Occupational exposure of farm workers to pesticides: Biochemical parameters and evaluation of genotoxicity

Environment International 35 (2009) 273-278

Contents lists available at ScienceDirect

Environment International j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e n v i n t

Occupational exposure of farm workers to pesticides: Biochemical parameters and evaluation of genotoxicity Aline Pértile Remor a, Carla Caprini Totti a, Dariele Alves Moreira a, Gustavo Pimentel Dutra b, Vanina Dahlström Heuser c, Jane Marlei Boeira a,b,d,⁎ a

Departamento de Ciências da Saúde, Universidade Regional Integrada do Alto Uruguai e das Missões (URI), Erechim, RS, Brazil Departamento de Biologia e Química, Universidade Regional do Noroeste do Estado do Rio Grande do Sul (UNIJUÍ), Ijuí, RS, Brazil Institute of Environmental Medicine, Division of Biochemical Toxicology, Karolinska Institute (KI), Stockholm, Sweden d Universidade Estadual do Rio Grande do Sul (UERGS), Unidade Novo Hamburgo, Novo Hamburgo, RS, Brazil b c

A R T I C L E

I N F O

Article history: Received 6 May 2008 Accepted 30 June 2008 Available online 3 August 2009 Keywords: Biomonitoring Pesticides ALA-D BChE Micronucleus Comet assay

A B S T R A C T To assess the effects of exposure to complex mixtures of pesticides in farm workers from two communities from Rio Grande do Sul, Brazil, we evaluated the activities of butyrylcholinesterase (BChE) and δaminolevulinic acid dehydratase (ALA-D) enzymes, hematological, lipid parameters, and genotoxicity using two tests to detect DNA damage, the Comet assay in peripheral blood leukocytes and the micronucleus (MN) test in oral mucosa cells. The use of personal protective equipment (PPE), age and smoke habits were considered in the analysis. There was a significant decrease in the BChE and ALA-D activities in farm workers (n = 37) relative to the control group (n = 20) (P ≤ 0.05 and P ≤ 0.001, respectively). The Comet assay in peripheral blood leukocytes showed that the Damage index and Damage frequency observed in the exposed group were significantly higher in relation to the controls (P ≤ 0.001, and P ≤ 0.05, respectively). No differences were detected regarding the hematological parameters, lipids profile, and MN frequencies. In addition, no significant differences were observed between younger (≤38 years) and older subjects (N 38 years), or between smokers and non-smokers within the groups, either by Comet assay or MN test. However, the use of PPE seems to be important in the prevention of contamination, as suggested by BChE levels and Comet assay results. © 2008 Elsevier Ltd. All rights reserved.

1. Introduction Brazil is one of the world leaders in pesticide consumption and exposed workers are numerous and diversified (Faria et al., 2007). Pesticides are responsible for several adverse effects on human health other than acute intoxications. Many studies have reported associations between exposure to agricultural chemicals and various health outcomes, including different kinds of cancer (Daniels et al., 1997; Khuder and Mutgi, 1997; Zahm and Ward, 1998) and degenerative diseases (Engel et al., 2001; Gauthier et al., 2001; Jenner, 2001). Effects in immune, hematological, nervous, endocrine and reproductive systems have been reported (Ojajarvi et al., 2000; Ritz and Yu, 2000; Figá-Talamanca and Petrelli, 2001; Mourad, 2005), and these compounds have been also associated with DNA damage in human populations (Gómez-Arroyo et al., 2000; Undeger and Basaran, 2002;

⁎ Corresponding author. Universidade Estadual do Rio Grande do Sul (UERGS), Unidade Novo Hamburgo, Av. Inconfidentes, 395; CEP 93340-140; Novo Hamburgo, RS, Brazil. E-mail address: [email protected] (J.M. Boeira). 0160-4120/$ – see front matter © 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.envint.2008.06.011

Costa et al., 2007; Ergene et al., 2007; Muniz et al., 2008; Ali et al., 2008; da Silva et al., in press). Exposure to low-level of pesticides is known to produce a variety of biochemical changes, some of which may be responsible for the adverse biological effects reported in human and experimental studies (Gupta et al., 1998; Banerjee et al., 1999; Panemangalore et al., 1999; Hernández et al., 2005). Conversely, some biochemical alterations may not necessarily lead to clinically recognizable symptoms, although all the biochemical responses can be used as markers of exposure or effect (Panemangalore et al., 1999; López et al., 2007). Blood cholinesterases have been widely used for monitoring exposure to organophosphorus and carbamate pesticides. The cholinesterase present in neural tissues, and also in erythrocytes, is known as true acetylcholinesterase (AChE). The cholinesterase found in blood serum and synthesized by liver has been termed pseudo- or butyrylcholinesterase (BChE). There are strong associations between exposures to pesticides and symptoms, and cholinesterase is significantly reduced in exposed populations (Nigg and Knaak, 2000; Mourad, 2005; Singh et al., 2007; Ali et al., 2008). For this reason the measurement of blood AChE and BChE activity have been considered a good biomarker for this kind of exposure.

