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Mutagenesis Advance Access originally published online on October 29, 2007
Mutagenesis 2008 23(1):35-41; doi:10.1093/mutage/gem040
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© The Author 2007. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

hOGG1326, XRCC1399 and XRCC3241 polymorphisms influence micronucleus frequencies in human lymphocytes in vivo

Raluca A. Mateuca1,*,{dagger}, Mathieu Roelants2, Gwenaelle Iarmarcovai3,{dagger}, Peter V. Aka1,{dagger}, Lode Godderis4,5,{dagger}, Annie Tremp1, Stefano Bonassi6, Michael Fenech7, Jean-Louis Bergé-Lefranc8,{dagger} and Micheline Kirsch-Volders1

1Laboratorium voor Cellulaire Genetica, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussel, Belgium 2Laboratorium voor Antropogenetica, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussel, Belgium 3Laboratoire de Biogénotoxicologie et Mutagenèse Environnementale (EA 1784; IFR PMSE 112), Faculté de Médecine, Université de la Méditerranée, Marseille, France 4Laboratorium voor Arbeidshygiëne en -Toxicologie, Katholieke Universiteit Leuven, Kapucijnenvoer 35/6, 3000 Leuven, Belgium 5IDEWE, Interleuvenlaan 58, 3001 Heverlee, Belgium 6Unit of Molecular Epidemiology, National Cancer Research Institute, Genoa, Italy 7CSIRO Health Sciences and Nutrition, PO Box 10041, Adelaide, SA 5000, Australia 8Laboratoire de Biochimie et Biologie Moléculaire, Hôpital de la Conception, 147 Boulevard Baille, 13385 Marseille cedex 5, France

A pooled analysis of five biomonitoring studies was performed to assess the influence of hOGG1326, XRCC1399 and XRCC3241 gene polymorphisms on micronuclei (MN) frequency in human peripheral blood lymphocytes, as measured by the ex vivo/in vitro cytokinesis-block micronucleus (CBMN) assay. Each study addressed a type of occupational exposure potentially able to induce DNA strand breakage (styrene, ionising radiation, cobalt/hard metal, welding fumes and inorganic arsenite compounds), and therefore MN, as a result of base excision repair and double-strand break repair deficiencies. The effect of genotype, age, exposure to genotoxic agents and smoking habit on MN induction was determined using Poisson regression analysis in 171 occupationally exposed male workers and in 132 non-exposed male referents. The analysis of genotype–genotype, genotype–smoking and genotype–exposure interactions by linear combinations of parameters showed significantly higher MN frequencies in the following subsets: (i) occupationally exposed workers carrying either the Thr/Thr or the Thr/Met XRCC3241 genotypes compared to their referent counterparts (P < 0.001) and (ii) carriers of the Met/Met XRCC3241 genotype compared to Thr/Thr XRCC3241 carriers, as far as they are non-exposed and bear the variant (Ser/Cys or Cys/Cys) hOGG1326 genotype (P < 0.01). Significantly lower MN frequencies were observed in carriers of the variant hOGG1326 genotype compared to Ser/Ser hOGG1326 carriers in the subgroup of non-smokers with Thr/Thr XRCC3241 genotype (P < 0.01). Stratified analysis by occupational exposure showed a significant MN increase with smoking in occupationally exposed carriers of the Arg/Gln XRCC1399genotype (P < 0.001). In contrast, a significant MN decrease with smoking was observed in referents carrying the Ser/Ser hOGG1326 genotype (P < 0.01). These findings provide evidence that the combination of different DNA repair genes and their interaction with environmental genotoxic agents may modulate MN induction. Understanding the complexity of the relationships between exposure, DNA repair and MN frequencies require larger scale studies and complementary biomarkers.


   Introduction
Top
 Introduction
Materials and methods
 Results
 Discussion
 Funding
 References
 
Micronuclei (MN) arise during cell division and mainly originate from acentric chromosome/chromatid fragments (chromosome breakage) or whole chromosomes/chromatids that fail to engage with the mitotic spindle during nuclear division (chromosome loss). The detection of MN in binucleated cells by means of the ex vivo/in vitro cytokinesis-block micronucleus (CBMN) assay (1Go) has been successfully employed as a reliable biomarker of exposure to both clastogenic and aneugenic agents (2Go–8Go).

Major steps in the validation of the ex vivo/in vitro CBMN assay for human biomonitoring were performed by the Human MicroNucleus (HUMN) working group (www.humn.org) that examined the major confounding factors influencing the baseline MN frequency, such as culture conditions, scoring criteria, inter-scorer variation, age, smoking and exposure to genotoxic agents (4Go,9Go–13Go). More recently, a large international cohort study conducted within the HUMN network provided evidence that the baseline MN frequency in cytokinesis-blocked lymphocytes is a predictive biomarker of cancer risk (14Go).

MN harbouring acentric chromosome/chromatid fragments result from double-strand DNA breaks (DSBs) induced either directly or indirectly by the conversion of single-strand DNA breaks (SSBs) into DSBs after cell replication. Therefore, genetic polymorphisms leading to mis-repair of SSBs and DSBs have the potential to influence MN frequencies (15Go). Similarly, the presence of MN harbouring whole chromosomes is likely to be influenced by genetic polymorphisms controlling the maintenance of the correct centrosome number (16Go), the reactivity of aneugens, e.g. inhibitors of tubulins, topoisomerases and cyclins or the activity of cell cycle check points (15Go).

The involvement of hOGG1, XRCC1 and XRCC3 gene products in the repair of oxidized bases, SSBs and DSBs, respectively, is well documented (17Go–21Go). Moreover, despite some controversial results (22Go–26Go), genetic variants in hOGG1, XRCC1 and XRCC3 genes have been associated with cancer risk.

hOGG1 is responsible for the removal of the highly mutagenic 7,8-dihydro-8-oxoguanine (8-OHdG) DNA lesion via its DNA glycosylase/apurinic lyase activities (17Go). The repair of SSBs arising directly from damage to the deoxyribose moieties or indirectly as intermediates of the base excision repair (BER) pathway (27Go) is facilitated by the scaffold protein XRCC1 via its ability to interact with DNA ligase III{alpha}, DNA polymerase β, APE1, polynucleotide kinase/phosphatase, poly (ADP-ribose) polymerases 1 and 2 (PARP-1 and 2), hOGG1, hNEIL1 and DNA-dependent protein kinase (DNA-PK) (28Go–36Go). The RAD 51 paralogue XRCC3 promotes the homologous recombination (HR) repair of DSBs (20Go) induced either directly or indirectly following replication of closely spaced SSBs (37Go). Additionally, XRCC3 was also shown to promote chromosome stability (38Go) and correct chromosome segregation in mammalian cells (39Go,40Go).

