Skip Navigation


Mutagenesis Advance Access originally published online on June 11, 2008
Mutagenesis 2008 23(5):415-422; doi:10.1093/mutage/gen031
This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
23/5/415    most recent
gen031v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (1)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by da Silva, J.
Right arrow Articles by Erdtmann, B.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by da Silva, J.
Right arrow Articles by Erdtmann, B.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?


© The Author 2008. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

Evaluation of genetic damage in a Brazilian population occupationally exposed to pesticides and its correlation with polymorphisms in metabolizing genes

Juliana da Silva1, Camila R. Moraes2, Vanina D. Heuser3,4, Vanessa M. Andrade3,5, Fernanda R. Silva3, Kátia Kvitko3, Vanessa Emmel3, Paula Rohr3, Diana Lilian Bordin6, Ana Cristina Andreazza6, Mirian Salvador6, João A. P. Henriques1,2,3,6,* and Bernardo Erdtmann6

1Laboratório de Genética Toxicológica, PPGGTA e PPGECIM, Universidade Luterana do Brasil, Canoas-RS, Brazil 2Departamento de Biofísica, Programa de Pós-Graduação em Biologia Celular e Molecular 3Departamento de Genética, Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul, Porto Alegre-RS, Brazil 4Division of Biochemical Toxicology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden 5Laboratório de Imunologia e Mutagênese, Programa de Pós-Graduação em Ciências da Saúde, Universidade do Extremo Sul Catarinense, Criciúma-SC, Brazil 6Instituto de Biotecnologia, Universidade de Caxias do Sul, Caxias do Sul, RS, Brazil

Cytogenetic damage in individuals occupationally exposed to pesticides has received the attention of investigators in several countries, but no definitive conclusions can yet be made. The present study aimed at assessing if prolonged exposure to complex mixtures of pesticides leads to an increase in cytogenetic damage. Vineyard workers exposed to pesticides in Caxias do Sul (Brazil) were evaluated using the micronucleus (MN) test in binucleated lymphocytes and the comet assay in peripheral leukocytes. In order to evaluate if genetically determined individual variations in xenobiotic metabolizing capacity could modify individual susceptibility to the possible genotoxic effects of pesticides, the subjects were genotyped for several genes: GSTT1, GSTM1, GSTP1, CYP1A1, CYP2E1 and PON. The study involved a total number of 173 men: 108 were agricultural workers exposed to pesticides and 65 were controls. The present study showed a high rate of MN and DNA damage in pesticide-exposed individuals (P ≤ 0.001; Mann–Whitney U-test). In addition, some effects of genetic polymorphisms in PON in the modulation of MN results were observed in the exposed group, and an association between GSTM1, GSTT1 and CYP2E1 polymorphisms was suggested.


   Introduction
Top
 Introduction
Materials and methods
 Results
 Discussion
 Funding
 References
 
Pesticides are extensively used all over the world and in recent years their use has increased. Large amounts of these chemicals are released into the environment, and many of them affect non-target organisms, being a potential hazard to human health. Pesticide exposure is ubiquitous, due not only to agricultural pesticides use and contamination of foods but also to the extensive use of these products in and around households. Individuals occupationally exposed to pesticides (such as field workers, mixers, loaders, appliers, etc.), who are in direct contact with these chemicals, may provide a good opportunity to study their adverse health consequences.

Exposure to pesticides has been associated with an increase in the incidence of non-Hodgkin's lymphoma (1Go,2Go), multiple myeloma (3Go), soft tissue sarcoma (4Go), lung sarcoma (5Go), pancreatic, stomach, liver, bladder and gall bladder cancer (6Go,7Go), Parkinson's disease (8Go) and reproductive outcomes (9Go) among others.

Regarding pesticide exposure, many reports dealing with chromosomal aberrations (10Go,11Go), sister chromatid exchange (SCE) (12Go,13Go), micronuclei (14Go,15Go) and the comet assay (11Go,16Go) found significant increases in these biomarkers, providing suggestive evidence of genotoxic effects induced by pesticides.

In view of these findings, the detection of populations at risk constitutes a very important topic. A wide range of methods is presently used for the detection of early biological effects of DNA-damaging agents in occupational settings. During the last few years, methods that are less time consuming are being required, as it is of public interest that hazardous chemicals are removed from the environment as soon as possible. Consequently, there is a need for rapid and reliable tests that detect DNA damage caused by agents under different exposure circumstances. Thus, the micronucleus (MN) test and the comet assay, which are used in human biomonitoring studies (16Go–18Go), seem to satisfy many of these criteria.

However, biomarkers’ studies are still not generating the type of reliable information needed for precise risk assessment. Some of the problems are due to inconsistent observation of biological effects from similarly exposed populations, lack of predictable dose–response relationship and existence of inter-individual variations in response to exposure (19Go). Individual variations in polymorphic genes involved in xenobiotic metabolism and DNA repair were linked to increased risk of cancer in several case–control studies (20Go). These individual differences may be important in the estimation of the risk to humans caused by the exposure to environmental toxicants. Understanding the significance of genetic polymorphisms in genotoxic response determination will also have an important influence on requirements concerning the use of human cells in genotoxicity testing (21Go,22Go).

In the present study, in order to assess if prolonged exposure to complex mixtures of pesticides could lead to an increase in cytogenetic damage, vineyard workers from Caxias do Sul (Brazil) exposed to pesticides were evaluated using the MN test in binucleated lymphocytes, and the comet assay in peripheral leukocytes. In order to evaluate if genetically determined individual variations in xenobiotic metabolizing capacity could modify individual susceptibility to the possible genotoxic effects of pesticides, the subjects were genotyped for several genes: GSTT1, GSTM1, GSTP1, CYP1A1, CYP2E1 and PON.


