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Mutation Research 608 (2006) 121–128

Association of DNA adducts and genotypes with birth weight

Radim J. Sram a,b,∗, Blanka Binkova a,b, Jan Dejmek a,b,Irena Chvatalova a,b, Ivo Solansky a,b, Jan Topinka a,b

a Laboratory of Genetic Ecotoxicology, Institute of Experimental Medicine, AS CR, Vıdenska 1083, 142 20 Prague, Czech Republicb Health Institute of Central Bohemia, Vıdenska 1083, 142 20 Prague, Czech Republic

Received 26 October 2005; received in revised form 18 April 2006; accepted 20 April 2006Available online 11 July 2006

Abstract

The relationships between DNA adducts and birth weight and between birth weight and genetic polymorphisms of metabolicgenotypes were studied using DNA from the children part of placental samples. The samples were collected in the districts ofTeplice and Prachatice and in the city of Prague. DNA adducts were analyzed by 32P-postlabeling in a total of 199 subjects,genetic polymorphisms in 1013 subjects. GSTM1, GSTP1, GSTT1, CYP1A1*2A, and CYP1A1*2C genotypes were determinedfor each subject. The level of DNA adducts was not correlated with birth weight in any group (N = 199), including that from thepolluted district of Teplice (N = 90). Birth weight was significantly decreased by smoking, ETS and alleles of CYP1A1*2C. The

isk of low birth weight and prematurity was significantly increased by genotypes of GSTM1 and CYP1A1*2C and the combinationSTM1+CYP1A1*2A. Genotypes are primarily effect modifiers, whose effect incorporates the effect of environmental factors. Thiseans that in the future, the impact of air pollution on children’s health should be studied together with their genetic polymorphisms.2006 Elsevier B.V. All rights reserved.

eywords: DNA adducts; Metabolic genotypes; Carcinogenic polycyclic arometardation

Abbreviations: ETS, environmental tobacco smoke; PAHs, poly-yclic aromatic hydrocarbons; c-PAHs, carcinogenic PAHs; B[a]P,enzo[a]pyrene; PM2.5, particles <2.5 �m; PM10, particles <10 �m;PRT, hypoxanthine–guanine phosphoribosyl-transferase locus; AhR,

ryl hydrocarbon receptor; PCR, polymerase chain reaction; RFLP,estriction fragment length polymorphisms; IUGR, intrauterine growthetardation; LBW, low birth weight <2500 g; HPLC, high perfor-ance liquid chromatography; US EPA, U.S. Environmental Protec-

ion Agency; GST, glutathione-S-transferase; NAT2, N-acetyl trans-erase 2; CYP1A1, cytochrome P-450 1A1∗ Corresponding author. Tel.: +420 241 062 596;

ax: +420 241 062 785.E-mail address: sram@biomed.cas.cz (R.J. Sram).

383-5718/$ – see front matter © 2006 Elsevier B.V. All rights reserved.doi:10.1016/j.mrgentox.2006.04.022

atic hydrocarbons; Low birth weight; Prematurity; Intrauterine growth

1. Introduction

A study of mothers from regions with differentannual average air pollution levels of PM10 (parti-cles <10 �m) and PAHs (polycyclic aromatic hydrocar-bons) in the Czech Republic showed that higher DNAadduct levels were detected in the group with a GSTM1null genotype in comparison with a GSTM1 positivegenotype (2.05 ± 1.30 versus 1.66 ± 1.39 adducts/108

nucleotides, p < 0.05). This finding was more pro-nounced in a polluted district [1]. Using multiple regres-sion analysis in the same cohort, it was found that DNA

adduct levels in placentas were also affected by the NAT2genotype [2].

In a cohort of 70 mothers and newborns from Poland,DNA adducts in maternal white blood cells were not

n Resea

122 R.J. Sram et al. / Mutatio

related to CYP1A1*2A (MspI) or GSTM1 genotypes,but DNA adducts were significantly higher in newbornsof CYP1A1*2A heterozygotes and homozygotes [3].An investigation of the relationship between PAH–DNAadduct levels and CYP1A1*2A alleles showed thatplacental PAH–DNA adducts levels were significantlyhigher in infants with the CYP1A1*2A restrictionsite compared to infants without the restriction site[4,5].