The aim of the present study was to determine through a pooled analysis of CBMN data the influence of common polymorphisms in BER [hOGG1326(Ser->Cys) and XRCC1399(Arg->Gln)] and DSB repair [XRCC3241(Thr->Met)] genes on MN levels in human peripheral blood lymphocytes (PBL). We selected five individual studies (41Go–44Go) (Mateuca R.A., Carton C., Roelants M., Lison D., Kirsch-Volders M., in preparation) involving occupational exposures potentially able to induce DNA strand breakage (e.g. styrene, ionising radiation, cobalt/hard metal, welding fumes and inorganic arsenite compounds) (45Go–49Go), and therefore MN, as a result of BER and DSB repair deficiencies. For ionizing radiation and cobalt/hard metal-induced DNA damage, the inter-individual differences in clastogenic effects essentially depend on genetic polymorphisms affecting the DNA repair capacity (50Go,43Go). For styrene, welding fumes and inorganic arsenite compounds, additional genetic polymorphisms (e.g. xenobiotic metabolism enzymes) may influence MN frequencies (51Go–53Go). The pooled approach, by combining data from several studies, increased the statistical power of the analysis (54Go), providing a greater potential to understand the contribution of environmental and genetic factors to genome stability. Our results indicate that the combination of different DNA repair genes and their interaction with environmental genotoxic agents may modulate MN induction.


   Materials and methods
Top
 Introduction
 Materials and methods
Results
 Discussion
 Funding
 References
 
Laboratories, study design and characteristics of the study population
Published (41Go–44Go) and unpublished (Mateuca R.A., Carton C., Roelants M., Lison D., Kirsch-Volders M., in preparation) data linking hOGG1326 [Database of single nucleotide polymorphisms (dbSNP) no. rs1052133)], XRCC1399 (dbSNP no. rs25487) and XRCC3241 (dbSNP no. rs861539) genotypes to MN frequencies were collected from five in vivo occupational studies conducted by three European laboratories (Table I). The original database comprised a total of 339 Caucasian male subjects for whom detailed information is provided in Table I. Due to missing data, 36 individuals from the original studies were excluded, leaving for the present pooled analysis 303 subjects with complete information on genotypes and MN frequencies; 171 of them were occupationally exposed to mutagens (styrene, ionising radiation, cobalt/hard metal, welding fumes and inorganic arsenite compounds) and 132 represented the non-exposed referent group. Data on age, exposure status and smoking habits were available for all individuals. The number of cigarettes smoked per day ranged between 1 and 60 (mean = 16.6; SD = 8.2). Information on alcohol consumption and diet was not available for all studies, and has therefore not been included in the present investigation. The age ranged from 18 to 68 years (mean = 39.7; SD = 10.2) in the occupationally exposed population and from 20 to 59 years (mean = 41.1; SD = 8.9) in the referents. All studies included in the pooled analysis were approved by local ethics committees. Each study used the same protocol to assess MN frequencies in cytokinesis-blocked PBL (1Go), and for four studies (41Go–43Go, Mateuca R.A., Carton C., Roelants M., Lison D., Kirsch-Volders M, in preparation), MN scoring was performed in the same laboratory. Methods of genotyping were described in the original articles (41Go–44Go). Polymerase chain reaction-restricted fragment length polymorphism genotyping was performed by the same laboratory for four studies out of five (41Go–43Go, Mateuca R.A., Carton C., Roelants M., Lison D., Kirsch-Volders M., in preparation). One study used M13-tagged sequencing primers (http://snp500cancer.nci.nih.gov) to detect XRCC1399 and XRCC3241 genotypes (44Go), and performed additional sequencing to detect hOGG1326 genetic variants for this pooled analysis. No deviations from the Hardy–Weinberg equilibrium were observed in the total population or within strata of occupational exposure (chi-squared test). The distribution of study subjects by genotype and exposure to genotoxic agents is shown in Table I.


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  		Table I. Overview of the studies included in the pooled analysis

 
Statistical methods
The influence of genotype, age, exposure status and smoking status on the frequency of micronucleated cells per 1000 binucleated cells was determined by quasi-Poisson regression analysis (54Go,55Go) and was expressed as frequency ratios (FRs) with their 95% confidence intervals (CIs), and corresponding P-values, as previously described (56GoGo). Statistical analysis was first performed in the total population without including the genotypes into the model. In a second step, models including genotypes were analysed in the total population and within strata of occupational exposure. To take the inter-study variation into account, each analysis was done with a mixed regression model and normalization of the inter-laboratory data was therefore not necessary (55Go). The model included genotype, age, exposure and smoking as fixed factors and study as a random factor. All possible two-way interactions were tested, but only the significant ones were kept in the model. The statistical analysis was carried out with the mlmRev package (0.98–1) for R version 2.2.0. (R Foundation for Statistical Computing, Vienna, 2005). Results were interpreted using linear combinations of estimated main effects and interactions from the Poisson regression analysis. For each linear combination, the P-value was considered significant when lower than 0.05 adjusted for the total number of comparisons performed in the model (Bonferroni correction). The total number of comparisons ranged between 5 and 22 according to the model.