   Materials and methods
Top
 Introduction
 Materials and methods
Results
 Discussion
 Funding
 References
 
Study population and sample collection
This study was approved by the Brazilian National Committee on Research Ethics (Comissão Nacional de Ética em Pesquisa), and informed written consent was obtained from each individual before the start of the study.

The study involved a total number of 173 individuals (men) from Caxias do Sul (in the northeastern region of the state of Rio Grande do Sul, south of Brazil). They were sampled from October to December, 2001 and 2002. Out of these, 108 were agricultural workers exposed to pesticides (mean age: 41.6 ± 11.6; exposed for ~29.8 ± 14.2 years) and 65 were controls (mean age: 37.8 ± 10.6). All individuals examined in the study were asked to answer a Portuguese version of a questionnaire from the International Commission for Protection against Environmental Mutagens and Carcinogens (23Go) and to participate in a face-to-face interview, which included standard demographic data (age, gender, etc.), as well as questions related to medical issues (exposure to X-rays, vaccinations, medication, etc.), life style (smoking, coffee and alcohol consumption, diet, etc.) and occupation (number of working hours per day, time exposed to organic solvents, use of protective measures, etc.). In all groups, individuals who smoked more than five cigarettes per day for at least 1 year were considered smokers (control smokers = 1; farmers = 8). Caxias do Sul is a wine-producing region, and therefore daily wine consumption is a frequent habit; however, no alcoholism was detected. All agricultural workers were regularly exposed to pesticides about twice or three times per week from September to January, comprising ~400 h/year. These pesticides consisted of complex mixtures of compounds, which changed according to the weather. Nevertheless, carbamates and organophosphates were the most used families of pesticides. Workers worked mainly in open fields, and the main crop was grapes. Pesticides were usually applied above the worker's head. Almost 90% of the pesticide-exposed workers reported using of some kind of protection during the preparation and application of pesticides (gloves, breathing masks, glasses, impermeable boots, etc.).

The control individuals were office employees living in the same region as the exposed individuals. Blood samples were collected during the same period for both groups. None of the control individuals were recently exposed to agrochemicals or any other suspected genotoxic agents, and they had no previous occupational exposure to genotoxins.

All blood samples were collected by venipuncture using two vacutainers (with heparin and ethylenediaminetetraacetic acid (EDTA)] and processed as quickly as possible, in order to prevent damage associated with storage; blood cell samples were transported to the laboratories at or below 8°C and processed within 8 h of collection.

MN test: cytokinesis-blocked human lymphocyte MN
For each blood sample, duplicate lymphocyte cultures were set up in culture flasks by adding 0.3 ml whole blood to 5 ml RPMI 1640 medium (Nutricell, Campinas-SP, Brazil), containing 1% (v/v) phytohaemagglutinin. Flasks incubated at 37°C for 44 h before adding 5 µg/ml of cytochalasin B (Sigma, St. Louis, MO, USA) and continuing incubation until the total incubation time reached was 72 h, as described by Fenech (24Go). After incubation, lymphocytes were harvested by centrifugation at 800 r.p.m. for 8 min, re-centrifuged, fixed in 3:1 (v/v) methanol/acetic acid, placed onto a clean microscope slide and stained with 5% (v/v) Giemsa. For each blood sample, 2000 binucleated cells (i.e. 1000 from each of the two slides prepared from the duplicate cultures) were scored for MN presence, which was assessed using bright-field optical microscopy at a magnification of x200–1000. All sides were coded to blind analysis.

Comet assay
The alkaline comet assay was performed as described by Singh et al. (25Go) with the modifications suggested by Tice et al. (26Go). Blood cells (5 µl) were embedded in 95 µl of 0.75% low melting point agarose, and after agarose solidified, slides were placed in lysis buffer (2.5 M NaCl, 100 mM EDTA and 10 mM Tris; pH 10.0–10.5) containing freshly added 1% (v/v) Triton X-100 and 10% (v/v) dimethyl sulphoxide for a minimum of 1 h and a maximum of 2 weeks. After treatment with lysis buffer, slides were incubated in freshly prepared alkaline buffer solution (300 mM NaOH and 1 mM EDTA; pH > 13) for 20 min, and DNA was submitted to electrophoresis for 20 min at 25 V (0.90 V/cm) and 300 mA, after which the buffer solution was neutralized with 0.4 M Tris (pH 7.5), and the DNA stained with ethidium bromide (2 µg/ml). Electrophoresis procedure and the efficiency of each electrophoresis run were checked using negative and positive internal controls, consisting of whole human blood collected in the laboratory, with the negative control being unmodified blood and the positive control 50 µl blood mixed with 13 µl (8 x 10–5 M) methyl methanesulphonate (CAS 66-27-3; Sigma, St Louis, MO, USA) and incubated for 2 h at 37°C. Each electrophoresis run was considered valid only if the negative and positive controls yielded the expected results.

Images of 100 randomly selected cells (50 cells from each of two replicate slides) were analysed for each individual using a fluorescence microscope equipped with a 12-nm BP546 excitation filter and a 590-nm barrier filter. Two parameters were evaluated: (i) damage index (DI), in which each cell was designated to one of five classes (from no damage = 0 to maximum damage = 4) according to tail size and shape [see figures in Heuser et al. (27Go)]. The values obtained for each individuals could range from 0 (0 x 100) to 400 (4 x 100) and (ii) damage frequency (DF), calculated as the percentage of damaged cells. International guidelines and recommendations for the comet assay consider that visual scoring of comets is a well-validated evaluation method. Although the DI parameter is subjective, it is highly correlated with computer-based image analysis (26Go,28Go).

