AUTHOR QUERIES Journal id: GTEC_A_195113 Corresponding author: VÉRONIQUE ANDRE Title: Evaluation of bulky DNA adduct levels after pesticide use: Comparison between open-field farmers and fruit growers AUTHOR: The following queries have arisen during the editing of your manuscript. Please answer the queries by making the necessary corrections on the CATS online corrections form. Once you have added all your corrections, please press the SUBMIT button.

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Toxicological & Environmental Chemistry, Month?? 2006; ??(?): 1–15

Evaluation of bulky DNA adduct levels after

pesticide use: Comparison between open-field5 farmers and fruit growers

VERONIQUE ANDRE1, JEREMIE LE GOFF1, DIDIER POTTIER1,PIERRE LEBAILLY1, MARCO PELUSO2, ARMELLE MUNNIA2, &PASCAL GAUDUCHON1

1GRECAN (EA1772 – Universite de Caen Basse-Normandie), Centre Francois Baclesse,10 Avenue General Harris, BP 5026, 14076 Caen cedex 05, France and 2CSPO – Scientific

Institute of Tuscany, Cancer Risk Factor Branch, Molecular Biology Laboratory, Via Pico della

Mirandola N. 24, 50131 Firenza, Italia

(Received 22 22 22; revised 22 22 22; in final form 22 22 22)

Abstract15 Genotoxic impact from pesticide use was evaluated and compared between open-field farmers and

fruit growers. Groups of farmers were classified according to the main pesticide sprayed (triazoles orchlorothalonil for open-field farmers n¼ 19; captan for fruit growers n¼ 29). Two blood samples(S1 and S3) were collected on consecutive days for each farmer, and white blood cell bulky DNAadduct levels were evaluated by 32P-postlabelling method. Exposure to pesticides was estimated using

20 a questionnaire. Within each group, no significant variation in the mean relative adduct level (RAL)values was observed between S1 and S3. A quantitative increase was observed at S3 for the subgroupof farmers exposed to chlorothalonil and associated insecticides. Between groups, the mean RALwas significantly higher for open-field farmers, a difference essentially attributable to the triazolesubgroup. Owing to the sampling chronology (farmers exposed to triazoles were sampled first, several

25 weeks before farmers exposed to chlorothalonil and associated insecticides), seasonal variations mayaccount for changes in DNA adduct levels in open-field farmers. Among fruit growers, a significantrelationship was found between RALS3 and two exposure variables generated by questionnaires(statistical general linear model).

Keywords: Pesticides, DNA adducts, occupational exposure, open-field farming, 32P-postlabelling

Correspondence: Veronique Andre, GRECAN (EA1772 – Universite de Caen Basse-Normandie), Centre Francois Baclesse,Avenue General Harris, BP 5026, 14076 Caen cedex 05. France. Tel.: 33-231-45-50-70. Fax: 33-231-45-51-72.E-mail: v.andre@baclesse.fr

ISSN 0277-2248 print/ISSN 1029-0486 online/06/000001–15 � 2006 Taylor & FrancisDOI: 10.1080/02772240600952026

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30 Introduction

In many industrialised countries, epidemiological studies have demonstrated that farmershave a lower risk than the general population for major causes of death such as heart diseaseand certain cancers, essentially those strongly associated with smoking and affecting thelung, bladder or oesophagus. For other cancers, farmers tend to show a higher incidence

35 rate, in particular those cancers with a low incidence occurrence (leukaemia, lymphoma,lip, skin, stomach, brain and soft-tissue sarcoma) and for prostate cancer [1,2,5,19,27]Pesticides are widely used and represent a heterogeneous group of biologically activecompounds. Some of these chemicals were reported as genotoxic and/or mutagenic invarious short-term tests (STT) or as carcinogenic in long-term animal studies

40 [10,11,16,21]. Some classes of pesticides (phenoxyacetic acid and triazine herbicides,organochlorine, organophosphate and arsenical insecticides) are associated with humancancer, mainly non-Hodgkin’s lymphoma, leukaemia and soft-tissue sarcoma [6,27].Occupational exposure to halogenated fumigant methyl bromide was significantlyassociated with a risk of prostate cancer [2]. Since evaluation of various biomarkers may

45 provide evidence regarding biological correlation between cancer and pesticide exposure,biomonitoring studies were conducted on farmers, agricultural workers or production plantworkers occupationally exposed to pesticides. Using short-term exposure biomarkers suchas urine mutagenicity [3,26,41] or DNA damage in lymphocytes [14,15,18,25], significanteffects, in general, were reported, except in a study conducted among Greek greenhouse

