Environ. Sci. Technol. 2009, 43, 6370–6377
Effect of Occupational Exposure to Multiple Pesticides on Translocation Yield and Chromosomal Aberrations in Lymphocytes of Plant Workers D A V O R Z E L J E Z I C , * ,† ANA LUCIC VRDOLJAK,† JOE N. LUCAS,‡ RUZICA LASAN,§ ALEKSANDRA FUCIC,† NEVENKA KOPJAR,† JELENA KATIC,† MARIN MLADINIC,† AND BOZICA RADIC† Institute for Medical Research and Occupational Health, Ksaverska 2, Zagreb, Croatia 10000, Department for Molecular Biology, Frederick Innovative Technology Center, ChromoTrax, Inc., Frederick, MD 21701, and Cytogenetic Laboratory, Department of Pediatrics, Zagreb University School of Medicine, Zagreb, Croatia 10000
Received March 23, 2009. Revised manuscript received June 12, 2009. Accepted July 8, 2009.
Employees handling pesticides are simultaneously exposed to different active substances. Occurring multiple chemical exposures may pose a higher risk than it could be deduced from studies evaluating the effect of a single substance. This study comprised 32 pesticide plant workers exposed to carbofuran, chlorpyrifos, metalaxyl, and dodine and an equal number of control subjects. Groups were matched by age (43.8 ( 10.16 vs 41.8 ( 7.42, respectively), sex (14 females; 18 males), and smoking (11 smokers; 21 nonsmokers). Chromosome aberration and translocation frequencies were determined using a standard aberration assay and fluorescent in situ hybridization (FISH) by applying painting probes for chromosomes 1, 2, and 4. Although significant, an observed increase in chromatid breaks (5.2 ( 2.49) compared to controls (2.1 ( 0.87), pPostHoc ) 0.000001 is biologically irrelevant. Genomic frequency of translocations was also significantly elevated (exposed 0.0165 ( 0.0070; control 0.0051 ( 0.0023, pPostHoc ) 0.0000004). The distribution of translocations among chromosomes 1, 2, and 4 did not differ from control subjects. It corresponded to the distribution of DNA content among selected chromosomes indicating randomness of DNA damage. A good translocation yield correlation within years spent in pesticide production indicates that multiple pesticide exposure may pose a risk to genome integrity. However, for more accurate health risk assessments, the use of probes for some other groups of chromosomes should be considered.
1. Introduction Nowadays, approximately 1000 active ingredients with pesticide properties could be found on the market, more than 600 in the U.S. and some 500 in EU (1). Ever wider presence of agrochemicals in the environment raises the * Corresponding author phone: 385-1-4673188; fax: +385-14673303; e-mail:
[email protected]. † Institute for Medical Research and Occupational Health. ‡ ChromoTrax, Inc. § Zagreb University School of Medicine. 6370
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concern about their adverse health effects. Major attention has been focused on the final consumers of agricultural products. However, mostly affected populations are employees of pesticide plants and applicators exposed to several times higher levels of agrochemicals over a long period of time on a daily basis (2). In most occupational exposures, individuals are simultaneously exposed to a range of different active substances and only their cumulative effect on health and genome status could be evaluated (3). Thus, studies on the effect of multiple pesticide exposure reveal very little knowledge on the mechanism of genotoxicity of a single active ingredient. However, they are of high importance because they look directly at human risk and make it possible to estimate the contribution of recorded type of exposure to the local population’s genomic pool status and its possible reflections on public health (4). The aim of the present study was to evaluate the effect of occupational multiple pesticide exposure on the genomic stability of pesticide production line workers taking into account other demographic characteristics as confounding factors. Examinees have been continuously exposed to carbofuran, chlorpyrifos, metalaxyl, and dodine. Key risks that may arise from chronic exposure to multiple pesticides are cancer, birth defects, and damage to the nervous and endocrine systems (5). Carbofuran belongs to the N-methylcarbamate insecticides that were introduced to the market in 1967 by Bayer A.G. Baligar et al. (6) reported its adverse effect on the estrous cycle in rats. Several epidemiological studies indicated a possible correlation between occupational exposure to carbofuran and a risk of non-Hodgkin lymphoma (7) and lung cancer development (8). Chlorpyrifos is an organophosphate insecticide that has been available on the market since 1965. Although it is not considered to be mutagenic, teratogenic, or carcinogenic, there are reports indicating that its extensive use led to a significant exposure response trend for rectal cancer and adult glioma (9, 10) A dose-dependent reduction in estradiol level was reported among men as well (11). There are no studies that evaluate the risk of cancer associated with exposure to metalaxyl, a phenylamide based fungicide used since 1977. However, a study by Vlastos et al. (12) suggested its genotoxic effect on farmers. An observed effect may be mediated by metalaxyl’s metabolite 2,6dimethylaniline, proved to be a nasal carcinogen (13). There are no epidemiological studies correlating occupational exposure to the fungicide dodine (dodecylguanidine acetate) and cancer incidence or its adverse effect on the endocrine system. Accordingly, EPA stated that dodine has not been fully evaluated for its carcinogenic potential in humans (14). The aim of this study was to evaluate the effects of a longterm simultaneous occupational exposure to carbofuran, chlorpyrifos, metalaxyl, and dodine on chromosome stability of 35 workers employed in pesticide production. To evaluate stable aberration frequency, we applied the genome equivalent principle using fluorescent in situ hybridization (FISH) of chromosomes 1, 2, and 4 (15). Observed genotoxic effects were tested for the correlation with the years spent in production.