DNA extraction and genotyping
Genomic DNA was isolated from whole blood (collected using vacutainers with EDTA) by the salting out method (29Go). Five polymorphic markers were investigated by genotyping using the polymerase chain reaction (PCR)–restriction fragment length polymorphism (RFLP) method.

GST genes: GSTM1, GSTT1 and GSTP1
GSTM1, GSTT1 and GSTP1 genes were typed by a multiplex PCR method, using a reaction mixture consisting of 100 ng of genomic DNA, 15 pmol of each primer, 10 mM Tris HCl, 4.5 mM MgCl2, 50 mM KCl, 100 mM dNTPs and 1.0 U Taq DNA polymerase in a total volume of 50 µl. The amplification protocol consisted of initial denaturation at 94°C for 5 min, six touchdown cycles of 1 min at 94°C, followed by 2 min at 59°C (decreasing to 54°C at a rate of 1°C per cycle) and 1 min at 72°C and 30 cycles at 94°C for 1 min, followed by 1 min at 55°C and 1 min at 72°C, plus a final extension of 5 min at 72°C. An aliquot of the amplification product was submitted to horizontal agarose gel (3.5%) electrophoresis to verify the presence or the absence of GSTM and GSTT fragments and the GSTP1 product was used as control for this reaction. Primer sequences were those reported by Harries et al. (30Go), Bell et al. (31Go) and Pemble et al. (32Go). A second aliquot of the amplified GSTP1 product was digested with BsmaI, as described by Harries et al. (30Go).

CYP450 genes: CYP1A1 and CYP2E1
CYP1A1*2C polymorphism was genotyped using the primers and the PCR conditions indicated by Cascorby et al. (33Go). CYP1A1*1A (wild) and CYP1A1*2C (variant) alleles were detected after digestion with BsrDI enzyme. CYP2E1 polymorphism was analysed using the primers and PCR conditions described by Kato et al. (34Go). An aliquot of the amplified product was submitted to PstI and RsaI enzymes in order to establish CYP2E1*1A/5B haplotypes.

PON gene
We investigated PON polymorphism in amino acid 192 (Gln192Arg) by PCR–RFLP, according to the description of Humbert et al. (35Go). An aliquot of the PCR product was digested with AlwI, and the genotypes were resolved in agarose gel. The Arg allele (G or B type) is present in the high-activity allozyme, and the Gln allele (A type) is present in the low-activity allozyme at position 192 of the protein (Gln = 99 pb fragment and Arg = 69 and 30 pb fragments).

Statistical analysis
The normality of variables was evaluated by the Kolmogorov–Smirnov test. {chi}2 and t-test were used to compare the demographic characteristics of studied populations. The statistical analysis of differences in MN and DNA damage, as measured by the comet assay, was carried out using Mann–Whitney U non-parametric test. Correlations between different variables were determined by Spearman rank correlation test when applicable. Gene frequencies were estimated by gene counting, and Hardy–Weinberg equilibrium was evaluated by the {chi}2 test for goodness of fit adjusted for small samples. Effect of combined PON and GSTM1, GSTT1, GSTP1, CYP1A1 or CYP2E1 variants on MN frequency [mean ± standard deviation (SD)] in control and exposed groups were investigated using Mann–Whitney U non-parametric test. The critical level for rejection of the null hypothesis was considered to be a P value of 5%, two tailed. All analyses were performed with the SPSS/PC statistical software package.


   Results
Top
 Introduction
 Materials and methods
 Results
Discussion
 Funding
 References
 
MN frequency in 2000 binucleated lymphocytes and comet assay results are presented in Table I. The comparison of MN frequencies shows statistically significant difference between controls and exposed individuals (P ≤ 0.001; Mann–Whitney U-test). Frequency ratio was ~1.7 times higher in exposed individuals as compared to controls. The analysis of comet assay values (mean ± SD) indicated a significant increase in DI and DF (P ≤ 0.001) for the exposed group as compared to the control group (Mann–Whitney U-test). DI and DF frequency ratios were ~4.6 and 5.7 times higher, respectively, in exposed as compared to control individuals. Negative (DI = 0–4) and positive (DI = 380–400) controls for each electrophoresis demonstrated negative and positive results, respectively (data not shown). No differences were observed between times of exposure—less and more than 3 days after pesticide application. No significant difference was detected in cytogenetic end points between the few smokers of both groups as compared to their non-smoking counterparts (data not shown). All individuals in this study were intentionally selected to be non-smokers in order to eliminate confounding factors, such as cigarette smoking.


View this table:
[in this window]
[in a new window]

  		Table I. Mean values (mean ± SD) obtained with the cytogenetic analysis in control and exposed groups

 
GSTT1, GSTM1, GSTP1, CYP1A1, CYP1E2 and PON genotype frequencies of exposed and non-exposed individuals are shown in Table II. No deviations from Hardy–Weinberg expectations were detected, either relative to polymorphism or sample group, and genotype and allele distributions were similar both in the control and the exposed group.