50 workers [36]. For cytogenetic damage measured in surrogate tissues [white blood cells(WBCs), lymphocytes and/or buccal cavity cells], results were more heterogeneous [8],but the quantity of chromosomal aberrations (CA) was frequently increased amongpesticide exposed individuals. These conflicting results might partly reflect the diversity ofthe exposure situations studied: (1) various types of chemicals/formulations, (2) various

55 exposure conditions (open-field, green house, plant workers, etc.) and (3) differences inabsorption routes between farmers and industrial plant workers [29]. The dose–effectrelationship between exposure to pesticides and cytogenetic effects seems difficult to firmlyestablish because exposure was generally poorly evaluated. In contrast, a few studieswith well-documented exposure did not report any effect of pesticide exposure on

60 cytogenetic biomarkers [28]. A combination of micronucleus (MN) and fluorescence in situ

hybridization (FISH) with an all-chromosome centromeric probe did not show anysignificant difference in MN frequency between floriculturists and controls [9]. However,a quantitative increase in MN frequency was observed in relation to (i) increased useof pesticides, (ii) number of pesticides used with positive responses in certain STT,

65 (iii) involvement in mixing loading steps and (iv) duration of exposure. Interestingly,a higher percentage of MN with centromeric probe was found in a particular subgroup offloriculturists exposed to benzimidazolic compounds (carbendazim and benomyl), a groupof pesticides in which some molecules are known to be aneugenic.

The genotoxic potential of pesticides is also estimated by their ability to generate70 DNA adducts, as previously demonstrated for some of these chemicals [12,40] and

in animals [33,34]. The two studies measuring DNA adducts among pesticide usersrevealed significantly higher DNA adduct levels in WBCs of floriculturists compared tocontrols [30,32].

The aim of the present study was a comparison of the genotoxic impact in relation75 with occupational exposure between open-field farmers and fruit growers. Agricultural

practices were clearly different between these two activities, in particular concerningthe type of pesticides used. Enrolment of farmers was based on the main pesticide

2 V. Andre et al.

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sprayed: chlorothalonil or triazoles for open-field farmers and captan for fruit growers.These three main pesticides were chosen not only because of their extensive use but also

80 because some genotoxic data are available, at least for two of them. Chlorothalonil induceskidney and forestomach tumours in both genders in rats and mice [22]. Even if classicalSTT were negative, including the capacity for the metabolites to form DNA adducts [40]chlorothalonil was shifted by IARC from group 3 to group 2B [22]. Captan was reportedgenotoxic in various STT [39,42] and potentially carcinogenic towards kidney, thyroid

85 and forestomach in rats [20] and in duodenum and other regions of the digestive tractin mice [13]. Captan is classified by IARC in group 3 but belongs to group B2 in the EPAclassification.

The use of pesticide mixtures is the rule for all farmers included in this study, a situationwhich is not studied during evaluation of the chemicals before marketing. Therefore,

90 it should be considered, as proposed by Maroni and Fait [28] that some of these agents‘‘might interact in an additive or synergistic way and therefore modify the pattern of effectsobserved in the case of monoexposure’’. Co-formulants and surfactants may also playa critical role: some solvents (benzene, chloroform, carbon tetrachloride, 1,2-dichlor-oethane, etc.) with evidence of carcinogenicity in humans or animals were found in

95 some pesticide formulations [35]. As an example, DNA adducts were generated in a dose-dependent manner in kidney and liver of mice after i.p. treatment with Roundup�, but notafter administration of isopropylammonium salt of glyphosate, the active ingredient [3].

In the present study, the WBC bulky DNA adduct levels were measured(32P-postlabelling method) the morning before and the morning after pesticide handling

100 during intensive spraying periods (March–June). Detailed questionnaires were completedin person to accurately estimate the exposure to pesticides. DNA adduct levels werecompared between groups, and for fruit growers, results were also discussed in the lightof exposure data.

Materials and methods

105 Reagents

Buffer-saturated phenol, proteinase K, ribonuclease A and T1, micrococcal nuclease,20deoxyadenosine 30monophosphate (dAp), nuclease P1, urea, formic acid and lithiumhydroxide were purchased from Sigma-Aldrich. Carrier-free [�-32P]ATP (3000 Ci mmol�1)was from Amersham. T4 polynucleotide kinase was from Q Biogen; phosphodiesterase

110 type II (calf spleen) was from Calbiochem. PEI-cellulose F plastic plates were obtainedfrom Merck.

