifying enzyme glutathione S-transferase M1 (GSTM1-null genotype) has been associated with a moderately increased risk of lung (8,9) and bladder cancer (10). Interactions between dietary exposures and genetic polymorphisms are receiving increasing attention. An effect modification of a high intake of cruciferous vegetables on colorectal cancer risk in GSTM1-null subjects has been reported (11,12). Further research is needed to take into account the combined effect of different polymorphisms and diet in cancer etiology.

DNA adducts have been used widely in order to identify health hazards and to evaluate the dose–response relationship in humans exposed to carcinogens and mutagenic compounds and are considered a biomarker of internal dose. DNA adducts tend to be higher among subjects heavily exposed to air pollutants, such as police officers and bus drivers (1315), and it has been suggested that high levels of DNA adducts might be predictive of cancer risk, reflecting both the exposure to environmental xenobiotics and genetic and acquired susceptibility to carcinogens (1619). We have suggested previously that DNA adduct levels might be modulated by diet (20) and by a group of dietary intake biomarkers (21). In particular, in the latter study, we have shown that individual levels of DNA adducts were modulated by plasma levels of a few selected micronutrients: six specific carotenoids, {alpha}- and {gamma}-tocopherol and retinol were measured in the same blood sample donated at enrollment by a group of 331 individuals (21).

The genetic deficiency in the detoxifying enzyme GSTM1-null genotype has been associated with increased PAH (polycyclic aromatic hydrocarbons)–DNA (22) and 4-aminobiphenyl hemoglobin (23) adducts. In a study, PAH–DNA adduct levels have been reported to be inversely correlated with vitamin E and also with smoking-adjusted vitamin C in GSTM1-null genotype subjects (24). Mooney et al. (25) reported a similar inverse association between plasma levels of retinol, ß-carotene and {alpha}-tocopherol and PAH–DNA adducts in subjects lacking the GSTM1 detoxification gene. In contrast, one study (26) did not report any association between the plasma levels of ß-carotene and {alpha}-tocopherol and level of DNA adducts in lymphocytes.

Here we further investigated the association between DNA adduct levels and consumption of major food groups and foods, and questionnaire-derived estimates of intake of major macronutrients and micronutrients, taking into account the role of selected metabolic polymorphisms and, particularly, their potential modifying effects. The loci chosen, CYP1A1, NAT2, MTHFR, GSTM1 and GSTT1, have all been implicated in the metabolism of various dietary components and toxicants, and each are polymorphic in the European population. The present study was based on a larger sample of 634 healthy adults, both sexes, aged 35–64 years, randomly sampled among a large series of over 47 000 volunteers enrolled in the Italian EPIC (European Prospective Investigation into Cancer and Nutrition) cohort.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Subjects
EPIC-Italy is the Italian section of the large prospective European project EPIC (27); recruitment of volunteers was carried out in the period January 1993–March 1998. Overall 47 749 residents, men and women, have been enrolled in the age interval of 35–64 years, in five participating centers, across different areas of the country: Varese (12 083 volunteers) and Turin (10 604) in the Northern part of the country; Florence (13 597) in Central Italy; Ragusa (6403) and Naples (5062 women) in Southern Italy (28).

A random sample of approximately 110 subjects, stratified by age, sex and center, was selected from each of the three main geographical study areas, Northern, Central and Southern Italy (21), and added to the previous sample of 308 participants (20), in order to obtain a larger combined sample of volunteers representative of the national cohort. Overall, results were thus available for 634 subjects (216, 208 and 210 adults of both sexes from the three main areas, respectively). In Southern Italy, where one center had enrolled only women, the final sample included 102 men and 54 women from Ragusa (Sicily) and 54 women from Naples.

Diet and life-style questionnaires
Dietary information on the frequency of consumption of more than 120 foods and drinks in a 12-month period prior to enrollment was obtained by a self-administered Food Frequency Questionnaire, validated in a pilot phase (29). All individual questionnaires were checked and coded by trained dieticians, computerized and then transformed into estimates of intake for a series of over 30 nutrients according to specifically developed Italian Food Tables (30). At enrollment, weight, height, waist and hip circumferences were measured for each participant, according to the international study protocol. A standardized life-style questionnaire, representing the Italian translation of a common English model adopted by all European centers (in two separate versions for men and women), was also filled out by each participant (28).

Blood collection and storage
Informed consent was obtained from all subjects prior to enrollment in the study. The project has been approved by the local Ethical Committee in Florence. Blood samples were collected in citrate tubes and processed by centrifugation in a dedicated laboratory in each center, on the same day of collection, divided into 28 aliquots of 0.5 ml each (12 plasma, eight serum, four concentrated red blood cells and four buffy coat), using an automatic aliquoting and sealing machine specifically developed by BICEF, France (Cryo-Bio Straw). The aliquots were stored in liquid nitrogen tanks at -196°C in a local biological bank in each center in Italy. Straws were retrieved and shipped in dry ice to laboratories for DNA extraction, DNA adduct analyses and for metabolic polymorphisms.