Age was categorized in two groups of comparable size, i.e. ≥40 years (N = 156 subjects) and <40 years (N = 147 subjects). Due to the low number of heavy smokers, an analysis based on the number of cigarettes smoked per day was not possible. Therefore, smoking status was defined on the basis of a smokers/non-smokers approach; the non-smokers category consisted of individuals who never smoked and former smokers who stopped smoking 5 years or more before sampling. XRCC1399 and XRCC3241 were coded as absence of mutant allele (wild-type homozygote), presence of one mutant allele (heterozygote) or presence of two mutant alleles (rare homozygote). Due to the low number of rare homozygotes (Table I), hOGG1326 genotypes were coded as wild type or variant (presence of at least one mutant allele). In all regression models, the wild-type homozygote was always taken as a reference category.


   Results
Top
 Introduction
 Materials and methods
 Results
Discussion
 Funding
 References
 
Tables II and III show the linear combinations of parameters from the Poisson regression analysis with and without including genetic polymorphisms in the models. Only results that remained significant after Bonferroni correction are discussed.


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  		Table II. Poisson regression analysis without genetic polymorphisms: linear combinations of parameters in the total population

 


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  		Table III. Poisson regression analysis including genetic polymorphisms: linear combinations of parameters in the total population and within strata of occupational exposure

 
The Poisson regression model including age, smoking status and exposure as covariates showed significantly higher MN frequencies in the older age group (≥40 years) than in the younger age group (<40 years) (FR = 1.30; 95% CI = 1.17–1.45; P < 0.001) (Table II). Moreover, a significant interaction between smoking and exposure status was also observed. Further analysis of the simultaneous exposure to occupational mutagens and smoking by the linear combination of parameters showed a significant increase of MN in occupationally exposed smokers when compared to non-smokers (FR = 1.21; 95% CI = 1.06–1.38; P < 0.01). Likewise, smokers co-exposed to occupational mutagens had significantly higher MN frequencies than referent smokers (FR = 1.53; 95% CI = 1.31–1.80; P < 0.001) (Table II). The models including genetic polymorphisms (Table III) confirmed the overall increase of MN in the older age group (FR = 1.32; 95% CI = 1.18–1.47; P < 0.001) and showed a significant overall influence of the hOGG1326 x XRCC3241, the hOGG1326 x smoking and the XRCC3241 x exposure interactions on MN induction. Further analysis of these interactions by linear combinations of parameters showed significantly higher MN frequencies in the following subsets: (i) occupationally exposed workers carrying either the Thr/Thr or the Thr/Met XRCC3241 genotypes compared to their referent counterparts (FR = 1.44, 95% CI = 1.20–1.72; FR = 1.34, 95% CI = 1.14–1.57, respectively; P < 0.001) and (ii) carriers of the Met/Met XRCC3241 genotype compared to wild-type Thr/Thr XRCC3241 carriers, as far as they are non-exposed and bear the variant (Ser/Cys or Cys/Cys) hOGG1326 genotype (FR = 1.65; 95% CI = 1.20–2.27; P < 0.01). Significantly lower MN frequencies were observed in carriers of the variant hOGG1326 genotype compared to wild-type Ser/Ser hOGG1326 carriers in the subgroup of non-smokers with Thr/Thr XRCC3241 genotype (FR = 0.72; 95% CI = 0.59–0.88; P < 0.01).

The results of the statistical analysis stratified by occupational exposure confirmed the age-dependent increase in MN frequencies in both the referent and the occupationally exposed populations (FR = 1.39, 95% CI = 1.18–1.63; FR = 1.30, 95% CI = 1.13–1.50, respectively; P < 0.001) (Table III). Moreover, significant two-way interactions between hOGG1326 or XRCC1399 and smoking status were found in the referent and occupationally exposed subjects, respectively. Analysis of the genotype–smoking interactions showed a significant MN increase with smoking in occupationally exposed carriers of the Arg/Gln XRCC1399genotype (FR = 1.49; 95% CI = 1.22–1.83; P < 0.001) (Table III). In contrast, a significant MN decrease with smoking was observed in referents carrying the wild-type hOGG1326 genotype (FR = 0.73; 95% CI = 0.60–0.89; P < 0.01).


   Discussion
Top
 Introduction
 Materials and methods
 Results
 Discussion
Funding
 References
 
The aim of this pooled analysis was to assess the relationship between DNA repair polymorphisms and MN induction in workers occupationally exposed to genotoxic agents and in their non-exposed referents.

Since all mutagens considered in this study essentially induce oxidative DNA damage, SSBs and DSBs (45Go–49Go,57Go,58Go) deficiencies in BER (hOGG1326 and XRCC1399) and DSB (XRCC3241) repair proteins are expected to influence the frequency of MN harbouring acentric chromatid/chromosome fragments. However, cobalt, hard metal (WC-Co) (M. De Boeck, personal communication), welding fumes (52Go) and inorganic arsenite compounds (49Go) may also induce MN through their interaction with spindle tubulins leading to chromosome loss.

Several association studies have recently addressed the link between DNA repair polymorphisms and MN induction (41Go–44Go,50Go,52Go,59Go–63Go), but the evidence that DNA repair polymorphisms influence MN frequencies remains limited. One of the major difficulties in the design of association studies is the large population required, especially for rare alleles, and when gene–environment or gene–gene interactions are investigated. Pooled analyses overcome this limitation by increasing the power of individual studies (54Go) and providing a greater potential to evaluate the interplay between genetic and environmental factors. However, a major limitation is the possible introduction of technical heterogeneity when data from different laboratories are pooled.

The strength of the present investigation lies in the limited extent of biological and technical heterogeneity: all the subjects were males, each study used the same protocol for the CBMN assay (1Go) and, for four out of five studies (41–43, Mateuca R.A., Carton C., Roelants M., Lison D., Kirsch-Volders M., in preparation), both genotyping and the CBMN assay were conducted in the same laboratory. A possible weakness of this analysis lies in the heterogeneity of the occupational genotoxins considered. However, from a mechanistic point of view, the repair of DNA damage induced by the different mutagens considered in this pooled analysis includes major common events (e.g. DNA lesion recognition and incision) that lead, in case of mis-repair, to DSB and thus to MN induction. Moreover, Poisson regression analysis performed separately for each individual study (data not shown) showed that the same trends were present in all studies for a given association, indicating that at this level there was no significant interaction between the type of exposure and genotype/MN associations.