Molecular epidemiological studies suggest that bio-logical mechanisms underlie the effect of air pollution onbirth outcomes. It has been shown that the levels of DNAadducts are positively related to the risk of intrauterinegrowth retardation (IUGR) [6], birth weight, birth length,head circumference [5,7], and hypoxanthine–guaninephosphoribosyl-transferase locus (HPRT) mutation fre-quency in infants [8].

PAHs and/or their metabolites may bind to the arylhydrocarbon receptor (AhR) and accumulate in thenucleus of cells, resulting in increased rates of mutage-nesis. As PAHs bind to the AhR, anti-estrogenic activitymay result through increased metabolism and the deple-tion of endogenous estrogens [9], thus disrupting theendocrine system by altering steroid functions. Bui et al.[10] have hypothesized that B[a]P exposure may inter-fere with uterine growth during pregnancy because of itsanti-estrogenic effects, thereby disrupting the endocrinesystem. Fetal toxicity may be further caused by DNAdamage, resulting in the activation of apoptotic pathways[11], or by binding of B[a]P to receptors for placentalgrowth factors, resulting in a decreased exchange of oxy-gen and nutrients [12].

The finding of higher DNA adduct levels in the infantcompared to the mother suggests an increased suscepti-bility of the developing fetus to DNA damage [5]. Withrespect to IUGR, it appears that the increased risk isprincipally due to exposure to carcinogenic PAHs (c-PAHs) [12]. This finding is consistent with the ideaof a primary role for c-PAHs in fetal growth modula-tion [12–16]. Perera et al. [17] considered PAHs to besignificant independent determinants of birth outcomes.In addition, there appears to be an interaction betweenexposure to PAH and genotype to produce DNA-adducts[18].

The evidence suggests a causal effect of air pollutionon birth weight (reviewed by [19]). Vassilev et al. [20]observed a risk of premature birth and low birth weightin a group exposed prenatally to high levels of poly-

cyclic organic matter [20]. It therefore seems plausibleto test the hypothesis that birth weight may be affected bypolymorphisms in the genes acting in the detoxificationprocess.

rch 608 (2006) 121–128

Perera et al. [8] presented data showing a rela-tionship between DNA adducts and birth weight. Asour samples of DNA adducts are of a similar size,our task was to analyze the relationship among DNAadducts, birth weight and genotypes. Further, we stud-ied in a larger sample the relationship between birthweight and genetic polymorphisms of metabolic geno-types.

2. Materials and methods

2.1. Subjects and sampling

Each woman involved in the study was systematicallyselected from the whole cohort of mothers giving birth to alive infant in the Teplice and Prachatice districts and the city ofPrague. DNA was chosen for DNA adduct analysis from sam-ples from Teplice and Prachatice collected 1994–1995 [2], forbirth weight from samples from Teplice, Prachatice and Praguecollected 2000–2002.

The district of Teplice lies in the brown coal basin of North-ern Bohemia, polluted by chemical factories, surface mining,and large coal power plants [21]. Since the year 1994 we havestudied the impact of air pollution on pregnancy outcome inthis district [12,22]. The district of Prachatice has been usedas a matching non-polluted control. Prague was later added tostudy the effect of traffic pollution.

Mothers for the study were selected as a nested case–controlstudy from women who gave birth to infants with a low birthweight (LBW, below 2500 g), premature births (PREM, <37weeks) (LBW + PREM together as cases), and controls. Thetotal number of all women in the sample was 199 for DNAadducts analysis and birth weight and 1013 for birth weight andgenotypes. For each mother involved in our study, the averagemonthly exposure to c-PAHs was calculated for each month ofgestation.

The study was approved by the Institutional Review Boardfor the Protection of Human Subjects of the Regional Instituteof Hygiene of Central Bohemia and the Institute of Experi-mental Medicine AS CR. The mother’s signature on a writteninformed consent form was the final condition for enrolmentin the study.