Laboratory methods
32P-DNA postlabeling technique
Leukocyte DNA was isolated and purified from stored buffy coats by enzymatic digestion of RNA and proteins followed by phenol–chloroform extractions (20). DNA samples (5 µg) were digested with 0.21 U of micrococcal nuclease and 0.174 U of spleen phosphodiesterase at 37°C for 4.5 h. After treatment of DNA samples with 5 µg of nuclease P1 for 30 min at 37°C, the hydrolysate enriched in adducted nucleotides were then labeled by incubation with 24 µCi of carrier free [{gamma}-32P]ATP (3000 Ci/mM) and 10 U of T4 polynucleotide kinase at 37°C for 30 min in 25 µl of bicine buffer mixture. Resolution of 32P-labeled DNA digests treated with nuclease P1 was carried out on PEI-cellulose TLC plates using the contact-transfer technique (20). The solvent systems selected were: (D1) 1 M sodium phosphate pH 6.8; (D3) 4 M lithium formate, 7.5 M urea, pH 3.5; (D4) 0.65 M LiCl, 0.45 M Tris–HCl, 7.7 M urea pH 8.0; (D5) 1.7 M sodium phosphate pH 5.0. The adduct spots were detected by autoradiography from 72 to 96 h at -80°C using Kodak XAR-5 films and intensifying screens. DNA adduct levels were determined by excising areas of chromatograms and measuring the levels of radioactivity present by Cerenkov counting. The results were expressed as relative adduct labeling = c.p.m. in adduct nucleotides/c.p.m. in total nucleotides. The detection limit of nuclease P1 modification of the 32P-DNA postlabeling technique was 0.1 adduct/109 nt, as reported previously (20). The reproducibility of the 32P-DNA postlabeling technique was verified analysing ~20% of DNA samples with a second independent experiment and the results of the two analyses were in perfect agreement (r = 0.98). All the analyses were carried out blindly prior to decoding. One standard was routinely included in the analysis, i.e. benzo[a]pyrene DNA adducts, from the liver of mice treated intraperitoneally with 0.06 mg/kg B[a]P for 24 h. The average levels of B[a]P DNA adducts were 5.1 ± 0.1 (SE, standard error) per 108 nucleotides.

Polymorphism analysis
A multiple PCR method was used to detect the presence or absence of the GSTM1 and GSTT1 genes and polymorphic alleles at CYP1A1 (human cytocrome P450 1A1 gene) MspI, NAT2 (N-acetyl-transferase 2) and MTHFR (methylene-tetra-hydrofolate reductase) loci in genomic DNA samples (obtained from stored buffy coats as described in the previous section).

GST
This method had both GST primer sets (GSTM1 5'-AACTCCCTGAAAAGCTAAAGC 5'-GTTGGGCTCAAATATACGGTGG and GSTT1 5'-TCCTTACTGGTCCTCACATCTC 5'-TCACCGGATCATGGCCAGCA) in the same PCR included a third primer set for albumin (5'-GCCCTCTGCTAACAAGTCCTAC, 5'-CCCTAAAAAGAAAATCGCCAATC) and used 30 cycles with denaturing at 94°C for 1 min, annealing at 64°C for 1 min, and extension at 72°C for 1 min.

CYP1A
DNA was amplified in a total reaction volume of 50 µl containing 1.2 mM dNTP, 1.2 µM oligonucleotide primers and 2.5 U Taq polymerase (Amplitaq, Perkin-Elmer, Boston, MA). DNA samples were amplified using the following primers: 5'-CTGACTGGCTTCAGCAAGTT and 3'-TAGGAGTCT TGTCTCATGCCT. PCR was performed for 45 cycles with denaturing at 95°C for 1 min, annealing at 56°C for 1 min and extension at 65°C for 2 min. PCR products were digested with excess MspI (New England Biolabs) for 3 h, and then electrophoresed through 1.8% agarose and visualized by ethidium bromide staining.

NAT2
Three known slow acetylator alleles (NAT2*5, NAT2*6 and NAT2*7) were identified. PCRs was carried out in a total volume of 50 µl using primers: 5'-TGACGGCAGGAATTACATTGTC and 3'-ACACAAGGGTTTATTTTGTTCC. The PCR mixture contained 5 µl DNA, 50 pM of each primer, 200 µM of dNTPs, 1.5 U Taq polymerase (Amplitaq, Perkin-Elmer), 10 mM Tris–HCl buffer, pH 8.3, 50 mM KCl and 1.5 mM MgCl2. PCR was performed for 35 cycles with denaturing at 94°C for 1 min, annealing at 56°C for 1 min, and extension at 72°C for 2 min. PCR products were incubated with restriction enzymes KpnI, TaqI and BamHI from Gibco (Carlsbad, CA). Rapid acetylator genotypes were defined as wild-type (*4) allele homo- or heterozygotes, while slow acetylator genotypes included all those with any two of the three slow acetylator alleles (*5, *6 or *7).