By investigating the effect of age, smoking and exposure status on MN induction, we observed an age-dependent increase of MN in the total population and within strata of occupational exposure (Tables II and III), which is consistent with literature studies (10Go,64Go). Increased levels of MN were also observed in smokers co-exposed to occupational mutagens, while no significant influence of smoking on MN induction was found in the referent subjects (Table II). The effect of smoking habit on MN frequencies is fully evident only at high doses (11Go), and therefore, to better evaluate the extent of interaction between these covariates, a sizeable number of heavy smokers should have been included. Unfortunately, our sample did not include enough heavy smokers to allow an analysis based on the number of cigarettes smoked per day and therefore smoking status was categorized based on the yes/no approach.

In our pooled analysis, the influence of XRCC1399 genotype on MN levels was restricted to the occupationally exposed population. Several studies (65Go–73Go) have associated the presence of the XRCC1399 (Arg->Gln) polymorphism with reduced DNA repair capacity. The functional significance of codon 399 polymorphism has been explained by its location in the PARP-binding region of the XRCC1 gene (34Go), which may possibly affect the XRCC1–PARP interaction, in this way influencing the efficiency of BER. However, evidence also exists that the variant XRCC1399 Gln allele does not negatively affect XRCC1-mediated repair (74Go–76Go). In our study, smokers co-exposed to occupational genotoxins and carrying the Arg/Gln XRCC1399 genotype had higher MN frequencies compared to their non-smoking counterparts. This result is in agreement with literature studies that support the association between deficiencies in XRCC1399 repair and increased risk of tobacco-related chromosomal damage, as assessed by the sister chromatid exchange assay (66Go,67Go,77Go). Moreover, a recent cohort study showed that the variant XRCC1399 Gln allele had a significant impact on chromosomal damage induction in both smokers and non-smokers, with smokers having slightly higher FR for cells with chromosomal aberrations, chromosome-type aberrations and chromatid gaps (78Go). An increase in tobacco-related cancers among light smokers carrying the variant XRCC1399 Gln genotype was also reported (23Go), although the opposite effect was seen in heavy smokers.

A functional impact of the hOGG1326 (Ser->Cys) polymorphism leading to decreased ability to repair 8-OHdG has been described in several studies (79Go–81Go), although other reports have not been conclusive [reviewed in (22Go)]. We observed a significant MN decrease with smoking in referents carrying the wild-type Ser/Ser hOGG1326 genotype (Table III). This decrease might be related to the high levels of tobacco-induced DNA damage, which may result in enhanced apoptosis (11Go) even in the presence of efficient 8-OHdG removal. However, other data from our study showed that carriers of the variant hOGG1326 genotype had significantly lower MN frequencies than wild-type Ser/Ser hOGG1326 carriers in the subgroup of non-smokers with wild-type Thr/Thr XRCC3241 genotype (Table III). This suggests that the effect of hOOG1326 polymorphism on DNA repair capacity may differ with the type and strength of the DNA-damaging exposures and may be influenced by the interaction between hOOG1326 and other genetic polymorphisms.

The XRCC3241 (Thr->Met) polymorphism has been associated with an increase in DNA damage in several studies (68Go,70Go), although the functional basis of such an association is not clear. XRCC3-deficient Chinese hamster ovary cells (irs1SF) transfected with the human hXRCC3241 wild-type or variant allele showed similar abilities to repair DSBs by HR (82Go). Moreover, the defective HR repair of an XRCC3-deficient human colon cancer cell line (HCT116) was restored by expression of either wild-type or variant hXRCC3241 cDNA (83Go). However, recent studies opened the possibility of an additional contribution of the XRCC3241 variants to the induction of MN arising from chromosome loss via malsegregation events (16Go,83Go). In this case, carriers of the XRCC3241 Met/Met alleles would present higher MN frequencies than their wild-type Thr/Thr XRCC3241 counterparts. This hypothesis seems confirmed by our results showing that carriers of the Met/Met XRCC3241 genotype had higher MN frequencies than Thr/Thr XRCC3241 carriers, as far as they are non-exposed and bear the variant hOGG1326 genotype (Table III).

Taken together, our results indicate that single DNA repair gene polymorphisms are not likely to have a major impact on MN frequencies but rather combinations of different DNA repair genes. Moreover, our findings provide evidence that the complex interplay between hOGG1326, XRCC1399, XRCC3241genotypes and environmental factors modulates MN levels. A better understanding of MN induction driven by genetic polymorphisms affecting DNA repair and/or genome stability, in particular XRCC3241, requires larger scale studies and the assessment of other relevant polymorphisms interacting with individual DNA repair capacity (e.g. xenobiotic and folate metabolism). Scoring of additional endpoints in micronucleated PBL [nucleoplasmic bridges; MN-FISH (fluorescence in situ hybridization) with pancentromeric probes] (84Go,85Go) might provide additional valuable information. Considering the complexity of the relationships between genetic polymorphisms in DNA repair enzymes and MN frequencies, the additional use of cellular DNA repair phenotypes might provide more insight in the understanding of gene–gene interactions and the induction of MN as a consequence of deficient DNA repair.


   Funding
Top
 Introduction
 Materials and methods
 Results
 Discussion
 Funding
References
 
Belgian Offices for Scientific, Technical and Cultural Affairs of the Prime Minister's Office (contract PS/03/35); European Union project Cancer Risk Biomarkers (contract no QLK4-2000-00628); Belgian Defense (Department RS&TD and DOVO) (VUB contract : WDGO251, study MS 03/01); the Associazione Italiana per la Ricerca sul Cancro; the Italian Space Agency (Project Mo.Ma., contract no I/014/06/); Environmental Cancer Risk, Nutrition and Individual Susceptibility, a network of excellence operating within the European Union 6th Framework Program, Priority 5: "Food Quality and Safety" (contract no 513943).


   Acknowledgments
 
The authors are grateful to Professor Dr D. Lison, Professor Dr H. Thierens, Professor Dr R. Veulemans and Dr C. Carton for their valuable scientific expertise in conducting the Belgian biomonitoring studies. The authors acknowledge Gina Plas, Sam Roesems, Ann Pauwels, Jocelyne Pompili, Chantal Bideau and Danielle Iniesta for their excellent technical support.