Farmer characteristics

All farmers were volunteers, professionally active and free of cancer. They gave theirinformed consent prior to their enrolment in the study. Forty-eight pairs of samples were

115 collected from 38 different male farmers working either on open-field farms (triazoles andchlorothalonil subgroups) or on fruit growing farms (captan group) as described in Table I.Open-field farming involved mainly three types of sprayers for pesticide application: rear-mounted sprayers, trailer sprayers and self-propelling sprayers (Figure 1) most often witha cabin. Pesticides are sprayed in large drops, very close to the ground (70–100 cm).

120 In contrast, pesticide application in fruit-growing farms involved use of a ‘‘between-rowtractor’’ with a spray reaching far higher than in open-field and with finer drops.

DNA adduct levels in open-field farmers and fruit growers 3

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Interviews of farmers were performed at home on each day of sampling and using astandardised questionnaire. The questionnaire gathered data on demographic character-istics, pesticides handled in the current spraying season, exposure parameters and potential

125 confounding factors such as smoking and drinking habits (for fruit growers, they were:less than once a day for 42%, once a day for 31% and more for 27%) or medicationhabits (open-field farmers: one farmer taking anti-inflammatory drugs and onefarmer taking anti-histaminic drugs; fruit growers: three farmers taking anti-histaminic,anti-hypertensive or anti-inflammatory drugs).

130 Collection of blood samples

Blood samples were collected on the morning before the beginning of the working day andon the following morning (namely samples S1 and S3) during intensive spraying season

Table I. Population characteristics and study design.

Age Smokers, n

Bloodsamples, n

Number-matchedsamples (S1/S3)

Open-fieldfarmers

Chlorothalonil subgroup n¼ 8 36.3� 7.1 8 38 19Triazoles subgroup n¼ 11

Fruit growers Sampled in 1998 and/or 2000(10 farmers participed twice)

38� 9 2 58 29

Total 10 96 48

(a)

(b)

(e)

(d)

(c)

Figure 1. Main types of sprayers in open field (a) Rear-mounted, (b) Trailer sprayer and(c) Self-propelling) and in fruit growing farms (d and e).

4 V. Andre et al.

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(March–June) (Figure 2 and Table I). The 96 samples were obtained by venipuncture(8–12 mL) using heparinised vacutainer tubes and were immediately stored at �80�C

135 until use.

DNA extraction

DNA was extracted from WBC using the phenol-chloroform method [4]. Briefly, bloodsamples were centrifuged, and the pellet was repeatedly washed with cold NH4Cl 0.17 Mbuffer (Tris-HCl, EDTA pH 7.4) of 1.2 mL was added to the WBC pellet together with

140 SDS 10%, RNAse T1 and RNAse A followed by proteinase K 30 mn later. Proteins wereeliminated by phenol extraction followed by phenol: SEVAG (chloroform/isoamyl alcohol,24 : 1) and SEVAG. The DNA was precipitated in cold ethanol, washed with ethanol, driedand dissolved in milliQ water. Purity was checked by the determination of UV spectrabetween 228 and 300 nm (expected ratios: 1.8 < A260/A280 < 1.95 and A260/A230 > 2.3).

145 The concentration was calculated from A260. DNA solutions were aliquoted and frozenat �80�C in glass vials.

Postlabelling method

The method was adapted from Reddy and Randerath [37]: 5mg of DNA were digested bymicrococcal nuclease and spleen phosphodiesterase for 3.5 h. The enrichment step was

150 performed by nuclease P1. Each sample was labelled with 1.1 MBq 32P-�ATP using T4polynucleotide kinase. Adducts were separated by bidimensional TLC on 12�12 cm2

PEI-cellulose sheets. Four migration solvents were used successively: D1¼ 1 M sodiumphosphate, pH 6.8; D2¼3 M lithium formate 7 M urea, pH 3.5; D3¼ 0.7 M lithiumchloride, 0.45 M Tris-HCl, 7.7 M urea, pH 8; D4¼ 1.7 M sodium phosphate, pH 5.

0

10

20

30

40

50

60

70

April June

S1 Blood samples S3

Spraying pesticide operations

Day 1 Day 2 (morning) (morning)

(Consecutive days)

Spr

ayed

are

a (H

a)

Figure 2. Sampling design. The top figure shows the frequency of pesticide use for one farmer duringone season in open-field farming. One segment corresponds to one application day. Segment heightreflects the area sprayed. Two blood samples (S1 and S3) were collected for each farmer on twoconsecutive days during the intensive spraying season (April–June). Spaying operations wereperformed on crops or apple trees on the day between the two samples.