MTHFR (677 C > T)
Primer sequences are 5'-TGAAGGAGAAGGTGTTCTGCGGGA and 5'-AGGACGGTGCGGTCAGAGTG. Amplification was performed using initial denaturation at 95°C for 2 min followed by 29 cycles of 94°C for 30 s, 60°C for 30 s and 72°C for 30 s with a final extension at 72°C for 10 min. The amplified product was then digested with Hinf1 before electrophoresis.

Statistical analysis
To investigate the relationship between DNA adduct levels and dietary habits and metabolic polymorphisms, we compared adduct values for different levels of food group consumption and nutrient intake according to selected polymorphic metabolic genes. Negative samples (those <0.1 adduct/109 normal nt, the threshold of detection of the 32P-post DNA labeling method) were arbitrarily assigned a value of 0.1. In order to carry out statistical analyses, we first divided all available subjects into tertiles of food consumption and nutrient intake. Geometric mean levels of DNA adducts across tertiles of consumption of foods or food groups and intake of nutrients were compared by analysis of covariance, introducing into each model terms for age, sex, center, smoking history (never, former and current), period and year of blood drawing, BMI (body mass index) and total caloric intake. Post hoc Dunnett tests were performed for multiple comparisons among nutrient tertiles. The tests for linear trends were calculated by including ordered variables in each covariance model with log transformed adduct values. The covariance analysis was performed separately according to selected polymorphic metabolic genes.

Multivariate logistic analyses were carried out to evaluate the existence of possible interactions between selected polymorphic metabolic genes and dietary variables in predicting high levels of DNA adducts (based on a dichotomous variable: above/below the median value). The statistical significance of these interactions was evaluated on a multiplicative scale, including an interaction term into a model containing the previously identified potential confounders and the two main effect variables (the metabolic polymorphic gene and each dietary variable); such an interaction means a departure from a multiplicative effect for the two factors combined. All the analyses were performed by the statistical package SAS. A P value <0.05 was considered statistically significant.


    Results
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Study subject characteristics
Results were available for 634 healthy adults (312 men) included in the combined random sample of EPIC Italy volunteers (Table I): 216 from Turin and Varese (108 men), the two centers in Northern Italy, 208 from Florence in Central Italy (102 men) and 210 from the two centers in Southern Italy (Ragusa with 156 subjects, 102 men and 54 women, and Naples with only 54 women). Overall, the mean age was 52.2 years for men and 52.0 years for women (range 35–64 years). The mean values for weight, height and BMI were 78.4 kg, 172 cm and 26.6 kg/m2 for men, and 64.9 kg, 158 cm and 26.0 kg/m2 for women, respectively. Never smokers represented the largest group among participants (255/634 or 40.2%), while 32.2% (204/634) reported themselves as former smokers and 27.0% (171/634) as current smokers.


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Table I. Adjusted geometric meansa of DNA adducts per 109 normal nucleotides, according to several sociodemographic and anthropometric characteristics (EPIC Italy, 634 subjects, 1993–1998)

 
Blood samples were originally obtained at enrollment in the period 1993–1998; the distribution was in agreement with that of the total cohort: 238 samples were drawn in 1993–1994, 294 in 1995–1996 and 102 in 1997 and in the first 2 months of 1998. Samples were obtained all the year round (except August) in all centers, usually with a peak in spring months.

DNA adducts
DNA adducts were detected in 76.0% of the samples, with some variation between centers (lowest in Ragusa 65.4%, and highest in Naples 88.9%) but not between genders (76.3 in males vs 75.8% in females). The crude mean DNA adduct level was 7.82/109 nt (SE ± 0.40). Differences among subjects from the five participating centers were evident: the geometric-adjusted DNA adduct levels were 5.84, 3.56, 2.22, 1.62 and 1.20 for volunteers from Naples, Florence, Varese, Turin and Ragusa, respectively. While the 54 subjects (all women) from Naples showed higher levels than the 208 participants from Florence (reference group), samples from Turin and Ragusa showed significantly lower levels than those from Florence. Only minor differences were found according to gender and smoking history. DNA adduct values tended to vary according to BMI, with lower values among overweight subjects.

Overall, DNA adduct values tended to decrease during the 5-year study period, the geometric mean being, respectively, 3.15 in the first 2-year period of enrollment (1993–1994), 2.65 in the period 1995–1996 and 1.78 in the period 1997–1998 (P for trend = 0.05) (Table I).

No statistically significant differences were evident (overall and according to study center) in the mean level of DNA adducts between the first and the second group of approximately 300 subjects sampled from the EPIC Italy cohorts. Within each group the dates of enrollment of volunteers were randomly distributed across the 5-year period. Overall, the geometric mean values of DNA adduct levels were 2.3 and 2.47/109 nt, respectively, in the first and the second group of samples.

DNA adducts and diet
In the analyses carried out in the whole sample of 634 EPIC volunteers a negative association of DNA adduct levels was found with the reported frequency of consumption of raw leafy vegetables and fresh fruit other than citrus fruit (Table II). Negative associations emerged also with the estimated intakes of potassium (P for trend = 0.01), niacin (P for trend = 0.04) and ß-carotene (P for trend = 0.05) (Table III).