2. Subjects and Methods 2.1. Study Population. Genome damage caused by occupational multiple pesticide exposure was evaluated among 32 workers recruited on the same production line (14 females; 10.1021/es900824t CCC: $40.75
2009 American Chemical Society
Published on Web 07/20/2009
18 males). Their average age was 43.8 ( 10.16 (range 24-59), and their average continuous exposure was 16.2 ( 10.9 (range 1-36). Examinees completed the questionnaires on their personal medical history (exposure to X-rays, vaccinations, medication, etc.), lifestyle (smoking, alcohol, diet), and occupation (working hours/day, years of exposure, etc.). Only individuals with no records of suffering any inflammatory and/or autoimmune disease, malignancies, psychological disorders, or any other state that would require chronic medical treatment and those who consume less than 4 units of alcohol per day (within the last year) or smoke less than 10 cigarettes per day (5.28 ( 4.22 within last year) were chosen to participate in the study. Heavy smokers, ex-smokers, and heavy drinkers were excluded. Workers (88.57%) declared nonuse of individual protective equipment more than 60% of the time spent working with pesticides. Another 21.43% of workers wore protective gloves more than 80% of the working hours but did not use masks. Continuous monitoring of the air quality in production halls has been conducted twice a year since 1997. During this period, mean air dust concentration was 3.1 ( 0.55 mg/m3 (2.4-3.8 mg/m3), carbofuran was 0.06 ( 0.017 mg/m3 (0.04-0.09 mg/m3), chlorpyrifos was 0.14 ( 0.02 mg/m3 (0.11-0.17 mg/m3), and metalaxyl was 0.68 ( 0.16 mg/m3 (0.40-0.94 mg/m3). Control subjects were selected from the initial group of 137 voluntary blood donors living in the same area as the exposed subjects. Donors completed the same questionnaires as the examinees. To avoid bias due to overcontrol, only individuals with no record of occupational or household/ vegetable/garden exposure to pesticide were left for further consideration. As previously described, health, alcohol consumption, and smoking criteria were used for further exclusion. Finally, 32 subjects were selected to match the exposed group by number of men (18), women (14), smokers (11), alcohol consumers (3), and approximately by age (41.8 ( 7.42) as shown in Table S1 in the Supporting Information. All participating subjects signed an informed consent form and could withdraw from the study at any time. The study was designed in accordance with the Helsinki II declaration and approved by the ethical committee of the Institute for Medical Research and Occupational Health. It is part of the project approved by the Ministry of Science, Education, and Sports of the Republic of Croatia. 2.2. Sample Collection and Lymphocyte Cultures. For exposed and control subjects, the blood sampling occurred simultaneously in February 2008. Peripheral blood samples were collected by venipuncture into vacutainers (Beckton Dickinson, U.K.) containing sodium heparin, coded, and immediately transported to the laboratory. The samples were kept on ice. Cultures of peripheral blood lymphocytes from whole venous blood were established within 3 h after collection. Five milliliters of blood was cultivated in a Chromosome kit P (EuroClone, Italy). Four identical cultures were set up from each sample and cultivated at 37 °C. Cultures for standard chromosomal aberration analyses were harvested in 48 h and for FISH in 72 h of incubation. Three hours before the end of cultivation, colchicine (Sigma) was added at the final concentration of 1.25 × 10-6 M. The cells were collected by centrifugation, resuspended in hypotonic solution (0.075MKCl), and fixed in acetic acid/methanol 1:3 (v/v) according to a standard procedure (16). 2.3. Chromosomal Aberration Analysis. The cell suspensions were dropped on cold and moisturized slides and left to dry for one day before staining with 0.5% Giemsa (Sigma). Per each subject, 1000 metaphases were scored, recording the number of chromatid and chromosome breaks, acentric fragments, or any other possible morphological abnormality (17, 18). A cell containing any type of aberration was considered aberrant.
