Variations in tobacco-related cancers, incidence and prevalence reflect differences in tobacco consumption in addition to genetic factors. Besides, genes related to lung cancer risk could be related to smoking behavior. Polymorphisms altering DNA repair capacity may lead to synergistic effects with tobacco carcinogen-induced lung cancer risk. Common problems in genetic association studies, such as presence of gene-by-environment (G x E) correlation in the population, may reduce the validity of these designs. The main purpose of this study was to evaluate the independence assumption for selected SNPs and smoking behaviour in a cohort of 320 healthy Spanish smokers. We found an association between the wild type alleles of XRCC3 Thr241Met or KLC3 Lys751Gln and greater smoking intensity (OR = 12.98, 95% CI = 2.86–58.82 and OR=16.90, 95% CI=2.09-142.8; respectively). Although preliminary, the results of our study provide evidence that genetic variations in DNA-repair genes may influence both smoking habits and the development of lung cancer. Population-specific G x E studies should be carried out when genetic and environmental factors interact to cause the disease.
Citation: Verde Z, Reinoso L, Chicharro LM, Resano P, Sánchez-Hernández I, Rodríguez González-Moro JM, et al. (2015) Are SNP-Smoking Association Studies Needed in Controls? DNA Repair Gene Polymorphisms and Smoking Intensity. PLoS ONE 10(5): e0129374. doi:10.1371/journal.pone.0129374
Academic Editor: Robert W. Sobol, University of South Alabama Mitchell Cancer Institute, UNITED STATES
Received: February 3, 2015; Accepted: May 7, 2015; Published: May 27, 2015
Copyright: © 2015 Verde et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Data Availability: All relevant data are within the paper.
Funding: This study was supported by a grant from Universidad Europea, Madrid (project number 2012/UEM17) and Cátedra Florencio Tejerina-UEM (project number 2010/UEM19). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Cigarette smoke contains large quantities of carcinogens, including polycyclic aromatic hydrocarbons, which damage DNA by covalent binding or oxidation . Although cigarette smoking is the major cause of lung cancer, only a small fraction of smokers develop smoking-related lung cancer, suggesting that other causes, including genetic susceptibility, may contribute to the variation in individual lung cancer risk [4–6]. This genetic susceptibility may be due, in part, to genetically determined variation in carcinogen metabolism  and/or in the capacity of DNA repair [8–10]. DNA-repair activities are essential for the protection of the genome from environmental damage such as tobacco smoke . However, contradictory results are often reported by various studies, making it difficult to interpret them [12,13]. Approximately 160 genes mediate DNA repair have been found in human cells . Several polymorphisms in DNA repair genes contribute to genetic instability and error accumulation due to reduced protein activity being associated to relatively risk of lung cancer in Caucasian population [15,16,17,18]. The NER (nucleotide excision repair) pathway repairs DNA damage caused by the tobacco-related carcinogen benzo(a)pyrene, while the BER (base excision repair) pathway repairs DNA caused by reactive oxygen species (ROS) results from cigarette smoke . In addition, DSBR (double strand break repair) pathway is the responsible for repairing double-strand breaks produced by exogenous agents such as environmental carcinogens present in tobacco smoke and endogenous generated ROS .
Variants in the genes encoding aforementioned proteins are very common in the population. Most of studies have analyzed genetic polymorphisms in XPD, XRCC1, APEX1 and XRCC3 genes. The presence of the alleles 312Asn and 751Gln of XPD has been associated with risk of lung cancer in Caucasian individuals [15,16]. BER genes repair DNA damage from oxidation, deamination and ring fragmentation . XRCC1 Arg399Gln polymorphism and lung cancer risk has been analyzed in relatively high number of studies [22,23,24,18]. XRCC3 participates in repair DNA-double strand break via homologous recombination, the polymorphism of XRCC3 Thr241Met has been indicated to be involved in the development of some cancers . In addition, APE1 protein plays a role in repairing abasic sites . Single-nucleotide polymorphisms of the APE1 gene have been demonstrated to be involved in carcinogenesis. However, the association between APE1 Asp148Glu polymorphism and lung cancer risk remains inconclusive in Caucasian population .