DNA adduct levels in open-field farmers and fruit growers 5

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155 Autoradiograms were obtained after exposure of Kodak Biomax film to cellulose sheetsfor 72 h at �80�C with intensifying screens.

Ninety-five out of the 96 samples were analysed at least twice. For fruit growers(58 samples), analyses were repeated four times for 41 samples (i.e. in duplicate within agiven experiment for each of two independent experiments) or five times for 16 samples and

160 six times for one sample.For each experiment, two samples with 5 pmol of 20deoxyadenosine 30monophosphate

(dAp) were also labelled and diluted with water to a final volume of 1 mL. From each ofthese two samples, three deposits of 4mL each were performed and separated on TLCsheets. After counting, the dAp mean value served as the estimation of the corresponding

165 labelling for 5mg of dNp (1 mg DNA correspond to 3240 pmol dNp). Results were expressedas the relative adduct levels (RALs) according to the following relation:

RAL ¼ 1:22� 10�6 cpmadducts=cpmdAp

(mean cpm for 0.02 pmol dAp/deposit: 32,520� 7300; range: 21,123-41,443 cpm).

Quantification

170 Areas on plates corresponding to spots on chromatograms were excised. The radioactivitywas quantified using a scintillation counter (Cerenkov mode).

Detection limit

DNA adduct levels were low, most frequently close to the method detection limit. Spotswere detected on 42% of the PEI-cellulose sheets (positive sheets). Each sample was

175 analysed at least four times, and consequently the number of positive sheets could vary from0 to 4 because of the technical fluctuations of the method. The information given by thesepositive sheets was used to affect a differential RAL value to the sheets without adductsin the following manner:

. One quarter of the lowest RAL observed within this group when all the replicates for the180 corresponding sample were without any spot at S1 and S3.

. Half of the lowest RAL when the replicates were without any spot at S1 or S3.

. Three quarters of the lowest RAL if only one of the replicates was free of spots.

Pesticide exposure

Pesticides used between S1 and S3 are listed in Table II. Certain parameters obtained from185 the questionnaires and may be associated with pesticide exposure are presented in Table III.

Statistical analysis

DNA adduct levels were compared between groups using an ANOVA. In the fruit growergroup, DNA adduct levels measured in S3 (RALS3) were correlated (Bravais–Pearson linearregression coefficient) with the level observed in S1 (RALS1). Consequently, the

190 explanation of RALS3 by exposure variables X were tested using a general linear modelin which RALS1 for each subject were always included: RALS3¼RALS1þ variable X

(Table IV). The variable X was considered as a class variable or a continuous variableas required (glm procedure). Analyses were carried out with SAS system (release 8.2).Farmers included in 1998 and in 2000 were treated as distinct subjects. The criterion for

195 significance was set at p < 0.05.

6 V. Andre et al.

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Tab

leII

.P

esti

cid

eex

posu

rech

arac

teri

stic

sfo

rth

ed

ayof

pes

tici

de

use

(act

ive

ingr

edie

nts

are

init

alic

s).

Op

enfi

eld

(cro

p)

farm

ers

(n¼

19)

Nu

mb

erof

use

rs(%

)

Pes

tici

des

use

dT

riaz

ole

ssu

bgr

ou

p(n¼

11)

Ch

loro

thal

on

ilsu

bgr

ou

p(n¼

8)

Fru

itgr

ow

ers

(n¼

29)

Nu

mb

erof

use

rs(%

)

Fu

ngi

cid

esT

riaz

ole

s10

(91%

)C

hlo

ron

itri

les

(chlo

roth

alo

nil)

8(1

00%

)P

hth

alim

ides

29

(100%

)(E

pox

yco

nazol

)7

(64%

)(C

apta

n)

9(1

00%

)(C

ypro

conazol

,te

buco

nazol

)4

(36%

)(F

olpet

orip

rodio

ne)

2(0

7%

)P

yrim

idin

amin

es(c

ypro

din

il)

7(6

4%

)M

orp

holin

es(fe

npro

pim

orphe)

4(3

6%

)B

enzi

mid

azolic

com

pou

nd

s(c

arb

endazim

)2

(25%

)B

enzi

mid

azolic

com

pou

nd

s(t

hio

phanate

met

hyl

orbe

nom

yl)

1(3

%)

Pip

erid

ines

(fe

npro

pid

ine)