274

A.P. Remor et al. / Environment International 35 (2009) 273-278

Changes in δ-aminolevulinic acid dehydratase (ALA-D), an erythrocyte enzyme, have been also reported after exposure to different pesticides both in vitro and in vivo (Panemangalore et al., 1999; Hernández et al., 2005). A 40% inhibition of ALA-D shortly after the administration of paraquat has also been reported, this being attributed to the generation of oxidative stress (Noriega et al., 2002). Therefore, this enzyme may become a sensitive biomarker that can be used together with AChE and∕or BchE for the assessment of long-term health risks of workers exposed to pesticides. DNA damage and oxidative stress have been proposed as mechanisms that could mechanistically link pesticide exposures to a number of health outcomes observed in epidemiological studies (Singh et al., 2007; Muniz et al., 2008). Although the genotoxic potential of pesticides is believed to be low, genotoxic monitoring in farm worker populations could be a useful tool to estimate genetic risk from exposure to complex pesticide mixtures over extended lengths of time (Moller et al., 2000). Genotoxic biomarker studies of workers exposed to pesticides have focused on cytogenetic endpoints, including chromosomal aberrations (CA), sister chromatid exchanges (SCE) and micronuclei (MN) frequency. In the last decade, single-cell gel electrophoresis or the Comet assay has been established as a sensitive and a rapid method for the detection of DNA single-strand breaks and incomplete excision repair. In the present study we used the Comet assay and micronucleus (MN) test because of their advantages for the screening of DNA damage caused by environmental mutagens (Salama et al., 1999; Martino-Roth et al., 2003). Briefly, in the Comet assay, cells embedded in agarose on a microscope slide are lysed with detergent and high salt to form nucleoids containing supercoiled loops of DNA linked to the nuclear matrix. Electrophoresis at high pH (alkaline version) results in structures resembling comets, observed by microscopy; the intensity of the comet tail relative to the head reflects the number of DNA breaks. The likely basis for this is that loops containing a break lose their supercoiling and become free to extend toward the anode (Collins, 2004). The Comet assay is ideally suited for human investigations because it requires no pre-labeling with radioactivity or other harmful procedures, and can be applied to easily obtainable cells (Moller et al., 2000; Collins, 2004). Micronuclei are acentric chromosome fragments or whole chromosomes left behind during mitotic cellular division, and appear in the cytoplasm of interphase cells as small additional nuclei. The MN test is faster and easier than metaphase analyses and it can be used both in vivo and in vitro in a variety of cells. This assay has also been shown to be a reliable and sensitive biomarker (Kirsch-Volders et al., 2003) for human biomonitoring, being an adequate alternative to the in vitro chromosomal aberration test (Lucero et al., 2000). The use of the MN test in exfoliated cells has substantially increased as it is considered a useful biomarker of genotoxic effects in populations

Table 1 Characteristics of the study population Controls No. of subjects 20 Age (in years) 38.95 ± 13.50 [mean ± SD] Years of exposure – [mean ± SD] Smoking status Non-smokers 16 (80%) Smokersa 4 (20%) Personal protective equipment (PPE) Yesb – No – a b

All farm workers

Erechim

Ijuí

37 41.14 ± 10.39

18 40.71 ± 11.14

19 41.53 ± 9.95

25.69 ± 10.14

27.00 ± 11.39

24.53 ± 9.05

29 (78.4%) 8 (21.6%)

15 (83.3%) 3 (16.7%)

15 (79%) 4 (21.0%)

25 (67.6%) 12 (32.4%)

13 (72.2%) 5 (27.8%)

12 (63.2) 7 (36.8%)

Individuals who smoke more than 5 cigarettes per day. At least two kinds of PPE during pesticide application.

Fig. 1. Box plot showing the distribution of BChE (a) and ALA-D (b) levels in controls and farm workers. Boxes are limited by 1st and 3rd quartiles divided by mean; vertical lines represent minimum and maximum values. ⁎P ≤ 0.05, and ⁎⁎P ≤ 0.001 significantly different from control group (Student's t-test, two-tailed).

exposed to genotoxicants, through direct contact with ingested or inhaled compounds (Salama et al., 1999). To assess the effects of prolonged exposure of farm workers in two communities from Rio Grande do Sul, Brazil (Erechim and Ijuí, RS) to complex mixtures of pesticides, we evaluated the biochemical parameters, as activities of BchE and ALA-D enzymes, hematological and lipid parameters. We also evaluated the genotoxicity occupational exposure to pesticides, using the Comet assay in peripheral blood leukocytes and the MN test in epithelial buccal cells. 2. Materials and methods 2.1. Study population The study used 37 male pesticides appliers (sprayers) exposed since childhood to a mixture of pesticides (mean age: 41.14 ± 10.39 years) from two adjacent communities from Rio Grande do Sul (Erechim, n = 18 and Ijuí, n = 19). The control group comprised 20 healthy males employees working in administrative offices from the same geographical area who had no history of exposure to chemicals or other potentially genotoxic substances (mean age: 38.95 ± 13.50 years). The samples were collected during the fall, a few days after the pesticides application. Characteristics of exposed and non-exposed groups are summarized in Table 1. Prior to the study, all the individuals completed a detailed questionnaire (Portuguese version of International Commission for Protection against Environmental Mutagens and Carcinogens) (Carrano and Natarajan, 1988), covering standard demographic questions, habits (sports, food, drugs, tobacco, alcohol, coffee, etc.), as well as occupational, medical and family history, duration of application of the pesticides, kind of pesticides and personal protective equipment (PPE) used. We consider as active smokers those individuals who smoke more than 5 cigarettes per day during at least one year. This study was approved by the Brazilian National Committee on Research Ethics (Comissão Nacional de Ética em Pesquisa — CONEP, Protocols 166-1/TCH/04 and 167-1/ TCH/04), and all individuals gave informed consent. Peripheral blood and oral mucosa cells samples were obtained following the procedure described below, and samples were further manipulated in accordance with ethical standards. Processing and scoring of the samples from exposed and control groups were immediately performed blind and concurrently. At the end of the study, the data from the questionnaire and the exposure records were linked to the code number for data analysis.