2.2. Air pollution monitoring

Air particles PM2.5 and PM10 (particles <2.5 and<10 �m) were collected daily over a 24 h period at threemonitoring sites—Teplice, Prachatice and Prague-Smichov.The extraction of quartz filters and polyurethane foamplugs and the quantitative chemical analysis of PAHsby HPLC with fluorimetric detection were performed in

the laboratories of the certified company Ecochem, a.s.,Prague (EN ISO CSN IEC 17025). All procedures wereperformed according to US EPA methods [23–25]. Eightcarcinogenic PAHs (c-PAHs) were determined accordingto IARC evaluation [26]: B[a]P, benzo[a]pyrene; B[b]F,

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cess. Table 3 presents only those combinations with asignificant effect. Multiple regression analysis indicatesa significant effect of smoking and ETS on decreasedbirth weight, while genotypes affected outcome when

Table 1Association between DNA adducts and birth weight (g)

Birth weight (g) p

All (N = 199)DNA adducts −12.3Gestation age (40) 167.7 <0.001Smoking −198.5 <0.01

Teplice (N = 90)

R.J. Sram et al. / Mutatio

enzo[b]fluoranthene; B[k]F, benzo[k]fluoranthene; B[a]A,enz[a]anthracene; B[ghi]P, benzo[ghi]perylene; CHRY,hrysene; DB[ah]A, dibenz[ah]anthracene, I[cd]P, andndeno[cd]pyrene.

.3. DNA isolation

Tissue samples were taken from the middle of the pedi-tric placenta, opposite to the umbilical cord. Placentas wererozen at −80 ◦C shortly after delivery. DNA was isolated byhe method of Gupta [27].

.4. 32P-Postlabeling assay

Samples of placental DNA (5 �g) were digested to 3′-ucleoside monophosphates with a mixture of micrococaluclease and spleen phosphodiesterase. The butanol enrich-ent procedure described by Gupta [28] was employed withinor modifications [2].

.5. Genotyping

Polymerase chain reaction (PCR) and restriction fragmentength polymorphisms (RFLP) techniques were used for geno-ype analysis.

A multiplex PCR for the simultaneous analysis of all threeSTM1, GSTT1 and GSTP1 genes was employed, according

o the protocol described in detail by Nedelcheva-Kristensent al. [29] and using the same primers. The presence of 80 and95 bp PCR products identified the GSTM1 positive genotype,hile a PCR product of 480 bp identified the GSTT1 positiveenotype. The 294 bp long fragment corresponding to GSTP1AA; Ile/Ile) was cut into 234 and 60 bp fragments in the casef the G allele. Therefore, fragments of 294, 234 and 60 bpdentified the AG (Ile/Val) genotype and fragments of 234 and0 bp identified the GG (Val/Val) genotype for the GSTP1 gene.

PCR product of 175 bp specific for the GSTM2 gene wassed as an internal control.

CYP1A1*2A (MspI) alleles were identified according tohe protocol of Kawajiri et al. [30]. The presence of a large40 bp fragment identified the homozygous wild type geno-ypes (TT; m1/m1), the presence of three fragments of 340,00 and 140 bp the heterozygous genotypes (TC; m1/m2) andhe presence of only the smaller 200 and 140 bp fragmentshe homozygous genotypes with both mutated alleles (CC;

2/m2).CYP1A1*2C (Ile/Val) alleles were identified according to

he method of Oyama et al. [31]. The presence of 139 and8 bp fragments identified the homozygous wild type geno-ypes (AA; Ile/Ile), the presence of four fragments of 139, 120,8 and 19 bp the heterozygous genotypes (AG; Ile/Val) and

he presence of 120, 48 and 19 bp fragments the homozygousenotypes with both mutated alleles (GG; Val/Val).

Ten percent of all samples for all genotypes were rean-lyzed. All second analyses corresponded to the originalesults.

rch 608 (2006) 121–128 123

2.6. Statistical analysis

SAS© multiple regression was used to estimate the impactof DNA adducts or genotypes on birth weight, and SAS© logis-tic regression to estimate the impact of genotypes on low birthweight (LBW, birth weight less then 2500 g) plus prematu-rity (PREM, birth before the 37th week of gestation). c-PAHs,smoking, ETS, ethnicity, and genotypes were tested as con-founders. Exposure to c-PAHs used in models was calculatedas per trimester average value. They were divided into ter-tils with cut-off points 5.4 and 15.2 ng/m3 (low = <5.4 ng/m3,medium = 5.4–15.2 ng/m3, high = >15.2 ng/m3).

3. Results

3.1. DNA adducts

Data on the association between DNA adducts andbirth weight are presented in Table 1. The level of DNAadducts was not correlated with birth weight in any group(N = 199), including in the polluted district of Teplice(N = 90). The only significant associations were observedbetween birth weight and gestation age (p < 0.001), andbetween birth weight and smoking (p < 0.01). Addition-ally, no effect of genotypes was observed.

3.2. Birth weight

The distribution of the analyzed genotypes in new-borns according to locality is presented in Table 2.