2.4. FISH Analysis. FISH was performed on metaphase spreads with whole chromosome-painting probes, following the instructions of the supplier (Cytocell Technologies Ltd., Cambridge, U.K.). Chromosomes 1, 2, and 4 were painted by directly labeled Aquarius chromosome-painting probes. They were labeled with a red fluorophore (Texas Red spectrum), green fluorophore (FITC spectrum), and a combination of both fluorophores, respectively. The chromosomes were counterstained with DAPI/antifade solution (Cytocell Technologies Ltd.). Probed slides were scored using an Olympus AX70 epifluorescence microscope (Olympus Optical, London, U.K.). At least 1000 metaphases per subject (17) were analyzed using a PAINT nomenclature system according to Tucker et al. (19), and they were recorded by CytoVision FISH software (Applied Imaging, Germany). Genomic frequencies of stable chromosomal exchanges were calculated according to the Lucas formula for multiple colors (20). Chromosome pairs 1, 2, and 4 represent 22.34% of the DNA content of the human genome (coding and noncoding regions) of women and 22.70% of men. Thus, labeling of chromosomes 1, 2, and 4 is expected to detect about 37.2% of chromosomal interchanges occurring in the complete genome (21). 2.5. Statistical Analysis. The distribution of each variable obtained in this study was compared with the Normal distribution using the Kolmogorov-Smirnov goodness-offit test. Multivariable statistical analysis was adjusted for potential confounders that are significantly associated with cytogenetic biomarkers: age (5-years age-class), gender, years in the pesticide production (0-4; 5-9; 10-14; 15-19;g20 years), smoking habit (never; 1-5 cigs/day; 6-10 cigs/day), and alcohol drinking (never; 1-2 units/day; 3-4 units/day), using them as covariates. Described categories of smoking and alcohol consumption intensity were coded with 0, 1, and 2. When testing differences between subgroups regarding smoking habits and gender, variables for smoking and gender, respectively, were used as independent ones instead of covariates. Scheffe´’s post hoc procedure for multiple comparisons at a significance level of 0.05 was used to test differences in the frequency of chromatid breaks, chromosome breaks, acentrics, aberrant cells, and translocations between the groups. To reveal the F values for the same set of data, MANOVA was used again taking into account age, years of exposure, gender, smoking, and alcohol as covariates. Wilk’s lamda statistics were used to test the differences between exposed and control groups and subgroups (gender, smoking habits) within them simultaneously considering chromatid, chromosome breaks, acentrics, aberrant cells, and translocations as dependent variables. Multiple regression analysis was done to evaluate strength of dependence of translocation and aberration frequencies on age, years spent in the production, gender, and smoking. Statistical analysis was performed using Statistica 5.5 (StatSoft, Tulsa, OK).