Variants in DNA repair genes modulate DNA repair activity in smokers and therefore could alter cancer risk . Inconsistent results have been published possibly due to low statistical power, false-positive results, heterogeneity across studies populations, failure to consider environmental exposures or publication bias .
Variations in tobacco-related cancers, incidence and prevalence reflect differences in tobacco consumption in addition to genetic factors. Besides, genes related to lung cancer risk could be related to smoking behavior.
Polymorphisms altering DNA repair capacity may lead to synergistic effects with tobacco carcinogen-induced lung cancer risk .
Published control group data on the associations of interest for gene-by-environment (G×E) interaction are limited . Common problems in genetic association studies, such as presence of G x E correlation in the population, may reduce the validity of these designs. The main purpose of this study was to evaluate the independent assumption for selected SNPs and smoking behaviour in a cohort of healthy Spanish smokers.
Polymorphisms of interest were single nucleotide changes (SNPs) in XRCC1 (Arg399Gln) [rs25487], APEX1 (Asp148Glu) [rs1130409], XRCC3 (Thr241Met) [rs861539], XPD (Asp312Asn) [rs1799793] and (Lys751Gln) [rs13181]. Lung cancer susceptibility has been examined in numerous epidemiological studies that have investigated the association between the development of the pathology and variants in candidate genes. We have analysed the aforementioned polymorphisms attending to previous publications and prevalence in Caucasian population [23,24,32,33,34]. We have selected five functional polymorphisms that have been considered as lung cancer risk factors in Caucasian population in order to replicate in a healthy smokers population.
Approval was obtained from the local Ethics Committee (Hospital Carlos III, Madrid) and all patients provided written informed consent. The study was in accordance with the Helsinki Declaration.
Three hundred and twenty healthy smokers (all of Caucasian (Spanish) descent for ≥3 generations) between 25 and 65 years of age were recruited from the Health and Safety Committee of Banco Popular, Madrid (Spain); Department of Neumology, Hospital Carlos III, Madrid, Spain; and Department of Neumology, Hospital Gregorio Marañón, Madrid, Spain; from 2010 to 2013. Eligible participants were 25–65 years old and reported smoking ≥ 1 cigarette per day for ≥ 5 years. Exclusion criteria included suffer from any illness related to smoking.
All participants completed a questionnaire regarding demographic characteristics, smoking habits, self-reported cigarettes per day (CPD), the number of years the person had smoked and pack years smoked (PYS). The PYS is used to describe the number of cigarettes a person has smoked over a lifetime and it is calculated by multiplying the number of cigarettes smoked per day by the number of years the person has smoked and divided by 20. Nicotine dependence was assessed with the Fagerstrom Test for Nicotine Dependence (FTND) . In addition, CO levels and lung function (spirometry) were measured in each participant. We divided the smokers attending CO levels (ppm) in: very light smoker (0–6), light smoker (7–10), smoker (11–20) and heavy smoker (>20). In order to check CPD reported we measure cotinine levels in 30% of participants.
Peripheral blood samples were obtained by venipuncture. Blood leukocyte DNA was extracted using a standard phenol chloroform protocol. The DNA isolation and genotype analyses were performed in the Biomedicine laboratory at the Universidad Europea, Madrid (Spain). The study followed recommendations for replicating genotype-phenotype association studies : genotyping was performed specifically for research purposes, and the researchers in charge of genotyping were totally blinded to the participants’ identities (blood and DNA samples were tracked solely with bar-coding and personal identities were only made available to the main study researcher who was not involved in actual genotyping). The DNA samples were diluted with sterile water and stored at -20°C until analysis.