3(2

7%

)D

ith

ioca

rbam

ates

(manco

zeb

)1

(12%

)T

riaz

ole

s(flutr

iafo

l)1

(12%

)T

riaz

ole

s(f

luzilazol

,tr

iadim

efon

,

pen

conazol

,m

ycl

obuta

nil)

4(1

4%

)

Ph

enols

(din

ocap)

3(1

0%

)D

iazi

nes

(buri

pim

ate

,

thin

omet

hio

nate

,pyra

zop

hos

)7

(24%

)

Ph

thal

imid

es(i

pro

dio

ne)

1(1

2%

)A

nilin

o-p

yrim

idin

es(p

yri

met

hanil)

2(2

5%

)T

hia

daz

ine

(dazom

et)

1(3

%)

Pyr

idin

e(p

yri

fenox

)3

(10%

)S

ulf

amid

e(t

olylflu

anid

e)1

(3%

)In

sect

icid

esO

rgan

op

hosp

horu

s(o

xydem

eton

-met

hyl,

dim

ethoa

te,

thio

met

on,

fenitro

thio

n)

6(7

5%

)O

rgan

op

hosp

horu

s(p

hos

alo

n,

dim

ethoa

te,

met

hid

ath

ion

vam

idot

hio

n)

3(1

0%

)

Org

anoch

lori

ne

(endos

ulfan)

2(2

5%

)O

rgan

och

lori

ne

(endos

ulfan)

2(7

%)

Pyr

eth

rin

oid

es(�

-cyfluth

rin,

bife

nth

rin,�-c

yalo

thri

n,

del

tam

ethri

n,

esfe

nvale

rate

,�-

fluvalinate

)

6(7

5%

)C

arb

amat

es(fe

nox

yca

rb,

carb

ary

l,pyri

mic

arb

)9

(31%

)

Ure

as(t

erflube

nzuro

n,

flufe

nox

uro

n)

7(2

4%

)

Ch

loro

nic

oti

nil

(im

idacl

opri

de)

2(7

%)

Form

amid

in(a

mitra

z)

1(3

%)

Ave

rmec

tin

(aba

mec

tin)

1(3

%)

Her

bic

ides

(Ben

tazon

,atr

azin

e,fluro

xypyr,

2,4

MC

PA

)3

(27%

)(S

imazin

e,diu

ron,

glyphos

ate

)1

(3%

)

DNA adduct levels in open-field farmers and fruit growers 7

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Results

Ninety-six samples were analysed in the study originating from 38 male farmers. Thereafter,for statistical analysis, each pair of matched samples (n¼ 48) (Table I) was considered asissued from distinct subjects. For 9/48 subjects (19%), no DNA adduct was detectable for

200 S1 and S3 samples (six among fruit growers, three among open-field farmers includingone smoker). For the remaining 27 non smokers, the range of DNA adducts was between0.3 and 109.6 per 1010 normal bases. Among the 10 smokers with DNA adducts at leastat one of the time points, the range was between 0.8 and 69.2 adducts per 1010 normalnucleotides. For five samples from smokers, no DNA adducts were detectable in either

205 the S1 or the S3 sample. Farmers were included in this study according to the use of one ofthe following three pesticides: triazoles or chlorothalonil for open-field farmers and captanfor fruit growers. However, pesticides were always used in association and/or different cropswere sprayed on the same day resulting in the use of different mixtures between the twotime points (Table II). Among open-field farmers, the triazoles subgroup was the first

210 sampled (March–April) and then the chlorothalonil subgroup in April–June. For fruitgrowers, blood samples were obtained in May–June.

The mean DNA adduct level in S1 (mean RALS1�SD) was significantly higheramong open-field farmers compared to fruit growers (13.9� 10�10

� 27.7 vs.

2.9�10�10�3.4). This difference was essentially attributable to the subgroup of open-

215 field farmers using triazoles (22.7�10�10�34.4) because the mean RALS1 were

comparable for the chlorothalonil subgroup and for fruit growers (1.9� 10�10� 1.2 and

2.8�10�10�3.4, respectively). Within groups, there were no statistically significant

variations of the mean DNA adduct levels between S3 and S1 (Figure 3).For fruit growers, various pesticide exposure variables derived from the questionnaire

220 were compared with DNA adduct levels (Tables IV and V). No relationship was identifiedbetween RALS1 and exposure variables reflecting exposure to pesticides that occurred priorto the first blood sample (Table V). The relation between RALS3 and variables that reflectexposure to pesticides during the day between the two blood samples was also investigatedin this group (Table IV). Significant positive relationships were found with the duration of

225 sprayer cleaning (when >10 min) and the volume of commercial mixture sprayed/acre.