View this table:
[in this window]
[in a new window]

  		Table II. Distribution of GSTM1, GSTT1, GSTP1, CYP1A1, CYP2E1 and PON genotypes in control and exposed groups

 
Table III shows the effect of individual genotype on the level of different biomarkers evaluated in control and exposed individuals. The control group showed an increase in DI and DF in CYP1A1*1A, as compared with CYP1A1*2C/– (P ≤ 0.01; Mann–Whitney U-test), and in DI in CYP2E1*5B/– relative to CYP2E1 *1A/*1A (P ≤ 0.05; Mann–Whitney U-test). There was a significant increase in MN frequencies in PON Arg/– individuals as compared to PON Gln/Gln (P ≤ 0.05; Mann–Whitney U-test). A significant increase in MN frequencies was observed in PON Gln/Gln individuals in the exposed group as compared to PON Arg/– individuals (P ≤ 0.05; Mann–Whitney U-test). No statistically significant effects of GSTM1, GSTT1, GSTP1, CYP1A1 or CYP2E1 variants were obtained in the comet assay or the MN test for the exposed group. No influence of duration of exposure on the comet assay and MN test was observed. Correlation between MN frequency and age was found to be significant for both the control (Rs = 0.272; P = 0.037) and the exposed (Rs = 0.233; P=0.001; Spearman correlation test) groups.


View this table:
[in this window]
[in a new window]

  		Table III. Effect of individual genotype on the level of different biomarkers evaluated in control and exposed group (mean ± SD)

 
As it was shown that the PON genotype is associated with levels of MN cells in exposed individuals, an analysis of combined alleles was performed, considering the presence of one of the PON genotypes (Gln/Gln or Gln/Arg or Arg/Arg) and the other studied polymorphic genes (Table IV). It was not possible to evaluate the combination of more than two genotypes because of the lack of individuals with the less common variant genotypes. Individuals of the PON Arg/– control group showed higher MN frequency values relative to the PON Gln/Gln genotype, independent of the type of combined polymorphism of GSTM1, GSTT1, GSTP1, CYP1A1 and CYP2E1 genes. However, a significant increase of MN was observed only in PON Arg/– genotype individuals with GSTP1 Ile/Val or Val/Val polymorphisms, as compared to PON Arg/– with GSTP1 Ile/Ile (P = 0.016; Mann–Whitney U-test). PON Gln/Gln individuals of the exposed group showed higher MN frequency values relative to the PON Arg/– genotype, when polymorphisms of GSTM1, GSTP1, CYP1A1 and CYP2E1 genes were combined. A significant increase was observed in PON Gln/Gln genotype with non-null GSTM1 (P = 0.023), non-null GSTT1 (P = 0.029) and CYP2E1 *1A/*1A (P = 0.026) in relation to PON Arg/- genotype with non-null GSTM1, non-null GSTT1 and CYP2E1 *1A/*1A, respectively (Mann–Whitney U-test).


View this table:
[in this window]
[in a new window]

  		Table IV. Effect of combined PON and GSTM1, GSTT1, GSTP1, CYP1A1 or CYP2E1 variants on MN frequency (mean ± SD) in control and exposed groups

 

   Discussion
Top
 Introduction
 Materials and methods
 Results
 Discussion
Funding
 References
 
Pesticides constitute a heterogeneous category of chemicals specifically designed for the control of pests, weeds or plant diseases. Possible abuse or misuse can lead to significant levels of exposure, particularly among those occupationally exposed. Cytogenetic damage in individuals occupationally exposed to pesticides has received the attention of investigators in several countries, but no definitive conclusions have been reached yet. Literature reviews on this subject (36Go,37Go) report that most studies found an increase in genotoxicity biomonitoring end points in pesticide appliers or users. Working environment, personal protective equipment, time of exposure and exposure conditions are described in the literature as factors capable of affecting cytogenetic damage levels (36Go). Another factor that complicates the comparison among different studies performed to date is the high number and variety of commonly used chemicals. The agricultural workers included in this study were also exposed to a great number of pesticides (>90% of the subjects were exposed to >10 different pesticides), and some of them are classified as carcinogenic by US Environmental Protection Agency (38Go) and hazardous by World Health Organization (39Go), but not yet listed by International Agency for Research on Cancer (40Go) (Table V).


View this table:
[in this window]
[in a new window]

  		Table V. List of pesticides used by the exposed individuals

 
In a recent review, Bull et al. (37Go) discussed genotoxicity in pesticide appliers and highlighted the importance of personal protective equipment usage. In our study, most workers (>70%) allegedly took all protective measures. Nevertheless, we noticed an increase in MN frequency, DI and DF among appliers, with no difference between those who used complete protective equipment and those who did not (data not shown). In addition, a significant association was found between age and MN. Age is known to affect MN frequency (27Go,36Go). Most pesticides have been tested in a wide variety of mutagenicity assays covering gene mutation, chromosomal alterations and DNA damage (36Go). As most occupational and environmental exposures to pesticides are to mixtures of these compounds, genotoxic potential evaluated in single compounds cannot be extrapolated to humans. A literature review on genotoxicity in human groups exposed to pesticides showed a large number of studies employing the chromosome aberration test, SCE analysis or the MN assay. Pesticide sprayers are the most frequently exposed group of agricultural workers, with positive findings obtained in 18 of 27 biomonitoring studies, presenting 1.12–7.67 higher exposure rates (36Go, 41Go). Negative results were obtained in 7 of 10 studies of exposure to single compounds and in only 2 of 17 studies on exposure to pesticide mixtures. In the present study, vineyard pesticide sprayers exposed to pesticide mixtures showed 5.7 and 1.7-fold higher DNA damage (comet assay) and MN frequency, respectively.