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Table II. Adjusted geometric meansa of DNA adducts per 109 normal nucleotides according to tertiles of average consumption of selected food groups or food items (EPIC Italy, 634 subjects, 1993–1998)

 

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Table III. Adjusted geometric meansa of DNA adducts per 109 normal nucleotides according to tertiles of estimated intake of selected nutrients (EPIC Italy, 634 subjects, 1993–1998)

 
DNA adducts and metabolic polymorphisms
The frequencies of GSTM1 and GSTT1-null genotypes in this series were 51.0 and 20.7%, respectively (Table IV). The frequencies of CYP1A1 polymorphic, NAT2 slow and MTHFR TT homozygous genotypes were 21.9, 52.9 and 20.0%, respectively. DNA adducts did not show any variation according to GSTM1 genotypes, but tended to be higher in subjects with the GSTT1-null genotype (geometric mean values: 3.04 vs 2.30/109 nt). No association between DNA adduct levels and CYP1A1, NAT2 and MTHFR genotypes was evident.


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Table IV. Adjusted geometric meansa of DNA adducts per 109 normal nucleotides according to genotype for selected metabolic polymorphisms (EPIC Italy, 634 subjects, 1993–1998)

 
DNA adducts, diet and metabolic polymorphisms
When we considered the association between DNA adducts and the consumption of selected foods and food groups in study subjects according to GSTM1 genotype, strong inverse associations were found with increasing consumption of total vegetables (all types combined) among the 307 GSTM1-null subjects; the same effect was particularly evident for leafy vegetables (and particularly for raw leafy vegetables). In addition, among GSTM1-null subjects, DNA adducts were negatively associated with increasing consumption of fish (Table V). On the other hand, among GSTM1 wild-type subjects, no association emerged for any food or food group analysed (Table VI).


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Table V. Adjusted geometric meansa of DNA adducts per 109 normal nucleotides according to tertiles of average consumption of selected food groups or food items in 307 GSTM1-null subjects (EPIC Italy, 1993–1998)

 

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Table VI. Adjusted geometric meansa of DNA adducts per 109 normal nucleotides according to tertiles of average consumption of selected food groups or food items in 295 GSTM1 wild-type subjects (EPIC Italy, 1993–1998)

 
Several strong inverse associations between DNA adduct level and estimated intakes of some micronutrients with antioxidant properties (ß-carotene and vitamin E), niacin and potassium, emerged among GSTM1-null subjects. Vitamin C (P = 0.08) and vegetable fat (P = 0.06) also tended to be negatively associated with DNA adduct levels (Table VII).


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Table VII. Adjusted geometric meansa of DNA adducts per 109 normal nucleotides according to tertiles of estimated average intake of various nutrients in 307 GSTM1-null subjects (EPIC Italy, 1993–1998)

 
No association emerged when the same analysis was carried out in the stratum of 295 GSTM1 wild-type subjects (Table VIII).


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Table VIII. Adjusted geometric meansa of DNA adducts per 109 normal nucleotides according to tertiles of estimated average intake of various nutrients in 295 GSTM1 wild-type subjects (EPIC Italy, 1993–1998)

 
Statistically significant interactions in predicting high DNA adduct levels (above the median level) were observed between the GSTM1-null genotype and the consumption of leafy vegetables (P = 0.01) and white meat (P = 0.04). When micronutrients were considered, interactions were also evident between GSTM1-null genotype and the intakes of all the major antioxidants, namely vitamin C (P = 0.04), vitamin E (P = 0.05) and ß-carotene (P = 0.02) (Table IX).


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Table IX. Statistically significant interactions between GSTM1-null genotype and food consumption or nutrient intake tertiles, in determining the individual levels of DNA adducts per 109 normal nucleotides (above/below the median) (EPIC Italy, 634 subjects, 1993–1998)

 
No modification of dietary effects on DNA adduct levels was evident when all other polymorphic genotypes were considered.


    Discussion
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Our results show that the strong inverse associations we found between vegetable consumption and dietary intake of antioxidants and DNA adduct levels, are restricted to GSTM1-null subjects. An inverse association between fish consumption and DNA adduct levels was also evident only among GSTM1-null subjects. In addition, when we explored the existence of statistical interactions between food or nutrient intakes and the GSTM1 polymorphism in determining high DNA adduct levels, a strong effect modification emerged for GSTM1-null genotype and high consumption of leafy vegetables and white meat. Additional statistically significant interactions between GSTM1-null genotype and high intakes of ß-carotene, vitamin C and E were also evident.

In this study, carried out in a large sample of healthy adults, both sexes, enrolled in the Italian EPIC cohorts, we evaluated the association between DNA adduct levels and consumption of selected foods and intake of macronutrients and micronutrients, taking into account the effect of metabolic polymorphisms. When analyses were carried out considering the whole series of 634 subjects, we found an inverse association of DNA adduct levels with high consumption of leafy raw vegetables and non-citrus fruit. An inverse association with high intakes of potassium, ß-carotene and niacin was also evident considering the whole dataset. In addition, we did not observe an independent effect of GSTM1-null genotype or any other selected metabolic polymorphic genotype on DNA adduct levels.