Discussion

Farmers are occupationally exposed to complex mixtures of pesticides. Apart from knownacute injuries, long-term effects are also suspected. The evaluation of biomarkers of

Table III. Some pesticide exposure characteristics for the day of pesticide use.

Open-field (crop) farmers

Exposure parameters Triazoles subgroup Chlorothalonil subgroup Fruit growers

Total farm area (acres) 362� 177 (185–775) 365� 146 (143–544) 40� 13.2 (15–64)Quantity of pesticide used (kg) 2.3� 1.1 (0.4–3.8) 24.1� 17.9 (9–57) 4.9� 2.4 (1.3–10.8)Number of tanks prepared 3.1� 1.1 2.25� 0.7 (1–3) 3.1� 1.8 (1–8)Area sprayed (acres) 82� 38 (17–124) 59� 31 (25–102) 8.2� 4.4 (2.9–22)Duration of spraying (h) 2.9� 1.2 (1–5) 2.2� 0.8 (1.25–3) 3.5� 1.9 (1.0–8.5)Duration of sprayer cleaning (min) Not available Not available 11.4� 6.0 (2–30) (n¼19)

Data are expressed as mean�SD (range).

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genotoxicity on small groups of volunteers [3,24–26,38] was associated with the classical230 evaluation of cancer incidence in a large cohort conducted over several years. The present

article reports the comparison between open-field farmers and fruit growers with WBCbulky DNA adduct levels measured during a period of intensive pesticides handling.Blood samples were collected early in the morning before the beginning of the working dayand on the following morning (namely samples S1 and S3). In previous studies involving

235 control groups and/or matched samples performed during and outside the sprayingseason, DNA adduct formation was found in relation to occupational exposure topesticides [24,30,32]. In the present study, the sampling chronology was clearly different,with a shorter interval between the two time points. In experimental models, this 24 hinterval between exposure and sampling was reported as being sufficient for the detection

240 of DNA adducts in target tissues and WBC of rats exposed to BaP, a referent genotoxic,via intratracheal, dermal or oral routes [17]. However, no equivalent kinetic data on DNA

22.7 20

0

20

40

60

80

100

120S1

S3

1.92.8

42.9

20

0

5

10

15

20

(a)

(b)

Triazoles subgroup Chlorothalonil subgroup

Triazolessubgroup

Chlorothalonilsubgroup Fruit growers

Fruit growersOpen-field farmers

RA

L (

×1010

)

Figure 3. Individual RAL (mean of repeated experiments) (�10�10) for the groups of farmers(S1 samples: black diamonds; S3 samples: open squares). White symbols indicate the mean RAL/group/time point. The corresponding value is given. (a) all values; (b) values lower than 20� 10�10.

DNA adduct levels in open-field farmers and fruit growers 9

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Table V. Exposure variables (collected through face by face questionnaire forfruit growers) used to assess relationships with DNA adducts levels measured inS1 sample for 27 fruit growers (two smokers excluded).

Variables

Month of the studya

Age of the farmersb

Number of years in farm-owningb

Number of years of herbicide useb

Number of years of insecticide useb

Number of years of fungicide useb

Total farm areab

Farm area devoted to cropsb

Farm area devoted to fruit growingb

Farm area devoted to tree applesb

Number of days since the last pesticide use before the S1 sampleb

Area sprayed with pesticides the day of the last useb

Vegetables consumption the day before the first blood samplea

Fruit consumption the day before the first blood samplea

Fruit juice consumption the day before the first blood samplea

aStudent’s test or ANOVA.bLinear regression.

Table IV. Exposure variables (X, collected through face by face questionnaire)used to assess relationships with DNA adducts levels changes between S1 andS3 samples (RALS3¼RALS1þX) for 27 fruit growers (two smokers excluded).

Variables concerning the day of the study

Formulation of the commercial product of captan (powder, etc.)a

Number of kg of commercial product used during the day of the studyb

Number of kg of captan used by hectareb

Concentration of captan used by hectareb

Volume of preparation sprayed/hectareb*Sprayer calibrated: yes/noa

Presence of cabin in the tractora: yes/noType of nozzles in the sprayera

Number of litres of the spraying tankb

Time duration of mixing-loading tasksb

Number of spraying tank filled (�3 or >3)a

Time duration of applicationb

Area sprayed with captanb

Total area sprayedb

Duration of sprayer cleaning (�9 min or >10 min)a*Wind speed: absence/moderatea

United Kingdom Predictive Operator Exposure Model (UK-POEM)b

Personal protective equipment

Glovesa

Maska

Waterproof coveralla

Hata

aStudent’s test or ANOVA for categorical variables.bLinear regression for continuous variables.*Significant positive relationship (p < 0.05).