Many recent studies have explored the influence of single genotypes and the interaction of genotypes on genotoxic exposure biomarkers levels (27Go,42Go–44Go). The determination of polymorphisms is becoming an increasingly important aspect that may increase the sensitivity and the specificity of assays identifying effects and sensitive subgroups (21Go). Glutathione S-transferases are a superfamily of polymorphic enzymes involved in the conjugation of reactive chemical intermediates and play an important role in the detoxification of endogenous and exogenous compounds. GSTM1 and GSTT1 polymorphisms owing to gene deletions result in null alleles, and homozygous individuals for deletions lack enzyme activity. When a GSTM1-null genotype is detected, it is impossible to metabolize some activated carcinogens, which increase the risk of DNA damage and may lead to cancer development (45Go). The lack of GSTM1 appears also to be associated with an increased sensitivity to tobacco-smoking genotoxicity (22Go). Cytochrome P-450 monooxygenases (CYPs) are phase-I enzymes that function in the metabolic activation of polycyclic aromatic hydrocarbons and other pre-carcinogens found in tobacco smoke. Many CYP isozymes are polymorphic, and genotypes associated with high enzyme activity or high inducibility are supposed to be at risk. There is a limited number of studies on the effect of CYP polymorphisms on chromosome damage, and their interpretation is complicated by unclear associations between CYP genotype and phenotype and rarity of variant alleles (22Go). Paraoxonases (PONs) are responsible for the metabolism of organophosphate-based insecticides. Serum PON (PON1) activity plays a major role in the metabolism of organophosphates. Isoforms of serum PON exhibit substrate-dependent polymorphism characterized by different efficiencies of metabolism of chemical compounds belonging to the organophosphate class (22Go).

The genotype and allele frequencies observed in the present study are generally similar to those observed in many samples of healthy Brazilians of European descent (46Go–49Go). A significant increase in DNA damage (comet assay) in CYP1A1 *1A/*1A and CYP2E1*5B/– subjects and in MN frequency in PON Arg/– individuals as compared to CYP1A1*2C/–, CYP2E1*1A/1A and PON Gln/Gln in control individuals was detected in this study. According to Norppa (22Go), polymorphisms of xenobiotic metabolizing enzymes may influence chromosome damage baseline level, if they participate in chromosome integrity inborn metabolism or if their substrate is a genotoxin to which most people are exposed. In addition, some variant genotypes seem to be related to a non-significant increase in MN frequency, as observed in the control group in this study, suggesting their possible influence on the background levels of this cytogenetic biomarker.

No significant increases in DNA damage and MN frequency related to GSTM1, GSTT1, GSTP1, CYP1A1 and CYP2E1 in exposed individuals were observed. A similar study was reported by Scarpato et al. (50Go). They investigated the associations between two detoxifying genes (GSTM1 and GSTT1) and one biomarker (chromosome breakage) among pesticide-exposed farmers. Those authors did not observe any association between pesticide exposure and elevated frequencies of chromosome aberrations. Other studies (10Go,36Go) also did not demonstrate any association between these genes and increases in cytogenetic damages.

A significant increase in MN frequency was observed in the PON Gln/Gln genotype. It was reported that enzymes from the PON genes are responsible for pesticide metabolism (10Go,36Go), suggesting that the ‘unfavourable’ alleles could have increased the body load of reactive genotoxic agents in exposed individuals. The importance of the metabolism of organophosphates has increased since their use increased >40 years ago. Paraoxon hydrolysis is catalysed by serum paraoxonase/arylesterase, an enzyme associated with the lipoprotein fraction of the serum. There is a 10- to 40-fold difference in serum PON activity between individuals, which is genetically determined by polymorphism. Humans may differ in their susceptibility to parathion poisoning depending on PON allelic status. The Gln 192 allele codifies for a low-activity enzyme in contrast with the Arg 192 allele, which encodes a high-activity enzyme (35Go). It has been suggested that individuals with low enzyme levels may be more susceptible to the toxic effects of organophosphates. This was observed in our study, where the exposed Gln/Gln homozygote individuals presented higher genotoxic effects caused by these pesticides, as detected by their higher MN frequency. No increase in DI or DF (repairable damage) for PON Gln/Gln was observed, which allows us to conclude that the micronuclei observed may be due some deficiency in DNA repair mechanisms.

In the present study, the effect of PON polymorphism was detected in association with the different genotypes. A significant increase in micronuclei was observed in PON Gln/Arg or Arg/Arg genotypes with GSTP1 Ile/Val or Val/Val in control individuals. GSTP1 is particularly important in the detoxification of inhaled toxicants, as it is the most abundant GST isoform in the lung. Recent studies suggested that the GSTP1 Val/Val genotype is associated with higher DNA adduct levels in human lymphocytes and in lung cancer (21Go,22Go). In the present study, GSTP1 seemed to modulate the basal MN frequency in the control group, as individuals with heterozygous or homozygous form (Ile/Val or Val/Val) presented higher values than those of individuals with the wild genotype (Ile/Ile). Since this effect was observed only in the exposed group (22Go), it suggests the existence of an exposure versus genotype interaction. A significant MN increase was detected in the PON Gln/Gln genotype with non-null GSTM1, non-null GSTT1 and CYP2E1 *1A/*1A in exposed individuals. This observation suggests an increased risk of genotoxic effects in individuals with these particular genotype combinations. Genetic polymorphisms in metabolic enzymes have been studied in the last few years in order to understand the importance of genetic determinants in DNA damage, and some enzymatic isoforms were associated with individual cancer susceptibility (10Go,36Go). The results obtained herein suggest that PON activity can modulate the levels of MN frequency and that GSTM1, GSTT1 and CYP2E2 genotype may influence MN frequencies in workers exposed to pesticides.