Genotyping was performed by Real-time PCR and Taqman probes with a Step One Real-Time PCR System (Applied Biosystems, Foster City, CA).
We compared smoking phenotypes among the different genotypes and combination of genotypes with the unpaired Student’s t-test. We used the χ2 test to assess deviations of genotype distributions from the Hardy-Weinberg equilibrium (HWE). Logistic regression analysis was carried out to calculate G-E interactions between smoking habits and genotypes or genotype combinations adjusted for different covariates (i.e., age and gender). All statistical analyses were adjusted for multiple comparisons using the Bonferroni method, in which the threshold P-value is obtained by dividing 0.05 by the number of tests. All analyses were performed with the PASW/SPSS Statistics 20.0 (SPSS Inc, Chicago, IL) program.
The study included 320 healthy current smokers, 55.00% men, all Caucasian with a mean age of 48.64 years (SD = 13.48). On average, they had been smoking for 24.57 years (SD = 10.88). The CPD and PYS ranged from 5 to 70 and 2 to 175 with an overall mean of 17.60 (10.59) cigarettes/day and 28.16 (24.44) PYS, respectively.
In order to check the number of CPD reported, the levels of CO (ppm) expired were tested in each smoker, resulting the following percentage in each category: very light smoker (19.6%), light smoker (15.6%), smoker (39.2%), and heavy smoker (25.6%). Statistically significant differences were found (P<0.001) among the following categories: very light smoker 9.77 CPD (SD = 6.52), light smoker 12.86 CPD (SD = 7.11), smoker 19.58 CPD (SD = 10.43), and heavy smoker 22.94 CPD (SD = 10.69). In addition, significant differences were found between PYS and CO levels (P<0.001): very light smoker 11.52 PYS (SD = 10.88), light smoker 14.91 PYS (SD = 10.38), smoker 24.38 PYS (SD = 22.06), and heavy smoker 29.43 PYS (SD = 19.68) (Figs 1 and 2).
Note: The smokers were divided considering CO levels (ppm) into: very light smoker (0–6), light smoker (7–10), smoker (11–20) and heavy smoker (>20). Abbreviations: CPD, cigarettes per day.
Note: The smokers were divided considering CO levels (ppm) into: very light smoker (0–6), light smoker (7–10), smoker (11–20) and heavy smoker (>20). Abbreviations: PYS, packs year smoked.
All genetic polymorphisms studied in the population were in Hardy Weinberg Equilibrium (HWE) except XRCC1 Arg399Gln polymorphism (P = 0.02). No differences in genotype distribution between females and males were observed (data not shown). Genotype frequencies were, respectively: XRCC1 Arg399Arg = 42.6%, Arg399Glu = 52.7, Glu399Glu = 4.7%; APEX1 Asp148Asp = 31.1, Asp148Gln = 45.1, Gln148Gln = 23.9; XRCC3 Thr241Thr = 35.3, Thr241Met = 48.0, Met241Met = 16.7; ERCC2 Asp312Asp = 43.9, Asp312Asn = 45.2, Asn312Asn = 10.9; KLC3 Lys751Lys = 41.8, Lys751Gln = 45.1 and Gln751Gln = 13.1; showed similar frequency as reported in previous studies in Spanish population .
Analyses focused on associations with genotype categorized using a recessive model (i.e. homozygotes of the most common allele plus heterozygotes were the referent group, compared to homozygotes of the minor allele).
Association between DNA repair variants and smoking behaviour
Genotype-smoking associations between XRCC3 Thr241Met and smoking intensity (PYS) and years smoking were found (P = 0.001 and P = 0.004, respectively). Logistic regression analysis showed an association between the most common allele of XRCC3 Thr241Met and greater smoking intensity (OR = 12.98, 95% CI = 2.86–58.82) and more years smoking (OR = 20.66, 95% CI = 2.57–166.62).