3. Results When taking into account all confounding factors (age, gender, smoking, alcohol intake), Scheffe´’s post hoc analysis showed that only the number of chromatid breaks in the lymphocytes of subjects occupationally exposed to pesticides was significantly higher than in controls (p < 0.01). The total number of cells bearing any structural aberrations was significantly elevated in pesticide production workers as well (Table 2). However, due to their extremely low frequency, both increases could be considered as biologically irrelevant. Multiple correlation coefficients obtained for number of chromatid breaks (R2)0.479) and aberrant cells (R2 ) 0.521) and exposure duration (Table S3 in the Supporting Information) suggest that an observed increase may be a result of VOL. 43, NO. 16, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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cumulative DNA damage due to multiple pesticide exposure. However, to give a final conclusion, additional studies with similar exposure conditions on cohorts from other countries should be performed and considered. Beside exposure time, both cytogenetic parameters significantly correlated with age of the subjects (R2 ) 0.544 and R2 ) 0.466, respectively). The number of chromatid breaks exhibited stronger correlation with age (β ) 0.667 vs exposure β ) 0.564), and the number of aberrant cells exhibited stronger correlation with employment time (β ) 0.686 vs age β ) 0.576). Although the number of chromatid breaks and aberrant cells did not differ among men and women (Table 2), chromatid breaks and aberrant cells among male workers were seriously affected by employment duration (R2 ) 0.650; R2 ) 0.647, respectively; Table S4 in the Supporting Information). No such correlation was observed among the exposed women (breaks: R2 ) 0.180; aberrant cells: R2 ) 0.273). Scheffe´’s post hoc analysis showed a significant difference of exposed subjects between smokers and nonsmokers only in number of chromosome breaks (p < 0.05; Table 2). Similar results were obtained by multiple correlation analysis. Of all aberration types, smoking habit influenced significantly only chromosome breaks (R2 ) 0.39; Table S3 in the Supporting Information). Chromosome breaks were highly affected by age of the workers but not by the years of exposure (Table S3 in the Supporting Information). Among control subjects, only frequency of chromosome breaks showed significant intergender differences (Table 2) being higher among females. In control smokers, post hoc analysis indicated a significantly increased number of chromatid breaks (p < 0.05), acentric fragments (p < 0.05), and aberrant cells (p < 0.001) compared to nonsmokers (Table 2). Multiple correlation analysis (Table S3 in the Supporting Information) indicated a significant effect of age on chromatid breaks (R2 ) 0.33), smoking habit on acentric fragments (R2 ) 0.121) and aberrant cells (R2 ) 0.184), and gender on chromosome breaks (R2 ) 0.310), which is in agreement with post hoc analysis results detecting a significant difference in their frequency between females and males (Table 2). However, on the level of subpopulations formed according to gender, acentric fragments correlated significantly with the age of the control women (R2 ) 0.624), while among men the dependence was not prominent (R2 ) 0.02). Multivariate analysis of variances indicated significantly higher frequency of translocations in the group of pesticide plant workers than in controls (Table 1). In the control group, we never observed more than a single translocation per lymphocyte, whereas in the exposed subjects some cells bore up to three translocations (Table 3), which turned out to be statistically significant (p ) 0.021). There were no statistical intergender differences in the translocation frequencies among exposed individuals. Also, smoking habits and alcohol intake did not affect translocation yield (Table 1). Multiple regression analysis (Table S3 in the Supporting Information) revealed a significant influence of age and years of employment on translocation frequency (R2 ) 0.274 and R2 ) 0.356, respectively). The influence of exposure duration was more prominent (β ) 0.623 vs age β ) 0.524). It is also interesting that at the level of subpopulations (Table S4 in the Supporting Information), among exposed males, translocations were correlated with years of employment (R2 ) 0.256) but not with the age of subjects (R2 ) 0.088). While among the exposed females, the influence of both, age (R2 ) 0.868) and employment duration (R2 ) 0.555), were observed. However, the influence of age slightly prevailed over the employment (β ) 0.932 and β ) 0.745, respectively). No correlation of translocation number with smoking or gender was found (Table S3 in the Supporting Information). 6372
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Since there are no differences in the frequency of use of protective equipment, no influence on translocation frequency and chromosomal aberrations was observed (R2 ) 0.03, p ) 0.86). As calculated by Scheffe´’s post hoc analysis, translocation yield among controls did not differ among gender subpopulations, smokers, and nonsmokers (Table 1). Multiple regression did not indicate correlation with any of confounding factors, except for the smoking habit (R2 ) 0.214). Although at the group level translocation yield did not correlate with age, their interdependence appeared to be significant among the control group of women (R2 ) 0.528), which was not the case for the control group of men (R2 ) 0.094, Table S1 in the Supporting Information). The distribution of translocations between chromosomes 1, 2, and 4 (Table 3) did not differ significantly among the groups (p ) 0.89). In controls, translocations of chromosome 1 were underrepresented insignificantly (p ) 0.88), and translocations of chromosome 4 were slightly overrepresented (p ) 0.88) as compared to the distribution of DNA among those chromosomes (22). Altogether, Wilk’s lamda statistics revealed that chromatid, chromosome breaks, acentric fragments, aberrant cells, and translocation frequencies as combination dependent variables differed significantly between examinees and control subjects, as well as between control smokers and nonsmokers (Table S2 in the Supporting Information).