A.P. Remor et al. / Environment International 35 (2009) 273-278

275

Table 3 Data of lipid profile of study groups (mean ± SD) Controls (n = 20)

Farm workers (n = 37)

Reference valuesa

Total cholesterol (mg/dl)

187.05 ± 31.92

194.57 ± 48.06

LDL (mg/dl)

102.30 ± 24.49

111.68 ± 45.50

Triglycerides (mg/dl)

151.10 ± 57.43

140.16 ± 18.93

HDL (mg/dl)

46.90 ± 16.93

46.89 ± 18.93

b 200: Desirable 200–239: Bordering ≥240: Increased b 130: Desirable 130–159: Bordering ≥160: Increased b 200: Desirable ≥200: Increased values ≤35: Desirable values

a

According to Consenso Brasileiro de Dislipidemias (1994).

gen of 0.062l mM− 1cm− 1 was used. Results were corrected for reagent blank and were calculated as the mean of two measurements, each done in triplicate. Activity was expressed in mM min− 1 L− 1. 2.2.3. Hematological and lipid parameters The following hematological markers were measured: leukocytes (granulocytes, lymphocytes, and monocytes), erythrocytes, hematocrit, hemoglobin, and platelets using an electronic counter (ABX MICROS 60). The lipid parameters analyzed were cholesterol, LDL (low density lipoprotein), triglycerides, and HDL (high density lipoprotein) by Labtest® methods. 2.3. Genotoxicity tests

Fig. 2. Box plot showing the distribution of BChE (a), and ALA-D (b) levels according to the use of PPE within the exposed group. Boxes are limited by 1st and 3rd quartiles divided by mean; vertical lines represent minimum and maximum values. Yes = at least two kinds of PPE during pesticides application; ⁎P ≤ 0.05, significantly different from the group that wore at least two kinds of during pesticides application (Student's t-test, two-tailed).

2.2. Biochemical analyses and sampling Blood samples were collected obtained from each donor by venipuncture using heparinised vacutainers. The samples were kept at 4 °C in a box with ice and transported to the laboratory. They were also protected from light to avoid enzymatic changes. 2.2.1. Determination of plasmatic BchE activity BchE activity was evaluated by Kit Doles Reagents® and measured less than 24 h after blood was collected. At pH 7.7, the cholinesterase catalyses esters choline hydrolyses as propionylcholine, and it liberates sulfidryl group thiocholine. The thiocoline reacts with acid 5,5’-ditiobis-2-nitrobenzoic (DTNB) producing a yellow compound directly proportional to the enzyme activity which is measured by spectrometer at 405 nm. 2.2.2. Determination of ALA-D activity in blood samples ALA-D activity was measured less than 24 h after blood sampling using the European Standardized Method (Berlin and Schaller, 1974). Spectrophotometer determination was carried out at 555 nm and an extinction coefficient of porphobilino-

2.3.1. Comet assay in peripheral blood leukocytes The alkaline Comet assay was performed according to the procedure described previously (Olive et al., 1992) with minor modifications. Samples of 5 μl of whole peripheral blood per slide (two slides per donor) were suspended in 100 μl agarose with low melting point (0.75% in phosphate buffer) and added to a microscope slide precoated with normal agarose (1% in phosphate buffer). To prevent additional DNA damage, the Comet assay was processed under minimal illumination at room temperature (Singh et al., 1988). Slides were then immersed in a tank filled with a freshly made lysis solution (2.5 M NaCl, 0.1 M EDTA, 10 mM Tris, pH 10, 10% dimethylsulphoxide, and 1% Triton X-100) for at least 1 h. To allow DNA unwinding, slides were incubated in a freshly made electrophoresis buffer (0.3 M NaOH and 1 mM EDTA, pH.13) for 20 min. Slides were then placed in a horizontal electrophoresis tank, immersed in fresh electrophoresis buffer, and exposed to 25 V (0.9 V/cm) for 15 min at 300 mA. After electrophoresis, slides were washed twice in freshly prepared neutralization buffer (0.4 M Tris, pH 7.5 with concentrated hydrochloric acid) and washed with deionized water for 2 min. The slides were dried for 1 h at room temperature and fixed for 10 min (15% w/v trichloroacetic acid, 5% w/v zinc sulfate, and 5% glycerol). After fixation the slides were washed three times in deionized water and dried for approximately 5 h at room temperature. Slides were stained with silver nitrate as describe previously (Nadin et al., 2001) and analyzed by optic microscope. Images of 100 randomly selected cells (50 cells from each of two replicate slides) were analyzed per individual. Cells were scored visually into five classes, according to tail size and shape (from undamaged—0, to maximally damaged—4), and a value (Damage index) was assigned to each comet according to its class (see Villela et al., 2006). Damage index thus ranged from 0 (completely undamaged: 100 cells × 0) to 400 (with maximum damage: 100 cells × 4) (Collins, 2004; Moura et al., 2007). The Damage frequency (%) was calculated based on the percentage of damaged cells (0– 100%). International guidelines and recommendations for the Comet assay consider that visual scoring of comets is a well-validated evaluation method. It has a high correlation with computer-based image analysis (Collins, 2004). Negative controls were processed together with farmers' samples and analyzed by two investigators. 2.3.2. MN test in epithelial buccal cells Exfoliated buccal mucosa cells were collected by swabbing the inner cheek of the individuals with a moistened wooden tongue depressor. The cells were transferred to a

Table 2 Hematological parameters in study groups (mean ± SD)

Leukocyte count (× 106/μl) Granulocytes (%) Lymphocytes (%) Monocytes (%) Erythrocytes count (×103/μl) Hematocrit (%) Hemoglobin (g/dl) Platelets (× 103/μl)

Control group (n = 20)