In addition, we found an association between the most common allele of KLC3 Lys751Gln and greater smoking intensity (OR = 16.90, 95% CI = 2.09–142.8) and years smoking (OR = 12.19, 95% CI = 1.49–100.00). For the remaining genotypes we didn´t find a statistically association with smoking habits. For additional data see Table 1.
Under the assumption that the combination of polymorphism can have additive or more than additive effects, the combination of two significant variants was investigated.
We analysed the combination of the most common alleles of KLC3 Lys751Gln and XRCC3 Thr241Met. When the study population was categorized according to the number of risk alleles, smoking habits (PYS) and years smoking were statistically significantly increased in individuals bearing three-four risk alleles (P<0.001) in both.
The case-only study design has been increasingly used to estimate the magnitude of statistical interaction between 2 measured exposures with respect to a given outcome, most commonly a genetic and an environmental exposure .
However, results from the case-only design can be misleading due to, at least, two problems. First, the assumption of independence of genetic and environmental factors, meaning that when genetic and environmental factors are associated, the design may wrongly lead to the conclusion that interaction exists . Second, a statistical interaction does not guarantee a biological relationship when genetic and environmental factors interact to cause the disease. The independent effect of either exposure, or interaction on the additive scale, cannot be estimated.
Little empirical work has been conducted to quantitatively assess the magnitude of control-only associations between DNA repair gene variations and smoking. Moreover, to our knowledge, only a few studies have investigated the associations between in vitro-induced DNA adduct levels and genetic variations in DNA repair genes in normal cells from healthy individuals.
Although asking for the number of CPD is currently accepted as the gold standard measure of exposure, it may not be a good indicator. There are many factors that alter the real exposure, such as individual variability, gender, type of cigarette or the lack of precision reporting the number of CPD. There is wide recognition that a proportion of current smokers underestimates tobacco consumption or even denies smoking entirely. In our sample, CPD reported by smokers were in accordance to CO levels tested, so the population was correctly phenotyped.
Expired CO levels correlate closely with specific cotinine assays and reliably reflect smoking habits . Our results showed that there was a significantly positive association between daily consumption of cigarettes and CO levels, and between PYS and CO levels in healthy smokers. We considered strict criteria for phenotypic measures. Despite of smoking may seem to be a simple phenotype with measurable parameters as cigarette smoked per day, describing a reliable phenotype could be a difficult problem in scientific research because subjective estimations are used instead of real measures .
Analysing the effect of DNA repair variants in smoking behaviour we found associations between XRCC3 Thr241Met and KLC3 Lys751Gln variants and smoking habits in Spanish population. Furthermore, when we investigated the combination of KLC3 Lys751 and XRCC3 Thr241 alleles, a highly significant association with smoking was observed in the subjects carrying three or more risk alleles. PYS showed the highest association, thus PYS is a feasible way to measure the amount a person has smoked over a long period of time .
Smoking amount (PYS) may be causally associated with the most common alleles of XRCC3 Thr241Met and KLC3 Lys751Gln. In addition, smokers with the XRCC3 Thr241or KLC3 Lys751 alleles presented more nicotine addiction measured by FTND and more years smoking. There is evidence that XRCC1 Arg399Gln, KLC3 Lys751Gln and XRCC3 Thr241Met variants are functional [42,43]. Several authors have analysed the effect of different combinations of DNA repair SNPs and the levels of DNA adducts [43–47]. Inverse significant associations on DNA adducts have been detected in XRCC3 Met241Met carriers . In the same way, other authors have also been described for XRCC3 Met241 carriers an association with reduced repair of X-ray-induced cytogenetic damage measured by chromatid aberrations [43,47]. The XRCC3 Thr241Met polymorphism is a non-conservative substitution with possible biological implications for the function of the enzyme and/or the interaction with others DNA repairing proteins. Amino acid variants in different domains of DNA repair proteins may not only affect different protein interactions, resulting in the expression of different phenotypes , but also the same polymorphism may have divergent effects on different DNA repair pathways and on different types of DNA damage .