4. Discussion The present study showed a significantly increased number of translocation frequencies among workers employed in the production line handling carbofuran, chlorpyrifos, metalaxyl, and dodine. Chromatid breaks and aberrant cells, although affected in exposed subjects, remained lower than the spontaneous number of aberrations reported in some other studies (16). Both chromatid breaks and translocations correlated significantly with the age of the individuals and years of exposure. Chromosome aberrations, which are unstable genome damage, may show a generally higher risk of cancer on the population level, while translocation frequency gives an insight into the cumulative genome damage on the individual level (23, 24). Over the last two decades, translocation frequency has been predominantly evaluated among subjects exposed to different levels of ionizing radiation by applying chromosome painting probes (25-27). Recently, several papers have been published reporting translocation yields due to occupational exposure to chemical mutagens (28, 29). However, there is a single study on possible effects of longterm exposure to pesticides on induction of stable chromosome aberrations (30). It is well-documented that agrochemicals are capable of inducing genome damage to both manufacturing workers and applicators. Findings included an increase in frequency of micronuclei (31-33), unstable chromosome aberrations (34, 35), and sister chromatid exchanges (32, 36). However, there are studies that failed to detect any significant increase in chromosome damage due to long-term pesticide exposure (37-39). Such disagreement may be explained either by different exposure conditions (protection measures used, indoor or outdoor exposure, and specific genotoxic potential of the substances used) or by demographic factors, individual habits, and associated genetic features (40). The frequency of aberrations observed in the present study for the controls, although in agreement with those published by Bonassi et al. (23), is lower than results obtained for many other cohort groups. Despite the increase, aberration frequencies among pesticide plant workers still remained below the commonly accepted yield for spontaneous chromosomal
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gender
age ((SD)
1152.7 ((125.1) 1273.6 ((174.4) 1119.2 ((152.5) F(1,30) ) 0.23 p ) 0.44 F(1,62) ) 0.05 p ) 0.83
0.0062 ((0.0027) 0.0043 ((0.0016) 0.0051 ((0.0023) F(1,27) ) 4.16d p ) 0.05 F(1,58) ) 26.00f p ) 0.000004
n/a n/a n/a n/a n/a
1098.4 ((57.0) 1129.1 ((139.1) 1095.3 ((142.9) F(1,30) ) 0.001 p ) 0.99
genome-equivalents scored ((SD)
0.0168 ((0.0061) 0.0163 ((0.0078) 0.0165 ((0.0070) F(1,26) ) 0.02b p ) 0.89
translocations per cell ((SD)
19.4 ((11.11) 13.8 ((10.29) 16.2 ((10.9) F(1,30) ) 0.06 p ) 0.80
years of exposure ((SD) age ((SD)
40.7 ((7.0) 42.3 ((7.76) 41.8 ((7.42) F(1,30) ) 0.05 p ) 0.81
yes n ) 11 42.4 ((10.18) no n ) 21 44.5 ((10.32) total n ) 32 43.8 ((10.16) F(1,30) ) 1.03 p ) 0.31
smoking
significance smokers vs nonsmokers control yes n ) 11 no n ) 21 total n ) 32 significance smokers vs nonsmokers
exposed
group
n/a n/a n/a n/a
12.9 ((7.49) 18.0 ((12.07) 16.2 ((10.9) F(1,30) ) 1.39 p ) 0.24
years of exposure ((SD)
translocations per cell ((SD)
0.0050 ((0.0020) 0.0052 ((0.0025) 0.0051 ((0.0023) F(1,27) ) 0.04e p ) 0.83
0.0159 ((0.0092) 0.0169 ((0.0059) 0.0165 ((0.0070) F(1,26) ) 0.64c p ) 0.42
regarding smoking habits
1180.0 ((187.7) 1251.3 ((139.6) 1119.2 ((152.5) F(1,30) ) 0.03 p ) 0.86
1098.7 ((144.0) 1155.8 ((163.7) 1153.3 ((111.6) F(1,30) ) 0.09 p ) 0.77
genome-equivalents scored ((SD)
a Results are presented regarding gender and smoking habits within study groups. For each subject, more than 1000 genomic equivalents were analyzed. Control smokers had 7.5 ( 3.15 cigarettes per day within the last year, and exposed smokers had 5.3 ( 4.22 cigarettes per day within the last year; there were no ex-smokers. b Significances were calculated by applying Scheffe’s post hoc procedure for multiple comparisons taking into account all confounding factors if applicable: age, years of exposure, smoking, alcohol intake. c Significances were calculated by applying Scheffe’s post hoc procedure for multiple comparisons taking into account all confounding factors if applicable: age, years of exposure, gender, alcohol intake. d Significances were calculated by applying Scheffe’s post hoc procedure for multiple comparisons taking into account all confounding factors if applicable: age, smoking, alcohol intake. e Significances were calculated by applying Scheffe’s post hoc procedure for multiple comparisons taking into account all confounding factors if applicable: age, gender, alcohol intake. f Significances were calculated by applying Scheffe’s post hoc procedure for multiple comparisons taking into account all confounding factors if applicable: age, gender, smoking, alcohol intake.