   Notes
 
* To whom correspondence should be addressed. Tel:+32 2 629 13 26; Fax: + 32 2 629 27 59; Email: rmateuca{at}vub.ac.be

{dagger} Authors who contributed data to the pooled analysis. Back


   References
Top
 Introduction
 Materials and methods
 Results
 Discussion
 Funding
 References
 

    1. Fenech M, Morley AA. Measurement of micronuclei in lymphocytes. Mutat. Res. (1985) 147:29–36.[CrossRef][Web of Science][Medline]

    2. Kirsch-Volders M, Elhajouji A, Cundari E, Van Hummelen P. The in vitro micronucleus test: a multi-endpoint assay to detect simultaneously mitotic delay, apoptosis, chromosome breakage, chromosome loss and non-disjunction. Mutat. Res. (1997) 392:19–30.[Web of Science][Medline]

    3. Surralles J, Natarajan AT. Human lymphocytes micronucleus assay in Europe. An international survey. Mutat. Res. (1997) 392:165–174.[Web of Science][Medline]

    4. Fenech M, Holland N, Chang WP, Zeiger E, Bonassi S. The HUman MicroNucleus Project—an international collaborative study on the use of the micronucleus technique for measuring DNA damage in humans. Mutat. Res. (1999) 428:271–283.[Web of Science][Medline]

    5. Kirsch-Volders M, Sofuni T, Aardema M, et al. Report from the in vitro micronucleus assay working group. Environ. Mol. Mutagen. (2000) 35:167–172.[CrossRef][Web of Science][Medline]

    6. Kirsch-Volders M, Sofuni T, Aardema M, et al. Report from the in vitro micronucleus assay working group. Mutat. Res. (2003) 540:153–163.[Web of Science][Medline]

    7. Kirsch-Volders M, Sofuni T, Aardema M, et al. Corrigendum to "report from the in vitro micronucleus assay working group" [Mutat Res. 540 (2003) 153–163]. Mutat. Res. (2004) 564:97–100.[Web of Science]

    8. Kirsch-Volders M, Vanhauwaert A, De Boeck M, Decordier I. Importance of detecting numerical versus structural chromosome aberrations. Mutat. Res. (2002) 504:137–148.[Web of Science][Medline]

    9. Fenech M. Important variables that influence base-line micronucleus frequency in cytokinesis-blocked lymphocytes—a biomarker for DNA damage in human populations. Mutat. Res. (1998) 404:155–165.[Web of Science][Medline]

    10. Bonassi S, Fenech M, Lando C, et al. HUman MicroNucleus project: international database comparison for results with the cytokinesis-block micronucleus assay in human lymphocytes: I. Effect of laboratory protocol, scoring criteria, and host factors on the frequency of micronuclei. Environ. Mol. Mutagen. (2001) 37:31–45.[CrossRef][Web of Science][Medline]

    11. Bonassi S, Neri M, Lando C, Ceppi M, Lin YP, Chang WP, Holland N, Kirsch-Volders M, Zeiger E, Fenech M. Effect of smoking habit on the frequency of micronuclei in human lymphocytes: results from the Human MicroNucleus project. Mutat. Res. (2003) 543:155–166.[CrossRef][Web of Science][Medline]

    12. Fenech M, Bonassi S, Turner J, et al. Intra- and inter-laboratory variation in the scoring of micronuclei and nucleoplasmic bridges in binucleated human lymphocytes. Results of an international slide-scoring exercise by the HUMN project. Mutat. Res. (2003) 534:45–64.[Web of Science][Medline]

    13. Fenech M, Chang WP, Kirsch-Volders M, Holland N, Bonassi S, Zeiger E. HUMN project: detailed description of the scoring criteria for the cytokinesis-block micronucleus assay using isolated human lymphocyte cultures. Mutat. Res. (2003) 534:65–75.[Web of Science][Medline]

    14. Bonassi S, Znaor A, Ceppi M, et al. An increased micronucleus frequency in peripheral blood lymphocytes predicts the risk of cancer in humans. Carcinogenesis (2007) 28:625–631.[Abstract/Free Full Text]

    15. Mateuca R, Lombaert N, Aka PV, Decordier I, Kirsch-Volders M. Chromosomal changes: induction, detection methods and applicability in human biomonitoring. Biochimie (2006) 88:1515–1531.[Medline]

    16. Lindh AR, Rafii S, Schultz N, Cox A, Helleday T. Mitotic defects in XRCC3 variants T241M and D213N and their relation to cancer susceptibility. Hum. Mol. Genet. (2006) 15:1217–1224.[Abstract/Free Full Text]

    17. Boiteux S, Radicella JP. The human OGG1 gene: structure, functions, and its implication in the process of carcinogenesis. Arch. Biochem. Biophys. (2000) 377:1–8.[CrossRef][Web of Science][Medline]

    18. Caldecott KW. XRCC1 and DNA strand break repair. DNA Repair (Amst) (2003) 2:955–969.[CrossRef][Medline]

    19. Thompson LH, West MG. XRCC1 keeps DNA from getting stranded. Mutat. Res. (2000) 459:1–18.[Web of Science][Medline]

    20. Pierce AJ, Johnson RD, Thompson LH, Jasin M. XRCC3 promotes homology-directed repair of DNA damage in mammalian cells. Genes Dev. (1999) 13:2633–2638.[Abstract/Free Full Text]

    21. Brenneman MA, Weiss AE, Nickoloff JA, Chen DJ. XRCC3 is required for efficient repair of chromosome breaks by homologous recombination. Mutat. Res. (2000) 459:89–97.[Web of Science][Medline]

    22. Weiss JM, Goode EL, Ladiges WC, Ulrich CM. Polymorphic variation in hOGG1 and risk of cancer: a review of the functional and epidemiologic literature. Mol. Carcinog. (2005) 42:127–141.[CrossRef][Web of Science][Medline]