Attending our results, across SNPs, XRCC3 Thr241Met and KLC3 Lys751Gln polymorphisms could be related to nicotine addiction measured as smoking amount (PYS) or years smoking.
In a meta-analysis Hodgson et al. reported similar associations as those we found . There is some evidence that variation in DNA repair activity may affect neurological and/or respiratory outcomes, which could in turn affect smoking behaviour [49,50]. Different aspects of smoking behaviour (smoking initiation, smoking cessation, intensity etc.) operate through multiple overlapping pathways, therefore would not be expected to be identically affected by DNA repair variation .
Population stratification could have contributed to the heterogeneity in G-E associations. Variant alleles are found at different frequencies in different ethnic groups within the same study, and smoking behaviour may also differ by ethnicity . Moreover most of the studies of G-E interaction with smoking amount information are lung cancer studies . G-E associations in controls may be population-specific.
Hung and cols., published typical problems regarding investigations of G-E interactions, in particular, the fact that among the generally negative results, some seemingly noteworthy associations are identified in subgroups of subjects who are defined on the basis of their tumor histology or smoking habits. In some cases exists the probability that the associations found are attributable to chance (i.e., false positives). The challenge is to distinguish the false-positive associations from the true positives . Several authors propose a simple Bayesian approach that is based on the estimation of a prior probability and the calculation of posterior probability . Meta-analysis or functional analysis can be extremely useful for obtaining prior estimates [51,53].
A weakness of our study was the low sample size of healthy smokers, yet we believe this can be partly overcome by the fact that our population is homogeneous, not stratified and well defined in terms of phenotype assessment.
Although preliminary, the results of our study provide evidence that several genetic variations in DNA-repair genes may influence not only smoking habits but also the development of lung cancer.
To our knowledge, there are no previous studies G-E on DNA repair genes polymorphisms and smoking habits in healthy Spanish population. The results of our study are overall consistent, as they comply with the following published guidelines : the smoking phenotypes and the study outcome were properly measured and accurately recorded by a researcher who was blind to the genetic information and was an expert in the area (Neumologist), we corrected all statistical inferences for multiple comparisons (Bonferroni’s criteria for the p-values); and the results are overall in accordance with previous research in the field. Studies with more sophisticated designs (including more appropriate smoking phenotype measurements and representative population) are required even with the risk of smaller sample size [21, 55].
The authors thank Cátedra Extraordinaria Roche de Diagnóstico e Innovación for the help to publish the research.
Conceived and designed the experiments: FGG CS FB ZV JMRGM. Performed the experiments: FGG CS ZV LMC. Analyzed the data: ZV LR. Contributed reagents/materials/analysis tools: LR PR ISH JMRGM FB LMC FGG CS ZV LMC. Wrote the paper: ZV. Conceived the project idea: ZV CS FGG.
- 1. World Health Organization. WHO report on the global tobacco epidemic, 2008: The MPOWER package. 2008.
- 2. US Department of Health and Human Services. The health consequences of smoking—50 years of progress: A report of the surgeon general. Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. 2014;17.
- 3. Hecht SS. Tobacco smoke carcinogens and lung cancer. J Natl Cancer Inst. 1999;91: 1194–1210. pmid:10413421
- 4. Kogevinas M, Rodríguez Suárez M, Adonina Tardón S. Cáncer laboral en españa. Valencia: Instituto Sindical de Trabajo, Ambiente y Salud (ISTAS). 2005.