Multiple regression analysis (Table 3) demonstratedan effect of CYP1A1*2C on decreased birth weight in thegroup of smoking mothers from Teplice (LBW + PREM)(p < 0.05). We analyzed many combinations between thegenotypes of phases I and II of the detoxification pro-

DNA adducts 3.7Gestation age (40) 159.0 <0.01Smoking −235.6 <0.05GSTM1 −25.4

p: statistical significance.

124 R.J. Sram et al. / Mutation Research 608 (2006) 121–128

Table 2Distribution of analyzed genotypes in newborns

Group Teplice Prachatice Praha All

Cases Con Cases Con Cases Con Cases Con

GSTM1 (1013)

Wild325 120 57 502

48.4% 52.4% 50.9% 49.5%100 225 22 98 32 25 154 348

Null347 109 55 512

51.6% 47.6% 49.1% 50.5%143 204 19 90 28 27 190 322

GSTT1 (1013)

Wild569 192 89 85084.7% 83.8% 79.5% 83.9%

205 364 33 159 46 43 284 567

Null103 37 23 163

15.3% 16.2% 20.5% 16.1%38 65 8 29 14 9 60 103

GSTP1 (1013)

Ile/Ile325 108 45 478

48.4% 47.2% 40.2% 47.1%115 210 23 85 21 24 159 319

Ile/Val288 105 51 44442.9% 45.9% 45.5% 43.9%

110 178 15 90 29 22 154 291

Val/Val59 16 16 91

8.8% 7.0% 14.3% 9.0%18 41 3 13 10 6 31 60

CYP1A1*2C (Ile/Val) (1013)

Ile/Ile632 214 101 94794.0% 93.4% 90.2% 93.4%

226 406 39 175 53 49 318 629

Ile/Val37 15 11 63

5.5% 6.6% 9.8% 6.3%16 21 2 13 7 4 25 39

Val/Val3 – – –0.4%1 2 – – – – – –

CYP1A1*2A (MspI) (1013)

TT555 187 88 830

85.6% 81.7% 78.6% 81.9%194 361 32 155 48 40 274 556

TC109 41 24 174

16.2% 17.9% 21.4% 17.3%46 63 9 32 12 12 67 108

CC8 1 – 91.2% 0.4% 0.9%3 5 0 1 – – 3 6

Cases: LBW + PREM; Con: controls. For each polymorphism the following data are given: number of newborns, percentage of the given gene inthe group, number of cases, number of controls.

R.J. Sram et al. / Mutation Research 608 (2006) 121–128 125

Table 3Effect of genetic polymorphism on birth weight

Genotype Group Intercept c-PAHs Smoking (cigarette/d) ETS Genotype variability

Middle/low High/low ≤10 ≥10

GSTM1 All 3168 8 −1 −74 −222+ −120+ −28TP 3232 −63 −52 −96 −314++ −101 (p = 0.086) −65

GSTT1 All 3154 7 −3 −75 −222+ −119+ −4TP 3193 −64 −57 −97 −310++ −100 (p = 0.088) 46

GSTP1 All 3155 8 −3 −74 −220+ −119+ −23TP 3196 −68 −59 −98 −318++ −99 (p = 0.090) 95

CYP1A1*2A All 3159 6 −4 −73 −220+ −119+ −27TP 3209 −67 −54 −90 −309++ −99 −70TP-SM 3140 57 121 −189 −146 (p = 0.094)

CYP1A1*2C All 3163 4 −5 −74 −224+ −118+ −103TP 3203 −64 −56 −95 −312++ −100 (p = 0.088) −37TP-cases SM 3140 −64 −134 −184 −315+

CYP1A1*2A + GSTP1 All 3145 6 4 −72 −224 (p < 0.05) −119 (p < 0.05) 23, 20TP-controls 3430 −3 4 −75 −121 −113 (p < 0.05) 60, −135 (p = 0.090)

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p < 0.05; p < 0.01; GSTM1, GSTT1: null vs. positive; GSTP1YP1A1*2C: Ile/Val + Val/Val vs. Ile/Ile; CYP1A1*2A + GSTP1: (mases: LBW + PREM; SM: smoking mothers.

hey were associated with smoking or a polluted local-ty.