Farm workers (n = 37)

7.44 ± 1.45 61.81 ± 9.76 32.57 ± 8.96 5.62 ± 2.01 4.77 ± 0.38 43.60 ± 3.15 14.33 ± 1.05 264.90 ± 65.24

7.69 ± 2.02 58.53 ± 10.75 34.50 ± 9.34 6.68 ± 3.18 4.83 ± 0.29 44.04 ± 3.88 14.54 ± 0.84 255.03 ± 541.53

Table 4 Comet assay and MN data obtained for controls and farm workers (mean ± SD) Comet assay (100 leukocytes/subject)

Controls Farm workers

Damage index (0–400)

Damage frequency (%)

3.10 ± 1.59 21.38 ± 14.80⁎⁎

2.35 ± 1.31 16.38 ± 11.68⁎

Micronucleus (2000 cells/subject) 0.55 ± 0.69 0.76 ± 0.68

⁎Difference significant relative to control group at ⁎P ≤ 0.05, and ⁎⁎P ≤ 0.01 (Mann– Whitney U-test, two-tail).

276

A.P. Remor et al. / Environment International 35 (2009) 273-278

Table 5 Influence of age on Comet assay and MN data (mean ± SD) Comet assay (100 leukocytes/subject)

Damage index (0–400) Controls ≤ 38 years old (n = 13) N 38 years old (n = 7) Farm workers ≤ 38 years old (n = 18) N 38 years old (n = 19)

2.92 ± 1.85 3.43 ± 0.96 20.56 ± 15.58⁎⁎ 22.16 ± 14.40⁎

Table 7 Effect of use of PPE on analyzed biomarkers in farm workers group (mean ± SD) Micronucleus (2000 cells/ subject)

Damage frequency (%) 2.15 ± 1.34 2.71 ± 1.25 15.61 ± 12.08⁎ 17.11 ± 11.57⁎

0.46 ± 0.66 0.71 ± 0.76

Comet assay (100 leukocytes/subject)

PPE Yesa (n = 25) No (n = 12) a

tube containing saline cold solution (0.9% NaCl), centrifuged (1000 rpm) for 5 min, and the pellets were washed twice in cold saline solution. After washing, a drop of cell suspension was placed on each of two microscope slides and dried at room temperature, fixed in 3:1 methanol/acetic acid, stained with Giemsa (10% in methanol) for 10 min. Micronuclei were scored when they were round-shaped and clearly separated from the main nucleus, when their chromatin structure and color were similar to main nucleus, and when they were found within the same cytoplasm (Tolbert et al., 1992). Cells undergoing degenerative processes (karyolysis, pycnosis, and nuclear fragmentation) were excluded from the evaluation. Two thousand cells (1000 cells from each slide) were scored per individual. 2.4. Statistical analysis The distribution of each variable obtained in this study was compared with the Normal distribution using the Kolmogorov–Smirnov goodness-of-fit test. To analyze the BChE and ALA-D enzymes activities we used Student's t-test (two-tail). Comet assay data and MN frequency in buccal cells, which were non-Normally distributed, were analyzed using the non-parametric Mann–Whitney U-test (two-tail). The Pearson's rank test and Spearman's test were used to analyze data correlations as appropriate. The critical level for rejection of the null hypothesis was taken to be a P value of 5%. 3. Results Features of controls and exposed groups are shown in Table 1. No significant differences were observed between the subjects from Ijuí and Erechim regarding age, time of exposure, smoking habits and use of PPE. Furthermore they were found to have all used the same pesticides, so that all the exposed subjects were lumped together as a single group of farm workers. Control and exposed subjects were similar regarding age and smoking habit. Duration of exposure in the exposed group was 25.69 ± 10.14 years, ranged from 12 to 50 years. Analysis of questionnaires revealed that almost 68% of the pesticide-exposed workers wore at least two kinds of PPE during pesticides application (gloves, breathing masks, glasses, impermeable clothes and boots). The two enzymes measured in this study showed significantly lower levels in pesticides appliers relative to controls. Fig. 1a and b shows the results of BChE and ALAD, respectively, in controls and farm workers. There was a significant decrease the BChE activity and in ALA-D activity in farm workers relative to the control group (P ≤ 0.05 and P ≤ 0.001, respectively; Student's t-test). Regarding the enzymes activity according to

13.56 ± 13.28 22.25 ± 2.53

0.80 ± 0.65 0.67 ± 0.78

the use of PPE, a significant decrease of 24% (P ≤ 0.05, Student's t-test) in BChE was observed in farmers who said that they did not use any kind of PPE during pesticide application (Fig. 2a), relative to the values observed for those who wore at least two kinds of PPE. For the ALA-D activity, a just non-significant decrease of 7% was detected (Fig. 2b). Table 2 reports the mean values of the various hematological parameters. No significant differences were found between the two groups, and both presented normal hematological values similar to reference values observed in the literature for several other Brazilian populations, as described by Karazawa and Jamra (1989). Lipids profile of controls and farm workers and the reference values are shown in Table 3. Only the HDL values of both exposed and non-exposed subjects were increased (borderline values) according to reference values (Consenso Brasileiro de Dislipidemias, 1994). Table 4 shows the data obtained using Comet assay and the MN test. The Comet assay in peripheral blood leukocytes showed that the Damage index and Damage frequency observed in the exposed group were significantly higher relative to the control group (P ≤ 0.001, and P ≤ 0.05, respectively; Mann–Whitney U-test). For the MN test in oral mucosa cells, no significant difference was detected between controls and exposed subjects. Also, no significant differences were observed between younger (≤38 years) and older subjects (N38 years) (Table 5), or between smokers and nonsmokers within the groups (Table 6), either by Comet assay or MN test. As expected, a negative correlation was observed between Damage index and ALA-D activity (rs = −0.333, P = 0.011; data not shown). Regarding the use of PPE, an increase in Comet assay value was observed in the group of farmers who wore none or just one kind of PPE during pesticide application (Table 7). However this increase was not statistically significant. According to the answers to our questionnaire, the great majority of subjects in the exposed group were in contact with many pesticides, including (in alphabetical order) 2,4-D (dichlorophenoxyacetic), Atrazine, Carbendazim, Copper oxychloride, Deltramethrin, Diflubenzuron, Diuron, Glyphosate, Imazethapyr, Imidacloprid, Mancozeb, Methamidophos, Methiodicarb, Monocrotophos, Paraquat, Permethrin, Simazine, Tebuconazole (Table 8). For this reason we could not associate the observed biochemical changes and DNA damage with a specific product or chemical class. In addition, no detailed data were available on the quantities of these pesticides used by the individuals.