exposed
females n ) 14 47.5 ((9.21) males n ) 18 40.8 ((10.09) total n ) 32 43.8 ((10.16) significance F(1,30) ) 2.45 females vs p ) 0.13 males control females n ) 14 40.6 ((6.62) males n ) 18 42.1 ((8.05) total n ) 32 41.8 ((7.42) significance F(1,30) ) 0.12 females vs p ) 0.72 males F(1,62) ) 0.81 significance p ) 0.37 exposed vs control
group
regarding gender
TABLE 1. Translocation Frequencies in Lymphocytes of Pesticide Plant Workers and Control Subjectsa
TABLE 2. Chromosomal Aberrations in Lymphocytes of Pesticide Plant Workers and Control Subjectsa average number per individual ((SD) group exposed
gender total n ) 32 females n ) 14 males n ) 18 smokers n ) 11 nonsmokers n ) 21
significance females vs males significance smokers vs nonsmokers control total n ) 32 females n ) 14 males n ) 18 smokers n ) 11 nonsmokers n ) 21 significance females vs males significance smokers vs nonsmokers significance exposed vs control
age ((SD) 43.8 47.5 40.8 42.4
( ( ( (
10.16 9.21 10.09 10.18
44.5 ( 10.32
years of exposure ((SD) 16.2 19.4 13.8 12.9
( ( ( (
10.9 11.11 10.29 7.49
5.2 5.5 4.9 5.2
( ( ( (
chromosome breaks
2.49 2.27 2.68 2.09
1.0 1.1 0.9 1.4
( ( ( (
acentric fragments
1.03 1.23 0.87 1.04
0.8 1.1 0.7 0.9
( ( ( (
aberrant cells/ percentile 0.69 ( 0.32 0.74 ( 0.32 0.65 ( 0.32 7.1 ( 0.30
0.82 0.95 0.68 0.83
5.14 ( 2.72
0.8 ( 0.98
F(1,30) ) 2.45 F(1,30) ) 0.06 p ) 0.13 p ) 0.80
F(1,26) ) 0.67b p ) 0.42
F(1,26) ) 0.19b F(1,26) ) 1.17b F(1,26) ) 0.13b p ) 0.66 p ) 0.28 p ) 0.71
F(1,30) ) 1.03 F(1,30) ) 1.39 p ) 0.31 p ) 0.24
F(1,26) ) 0.60c p ) 0.44
F(1,26) ) 5.57c F(1,26) ) 1.57c F(1,26) ) 1.76c p ) 0.02 p ) 0.22 p ) 0.19
41.8 40.6 42.1 40.7
( ( ( (
18.0 ( 12.07
chromatid breaks
( ( ( (
7.42 6.62 8.05 7.0
n/a n/a n/a n/a
2.1 2.1 2.2 2.4
0.87 1.07 0.71 1.13
42.3 ( 7.76
n/a
2.0 ( 0.67
0.6 0.8 0.4 0.8
( ( ( (
0.8 ( 0.83
0.71 0.77 0.61 0.75
0.5 0.6 0.5 0.6
0.5 ( 0.68
( ( ( (
6.8 ( 0.34
0.31 ( 0.13 0.33 ( 0.16 0.29 ( 0.10 3.8 ( 0.15
0.13 0.65 0.48 0.67
0.2 ( 0.44
2.7 ( 0.10
F(1,30) ) 0.12 n/a p ) 0.72
F(1,27) ) 0.08 p ) 0.42
F(1,27) ) 4.29 p ) 0.05
F(1,30) ) 0.05 n/a p ) 0.81
F(1,27) ) 4.30e p ) 0.047
F(1,27) ) 1.08e F(1,27) ) 4.20e F(1,27) ) 9.01e p ) 0.30 p ) 0.049 p ) 0.0057
F(1,62) ) 0.81 n/a p ) 0.37
F(1,58) ) 55.19f F(1,58) ) 3.25f p ) 0.000001 p ) 0.08
d
d
F(1,27) ) 0.03 p ) 0.84
d
F(1,58) ) 0.34f p ) 0.64
F(1,27) ) 1.00d p ) 0.32
F(1,58) ) 52.74f p ) 0.0000001
a Results are presented according to gender and smoking habits within study groups. For each subject, 1000 metaphases were analyzed; thus, the presented average numbers correspond to percentiles. Control smokers had 7.5 ( 3.15 cigarettes per day within the last year, and exposed smokers had 5.3 ( 4.22 cigarettes per day within the last year; there were no ex-smokers. b Significances were calculated by applying Scheffe’s post hoc procedure for multiple comparisons taking into account all confounding factors if applicable: age, years of exposure, smoking, alcohol intake. c Significances were calculated by applying Scheffe’s post hoc procedure for multiple comparisons taking into account all confounding factors if applicable: age, years of exposure, gender, alcohol intake. d Significances were calculated by applying Scheffe’s post hoc procedure for multiple comparisons taking into account all confounding factors if applicable: age, smoking, alcohol intake. e Significances were calculated by applying Scheffe’s post hoc procedure for multiple comparisons taking into account all confounding factors if applicable: age, gender, alcohol intake. f Significances were calculated by applying Scheffe’s post hoc procedure for multiple comparisons taking into account all confounding factors if applicable: age, gender, smoking, alcohol intake.
TABLE 3. Complexity and Distribution of Translocations among Painted Chromosomes 1, 2, and 4 in Lymphocytes of Pesticide Plant Workers and Controlsa exposed (n ) 32)
group
controls (n ) 32) involvement in translocations
percentage of average (SD
involvement in translocations
reciprocal translocations
complex rearrangements
Chr 1
Chr 2
Chr 4
reciprocal translocations
complex rearrangements
Chr 1
Chr 2
Chr 4
67.8 (1.34
8.5 (0.51
37.3 (1.55
35.8 (1.20
26.9 (1.08
80.1 (1.83
0.00 (0.00