Logistic regression analysis was employed to studyhe effect of genotypes on low birth weight plus prema-urity for selected genotypes showing significant differ-nces (Table 4). The risk of LBW plus PREM was sig-ificantly increased for the GSTM1 null genotype in allroups (OR = 1.33, 95% CI, 1.02–1.74, p < 0.05) as wells in the Teplice group (OR = 1.54, 95% CI, 1.10–2.14,< 0.05). An effect of GSTT1, GSTP1, or CYP1A1*2Aas not observed. CYP1A1*2C mutations affected birtheight and prematurity in smokers (OR = 2.89, 95% CI,.07–7.79, p < 0.05). Among the different combinationsf genotypes, the only significant effect on LBW plusREM was observed for genotypes CYP1A1*2A restric-

ion site + GSTM1 null (OR = 1.51, 95% CI, 1.06–2.15,< 0.05).

Birth weight was significantly decreased by smoking,TS and of CYP1A1*2C mutated alleles. The risk of an

ncreased number of infants born prematurely with a lowirth weight was significantly increased by genotypesf GSTM1 and CYP1A1*2C and the combination ofSTM1+CYP1A1*2A mutated alleles.

. Discussion

Our results did not confirm the results of Perera et al.8] on the association between DNA adducts and birtheight. As the pollution by c-PAHs in both localities,

l+Val/Val vs. Ile/Ile; CYP1A1*2A: m1/m2 + m2/m2 vs. m1/m1;m2/m2) + (Ile/Val + Val/Val) vs. residue. All: all cohort; TP: Teplice;

Cracow in Poland and Teplice in the Czech Republic,seems to be similar, the only explanation could be theeffect of ETS in Cracow.

An effect of air pollution on LBW and prematuritywas observed for SO2, NOx, CO, TSP and PM10 [19].The evidence suggests a causal effect of air pollutionon birth weight. Further studies are needed to exam-ine whether the impaired reproductive outcomes haveany long-term consequences for the children’s health.Such an idea may be supported from studies on airpollution and IUGR (intrauterine growth retardation isdefined as a birth weight below the 10th percentile ofbirth weights for the gestational age and gender). IUGRis an interesting endpoint, which may predict functionalchanges in adulthood such as hypertension and coro-nary heart disease [32]. Data by Dejmek et al. [12] andVassilev et al. [33] imply a critical role for PAHs. Itis possible that c-PAHs are responsible for the biologi-cal activity of complex mixtures adsorbed to respirableair particles that can result in IUGR. In this context wecan speculate that genotypes affecting c-PAHs detox-ification can also significantly affect the birth weight(Fig. 1). This idea is similar to the well-known scheme ofexposure to carcinogens–biomarkers–cancer [34]. Whilethe specific steps of these pathways need to be further

clarified, the molecular epidemiology studies, and thesimilarity of the effects of air pollution to those of smok-ing [35,36], support the biological plausibility of theeffects.

126 R.J. Sram et al. / Mutation Research 608 (2006) 121–128

Table 4Effect of genetic polymorphisms on low birth weight plusprematurity—logistic regression analysis, 1st trimester

Genotype group OR CI p

GSTM1All N = 1013

c-PAHs-medium 1.25 0.88–1.78 0.21c-PAHs-high 1.30 0.92–1.85 0.14Smoking-low 1.02 0.72–1.45 0.92Smoking-high 1.99 1.11–3.57 0.022ETS 1.33 0.97–1.82 0.076GSTM1+/GSTM1− 1.33 1.02–1.74 0.037

Teplice, all N = 672c-PAHs-medium 1.43 0.91–2.26 0.12c-PAHs-high 1.46 0.94–2.27 0.092Smoking-low 1.04 0.68–1.60 0.84Smoking-high 3.24 1.58–6.65 0.001ETS 1.25 0.83–1.86 0.28GSTM1+/GSTM1− 1.54 1.10–2.14 0.011

GSTT1Non-smokers, N = 669

c-PAHs-medium 1.48 0.96–2.31 0.078c-PAHs-high 1.37 0.88–2.15 0.17ETS 1.29 0.92–1.81 0.14GSTM1+/GSTM1− 1.13 0.73–1.77 0.57

Non-smokers, Prachatice N = 150c-PAHs-medium 4.19 1.13–15.6 0.003c-PAHs-high 3.59 0.86–15.1 0.003ETS 2.09 0.90–4.82 0.086GSTM1+/GSTM1− 1.46 0.49–4.39 0.50