- 5. Xing D, Tan W, Wei Q, Lin D. Polymorphisms of the DNA repair gene XPD and risk of lung cancer in a chinese population. Lung Cancer. 2002;38: 123–129. S0169500202001848 [pii]. pmid:12399122
- 6. Mohrenweiser HW. Genetic variation and exposure related risk estimation: Will toxicology enter a new era? DNA repair and cancer as a paradigm. Toxicol Pathol. 2004;32 Suppl 1: 136–145. pmid:15209414
- 7. Caporaso N, Landi MT, Vineis P. Relevance of metabolic polymorphisms to human carcinogenesis: Evaluation of epidemiologic evidence. Pharmacogenetics. 1991;1: 4–19. pmid:1844821
- 8. Kazma R, Cardin NJ, Witte JS. Does accounting for gene-environment interactions help uncover association between rare variants and complex diseases? Hum Hered. 2012;74: 205–214. doi: 10.1159/000346825. pmid:23594498
- 9. Kazma R, Babron MC, Gaborieau V, Genin E, Brennan P, Hung RJ, et al. Lung cancer and DNA repair genes: Multilevel association analysis from the international lung cancer consortium. Carcinogenesis. 2012;33: 1059–1064. doi: 10.1093/carcin/bgs116. pmid:22382497
- 10. Li W, Li K, Zhao L, Zou H. DNA repair pathway genes and lung cancer susceptibility: A meta-analysis. Gene. 2014;538: 361–365. doi: 10.1016/j.gene.2013.12.028. pmid:24368330
- 11. Hoeijmakers JH. Genome maintenance mechanisms for preventing cancer. Nature. 2001;411: 366–374. doi: 10.1038/35077232. pmid:11357144
- 12. Li W, Yang F, Gui Y, Bian J. DNA repair gene XRCC1 Arg194Trp polymorphism and susceptibility to hepatocellular carcinoma: A meta-analysis. Oncol Lett. 2014;8: 1725–1730. doi: 10.3892/ol.2014.2351. pmid:25202399
- 13. Wang R, Zhang Y, Zhang J, Zhi X. Association of X-ray repair cross-complementing group 1 promoter rs3213245 polymorphism with lung cancer risk. Tumour Biol. 2014;35: 1739–1743. doi: 10.1007/s13277-013-1435-2. pmid:24470137
- 14. Wood RD, Mitchell M, Lindahl T. Human DNA repair genes, 2005. Mutat Res. 2005;577: 275–283. S0027-5107(05)00163-6 [pii]. pmid:15922366
- 15. Popanda O, Schattenberg T, Phong CT, Butkiewicz D, Risch A, Edler L, et al. Specific combinations of DNA repair gene variants and increased risk for non-small cell lung cancer. Carcinogenesis. 2004;25: 2433–2441. doi: 10.1093/carcin/bgh264. pmid:15333465
- 16. Zienolddiny S, Campa D, Lind H, Ryberg D, Skaug V, Stangeland L, et al. Polymorphisms of DNA repair genes and risk of non-small cell lung cancer. Carcinogenesis. 2006;27: 560–567. bgi232 [pii]. pmid:16195237
- 17. Lopez-Cima MF, Gonzalez-Arriaga P, Garcia-Castro L, Pascual T, Marron MG, Puente XS, et al. Polymorphisms in XPC, XPD, XRCC1, and XRCC3 DNA repair genes and lung cancer risk in a population of northern spain. BMC Cancer. 2007;7: 162. 1471-2407-7-162 [pii]. pmid:17705814
- 18. Buch SC, Diergaarde B, Nukui T, Day RS, Siegfried JM, Romkes M, et al. Genetic variability in DNA repair and cell cycle control pathway genes and risk of smoking-related lung cancer. Mol Carcinog. 2012;51 Suppl 1: E11–20. doi: 10.1002/mc.20858. pmid:21976407
- 19. Wilson DM 3rd. Properties of and substrate determinants for the exonuclease activity of human apurinic endonuclease Ape1. J Mol Biol. 2003;330: 1027–1037. S0022283603007125 [pii]. pmid:12860125