35.1 (1.67
34.7 (1.35
30.2 (1.56
a FISH painting probes for chromosomes 1, 2, and 4 were used to analyze more than 1000 genomic equivalents per subject. Chr, chromosome; no statistical differences were found between the exposed and control group.
aberrations (16), which makes the increase biologically insignificant. Although earlier biomonitoring studies were controversial about the influence of sex and age on chromosome aberration frequency, it is generally accepted that their number increases with age and that the increase in acentric fragments is more evident among women (41, 42). Similar results were obtained in the present study for control subjects (Tables S3 and S4 in the Supporting Information). Of demographic parameters, age and employment duration in the exposed group showed significant correlation (R2 ) 0.50). Other demographic parameters did not interrelate significantly. Thus, it would be expected that observed 6374
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cytogenetic effects correlate with both age and employment with similar strength. However, a higher correlation of translocations was observed with years of exposure (R2 ) 0.356) than with age (R2 ) 0.274), indicating a slightly prevailing effect of pesticide exposure over the age. The same was not the case for chromosomal aberration. This observation is in agreement with the fact that translocations as stable aberrations reflect the cumulative effect of exposure, while unstable aberrations beside cumulative dose also reflect the effect of more recent exposure. A significant dependence of chromatid breaks and aberrant cells on years of employment was observed only among men (Table S4 in the Supporting
Information), while among women significance was restricted only to the influence of age. Since there were no significant demographic differences between our exposed male and female subgroups, it may indicate that another confounding factor, such as the endocrine system may interfere. There are reports on endocrine disruption caused by carbofuran and chlorpyrifos, but the exact mechanisms that could cause differences in the correlation of the genotoxic effect and extent of exposure between the sexes are still unknown. Meeker et al. (43) found inverse association between exposure to chlorpyrifos and testosterone levels. The authors also reported increased genome lesions in sperm cells, suggesting that chlorpyrifos may be associated with direct DNA damage in men. Carbofuran was also shown to decrease testosterone level but increase sperm abnormalities (44). Rawlings et al. (45) observed a significant increase in thyroxine level in ewes exposed to carbofuran. The influence of carbofuran on chromosomal aberrations is not clear yet. Timchenko (46) reported it to possess both mutagenic and antimutagenic properties, while Djelic et al. (47) detected its genotoxic activity only at higher concentrations. Despite the lack of epidemiological studies, there are published data indicating the inducibility of chromosome instabilities by the exposure of other pesticides to the workers on the production line. Metalaxyl was found to induce chromosomal aberrations in human lymphocytes in vitro. However, the administration of 75-300 mg/kg body weight to mice did not result in any significant change in the frequency of micronuclei in polychromatic erythrocytes (48). Chauhan et al. (49) showed that carbofuran induced chromosomal aberrations in bone marrow cells of mice. Although chlorpyrifos did not affect the aberration frequency in rat lymphocytes in vitro (50), Rahman et al. (51) reported its ability to significantly affect DNA migration. Results obtained with active ingredients in vitro cannot be extrapolated to humans, since they do not consider the effect of adjuvants that may significantly alter the toxicity of an active ingredient. These substances are generally not identified on product labels and are often claimed to be confidential business information (52). Chemical mutagens, which do not induce DNA strand breaks directly but cause other lesions, were shown to induce only chromatid type aberrations considered to be insufficient to induce a translocation (24). However, epidemiological studies