Our results thus show a clear modulating role of GSTM1 polymorphic genotype on the effects of diet on DNA adduct levels, in agreement with our previous findings (21). An interaction between GSTM1-null genotype and high consumption of cruciferous vegetables has been described in relation to development of adenomas (31) and colorectal cancer (11,12). This gene–environment interaction seems to be quite complex considering that active compounds identified (including isothiocyanates and indoles) are believed to inhibit phase I activating enzymes and induce phase II detoxification enzymes and this mechanism could explain the protective effect of high consumption of these vegetables through an effect on the metabolism of pro-carcinogens, a mechanism that has been suggested also for other cancer sites. On the other hand, GST enzymes also metabolize isothiocyanates, and subjects with low or no activity of GST enzymes could metabolize at a lower rate these compounds, thus reducing the risk in this subgroup of subjects (enhancing their protective effect). In a prospective study carried out in men in Shangai, subjects with detectable isothiocyanates in the urine collected at the enrollment were at decreased risk for lung cancer; this effect, however, was primarily evident in subjects with homozygous deletion of GSTM1 (32).

Although understanding the mechanism of GSTM1 polymorphism/dietary interaction will require further research into specific patterns of DNA adducts found in wild-type and null individuals, we can speculate that our data are consistent with a model in which GSTM1 and some components in dietary vegetables both act to reduce DNA adduct formation. GSTM1-null individuals would suffer an increase in levels of toxic metabolites (which cannot be removed by GST) and therefore of adducts, unless they consume sufficient amount of vegetables to block adduct formation.

Both diet and metabolic polymorphisms can affect DNA adduct levels. Antioxidant compounds such as vitamins C, E and ß-carotene may act directly to inhibit oxidants and hence reduce DNA damage, while GST can catalyze the conjugation reaction between glutathione and substrates with electrophilic sites, increasing the detoxification of several procarcinogens.

We have shown previously that the consumption of fresh fruit and vegetables and the intake of several related micronutrients (including all major anti-oxidants) are relevant determinants of DNA adduct levels in a population exposed to genotoxic agents commonly present in the environment (20). Dietary constituents in fresh fruit and vegetables might play a relevant role in DNA adduct formation by inducing or inhibiting enzymatic activities (33,34). Anti-oxidant micronutrients have been shown experimentally to inhibit DNA damage by PAH and other carcinogens and to alter the expression of metabolic enzymes (35,36). Animal studies have shown that natural compounds present in human diet are able to induce GST activities and reduce DNA adduct formation by PAH (37).

An inverse association between blood levels of {alpha}-tocopherol and vitamin C and PAH–DNA adducts in lymphocytes of subjects with the GSTM1-null genotype was found in a cross-sectional study on 63 male heavy cigarette smokers (24). A similar inverse association was reported between plasma levels of retinol, ß-carotene and {alpha}-tocopherol and PAH–DNA adducts in subjects lacking the GSTM1 detoxification gene in a study carried out on 159 current smokers (25). Another study (26) did not report any association between the plasma levels of ß-carotene and {alpha}-tocopherol and level of DNA adducts in lymphocytes. Recently, we have found that plasma levels of antioxidant vitamins may play an important role in inhibiting DNA adduct formation in subjects who do not have the capacity to detoxify carcinogens via the GSTM1 pathway (21). Specific patterns of associations between antioxidant levels and DNA adducts emerged when analyses were carried out stratifying by GSTM1 genotype, with high plasma levels of {alpha}- and ß-carotene showing an effect only among GSTM1-null subjects.

A similar effect on DNA adduct levels was also reported by us for high plasma levels of retinol (21). No effect of preformed retinol intake on DNA adduct level was evident in the present study considering either the whole series of 634 subjects or in the analyses carried out according to GSTM1 genotypes. Nevertheless, we have to consider that ß-carotene and other carotenoids are converted to retinol in many tissues and the effect we observed in relation to plasma levels of retinol could be actually related to dietary intake of its precursors.

An inverse association of high dietary level of niacin with DNA adduct levels was found in subjects with GSTM1-null genotype. Niacin is the generic descriptor for NA (nicotinic acid) and NAM (nicotinamide) that are both dietary precursors of NAD+ (nicotinamide adenine nucleotide) the substrate for the enzyme PARP [poly(ADP-ribose) polymerase]-1. This enzyme activated by DNA strand breaks has been shown to be involved in the BER pathway (38). A role of PARP-1 has been also suggested in the repair of bulky DNA adducts (39), but a study that attempted to evaluate the role of niacin supplementation on DNA damage (cytogenetics damage) in a group of smokers did not find evidence of this effect on peripheral blood lymphocytes (40).