    23. Hung RJ, Hall J, Brennan P, Boffetta P. Genetic polymorphisms in the base excision repair pathway and cancer risk: a HuGE review. Am. J. Epidemiol. (2005) 162:925–942.[Abstract/Free Full Text]

    24. Hu Z, Ma H, Chen F, Wei Q, Shen H. XRCC1 polymorphisms and cancer risk: a meta-analysis of 38 case-control studies. Cancer Epidemiol. Biomarkers Prev. (2005) 14:1810–1818.[Abstract/Free Full Text]

    25. Manuguerra M, Saletta F, Karagas MR, Berwick M, Veglia F, Vineis P, Matullo G. XRCC3 and XPD/ERCC2 single nucleotide polymorphisms and the risk of cancer: a HuGE review. Am. J. Epidemiol. (2006) 164:297–302.[Abstract/Free Full Text]

    26. Han S, Zhang HT, Wang Z, Xie Y, Tang R, Mao Y, Li Y. DNA repair gene XRCC3 polymorphisms and cancer risk: a meta-analysis of 48 case-control studies. Eur. J. Hum. Genet. (2006) 14:1136–1144.[CrossRef][Web of Science][Medline]

    27. Brem R, Hall J. XRCC1 is required for DNA single-strand break repair in human cells. Nucleic Acids Res. (2005) 33:2512–2520.[Abstract/Free Full Text]

    28. Caldecott KW, Aoufouchi S, Johnson P, Shall S. XRCC1 polypeptide interacts with DNA polymerase beta and possibly poly (ADP-ribose) polymerase, and DNA ligase III is a novel molecular ‘nick-sensor’ in vitro. Nucleic Acids Res. (1996) 24:4387–4394.[Abstract/Free Full Text]

    29. Kubota Y, Nash RA, Klungland A, Schar P, Barnes DE, Lindahl T. Reconstitution of DNA base excision-repair with purified human proteins: interaction between DNA polymerase beta and the XRCC1 protein. EMBO J. (1996) 15:6662–6670.[Web of Science][Medline]

    30. Marsin S, Vidal AE, Sossou M, Menissier-de Murcia J, Le Page F, Boiteux S, de Murcia G, Radicella JP. Role of XRCC1 in the coordination and stimulation of oxidative DNA damage repair initiated by the DNA glycosylase hOGG1. J. Biol. Chem. (2003) 278:44068–44074.[Abstract/Free Full Text]

    31. Vidal AE, Boiteux S, Hickson ID, Radicella JP. XRCC1 coordinates the initial and late stages of DNA abasic site repair through protein-protein interactions. EMBO J. (2001) 20:6530–6539.[CrossRef][Web of Science][Medline]

    32. Whitehouse CJ, Taylor RM, Thistlethwaite A, Zhang H, Karimi-Busheri F, Lasko DD, Weinfeld M, Caldecott KW. XRCC1 stimulates human polynucleotide kinase activity at damaged DNA termini and accelerates DNA single-strand break repair. Cell (2001) 104:107–117.[CrossRef][Web of Science][Medline]

    33. Schreiber V, Ame JC, Dolle P, Schultz I, Rinaldi B, Fraulob V, Menissier-de Murcia J, de Murcia G. Poly(ADP-ribose) polymerase-2 (PARP-2) is required for efficient base excision DNA repair in association with PARP-1 and XRCC1. J. Biol. Chem. (2002) 277:23028–23036.[Abstract/Free Full Text]

    34. Masson M, Niedergang C, Schreiber V, Muller S, Menissier-de Murcia J, de Murcia G. XRCC1 is specifically associated with poly(ADP-ribose) polymerase and negatively regulates its activity following DNA damage. Mol. Cell. Biol. (1998) 18:3563–3571.[Abstract/Free Full Text]

    35. Wiederhold L, Leppard JB, Kedar P, et al. AP endonuclease-independent DNA base excision repair in human cells. Mol. Cell (2004) 15:209–220.[CrossRef][Web of Science][Medline]

    36. Levy N, Martz A, Bresson A, Spenlehauer C, de Murcia G, Menissier-de Murcia J. XRCC1 is phosphorylated by DNA-dependent protein kinase in response to DNA damage. Nucleic Acids Res. (2006) 34:32–41.[Abstract/Free Full Text]

    37. O'Driscoll M, Jeggo PA. The role of double-strand break repair—insights from human genetics. Nat. Rev. Genet. (2006) 7:45–54.[CrossRef][Web of Science][Medline]

    38. Liu N, Lamerdin JE, Tebbs RS, et al. XRCC2 and XRCC3, new human Rad51-family members, promote chromosome stability and protect against DNA cross-links and other damages. Mol. Cell (1998) 1:783–793.[CrossRef][Web of Science][Medline]

    39. Griffin CS, Simpson PJ, Wilson CR, Thacker J. Mammalian recombination-repair genes XRCC2 and XRCC3 promote correct chromosome segregation. Nat. Cell Biol. (2000) 2:757–761.[CrossRef][Web of Science][Medline]

    40. Griffin CS. Aneuploidy, centrosome activity and chromosome instability in cells deficient in homologous recombination repair. Mutat. Res. (2002) 504:149–155.[Web of Science][Medline]

    41. Godderis L, De Boeck M, Haufroid V, Emmery M, Mateuca R, Gardinal S, Kirsch-Volders M, Veulemans H, Lison D. Influence of genetic polymorphisms on biomarkers of exposure and genotoxic effects in styrene-exposed workers. Environ. Mol. Mutagen. (2004) 44:293–303.[CrossRef][Web of Science][Medline]

    42. Aka P, Mateuca R, Buchet JP, Thierens H, Kirsch-Volders M. Are genetic polymorphisms in OGG1, XRCC1 and XRCC3 genes predictive for the DNA strand break repair phenotype and genotoxicity in workers exposed to low dose ionising radiations? Mutat. Res. (2004) 556:169–181.[Web of Science][Medline]

    43. Mateuca R, Aka PV, De Boeck M, Hauspie R, Kirsch-Volders M, Lison D. Influence of hOGG1, XRCC1 and XRCC3 genotypes on biomarkers of genotoxicity in workers exposed to cobalt or hard metal dusts. Toxicol. Lett. (2005) 156:277–288.[CrossRef][Web of Science][Medline]