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adduct formation are available after human occupational exposure to pesticides. Half-liveswere available in the literature for some pesticides. They were determined in rodents,most often after oral or I.P. administration route. For example, the half-life of chlorothalonil

245 was estimated between 6 and 8h in rat, following oral administration. After 24 h, urinaryexcretion was greater than 90% for a dose of 5 mg kg body weight�1. The present study wasperformed on occupationally exposed farmers, mainly with cutaneous penetration route.Even if half-lives available in the literature were not directly transposable to farmers,samples were performed within a 24 h interval. One must keep in mind, however, that

250 this interval could be too short to allow absorption, distribution, possible metabolism andfinally interaction with target DNA, resulting in adduct production. Moreover, farmerswere sampled during a period of intensive pesticide use and therefore were not free ofexposure before sampling. It is possible that DNA adducts were already generatedconsequent to previous exposure, leading to a steady state for this biomarker, at least for the

255 triazoles subgroup.Among open-field farmers, mean RAL was doubled between S1 and S3 in the subgroup

who sprayed chlorothalonil associated mainly with insecticides. For these eight farmersincluded in a larger group (n¼16), urine mutagenicity (Ames test) and DNA damage(Comet assay) were already evaluated with the same chronology (S1 and S3) for urine and

260 blood sampling [3,25]. Between the two blood samples, significant increase of DNAdamage levels measured by the comet assay was reported, and the magnitude of thesemodifications was correlated with two exposure parameters (the area sprayed between S1and S3 and the number of tanks used). For urine mutagenicity, the proportion of mutagenicsamples increased from S1 to S3 among nonsmokers (n¼ 10). The small size of the

265 chlorothalonil subgroup was a clear limit for the interpretation of DNA adduct variations.However, the converging observations with two different biomarkers (DNA adducts andurine mutagenicity) and the significant relationship obtained with the third (DNA damagemeasured by the comet assay), associated with significant correlation with exposurevariables, may lead to the assumption of a genotoxic impregnation in relation with

270 occupational exposure among farmers included in this subgroup.The results among fruit growers were clearly in contrast with those of the chlorothalonil

subgroup. Fruit growers were also previously analysed for urine mutagenicity, and for 12of them, induction of lymphocyte DNA damage was measured (comet assay) [26].No significant variations were found between S1 and S3 for DNA damage. The proportion

275 of mutagenic urine samples did not vary between the two time points. Overall, nomodifications in the levels of the three biomarkers (urine mutagenicity, DNA adducts andDNA damage) were observed between S1 and S3. Thus, 1-day exposure of fruit growers tocaptan and associated pesticides did not lead to a detectable modification of the genotoxicresponse. These data are in contrast to the fact that captan and some structurally close

280 phthalimides were found to be genotoxic in some experimental models.Mean RALS1 were significantly higher among open-field farmers compared to fruit

growers, but this difference was mainly attributable to the triazoles subgroup. The latter wassampled earlier in the season (March–April), and it may be assumed that these higher DNAadduct levels were attributable to previous exposures to pesticides. If blood cells bearing the

285 highest levels of damage were eliminated, DNA adduct levels consequently decreased closeto those observed among open-field farmers sampled a few weeks later (chlorothalonilsubgroup) as well as in fruit growers. These data suggest seasonal variations in DNA adductlevels in relation to pesticide exposure are in agreement with results recently publishedby our group [24]. A significant increase of DNA adduct level was observed at the time

290 of heavy pesticide use, exclusively among farmers, compared to the non exposed

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period (winter). DNA adduct levels measured for non exposed group and for farmerssampled after several weeks free of exposure to pesticides were similar to those measured inthe present study for fruit growers and chlorothalonil subgroups. Samples included in thepresent study and in that Le Goff et al. [24] were analysed by 32P-postlabelling in distinct

295 years, and the comparable levels observed reinforce the accuracy of our method.Roulland et al. [38] reported an increased BCL2-IGH prevalence together with a rise

in the frequency of BCL2-IGH-bearing cells in a population of 56 open-field farmers.A relationship with occupational exposure to pesticides was suggested since this biomarkerwas elevated especially during the high pesticide use period and correlated with farm area

300 devoted to crops. Interestingly, this biomarker of early effect was the most frequentchromosomal translocation involved in non-Hodgkin’s lymphoma, one of the diseasesfound in excess among farmers.