Salvador et al. (51), using the same group of farmers from Caxias do Sul, showed that mean cholinesterase level, which is depressed by organophosphates and carbamates, was significantly lower in farmers (5572 ± 2368 U/l) than in controls (7284 ± 2519 U/l). Although cholinesterase levels remained within the normal range in both groups, farmers’ values demonstrated exposure to organophosphates and carbamates. Among the oxidative parameters analysed by Salvador et al. (51), only thiobarbituric acid reactive substances and catalase levels were increased (~3-fold) in the farmers’ group. When our results were compared with the Salvador et al. (51) data, no relation was found between PON activity and cholinesterase level (data not shown). Despite the reported relation between PON activity and the toxic effects of organophosphates (35Go), the results of the present study demonstrate the action of a complex mixture of pesticides in blood cells of the farmers.

Genotoxic damage caused by chemical compounds can also be influenced by the individual inheritance of variant polymorphic genes involved in the metabolism of chemical compounds and in DNA repair mechanisms. Although the available data on agricultural worker populations suggest that subjects with unfavourable metabolizing alleles are more susceptible to genotoxic effects than those with favourable alleles, there are no conclusive findings as to whether metabolic polymorphisms affect chromosomal damage induced by pesticides. As workers are frequently exposed to complex mixtures of pesticides, it is difficult to attribute genotoxic damage to any particular chemical class or compound. The organochlorine compounds used in the past have been replaced by organophosphates and carbamates and more recently by pyrethroids, which is currently the most frequently used chemical class of pesticides. Experimental evidence shows that many of these compounds induce genotoxic effects on different genetic end points in bacterial and mammalian systems [see Bolognesi (36Go)]. Although the significance of increased genotoxic effects is difficult to predict for individual subjects, the positive findings of biomonitoring studies suggest a genotoxic hazard at the group level. The evidence of a genetic hazard related to exposure resulting from the intensive use of pesticides stresses the need for educational programmes for agricultural workers in order to reduce the use of chemicals in agriculture and to implement protection measures. In conclusion, the present study showed an elevated rate of MN and DNA damage in pesticide-exposed individuals. In addition, some effects of PON genetic polymorphisms on the modulation of MN in the exposed group were observed, and an association between GSTM1, GSTT1 and CYP2E1 polymorphisms is suggested.


   Funding
Top
 Introduction
 Materials and methods
 Results
 Discussion
 Funding
References
 
CNPq-Plano Sul (521017/99-8); FAPERGS; CITOCEL; GENOTOX.


   Acknowledgments
 
The authors express their gratitude to all the individuals who volunteered to participate in this study. This study was only possible with the help of the ‘Sindicato dos Agricultores de Caxias do Sul (RS, Brazil)’ (Farmers Union of Caxias do Sul), especially Antonio Garbim.

Conflict of interest statement: None declared.


   Notes
 
* To whom correspondence should be addressed. Tel: +55 51 33166069; Fax: +55 51 33166084; Email: pegas{at}cbiot.ufrgs.br


   References
Top
 Introduction
 Materials and methods
 Results
 Discussion
 Funding
 References
 

    1. Hardell L, Eriksson M. A case-control study of non-Hodgkin lymphoma and exposure to pesticides. Cancer (1999) 85:1353–1360.[CrossRef][Web of Science][Medline]

    2. Zheng T, Zahm SH, Cantor KP, Weisenburger DD, Zhang Y, Blair A. Agricultural exposure to carbamate pesticides and risk of non-Hodgkin lymphoma. J. Occup. Environ. Med. (2001) 43:641–649.[Web of Science][Medline]

    3. Khuder SA, Mutgi AB. Meta-analyses of multiple myeloma and farming. Am. J. Ind. Med. (1997) 32:510–551.[CrossRef][Web of Science][Medline]

    4. Kogevinas M, Kauppinen T, Winkelmann R, et al. Soft tissue sarcoma and non-Hodgkin's lymphoma in workers exposed to phenoxy herbicides, chlorophenols, and dioxins: two nested case-control studies. Epidemiology (1995) 6:396–402.[Web of Science][Medline]

    5. Blair A, Grauman DJ, Lubin JH, Fraumeni JF Jr. Lung cancer and other causes of death among licensed pesticide appliers. J. Natl Cancer Inst. (1983) 71:31–37.[Web of Science][Medline]

    6. Shukla VK, Rastogi AN, Adukia TK, Raizada RB, Reddy DCS, Singh S. Organochlorine pesticides in carcinoma of the gallbladder: a case-control study. Eur. J. Cancer Prev. (2001) 10:153–156.[CrossRef][Web of Science][Medline]

    7. Ji BT, Silverman DT, Stewart PA, et al. Occupational exposure to pesticides and pancreatic cancer. Am. J. Ind. Med. (2001) 39:92–99.[CrossRef][Web of Science][Medline]

    8. Gauthier E, Fortier I, Courchesne F, Pepin P, Mortimer J, Gauvreau D. Environmental pesticide exposure as a risk factor for Alzheimer's disease: a case-control study. Environ. Res. (2001) 86:37–45.[Medline]

    9. Arbuckle TE, Lin L, Mery LS. An exploratory analysis of the effect of pesticide exposure on the risk of spontaneous abortion in an Ontario farm population. Environ. Health Perspect. (2001) 109:851–857.[Web of Science][Medline]

    10. Au WW, Sierra-Torres CH, Cajas-Salazar N, Shipp BK, Legator MS. Cytogenetic effects from exposure to mixed pesticides and the influence from genetic susceptibility. Environ. Health Perspect. (1999) 107:501–515.[Web of Science][Medline]

    11. Zeljezic D, Garaj-Vrhovac V. Chromosomal aberration and single-cell electrophoresis (comet) assay in the longitudinal risk assessment of occupational exposure to pesticides. Mutagenesis (2001) 16:359–363.[Abstract/Free Full Text]

    12. Zeljezic D, Garaj-Vrhovac V. Sister chromatid exchange and proliferative rate index in the longitudinal risk assessment of occupational exposure to pesticides. Chemosphere (2001) 46:295–303.