- 20. Khanna KK, Jackson SP. DNA double-strand breaks: Signaling, repair and the cancer connection. Nat Genet. 2001;27: 247–254. doi: 10.1038/85798. pmid:11242102
- 21. Frosina G. Commentary: DNA base excision repair defects in human pathologies. Free Radic Res. 2004;38: 1037–1054. UC6NBD9QW15UHLKK [pii]. pmid:15512792
- 22. Peluso M, Munnia A, Piro S, Armillis A, Ceppi M, Matullo G, et al. Smoking, DNA adducts and number of risk DNA repair alleles in lung cancer cases, in subjects with benign lung diseases and in controls. J Nucleic Acids. 2010;2010: 386798. doi: 10.4061/2010/386798. pmid:20976253
- 23. Uppal V, Mehndiratta M, Mohapatra D, Grover RK, Puri D. XRCC-1 gene polymorphism (Arg399Gln) and susceptibility to development of lung cancer in cohort of north indian population: A pilot study. J Clin Diagn Res. 2014;8: CC17–20. doi: 10.7860/JCDR/2014/10061.5132. pmid:25584213
- 24. Letkova L, Matakova T, Musak L, Sarlinova M, Krutakova M, Slovakova P, et al. DNA repair genes polymorphism and lung cancer risk with the emphasis to sex differences. Mol Biol Rep. 2013;40: 5261–5273. doi: 10.1007/s11033-013-2626-z. pmid:23673479
- 25. Wang R, Persky NS, Yoo B, Ouerfelli O, Smogorzewska A, Elledge SJ, et al. DNA repair. mechanism of DNA interstrand cross-link processing by repair nuclease FAN1. Science. 2014;346: 1127–1130. doi: 10.1126/science.1258973. pmid:25430771
- 26. Lindahl T. Instability and decay of the primary structure of DNA. Nature. 1993;362: 709–715. doi: 10.1038/362709a0. pmid:8469282
- 27. Cai L, Fu Y, Zhang Y. APE1 Asp148Glu polymorphism and lung cancer susceptibility. Tumour Biol. 2014;35: 5237–5244. doi: 10.1007/s13277-014-1681-y. pmid:24523018
- 28. Dong Z, Guo W, Zhou R, Wan L, Li Y, Wang N, et al. Polymorphisms of the DNA repair gene XPA and XPC and its correlation with gastric cardiac adenocarcinoma in a high incidence population in north china. J Clin Gastroenterol. 2008;42: 910–915. doi: 10.1097/MCG.0b013e3180f6262c. pmid:18645534
- 29. 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. kwi318 [pii]. pmid:16221808
- 30. Ito H, Matsuo K, Hamajima N, Mitsudomi T, Sugiura T, Saito T, et al. Gene-environment interactions between the smoking habit and polymorphisms in the DNA repair genes, APE1 Asp148Glu and XRCC1 Arg399Gln, in japanese lung cancer risk. Carcinogenesis. 2004;25: 1395–1401. doi: 10.1093/carcin/bgh153. pmid:15044328
- 31. Hodgson ME, Poole C, Olshan AF, North KE, Zeng D, Millikan RC. Smoking and selected DNA repair gene polymorphisms in controls: Systematic review and meta-analysis. Cancer Epidemiol Biomarkers Prev. 2010;19: 3055–3086. doi: 10.1158/1055-9965.EPI-10-0877. pmid:20935063
- 32. Buch SC, Diergaarde B, Nukui T, Day RS, Siegfried JM, Romkes M, et al. Genetic variability in DNA repair and cell cycle control pathway genes and risk of smoking-related lung cancer. Mol Carcinog. 2012;51 Suppl 1: E11–20. doi: 10.1002/mc.20858. pmid:21976407
- 33. Lopez-Cima MF, Alvarez-Avellon SM, Pascual T, Fernandez-Somoano A, Tardon A. Genetic polymorphisms in CYP1A1, GSTM1, GSTP1 and GSTT1 metabolic genes and risk of lung cancer in asturias. BMC Cancer. 2012;12: 433-2407-12-433. doi: 10.1186/1471-2407-12-433.