Our finding of an inverse association between a high consumption of fish and DNA bulky adduct levels is consistent with previous animal studies reporting an inhibitory effect of fish oil, rich in {omega}-3 fatty acids, on DNA adduct formation following dietary exposure to heterocyclic amines (41,42). We have no explanation for the inverse association with white meat, although a high consumption of this source of animal proteins could be a marker of ‘prudent diet’, in contrast to consumption of red or preserved meats; in a cross-sectional study within the Italian EPIC cohorts the consumption of poultry correlated with plasma {omega}-3 fatty acids (43).

The results of the assays for the two random samples of approximately 300 subjects (20,21), which were combined for the present study, were compared and the mean values did not differ. In addition, within each group the dates of enrollment of volunteers were randomly distributed across the 5-year period. The decrease of DNA adduct levels during the study period is thus probably due to a parallel decrease in the exposure to vehicle traffic pollutants, following major decisions at the national level during the mid 1990s (including modifications of fuels, large-scale introduction of catalytic exhaust systems, banning of older vehicle models). We have carried out previously a specific analysis for the Florence volunteers because of the availability of additional information on environmental concentrations of pollutants and occupational exposures (15) showing higher levels in traffic-exposed workers in comparison with randomly sampled volunteers. Overall, determinants of DNA adduct levels appear to be strongly related to vehicle traffic and, possibly, photochemical pollution in warmer months.

Overall, our results show an important role of antioxidants in preventing DNA adduct formation when the detoxifying activity of GSTM1 isoenzyme is lacking. Information about this and other metabolic polymorphisms should be included in the design and analysis of molecular epidemiology studies focused on diet and genotoxic damage (or cancer), in order to better understand possible associations. Approximately 50% of the general population is represented by GSTM1-null individuals: thus current dietary guidelines including recommendations to increase the consumption of fresh fruit and vegetables are supported by these findings.


    Notes
 
7 To whom correspondence should be addressed Email: d.palli{at}cspo.it Back


    Acknowledgments
 
The authors wish to thank the cooperation of all study participants and collaborators of EPIC Italy Study Group, A.Decarli (University of Brescia) for helpful comments and M.Ceroti (CSPO, Florence) for support with statistical analyses. EPIC Italy has been supported by a long-term generous grant from Associazione Italiana per la Ricerca sul Cancro (AIRC, Milan), to D.P. The study has been carried out in cooperation with several local organizations (AVIS, Turin; UNICOOP, Florence; AVIS, Ragusa). EPIC is coordinated at the international level by Elio Riboli (IARC, Lyon) and supported by the European Union (DG SANCO-SPC 2002332).