Table 8 List of pesticides used by the exposed subjects Pesticide

Common name

Chemical class

IARC

WHO

Fungicides

2,4-D (2,4 dichlorophenoxyacetic) Copper oxychloride Mancozeb Tebuconazole Atrazine Diuron Glyphosate Paraquat Simazine Imazethapyr Imidacloprid Carbendazim Deltramethrin Diflubenzuron Methamidophos Methiodicarb Monocrotophos Permethrin

Chlorophenoxyacetic Copper compounds Dithiocarbamate Azole Triazine Urea Phosphanoglycine Bipyridilium Triazine Imidazolinone Chloronicotinyl Benzimidazole Pyretroyd Benzoilurea Organophosphorus N-Methyl Carbamate Organophosphorus Pyretroyd

NL NL NL NL 2B NL NL NL 3 NL NL NL 3 NL 3 NL NL 3

II III U III U U U II U U II U II U Ib Ib Ib II

Table 6 Influence of smoking habits in Comet assay and MN data (mean ± SD)

Controls Non-smokers (n = 16) Smokersa (n = 4) Farm workers Non-smokers (n = 29) Smokersa (n = 8)

18.16 ± 16.99 28.08 ± 3.82

At least two kinds of PPE during pesticide application.

Herbicides

Damage index (0–400)

Damage frequency (%)

0.94 ± 0.64 0.58 ± 0.69

⁎Difference significant relative to control group at P ≤ 0.05, and ⁎⁎P ≤ 0.01 (Mann– Whitney U-test, two-tail).

Comet assay (100 leukocytes/subject)

Damage index (0–400)

Micronucleus (2000 cells/ subject)

Micronucleus (2000 cells/ subject)

Damage frequency (%)

2.88 ± 1.59 4.00 ± 1.41

2.31 ± 1.45 2.50 ± 0.58

0.56 ± 0.73 0.50 ± 0.58

15.88 ± 15.22⁎ 22.90 ± 14.58⁎

12.38 ± 12.31⁎ 17.38 ± 12.31⁎

0.69 ± 0.66 1.00 ± 0.76

a Individuals who smoke more than 5 cigarettes per day; ⁎difference significant relative to control group at P ≤ 0.001 (Mann–Whitney U-test, two-tail).

Insecticides

IARC (1991) classification: 2B = possibly carcinogenic to humans; 3 = not classifiable as to carcinogenicity to humans; NL = not listed. WHO (2005) classification: Ib = highly hazardous; II = moderately hazardous; III = slightly hazardous; U = unlikely to pose acute hazard in normal use.

A.P. Remor et al. / Environment International 35 (2009) 273-278

4. Discussion The aim of the study was to determine possible changes in enzymatic, hematological and lipid parameters, and DNA damage in the particular group of farmers occupationally exposed to a complex mixture of pesticides. Our results showed an association between the exposure to these substances and decreasing activity of BChE and ALAD enzymes, as well as an increase in the DNA damage detected by Comet assay. The enzymes measured in this study showed significant reductions of 28% for BChE and 15% for ALA-D in the pesticides appliers, relative to the control group. BChE is an important enzyme for the nervous system and is responsible for the degradation of the acetylcholine. If acetylcholine remains in neural synapses, it can disrupt the normal functioning of the nervous system. Organophosphates can disrupt cholinesterase activity and result in the accumulation of acetylcholine in synapses (Ali et al., 2008). The significant decrease in the level of BChE in farm workers indicates that exposure to pesticides has the potential to disrupt nervous system function. The use of the insecticides Methamidophos, Methiocarb, and Monocrotophos, by farm workers in this study, could justify these findings. These results are consistent with those of previous studies (Panemangalore et al., 1999; Hernández et al., 2005; Mourad, 2005; Ali et al., 2008), and confirm that the measurement of plasmatic cholinesterase can be useful as biomarker in the monitoring of populations exposed to organophosphorus and carbamates pesticides. The inhibition of ALA-D in exposed subjects can result from pesticides binding on enzyme, leading to inhibition of enzyme activity (Hodgson and Levi, 1996; Panemangalore et al., 1999). Some studies also suggest that exposure to pesticides of different categories induces the generation of reactive oxygen species (ROS) (Prakasan et al., 2001), which can generate free radicals within erythrocytes, resulting in lipid peroxidation in the erythrocyte membrane (Kehrer,1993; Banerjee et al., 1999; Panemangalore et al., 1999), which could inhibit ALA-D activity. Some researchers have reported that subjects exposed to pesticides can present hematological alterations (i.e. anaemia) (Mourad, 2005) and this could to be related with ALA-D enzyme inhibition. However, in agreement with the results of Lebailly et al. (2003) and Pastor et al. (2002) from farm workers exposed to pesticide mixtures, the values obtained in our study for the hematological parameters showed no significant differences between control and exposed groups for the parameters analyzed. The Comet assay has been used to determine the extent of DNA damage in leukocytes from farm workers with occupational exposure to a variety of pesticides (Garaj-Vrhovac and Zeljezic, 2001; Undeger and Basaran, 2002; Shadnia et al., 2005; Muniz et al., 2008; da Silva et al., in press). Our study, showing that DNA damage was greater in leukocytes of farm workers, is consistent with these previous reports. These data suggest that the farm workers had been exposed to genotoxic components of pesticides. Among the pesticides used, positive results for genotoxicity were observed for Atrazine (Ribas et al., 1995), 2,4-D (González et al., 2005), Paraquat (Ribas et al., 1995), and Permethrin (Undeger and Basaran, 2005) in vitro; for Methamidophos in vivo (Karabay and Oguz, 2005); and for Imidacloprid (Karabay and Oguz, 2005; Demsia et al., 2007), Monocrotophos (Jamil et al., 2004), and Deltamethrin (Chauhan et al., 2007) for both in vitro and in vivo tests. Synergistic interaction can also be expected in mixtures of pesticides, as described by Karabay and Oguz (2005) for Metamidophos + Imidacloprid in the induction of Chromosomes Aberration in rat bone marrow cells. Furthermore, there are also concerns that the risk of genotoxicity from some pesticides might be appreciably greater than that predicted from toxicity tests (Bolognesi, 2003). Because tobacco smoke is a well-documented source of a variety of potentially mutagenic and carcinogenic compounds, smokers should be a suitable study group with relevant mutagen exposure. Tobacco consumption did not affect the results for DNA damage used in this study, although a non-significant increase in Comet assay values was