For fruit growers, despite the lack of significant variations between the mean RALS3 andthe mean RALS1 for the whole group, some interindividual variations were observed and

305 correlations with exposure data collected through the questionnaires were tested.Variables for assessing occupational exposure to pesticides such as area sprayed, whole

quantities of pesticides used, duration of spraying operations or the wearing of protectiveclothing were not significantly related with RALS3. The detailed description of the practicesobtained through the questionnaire allowed the use of a second set of parameters. The

310 duration of sprayer cleaning and the volume of pesticides sprayed per acre were positivelylinked to the DNA adduct levels.

Quantitative results were classically expressed in RAL, but the method used for thiscalculation is not standardised, i.e. largely depending on radioactivity measured in parallelin total nucleotides or in dAp samples. These values and the protocols applied to obtain

315 them are rarely presented with details in publications, although they largely account forinterlaboratory variations. Nevertheless, our data was compared with the two studiesdealing with occupational exposure to pesticides [30,32]. Overall, for 39/48 pairs of samples(81%), DNA adducts were detected in the two blood samples S1 and S3, with levelsranging from 0.1 to 109.6 adducts for 1010 normal nucleotides. Peluso et al. [32] reported a

320 range of DNA adducts between 17 and 310� 10�10 among Ligurian floriculturists, and in asecond study the mean RAL was 85� 10�10 [30]. Among farmers included in the presentstudy, the mean RALS1 were 1.9, 2.9 and 22.7�10�10 depending on the group orsubgroup considered. Thus, DNA adducts were detected more frequently (81 vs. 42%), butwith somewhat lower intensity. The working conditions were notably different for farmers

325 in the present study compared to the floriculturist groups. Potentially higher exposure maybe assumed for the latter due to (1) closed greenhouse environment, (2) frequent manualcontact with contaminated flowers or foliar surface and (3) continuous production offlowers without seasonal variations or rest. In our study, farmers mainly used a variety offungicides in contrast with floriculturists who applied more insecticides.

330 Globally, RAL levels measured in a pesticide exposure context were lower than thosereported in many other occupational studies dealing mainly with polycyclic aromatichydrocarbons (PAH) exposures [23], even in an environmental context such as for theEuropean Prospective Investigation into Cancer and Nutrition (EPIC) study [31]. Severalexplanations are possible. Pesticides consist in a very large class of chemicals (more than

335 900 pesticides are used world-wide) and less than 60 have been evaluated by IARC andclassified mainly 2B or 3, in contrast with PAH or many aromatic amines which areclassified 1 or 2A. Levels of occupational exposure to pesticides are thought to be lowerthan occupational exposure to PAH, as most of the time it is sequential (at least in open-field farming and fruit growing), a situation that is different compared to continuous

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340 occupational exposure to PAH (coke oven workers for example). Moreover, it is generallyaccepted that farmers have a priori better living conditions (healthy lifestyle, lowerfrequency of smoking, physical activity, outdoor work and healthier food).

In conclusion, the present study underlines the interest of a comparative approachincluding several groups of farmers, reflecting various classes of pesticides used through

345 different agricultural practices. It also stresses the interest of the evaluation of multiplebiomarkers, applied on biological samples obtained under real occupational exposureconditions, in particular, after the use of pesticide mixtures. However, on the other hand,due to the complexity and the diversity of pesticides used, it would be a difficult task toincriminate any specific molecule when a biological response is observed.

350 Acknowledgments

The helpful collaboration of the Chambre Departementale d’Agriculture du Calvados(Mr Soulas and Mr Dupont), the Association de Coordination Technique Agricole(Mr Beaufreton) and the Cooperative agricole SICOLY (Mr Massardier) in the enrolmentof farmers is acknowledged. We thank the nurses who collected blood samples at home,

355 and Miss Bardou and Miss Brouet for interviews with fruit growers. We are grateful toMrs Bernaud and Mrs Durand and to Mr Devaux and Mr Severin for their implication inthe study undertaken with fruit growers. Lastly, we particularly thank O. and F. Perinfor their invaluable technical and scientific assistance on 32P postlabelling.

Financial support was obtained from Ligue Nationale Contre le Cancer (Comites du360 Calvados, du Rhone et de la Manche), Association pour la Recherche sur le Cancer (ARC),

Union des Industries pour la Protection des Plantes (UIPP), Conseil General du Calvados(CG14). J. Le Goff was a recipient of a fellowship from the Ligue Nationale Contre leCancer (Comite du Calvados) and from the Conseil Regional de Basse-Normandie.

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