    13. Shaham J, Kaufman Z, Gurvich R, Levi Z. Frequency of sister-chromatid exchange among greenhouse farmers exposed to pesticides. Mutat. Res. (2001) 491:71–80.[Web of Science][Medline]

    14. Falk G, Hirvonen A, Scarpato R, Saarikoski ST, Migliore L, Norppa H. Micronuclei in blood lymphocytes and genetic polymorphisms for GSTM1, GSTT1 and NAT2 in pesticide-exposed greenhouse workers. Mutat. Res. (1999) 44:225–237.

    15. Pastor S, Creus A, Parrón T, Cebulska-Wasilewska A, Siffel C, Piperakis S, Marcos R. Biomonitoring of four European populations occupationally exposed to pesticides: use of micronuclei as biomarkers. Mutagenesis (2003) 18:249–258.[Abstract/Free Full Text]

    16. Grover P, Danadevi K, Mahboob M, Rozati R, Banu BS, Rahman MF. Evaluation of genetic damage in workers employed in pesticide production utilizing the Comet assay. Mutagenesis (2003) 18:201–205.[Abstract/Free Full Text]

    17. Fairbairn DW, Olive PL, O'Neill KL. The Comet assay: a comprehensive review. Mutat. Res. (1995) 339:37–59.[Web of Science][Medline]

    18. Moller P, Knudsen LE, Loft S, Wallin H. The Comet assay as a rapid test in biomonitoring occupational exposure to DNA-damaging agents and effect of confounding factors. Cancer Epidemiol. Biomarkers Prev. (2000) 9:1005–1015.[Abstract/Free Full Text]

    19. Au WW, Cajas-Salazar N, Salama S. Factors contributing to discrepancies in population monitoring studies. Mutat. Res. (1998) 400:467–478.[Web of Science][Medline]

    20. International Agency for Research on Cancer (IARC). Metabolic polymorphisms and susceptibility to cancer. Vincis P, Malats N, Lang M, d'Errico A, Caporaso N, Cuzic J, Boffetta P, eds. (1999) IARC, Lyon: IARC, Scientific Publications.

    21. Norppa H. Cytogenetic markers of susceptibility: influence of polymorphic carcinogen-metabolizing enzymes. Environ. Health Perspect. (1997) 105:829–835.[CrossRef][Web of Science][Medline]

    22. Norppa H. Cytogenetic biomarkers and genetic polymorphisms. Toxicol. Lett. (2004) 149:309–334.[CrossRef][Web of Science][Medline]

    23. Carrano AV, Natarajan AT. Considerations for population monitoring using cytogenetic techniques, International Commission for Protection against Environmental Mutagens and Carcinogens (ICPEMC publication 14). Mutat. Res. (1988) 204:379–406.[CrossRef][Web of Science][Medline]

    24. Fenech M. The cytokinesis-block micronucleus technique: a detailed description of the method and its application to genotoxicity studies in human populations. Mutat. Res. (1993) 285:35–44.[Web of Science][Medline]

    25. Singh NP, McCoy MT, Tice RR, Schneider EL. A simple technique for quantification of low levels of DNA damage in individual cells. Exp. Cell Res. (1988) 175:184–191.[CrossRef][Web of Science][Medline]

    26. Tice RR, Agurell E, Anderson D, et al. Single cell gel/comet assay: guidelines for in vitro and in vivo genetic toxicology testing. Environ. Mol. Mutagen. (2000) 35:206–221.[CrossRef][Web of Science][Medline]

    27. Heuser VD, Erdtmann B, Kvitko K, Rohr P, Da Silva J. Evaluation of genetic damage in Brazilian footwear-workers: biomarkers of exposure, effect, and susceptibility. Toxicology (2007) 232:235–247.[CrossRef][Web of Science][Medline]

    28. Collins AR. The comet assay for DNA damage and repair: principles, applications, and limitations. Mol. Biotechnol. (2004) 26:249–261.[CrossRef][Web of Science][Medline]

    29. Miller AS, Dykes DD, Polesky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res. (1995) 16:1215.

    30. Harries LW, Stubbins MJ, Forman D, Howard GCW, Wolf CR. Identification of genetic polymorphisms at the glutathione S-transferase Pi locus and association with susceptibility to bladder, testicular and prostate cancer. Carcinogenesis (1991) 18:641–644.[CrossRef]

    31. Bell DA, Taylor JA, Paulson DF, Robertson CN, Mohler JL, Lucier GW. Genetic risk and carcinogen exposure: a common inherited defect of the carcinogen-metabolism gene glutathione S-transferase M1 (GSTM1) that increases susceptibility to bladder cancer. J. Natl Cancer Inst. (1993) 85:1159–1164.[Abstract/Free Full Text]

    32. Pemble S, Schroeder KR, Spencer SR, Meyer DJ, Hallier E, Bolt HM, Ketterer B, Taylor JB. Human glutathione S-transferase theta (GSTT1): cDNA cloning and the characterization of a genetic polymorphism. Biochem. J. (1994) 300:271–276.[Web of Science][Medline]