277

observed in smokers when compared with non-smokers in both control and farm workers. The effect of smoking on Comet assay remains a controversial issue. In accordance with other studies (Moller et al., 2000; Speit et al., 2003), our data suggest a slight increase of DNA damage in smokers. The results obtained in this study show that there is no exposure related induction of MN in buccal epithelial cells. Although only a few studies have been conducted, data reported using these cells indicate both negative (Lucero et al., 2000; Pastor et al., 2001) and positive results (Gomez-Arroyo et al., 2000). The use of the MN test in exfoliated cells has substantially increased as it is considered a useful biomarker of genotoxic effects in populations exposed to genotoxicants through direct contact with ingested or inhaled compounds. It must be recalled that epithelial cells are highly proliferative and are the origin of more than 90% of cancers, for which their use in biomonitoring can be really useful (Salama et al., 1999). A major problem in interpreting biomonitoring studies is estimating the degree of exposure. Possible abuse or misuse could lead to significant levels of exposure (Bolognesi, 2003). Until now, many biomonitoring studies have been performed in people from different regions and under a variety of exposure conditions, using several different biomarkers. In this context, it is not surprising that the results obtained by different authors have also shown great variability. Also, since workers are frequently exposed to complex mixtures of pesticides, it is difficult to attribute the genotoxic damage to any particular chemical class or compound. The lack of information about the behavior of toxic substances in complex mixtures is often avoided by assuming that the toxicity of a mixture is simply the sum of the expected effects from each mixture component, i.e. that no synergistic or antagonistic interactions (Ergene et al., 2007). The main absorption path for pesticides is through skin and the respiratory system (Faria et al., 2007). For this reason, the use of appropriate clothes, masks and gloves is necessary to prevent the contamination. In a recent review, Bull et al. (2006) referred to genotoxicity in pesticide appliers and highlighted the importance of PPE usage. Only 68% of the workers in our study wore appropriate protection, and this fact could justify the parameters found in BChE, ALA-D and Comet assay. Lander et al. (2000) and Costa et al. (2007) also reported that cytogenetic effects are observed primarily in workers who did not wear PPE as appropriated. However, in the present study, even for those farm workers who said they wore adequate PPE, a decrease in BChE activity was observed together with an increase in Comet assay values, although these effects were not significant. A possible explanation is that farm workers from rural areas in Brazil, like those in most of developing countries, do not always pay enough attention to the renewal or cleaning of their protective clothing or equipment. If the equipment is seldom changed or cleaned, the effective protection afforded by them can be very low. Acknowledgments The authors express their gratitude to all the individuals who volunteered to participate in this study. We also thank to Ms C Sandra Manoela Dias Macedo for valuable help in enzymatic tests and to EMATER/ASCAR (Council of Paulo Bento, RS) for aid on visits to communities, and for providing pesticide information. This work was financially supported by Brazilian Universities: Universidade Regional Integrada do Alto Uruguai e das Missões (URI/SETEX, Erechim, RS) and Universidade do Noroeste do Estado do Rio Grande do Sul (UNIJUI, RS). References Ali T, Bhalli JA, Rana SM, Khan QM. Cytogenetic damage in female Pakistani agricultural workers exposed to pesticides. Environ. Mol. Mutagen 2008;49:374–80. Banerjee BD, Seth V, Bhattacharya A, Pasha ST, Chakraborty AK. Biochemical effects of some pesticide on lipid peroxidation and free-radical scavengers. Toxicol Lett 1999;107:33–47.