    References
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

  1. Willett,W.C. (2000) Diet and cancer. Oncologist, 5, 393–404.[Abstract/Free Full Text]
  2. Key,T.J., Allen,N.E., Spencer,E.A. and Travis, R.C. (2002) The effect of diet on risk of cancer. Lancet, 360, 861–868.[CrossRef][ISI][Medline]
  3. Kasum,C.M., Jacobs,D.R.,Jr, Nicodemus,K. and Folsom,A.R. (2002) Dietary risk factors for upper aerodigestive tract cancers. Int. J. Cancer, 99, 267–272.[CrossRef][ISI][Medline]
  4. Botterweck,A.A., Van den Brandt,P.A. and Goldbohm,R.A. (1998) A prospective cohort study on vegetable and fruit consumption and stomach cancer risk in the Netherlands. Am. J. Epidemiol., 148, 842–853.[Abstract]
  5. Rohan,T.E., Jain,M., Howe,G.R. and Miller,A.B. (2002) A cohort study on dietary carotenoids and lung cancer risk in women (Canada). Cancer Causes Control, 3, 231–237.
  6. Terry,P., Giovannucci,E., Michels,K.B., Bergkvist,L., Hansen,H., Holmberg,L. and Wolk,A. (2001) Fruit, vegetables, dietary fiber, and risk of colorectal cancer. J. Natl Cancer Inst., 93, 525–533.[Abstract/Free Full Text]
  7. D'Errico,A., Malats,N., Vineis,P. and Boffetta,P. (1999) Reviews of studies of selected metabolic polymorphisms and cancer. In Vineis,P., Malats,N., Lang,M., D'Errico,A., Caporaso,N.E., Cuzick,J. and Boffetta,P. (eds) Metabolic Polymorphisms and Susceptibility to Cancer. IARC Scientific Publications, IARC, Lyon, vol. 148, pp. 323–393.
  8. Strange,R.C. and Fryer,A.A. (1999) The Glutathione S-Transferases: Influence of Polymorphism on Cancer Susceptibility. IARC Scientific Publications, IARC, Lyon, vol. 148, pp. 231–249.
  9. Nair,U. and Bartsch,H. (2001) Metabolic Polymorphisms as Susceptibility Markers for Lung and Oral Cavity Cancer. IARC Scientific Publications, IARC, Lyon, vol. 154, pp. 271–290.
  10. Engel,L.S., Taioli,E., Pfeiffer,R. et al. (2002) Pooled analysis and meta-analysis of glutathione S-transferase M1 and bladder cancer: a HuGE review. Am. J. Epidemiol., 56, 95–109.
  11. Seow,A., Yuan,J.M., Sun,C.L., Van Den Berg,D., Lee,H.P. and Yu,M.C. (2002) Dietary isothiocyanates, glutathione S-trasferase polymorphisms and colorectal cancer risk in the Singapore Chinese Health Study. Carcinogenesis, 23, 2055–2061.[Abstract/Free Full Text]
  12. Slattery,M.L., Kampan,E., Samowitz,W., Caan,B.J. and Potter,J.D. (2000) Interplay between dietary inducers of GST and GSTM-1 genotype in colon cancer. Int. J. Cancer, 87, 728–733.[CrossRef][ISI][Medline]
  13. Nielsen,P.S., De Pater,N., Okkels,H. and Autrup,H. (1996) Environmental air pollution and DNA adducts in Copenhagen bus drivers. Effect of GSTM1 and NAT2 genotypes on adduct levels. Carcinogenesis, 17, 1021–1027.[Abstract]
  14. Peluso,M., Merlo,F., Munnia,A., Valerio,F., Perrotta,A., Puntoni,R. and Parodi,S. (1998) 32P-Postlabeling detection of aromatic adducts in the white blood cell DNA of nonsmoking police officers. Cancer Epidemiol. Biomarkers Prev., 7, 3–11.[Abstract]
  15. Palli,D., Russo,A., Masala,G., Saieva,C., Guarrera,S., Carturan,S., Munnia,A., Matullo,G. and Peluso,M. (2001) DNA adduct levels and DNA repair polymorphisms in traffic-exposed workers and a general population sample. Int. J. Cancer, 94, 124–127.
  16. Vineis,P. and Perera,F. (2000) DNA adducts as markers of exposure to carcinogens and risk of cancer. Int. J. Cancer, 88, 325–328.[CrossRef][ISI][Medline]
  17. Veglia,F., Matullo,G. and Vineis,P. (2003) Bulky DNA adducts and risk of cancer: a meta-analysis. Cancer Epidemiol. Biomarkers Prev., 12, 157–160.[Abstract/Free Full Text]
  18. Peluso,M., Airoldi,L., Munnia,A., Martone,T., Coda,R. and Malaveille,C. (1998) White blood cell DNA adducts, smoking, and NAT2 and GSTM1 genotypes in bladder cancer. A case-control study. Cancer Epidemiol. Biomarkers Prev., 7, 341–346.[Abstract]
  19. Tang,D., Phillips,D.H., Stampfer,M. et al. (2001) Association between carcinogen DNA adducts in white blood cells and lung cancer risk in the physicians health study. Cancer Res., 61, 6708–6712.[Abstract/Free Full Text]
  20. Palli,D., Vineis,P., Russo,A. et al. (2000) Diet, metabolic polymorphisms and DNA adducts: the EPIC—Italy cross-sectional study. Int. J. Cancer, 87, 444–451.[CrossRef][ISI][Medline]
  21. Palli,D., Masala,G., Vineis,P. et al. (2003) Biomakers of dietary intake of micronutrients modulate DNA adduct levels in healthy adults. Carcinogenesis, 24, 739–746.[Abstract/Free Full Text]
  22. Rundle,A., Tang,D., Zhou,J., Cho,S. and Perera,F.P. (2000) The association between glutathione S-transferase M1 genotype and polycyclic aromatic hydrocarbon-DNA adducts in breast tissue. Cancer Epidemiol. Biomarkers Prev., 9, 1079–1085.[Abstract/Free Full Text]
  23. Yu,M.C., Ross,R.K., Chan,K.K., Henderson,B.E., Skipper,P.L., Tannenbaum,S.R. and Coetzee,G.A. (1995) Glutathione S-transferase M1 genotype affects aminobiphenyl-hemoglobin adduct levels in white, black and Asian smokers and nonsmokers. Cancer Epidemiol. Biomarkers Prev., 4, 861–864.[Abstract]