    33. Cascorby I, Brockmöller J, Roots IA. C4887A polymorphism in exon 7 of human CYP1A1: population frequency, mutation linkages, and impact on lung cancer susceptibility. Cancer Res. (1996) 56:4965–4969.[Abstract/Free Full Text]

    34. Kato S, Shield PG, Caporoso NE, Hoover RN, Trump BF, Sugimura H, Weston A, Harris CC. Cytochrome P450IIE1 genetic polymorphism, racial variation, and lung cancer risk. Cancer Res. (1992) 52:6712–6715.[Abstract/Free Full Text]

    35. Humbert R, Adler DA, Disteche CM, Hasset C, Omiecinski CJ, Furlong CE. The molecular basis of the human serum paraoxonase activity polymorphism. Nat. Genet. (1993) 3:73–76.[CrossRef][Web of Science][Medline]

    36. Bolognesi C. Genotoxicity of pesticides: a review of human biomonitoring studies. Mutat. Res. (2003) 543:251–272.[CrossRef][Web of Science][Medline]

    37. Bull S, Fletcher K, Boobis AR, Battershill JM. Evidence for genotoxicity of pesticides in pesticide appliers: a review. Mutagenesis (2006) 21:93–103.[Abstract/Free Full Text]

    38. Environmental Protection Agency (EPA). Integrated Risk Information (IRIS) (2006) Washington, DC. (http://www.epa.gov/iris), last accessed 20 September 2006.

    39. World Health Organization (WHO). The WHO Recommended Classification of Pesticides and Guidelines to Classification: 2004 (2004) Geneva: World Health Organization.

    40. International Agency for Research on Cancer (IARC). Monographs on the Evaluation of Carcinogenic Risk to Humans (2007) Lyon: World Health Organization. http://monographs.iarc.fr/ENG/Classification/index.php, last accessed 31 January 2007.

    41. Joksic G, Vidakovic A, Spasojevic-Tisma V. Cytogenetic monitoring of pesticide sprayers. Environ. Res. (1997) 75:113–118.[Medline]

    42. Pitarque M, Vaglenov A, Nosko M, Hirvonen A, Norppa H, Creus A, Marcos R. Evaluation of DNA damage by Comet assay in footwear-workers exposed to toluene and other organic solvents. Mutat. Res. (1999) 441:115–127.[Web of Science][Medline]

    43. Pavanello S, Clonfero E. Biological indicators of genotoxic risk and metabolic polymorphisms. Mutat. Res. (2000) 463:285–308.[CrossRef][Web of Science][Medline]

    44. Pitarque M, Vaglenov A, Nosko M, Pavlova S, Petkova V, Hirvonen A, Creus A, Norppa H, Marcos R. Sister chromatid exchanges and micronuclei in peripheral lymphocytes of shoe factory workers exposed to solvents. Environ. Health Perspect. (2002) 110:339–404.

    45. Wu X, Shi H, Jiang H, Kemp B, Hong WK, Delclos GL, Spitz MR. Association between cytochrome P4502E1 genotype, mutagen sensibility, cigarette smoking and susceptibility to lung cancer. Carcinogenesis (1997) 18:967–973.[Abstract/Free Full Text]

    46. Amorim LMFA, Rossini A, Mendonça GAS, Lotsch PF, Simão TA, Gallo CVM, Pinto LFR. CYP1A1, GSTM1, and GSTT1 polymorphisms and breast cancer risk in Brazilian women. Cancer Lett. (2002) 181:179–186.[CrossRef][Web of Science][Medline]

    47. Rossini A, Rapozo DCM, Amorim LMF, Macedo JMB, Medina R, Neto JFN, Gallo CVM, Pinto LRF. Frequencies of GSTM1, GSTT1, and GSTP1 polymorphisms in a Brazilian population. Genet. Mol. Res. (2002) 1:233–240.[Medline]

    48. Gaspar P, Moreira J, Kvitko K, Torres M, Moreira A, Weimer T. CYP1A1, CYP2E1, GSTM1, GSTT1, GSTP1, and TP53 polymorphisms: do they indicate susceptibility to chronic obstructive pulmonary disease and non-small-cell lung cancer? Genet. Mol. Biol. (2004) 27:133–138.

    49. Gattás GJF, Kato M, Soares-Vieira JA, Siraque MS, Kohler P, Gomes L, Rego MAV, Bydlowski SP. Ethnicity and glutathione S-transferase (GSTM1/GSTT1) polymorphisms in a Brazilian population. Braz. J. Med. Biol. Res. (2004) 37:451–458.[Web of Science][Medline]

    50. Scarpato R, Hirvonen A, Migliore L, Falk G, Norppa H. Influence of GSTM1 and GSTT1 polymorphisms on the frequency of chromosome aberrations in lymphocytes of smokers and pesticide-exposed greenhouse workers. Mutat. Res. (1997) 389:227–235.[Web of Science][Medline]

    51. Salvador M, Bordin LD, Andreazza AC, Da-Silva J, Henriques JAP, Erdtmann B. Determination of oxidative stress markers and serum cholinesterase among pesticide sprinklers in southern Brazil. Toxicol. Environ. Chem. in press.

Received on September 4, 2007; revised on April 24, 2008; accepted on April 25, 2008.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?



This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
23/5/415    most recent
gen031v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (1)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by da Silva, J.
Right arrow Articles by Erdtmann, B.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by da Silva, J.
Right arrow Articles by Erdtmann, B.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?