278

A.P. Remor et al. / Environment International 35 (2009) 273-278

Berlin A, Schaller KH. European standardized method for the determination of daminolevulinic acid dehydratase in blood. Z Klin Chem Biochem 1974;2:389–90. Bolognesi C. Genotoxicity of pesticides: a review of human biomonitoring studies. Mutat Res 2003;543:251–72. Bull S, Fletcher K, Boobis AR, Battershil JM. Evidence for genotoxicity of pesticides in pesticide applicators: a review. Mutagenesis 2006;21:93–103. 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. Chauhan LK, Kumar M, Paul BN, Goel SK, Gupta SK. Cytogenetic effects of commercial formulations of deltamethrin and/or isoproturon on human peripheral lymphocytes and mouse bone marrow cells. Environ Mol Mutagen 2007;48:636–43. Collins AR. The Comet assay for DNA damage and repair: principles, applications and limitations. Mol. Biotechnol. 2004;26:249–61. Consenso Brasileiro sobre Dislipedemias (Detecção, avaliação, tratamento). Arq Bras Cardiol 1994;63:67–79. Costa C, Silva S, Coelho P, Roma-Torres J, Teixeira JP, Mayan O. Micronucleus analysis in a Portuguese population exposed to pesticides: preliminary survey. Int J Hyg Environ Health 2007;210:415–8. Daniels JL, Olshan AF, Savitz DA. Pesticides and childhood cancers. Environ Health Perspect 1997;105:1068–77. da Silva J, Moraes CR, Heuser VD, de Andrade VM, Silva RF, Kvitko K, et al., Evaluation of genetic damage in a Brazilian population occupationally exposed to pesticides and its correlation with polymorphisms in metabolizing genes. Mutagenesis (in press). Demsia G, Vlastos D, Goumenou M, Matthopoulos DP. Assessment of the genotoxicity of imidacloprid and metalaxyl in cultured human lymphocytes and rat bone-marrow. Mutat Res 2007;634:32–9. Engel L, Checkoway H, Keifer M, Seixas N, Longstreth W, Scott K, et al. Parkinsonism and occupational exposure to pesticides. Occup Environ Med 2001;58:581–9. Ergene S, Celik A, Cavaş T, Kaya F. Genotoxic biomonitoring study of population residing in pesticide contaminated regions in Göksu Delta: micronucleus, chromosomal aberrations and sister chromatid exchanges. Environ Int 2007;33:877–85. Faria NMX, Fassa AG, Facchini LA. Pesticides poisoning in Brazil: the official notification system and challenges to conducting epidemiological studies. Cien Saude Colet 2007;12:25–38. Figá-Talamanca I, Petrelli G. Reduction in fertility in male greenhouse workers exposed to pesticides. Eur J Epidemiol 2001;17:675–7. Garaj-Vrhovac V, Zeljezic D. Cytogenetic monitoring of croatian population occupationally exposed to a complex mixture of pesticides. Toxicology 2001;165:153–62. Gauthier E, Forthier I, Gourchesne 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. Gómez-Arroyo S, Díaz-Sánchez Y, Meneses-Pérez M, Villalobos-Pietrini R, Rodríguez JL. Cytogenetic biomonitoring in a Mexican floriculture worker group exposed to pesticides. Mutat Res 2000;466:117–24. González M, Soloneski S, Reigosa MA, Larramendy ML. Genotoxicity of the herbicide 2,4-dichlorophenoxyacetic and a commercial formulation, 2,4-dichlorophenoxyacetic acid dimethylamine salt. I. Evaluation of DNA damage and cytogenetic endpoints in Chinese Hamster ovary (CHO) cells. Toxicol In Vitro 2005;19:289–97. Gupta S, Govil YC, Misra PK, Nath R, Srivastava KL. Trends in poisoning in children: experience at a large referral teaching hospital. Natl Med J India 1998;11:166–8. Hernández AF, López O, Rodrigo L, Gil F, Pena G, Serrano JL, et al. Changes in erythrocyte enzymes in humans long-term exposed to pesticides influence of several markers of individual susceptibility. Toxicol Lett 2005;159:13–21. Hodgson E, Levi PE. Pesticides: an important but under used model for environmental health sciences. Environ Health Perspect 1996;104:97–106. IARC (International Agency for Researches on Cancer). Occupational exposure in insecticide application and some pesticides. IARC Monographs on the Evaluation of Carcinogenic Risk to Humans. IARC 1991;53:179–250. Jamil K, Shaik AP, Mahboob M, Krishna D. Effect of organophosphorus and organochlorine pesticides (monochrotophos, chlorpyriphos, dimethoate, and endosulfan) on human lymphocytes in vitro. Drug Chem Toxicol 2004;27:133–44. Jenner P. Parkinson's disease, pesticides and mitochondrial dysfunction. Trends Neurosci 2001;24:245–7. Karazawa EH, Jamra M. Normal hematologic parameters. Rev Saude Publ 1989;23:58–66. Karabay NU, Oguz MG. Cytogenetic and genotoxic effects of the insecticides, imidacloprid and methamidophos. Genet Mol Res 2005;4:653–62. Kehrer JP. Free radicals as medators of tissue injury and disease. Crit Rev Toxicol 1993;23:21–48. Khuder SA, Mutgi AB. Meta-analyses of multiple myeloma and farming. Am J Ind Med 1997;32:510–6. Kirsch-Volders M, Sofuni T, Ardema M, Albertini S, Eastmond D, Fenech M, et al. Report from the in vitro micronucleus assay working group. Mutat Res 2003;540:153–63. Lander B, Knudsen L, Gamborg M, Jarventaus H, Norppa H. Chromosome aberrations in pesticide-exposed greenhouse workers. Scand J Work Environ Health 2000;26:436–42. Lebailly P, Devaux A, Pottier D, De Meo M, Andre V, Baldi I, et al. Urine mutagenicity and lymphocyte DNA damage in fruit growers occupationally exposed to the fungicide captan. Occup Environ Med 2003;60:910–7. López O, Hernández AF, Rodrigo L, Gil F, Pena G, Serrano JL, et al. Changes in antioxidant enzymes in humans with long-term exposure to pesticides. Toxicol Lett 2007;171:146–53. Lucero L, Pastor S, Suárez S, Durbán R, Gómez C, Parrón T, et al. Cytogenetic biomonitoring of Spanish greenhouse workers exposed to pesticides: micronuclei analysis in peripheral blood lymphocytes and buccal epithelial cells. Mutat Res 2000;464:255–62. Martino-Roth MG, Viégas J, Roth DM. Occupational genotoxicity risk evaluation through the comet assay and the micronucleus test. Genet Mol Res 2003;2:410–7.