    44. Iarmarcovai G, Sari-Minodier I, Chaspoul F, Botta C, De Meo M, Orsiere T, Berge-Lefranc JL, Gallice P, Botta A. Risk assessment of welders using analysis of eight metals by ICP-MS in blood and urine and DNA damage evaluation by the comet and micronucleus assays; influence of XRCC1 and XRCC3 polymorphisms. Mutagenesis (2005) 20:425–432.[Abstract/Free Full Text]

    45. Laffon B, Pasaro E, Mendez J. Evaluation of genotoxic effects in a group of workers exposed to low levels of styrene. Toxicology (2002) 171:175–186.[CrossRef][Web of Science][Medline]

    46. Choi KM, Kang CM, Cho ES, Kang SM, Lee SB, Um HD. Ionizing radiation-induced micronucleus formation is mediated by reactive oxygen species that are produced in a manner dependent on mitochondria, Nox1, and JNK. Oncol. Rep. (2007) 17:1183–1188.[Web of Science][Medline]

    47. De Boeck M, Kirsch-Volders M, Lison D. Cobalt and antimony: genotoxicity and carcinogenicity. Mutat. Res. (2003) 533:135–152.[Medline]

    48. Danadevi K, Rozati R, Banu BS, Grover P. Genotoxic evaluation of welders occupationally exposed to chromium and nickel using the Comet and micronucleus assays. Mutagenesis (2004) 19:35–41.[Abstract/Free Full Text]

    49. Rossman TG. Mechanism of arsenic carcinogenesis: an integrated approach. Mutat. Res. (2003) 533:37–65.[Medline]

    50. Angelini S, Kumar R, Carbone F, Maffei F, Forti GC, Violante FS, Lodi V, Curti S, Hemminki K, Hrelia P. Micronuclei in humans induced by exposure to low level of ionizing radiation: influence of polymorphisms in DNA repair genes. Mutat. Res. (2005) 570:105–117.[Web of Science][Medline]

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

    52. Iarmarcovai G, Sari-Minodier I, Orsiere T, De Meo M, Gallice P, Bideau C, Iniesta D, Pompili J, Berge-Lefranc JL, Botta A. A combined analysis of XRCC1, XRCC3, GSTM1 and GSTT1 polymorphisms and centromere content of micronuclei in welders. Mutagenesis (2006) 21:159–165.[Abstract/Free Full Text]

    53. Ghosh P, Basu A, Mahata J, et al. Cytogenetic damage and genetic variants in the individuals susceptible to arsenic-induced cancer through drinking water. Int. J. Cancer (2006) 118:2470–2478.[CrossRef][Web of Science][Medline]

    54. Taioli E, Bonassi S. Methodological issues in pooled analysis of biomarker studies. Mutat. Res. (2002) 512:85–92.[CrossRef][Web of Science][Medline]

    55. Blettner M, Sauerbrei W, Schlehofer B, Scheuchenpflug T, Friedenreich C. Traditional reviews, meta-analyses and pooled analyses in epidemiology. Int. J. Epidemiol. (1999) 28:1–9.[Abstract/Free Full Text]

    56. Kirsch-Volders M, Mateuca RA, Roelants M, et al. The effects of GSTM1 and GSTT1 polymorphisms on micronucleus frequencies in human lymphocytes in vivo. Cancer Epidemiol. Biomarkers Prev. (2006) 15:1038–1042.[Abstract/Free Full Text]

    57. Marczynski B, Peel M, Baur X. New aspects in genotoxic risk assessment of styrene exposure—a working hypothesis. Med. Hypotheses (2000) 54:619–623.[CrossRef][Web of Science][Medline]

    58. Antonini JM, Leonard SS, Roberts JR, Solano-Lopez C, Young SH, Shi X, Taylor MD. Effect of stainless steel manual metal arc welding fume on free radical production, DNA damage, and apoptosis induction. Mol. Cell. Biochem. (2005) 279:17–23.[CrossRef][Web of Science][Medline]

    59. Ishikawa H, Yamamoto H, Tian Y, Kawano M, Yamauchi T, Yokoyama K. Effects of ALDH2 gene polymorphisms and alcohol-drinking behavior on micronuclei frequency in non-smokers. Mutat. Res. (2003) 541:71–80.[Web of Science][Medline]

    60. Leng S, Cheng J, Zhang L, Niu Y, Dai Y, Pan Z, Li B, He F, Zheng Y. The association of XRCC1 haplotypes and chromosomal damage levels in peripheral blood lymphocyte among coke-oven workers. Cancer Epidemiol. Biomarkers Prev. (2005) 14:1295–1301.[Abstract/Free Full Text]

    61. Laffon B, Teixeira JP, Silva S, Loureiro J, Torres J, Pasaro E, Mendez J, Mayan O. Genotoxic effects in a population of nurses handling antineoplastic drugs, and relationship with genetic polymorphisms in DNA repair enzymes. Am. J. Ind. Med. (2005) 48:128–136.[CrossRef][Web of Science][Medline]

    62. Zijno A, Verdina A, Galati R, Leopardi P, Marcon F, Andreoli C, Rossi S, Crebelli R. Influence of DNA repair polymorphisms on biomarkers of genotoxic damage in peripheral lymphocytes of healthy subjects. Mutat. Res. (2006) 600:184–192.[Web of Science][Medline]

    63. Ishikawa H, Tian Y, Piao F, et al. Genotoxic damage in female residents exposed to environmental air pollution in Shenyang city, China. Cancer Lett. (2006) 240:29–35.[Web of Science][Medline]

    64. Norppa H, Falck GC. What do human micronuclei contain? Mutagenesis (2003) 18:221–233.[Abstract/Free Full Text]

    65. Lunn RM, Langlois RG, Hsieh LL, Thompson CL, Bell DA. XRCC1 polymorphisms: effects on aflatoxin B1-DNA adducts and glycophorin A variant frequency. Cancer Res. (1999) 59:2557–2561.[Abstract/Free Full Text]