of Zheng et al. (53) and Bonner et al. (8) reported correlations between occupational exposure to carbofuran exposure with non-Hodgkin’s lymphoma and lung cancer, respectively. This fact suggests that these chemicals may affect the frequency of stable aberrations to an extent. Our study found possible support to this hypothesis in the results of multiple regression indicating good correlation between translocations and chromatid break frequencies (R2 ) 0.26) in pesticide plant workers, which was not the case among controls (R2 ) 0.07). As reported by Johnson et al. (54), the frequency of translocations increased with age. The authors also reported that distribution of translocations among chromosomes 1, 2, and 4 was not affected. Both findings are in agreement with our results (Tables S3 and S4 in the Supporting Information). In a collaborative study of Sigurdson et al. (55), translocations did not differ by sex. Likewise, no significant difference in the translocation yield between sexes was found in our study (p ) 0.89, Table 1). In both groups, observed proportion of “one-way” translocations was rather high (up to 38%), but according to Fomina et al. (56), it should be presumed that most of them are in fact reciprocal at the molecular level, which is below the resolution of multicolor FISH. Significant correlation observed for translocations and employment duration, stronger among women (R2 ) 0.256)
than men (R2 ) 0.555), may indicate the adverse effect of long-term multiple pesticide exposure. However, to give a relevant conclusion on translocations inducibility by handling pesticides, additional studies with similar exposure conditions on cohorts from other countries should be performed and considered. Since distribution of translocations among chromosomes 1, 2, and 4 of workers did not differ significantly from the control group and corresponded (p ) 0.98) to the fraction of the genome disposed among these three chromosomes (Chr1/Chr2/Chr3 ) 36.9%:35.1%:28.0%) (22), it could be concluded that the genome damage due to multiple pesticide exposure is random. However, multiple correlation analysis indicated a significant dependence of the involvement of chromosome 4 on years of exposure (Table S6 in the Supporting Information). Beskid et al. (29) suggested that translocation frequency for a specific chromosome might also be affected by the activation or deactivation of regulatory genes on a specific chromosome due to exposure to agents or their metabolites. Thus, our study together with published data (29, 57) suggest that distribution of chromosome damage induced by pesticides, except for being random, may be a result of chromatin organization within chromosome areas as a function of gene activity rather than of their relative position within nuclei. Contemporary industrial technologies provide long-term, low-dose exposures in the working environment. Cancer risk associated with long-term, low-dose exposure is still evaluated. Fluorescent in situ hybridization is the most relevant available method for estimating cumulative genome damage on the individual level. Just as in the case with a chromosome aberration assay, future studies of data on translocation frequency in combination with national cancer registers will provide crucial information about the correlation between exposure and individual risk of developing a certain type of cancer.
Acknowledgments We would like to thank Miljenko Huzak, PhD, associate professor at the Faculty of Science, Mathematical Department, University of Zagreb for his valuable help with statistical analysis. This work was entirely supported by the Ministry of Science, Education, and Sports of the Republic of Croatia as a part of Grants Nos. 022-0222148-2139 and 022-02221482137. J.N.L.’s work was supported by Maryland Technology Developmental Corporation MTTF-2008-000-00210.
Supporting Information Available The Supporting Information section contains tables presenting demographic characteristics of the study population, Wilk’s lambda statistics, and results of multiple correlation analysis. This material is available free of charge via the Internet at http://pubs.acs.org.
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