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;9:1005–15. Moura DJ, Richter MF, Boeira JM, Henriques JAP, Saffi J. Antioxidant properties of betacarboline alkaloids are related to their antimutagenic and antigenotoxic activities. Mutagenesis 2007;22:293–302. Mourad TA. Adverse impact of insecticides on the health of Palestinian farm workers in the Gaza Strip: a hematologic biomarker study. Int J Occup Environ Health 2005;11:144–9. Muniz JF, McCauley L, Scherer J, Lasarev M, Koshy M, Kow YW, et al. Biomarkers of oxidative stress and DNA damage in agricultural workers: a pilot study. Toxicol Appl Pharmacol 2008;227:97–107. Nadin SB, Vargas-Roig LM, Ciocca DR. A silver staining method for single-cell gel assay. J Histochem Cytochem 2001;49:1183–6. Noriega GO, Gonzales S, Tomaro ML, Batle AM. Paraquat-generated oxidative stress in rat liver induces hemeoxygenase-1 and aminolevulinic acid synthase. Free Radic Res 2002;36:633–9. Nigg HN, Knaak JB. Blood cholinesterases as human biomarkers of organophosphorus pesticide exposure. Rev Environ Contam Toxicol 2000;163:29–111. Ojajarvi I, Partanen T, Ahlbom A, Boffetta P, Hakulinen T, Jourenkova N, et al. Occupational exposures and pancreatic cancer: a meta-analysis. Occup Environ Med 2000;57:316–24. Olive PL, Wlodek D, Durand RE, Banáth JP. Factors influencing DNA migration from individual cells subjected to gel electrophoresis. Exp Cell Res 1992;198:259–67. Panemangalore M, Dowla HA, Byers ME. Occupational exposure to agricultural chemicals: effect on the activities of some enzymes in the blood of farm workers. Environ Heath Progr 1999;72:84–8. Pastor S, Gutiérrez S, Creus A, Cebulska-Wasilewskab A, Marcos R. Micronuclei in peripheral blood lymphocytes and buccal epithelial cells of Polish farmers exposed to pesticides. Mutat. Res. 2001;495:147–56. Pastor S, Lucero L, Gutiérrez S, Durbán R, Gómez C, Párron T, et al. Follow-up study on micronucleus frequency in Spanish agricultural workers exposed to pesticides. Mutagenesis 2002;17:79–82. Prakasan A, Sethupathy S, Lalitha S. Plasma and RBCs antioxidant status in occupational male pesticide sprayers. Clin Chim Acta 2001;310:107–12. Ribas G, Frenzilli G, Barale R, Marcos R. Herbicide-induced DNA damage in human lymphocytes evaluated by the single-cell gel electrophoresis (SCGE) assay. Mutat Res 1995;344:41–54. Ritz B, Yu F. Parkinson's disease mortality and pesticide exposure in California 1984– 1994. Int J Epidemiol 2000;29:323–9. Salama SA, Serrana M, Au WW. Biomonitoring using accessible human cells for exposure and health risk assessment. Mutat Res 1999;436:99–112. Shadnia S, Azizi E, Hosseini R, Khoei S, Fouladdel S, Pajoumand A, et al. Evaluation of oxidative stress and genotoxicity in organophosphorus insecticide formulators. Hum Exp Toxicol 2005;24:439–45. Singh NP, McCoy MT, Tice RR, Scheider EL. A simple technique for quantification of low levels of DNA damage in individual cells. Exp Cell Res 1988;175:184–91. Singh VK, Jyoti, Krishna Reddy MM, Kesavachandran C, Rastogi SK, Siddiqui MK. Biomonitoring of organochlorines, glutathione, lipid peroxidation and cholinesterase activity among pesticide sprayers in mango orchards. Clin Chim Acta 2007;377:268–72. Speit G, Witton-Davies T, Heepchantree W, Trenz K, Hoffmann H. Investigations on the effect of cigarette smoking in the comet assay. Mutat Res 2003;542:33–42. Tolbert PE, Shy CM, Allen JW. Micronuclei and other nuclear anomalies in buccal smears: methods development. Mutat Res 1992;271:69–77. Undeger U, Basaran N. Assessment of DNA damage in workers occupationally exposed to pesticides mixtures by the alkaline comet assay. Genotoxicity 2002;76:430–6. Undeger U, Basaran N. Effects of pesticides on human peripheral lymphocytes in vitro: induction of DNA damage. Arch Toxicol 2005;79:169–76. Villela IV, de Oliveira IM, da Silva J, Henriques JAP. DNA damage and repair in haemolymph cells of golden mussel (Limnoperna fortunei) exposed to environmental contaminants. Mutat Res 2006;605:78–86. WHO (World Health Organization). The WHO Recommended Classification of Pesticides by Hazard and Guideline to Classification. Geneva, Switzerland: WHO; 2005. Zahm SH, Ward MH. Pesticides and childhood cancer. Environ Health Perpect 1998;106:893–908.