    66. Duell EJ, Wiencke JK, Cheng TJ, Varkonyi A, Zuo ZF, Ashok TD, Mark EJ, Wain JC, Christiani DC, Kelsey KT. Polymorphisms in the DNA repair genes XRCC1 and ERCC2 and biomarkers of DNA damage in human blood mononuclear cells. Carcinogenesis (2000) 21:965–971.[Abstract/Free Full Text]

    67. Abdel-Rahman SZ, El-Zein RA. The 399Gln polymorphism in the DNA repair gene XRCC1 modulates the genotoxic response induced in human lymphocytes by the tobacco-specific nitrosamine NNK. Cancer Lett. (2000) 159:63–71.[CrossRef][Web of Science][Medline]

    68. Matullo G, Palli D, Peluso M, et al. XRCC1, XRCC3, XPD gene polymorphisms, smoking and (32)P-DNA adducts in a sample of healthy subjects. Carcinogenesis (2001) 22:1437–1445.[Abstract/Free Full Text]

    69. Hu JJ, Smith TR, Miller MS, Mohrenweiser HW, Golden A, Case LD. Amino acid substitution variants of APE1 and XRCC1 genes associated with ionizing radiation sensitivity. Carcinogenesis (2001) 22:917–922.[Abstract/Free Full Text]

    70. Au WW, Salama SA, Sierra-Torres CH. Functional characterization of polymorphisms in DNA repair genes using cytogenetic challenge assays. Environ. Health Perspect. (2003) 111:1843–1850.[Web of Science][Medline]

    71. Wang Y, Spitz MR, Zhu Y, Dong Q, Shete S, Wu X. From genotype to phenotype: correlating XRCC1 polymorphisms with mutagen sensitivity. DNA Repair (Amst) (2003) 2:901–908.[CrossRef][Medline]

    72. Vodicka P, Kumar R, Stetina R, et al. Genetic polymorphisms in DNA repair genes and possible links with DNA repair rates, chromosomal aberrations and single-strand breaks in DNA. Carcinogenesis (2004) 25:757–763.[Abstract/Free Full Text]

    73. Qu T, Morii E, Oboki K, Lu Y, Morimoto K. Micronuclei in EM9 cells expressing polymorphic forms of human XRCC1. Cancer Lett. (2005) 221:91–95.[CrossRef][Web of Science][Medline]

    74. Taylor RM, Thistlethwaite A, Caldecott KW. Central role for the XRCC1 BRCT I domain in mammalian DNA single-strand break repair. Mol. Cell. Biol. (2002) 22:2556–2563.[Abstract/Free Full Text]

    75. Pachkowski BF, Winkel S, Kubota Y, Swenberg JA, Millikan RC, Nakamura J. XRCC1 genotype and breast cancer: functional studies and epidemiologic data show interactions between XRCC1 codon 280 His and smoking. Cancer Res. (2006) 66:2860–2868.[Abstract/Free Full Text]

    76. Tuimala J, Szekely G, Gundy S, Hirvonen A, Norppa H. Genetic polymorphisms of DNA repair and xenobiotic-metabolizing enzymes: role in mutagen sensitivity. Carcinogenesis (2002) 23:1003–1008.[Abstract/Free Full Text]

    77. Lei YC, Hwang SJ, Chang CC, Kuo HW, Luo JC, Chang MJ, Cheng TJ. Effects on sister chromatid exchange frequency of polymorphisms in DNA repair gene XRCC1 in smokers. Mutat. Res. (2002) 519:93–101.[Web of Science][Medline]

    78. Skjelbred CF, Svendsen M, Haugan V, Eek AK, Clausen KO, Svendsen MV, Hansteen IL. Influence of DNA repair gene polymorphisms of hOGG1, XRCC1, XRCC3, ERCC2 and the folate metabolism gene MTHFR on chromosomal aberration frequencies. Mutat. Res. (2006) 602:151–162.[Web of Science][Medline]

    79. Tarng DC, Tsai TJ, Chen WT, Liu TY, Wei YH. Effect of human OGG1 1245C->G gene polymorphism on 8-hydroxy-2'-deoxyguanosine levels of leukocyte DNA among patients undergoing chronic hemodialysis. J. Am. Soc. Nephrol. (2001) 12:2338–2347.[Abstract/Free Full Text]

    80. Chen SK, Hsieh WA, Tsai MH, Chen CC, Hong AI, Wei YH, Chang WP. Age-associated decrease of oxidative repair enzymes, human 8-oxoguanine DNA glycosylases (hOgg1), in human aging. J. Radiat. Res. (Tokyo) (2003) 44:31–35.[Medline]

    81. Yamane A, Kohno T, Ito K, Sunaga N, Aoki K, Yoshimura K, Murakami H, Nojima Y, Yokota J. Differential ability of polymorphic OGG1 proteins to suppress mutagenesis induced by 8-hydroxyguanine in human cell in vivo. Carcinogenesis (2004) 25:1689–1694.[Abstract/Free Full Text]

    82. Araujo FD, Pierce AJ, Stark JM, Jasin M. Variant XRCC3 implicated in cancer is functional in homology-directed repair of double-strand breaks. Oncogene (2002) 21:4176–4180.[CrossRef][Web of Science][Medline]

    83. Yoshihara T, Ishida M, Kinomura A, Katsura M, Tsuruga T, Tashiro S, Asahara T, Miyagawa K. XRCC3 deficiency results in a defect in recombination and increased endoreduplication in human cells. Embo J. (2004) 23:670–680.[CrossRef][Web of Science][Medline]

    84. Elhajouji A, Van Hummelen P, Kirsch-Volders M. Indications for a threshold of chemically-induced aneuploidy in vitro in human lymphocytes. Environ. Mol. Mutagen. (1995) 26:292–304.[Web of Science][Medline]

    85. Elhajouji A, Tibaldi F, Kirsch-Volders M. Indication for thresholds of chromosome non-disjunction versus chromosome lagging induced by spindle inhibitors in vitro in human lymphocytes. Mutagenesis (1997) 12:133–140.[Abstract/Free Full Text]

Received on August 29, 2007; revised on September 14, 2007; accepted on September 16, 2007.


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