CYP1A1*2AAll N = 1013

c-PAHs-medium 1.27 0.90–1.80 0.18c-PAHs-high 1.33 0.94–1.90 0.11Smoking-low 1.02 0.72–1.45 0.93Smoking-high 1.95 1.08–3.50 0.026ETS 1.31 0.96–1.79 0.35CYP1A1*2A 1.18 0.84–1.67 0.09

Teplice, all N = 672c-PAHs-medium 1.45 0.90–1.80 0.11c-PAHs-high 1.49 0.94–1.90 0.07Smoking-low 1.03 0.72–1.45 0.88Smoking-high 3.14 1.08–3.50 0.002ETS 1.24 0.96–1.79 0.29CYP1A1*2A 1.18 0.84–1.67 0.45

CYP1A1*2CAll, smokers N = 324

c-PAHs-medium 0.96 0.53–1.75 0.89c-PAHs-high 1.23 0.69–2.21 0.48ETS 1.21 0.51–2.89 0.67CYP1A1*2C 2.89 1.07–7.79 <0.05

Smokers, Teplice N = 324c-PAHs-medium 1.63 0.82–3.27 0.17c-PAHs-high 1.87 0.97–3.62 0.063ETS 1.47 0.46–4.73 0.52CYP1A1*2C 2.91 0.99–8.56 <0.05

Table 4 (Continued )

Genotype group OR CI p

CYP1A1*2A + GSTM1All N = 1013

c-PAHs-medium 1.27 0.90–1.81 0.18c-PAHs-high 1.31 0.92–1.87 0.13Smoking-low 1.00 0.70–1.43 0.99Smoking-high 1.97 1.09–3.53 0.024ETS 1.33 0.97–1.82 0.075GSTM1−/CYP1A1*2A 1.29 0.97–1.71 0.082GSTM1−/CYP1A1*2A(wml1/m1m1)

1.63 0.99–2.68 0.053

Teplice, all N = 672c-PAHs-medium 1.46 0.93–2.30 0.10c-PAHs-high 1.46 0.94–2.27 0.093Smoking-low 1.02 0.67–1.57 0.91Smoking-high 3.23 1.57–6.66 0.001ETS 1.23 0.82–1.83 0.32GSTM1−/CYP1A1*2A 1.51 1.06–2.15 0.021GSTM1−/CYP1A1*2A(wml1/m1m1)

1.80 0.98–3.33 0.060

c-PAHs-medium: 5.4–15.2 ng/m3; c-PAHs-high: >15.2 ng/m3;smoking-low: 1–10 cigarettes/day; smoking-high: 11+ cigarettes/day;ETS: environmental tobacco smoke.

Under the conditions of this study, an effect of theGSTM1, CYP1A1*2A, and CYP1A1*2C genotypeswas observed. We may postulate that the deleteriouseffect of environmental c-PAHs pollution, smoking, orETS may be increased due to the deletion of a gene or tomutations. At the present time our group of 1013 new-borns seems to be the largest group ever studied in thiscontext. However, our results indicate that our subgroups(e.g. cases versus controls, polluted versus control dis-trict, smokers versus non-smokers in a selected district)occasionally lack a sufficient number of subjects to seea significant effect.

Usually, LBW and IUGR are known to influencethe future destiny of the affected individual. Increasedmortality and morbidity in childhood and an elevatedrisk of hypertension, ischemic heart disease and non-insulin dependent diabetes were observed in such indi-viduals. This indicates that a decrease in birth weightmay be related to some functional insufficiency, whichmay manifest itself as child morbidity during child-hood [37] as well as increased morbidity in middleage.

Genotypes are primarily effect modifiers. Their effectincludes the effect of environmental factors, meaningthat in the future, it will be necessary to study the impact

of air pollution on pediatric health together with geneticpolymorphisms. We may speculate about seeing a signif-icant effect of genetic polymorphisms, e.g. in metabolicand DNA repair enzyme genotypes, in regions with

R.J. Sram et al. / Mutation Research 608 (2006) 121–128 127

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y their genetic load for decades.

cknowledgements

The authors would like to thank Mr. James Duttor correction of the English language usage. Thistudy was supported by the Ministry of the Environ-ent of the Czech Republic (grants no. VaV/340/2/00,aV/740/5/03 and VaV-SL/5/160/05) and the Commis-ion of the European Communities (grant QLK4-CT-002-02198 ChildrenGenoNetwork).

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