  24. Grinberg-Funes,R.A., Singh,V.N., Perera,F.P., Bell,D.A., Young,T.L., Dickey,C., Wang,L.W. and Santella,R.M. (1994) Polycyclic aromatic hydrocarbon-DNA adducts in smokers and their relationship to micronutrient levels and the glutathione-S-transferase M1 genotype. Carcinogenesis, 15, 2449–2454.[Abstract]
  25. Mooney,L.A., Bell,D.A., Santella,R.M. et al. (1997) Contribution of genetic and nutritional factors to DNA damage in heavy smokers. Carcinogenesis, 18, 503–509.[Abstract]
  26. Wang,Y., Ichiba,M., Oishi,H., Iyadomi,M., Shono,N. and Tomokuni,K. (1997) Relationship between plasma concentrations of ß-carotene and {alpha}-tocopherol and life-style factors and levels of DNA adducts in lymphocytes. Nutr. Cancer, 27, 69–73.[ISI][Medline]
  27. Riboli,E., Hunt,K.J., Slimani,N. et al. (2002) European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection. Public Health Nutr., 5, 1113–1124.[CrossRef][ISI][Medline]
  28. Palli,D., Berrino,F., Vineis,P. et al. on behalf of EPIC-Italy. (2003) A molecular epidemiology project on diet and cancer: the EPIC-Italy prospective study. Design and baseline characteristics of participants. Tumori, 89, 586–593.[ISI][Medline]
  29. Pisani,P., Faggiano,F., Krogh,V., Palli,D., Vineis,P. and Berrino,F. (1997) Relative validity and reproducibility of a food-frequency dietary questionnaire for use in the Italian EPIC centres. Int. J. Epidemiol., 26, S152–S160.[Abstract/Free Full Text]
  30. Salvini,S., Parpinel,M., Gnagnarella,P., Maisonneuve,P. and Turrini,A. (eds) (1998) Banca Dati di Composizione degli Alimenti per Studi Epidemiologici in Italia. Istituto Europeo di Oncologia, Milan.
  31. Lin,H.J., Probst-Hensch,N.M., Louie,A.D., Kau,I.H., Witte,J.S., Ingles,S.A., Frankl,H.D., Lee,E.R. and Haile,R.W. (1998) Glutathione transferase null genotype, broccoli, and lower prevalence of colorectal adenomas. Cancer Epidemiol. Biomakers Prev., 7, 647–652.[Abstract]
  32. London,S.J., Yuan,J.-M., Chung,F.-L., Gao,Y.-T., Coetzee,G.A., Ross,R.K. and Yu,M.C. (2000) Isothiocyanates, glutathione S-transferase M1 and T1 polymorphisms, and lung-cancer risk: a prospective study of men in Shanghai, China. Lancet, 356, 724–729.[CrossRef][ISI][Medline]
  33. Malaveille,C., Hautefeuille,A., Pignatelli,B., Talaska,G., Vineis,P. and Bartsch,H. (1996) Dietary phenolics as anti-mutagens and inhibitors of tobacco-related DNA adduction in the urothelium of smokers. Carcinogenesis, 17, 2193–2200.[Abstract]
  34. Wargovich,M.J. (1997) Experimental evidence for cancer preventive elements in foods. Cancer Lett., 114, 11–17.[CrossRef][ISI][Medline]
  35. Block,G. (1992) The data support a role for antioxidants in reducing cancer risk. Nutr. Rev., 50, 207–213.[ISI][Medline]
  36. Perera,F.P. and Mooney,L.A. (1993) The role of molecular epidemiology in cancer prevention. In DeVita,V.T.,Jr, Hellman,S. and Rosenberg,S.A. (eds), Cancer Prevention. J.B. Lippincott, Philadelphia, pp. 1–15.
  37. Kleiner,H.E., Vulimiri,S.V., Miller,L., Johnson,W.H.,Jr, Whitman,C.P. and DiGiovanni,J. (2001) Oral administration of naturally occurring coumarins leads to altered phase I and II enzyme activities and reduced DNA adduct formation by polycyclic aromatic hydrocarbons in various tissues of SENCAR mice. Carcinogenesis, 22, 73–82.[Abstract/Free Full Text]
  38. Hageman,G.J. and Stierum,R.H. (2001) Niacin, poly (ADP-ribose) polymerase-1 and genomic stability. Mutat. Res., 475, 45–56.[ISI][Medline]
  39. Stierum,R.H., Van Herwijnen,M.H., Hageman,G.J. and Kleinjans,J.C. (1994) Increased poly(ADP-ribose) polymerase activity during repair of (+/-)-anti-benzo[a]pyrene diolepoxide-induced DNA damage in human peripheral blood lymphocytes in vitro. Carcinogenesis, 15, 745–751.[Abstract]
  40. Hageman,G.J., Stierum,R.H., Van Herwijnen,M.H., Van der Veer,M.S. and Kleinjans,J.C. (1998) Nicotinic acid supplementation: effects on niacin status, cytogenetic damage, and poly (ADP-ribosylation) in lymphocytes of smokers. Nutr. Cancer, 32, 113–120.[ISI][Medline]
  41. Schut,H.A., Wang,C.L., Twining,L.M. and Earle,K.M. (1997) Formation and persistence of DNA adducts of 2-amino-3-methylimidazo[4,5-f]quinoline (IQ) in CDF1 mice fed a high omega-3 fatty acid diet. Mutat. Res., 378, 23–30.[ISI][Medline]
  42. Josyula,S. and Schut,H.A. (1999) Dietary omega-3 fatty acids as potential inhibitors of carcinogenesis: effect on DNA adduct formation of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) in mice and rats. Food. Chem. Toxicol., 37, 287–296.[CrossRef][ISI][Medline]
  43. Fusconi,E., Pala,V., Riboli,E. et al. (2003) Relationship between plasma fatty acid composition and diet over previous year in the Italian centres of European Prospective Investigation into Cancer and Nutrition (EPIC). Tumori, 89, 624–635.[ISI][Medline]
Received September 25, 2003; revised November 5, 2003; accepted November 15, 2003.