- 34. Vineis P, Manuguerra M, Kavvoura FK, Guarrera S, Allione A, Rosa F, et al. A field synopsis on low-penetrance variants in DNA repair genes and cancer susceptibility. J Natl Cancer Inst. 2009;101: 24–36. doi: 10.1093/jnci/djn437. pmid:19116388
- 35. Lessov-Schlaggar CN, Pergadia ML, Khroyan TV, Swan GE. Genetics of nicotine dependence and pharmacotherapy. Biochem Pharmacol. 2008;75: 178–195. S0006-2952(07)00576-X [pii]. pmid:17888884
- 36. Chanock SJ, Manolio T, Boehnke M, Boerwinkle E, Hunter DJ, Thomas G, et al. Replicating genotype–phenotype associations. Nature. 2007;447: 655–660. pmid:17554299
- 37. Hafeman DM, VanderWeele TJ. Alternative assumptions for the identification of direct and indirect effects. Epidemiology. 2011;22: 753–764. doi: 10.1097/EDE.0b013e3181c311b2. pmid:20502339
- 38. Albert PS, Ratnasinghe D, Tangrea J, Wacholder S. Limitations of the case-only design for identifying gene-environment interactions. Am J Epidemiol. 2001;154: 687–693. pmid:11590080
- 39. Leitch D, Harkawat R, Askew J, Masel P, Hendrick D. Relation of expired carbon monoxide to smoking history, lapsed time, T< sub> L CO measurement and passive smoking. Respir Med. 2005;99: 32–38. pmid:15672846
- 40. Lazary J, Dome P, Faludi G. Genetic and pharmacogenomic data on smoking: The bigger sample size, the less reliable phenotype? A critical review. Neuropsychopharmacol Hung. 2011;13: 7–13. pmid:21451187
- 41. Verde Z, Santiago C, Rodriguez Gonzalez-Moro JM, de Lucas Ramos P, Lopez Martin S, Bandres F, et al. 'Smoking genes': A genetic association study. PLoS One. 2011;6: e26668. doi: 10.1371/journal.pone.0026668. pmid:22046326
- 42. Matullo G, Guarrera S, Carturan S, Peluso M, Malaveille C, Davico L, et al. DNA repair gene polymorphisms, bulky DNA adducts in white blood cells and bladder cancer in a case-control study. Int J Cancer. 2001;92: 562–567. doi: 10.1002/ijc.1228. [pii]. pmid:11304692
- 43. Matullo G, Palli D, Peluso M, Guarrera S, Carturan S, Celentano E, et al. XRCC1, XRCC3, XPD gene polymorphisms, smoking and (32)P-DNA adducts in a sample of healthy subjects. Carcinogenesis. 2001;22: 1437–1445. pmid:11532866
- 44. Lu X, Liu Y, Yu T, Xiao S, Bao X, Pan L, et al. ERCC1 and ERCC2 haplotype modulates induced BPDE-DNA adducts in primary cultured lymphocytes. PLoS One. 2013;8: e60006. doi: 10.1371/journal.pone.0060006. pmid:23593158
- 45. Duell EJ, Wiencke JK, Cheng TJ, Varkonyi A, Zuo ZF, Ashok TD, et al. Polymorphisms in the DNA repair genes XRCC1 and ERCC2 and biomarkers of DNA damage in human blood mononuclear cells. Carcinogenesis. 2000;21: 965–971. pmid:10783319
- 46. Peluso M, Munnia A, Piro S, Armillis A, Ceppi M, Matullo G, et al. Smoking, DNA adducts and number of risk DNA repair alleles in lung cancer cases, in subjects with benign lung diseases and in controls. J Nucleic Acids. 2010;2010: 386798. doi: 10.4061/2010/386798. pmid:20976253
- 47. Lunn RM, Helzlsouer KJ, Parshad R, Umbach DM, Harris EL, Sanford KK, et al. XPD polymorphisms: Effects on DNA repair proficiency. Carcinogenesis. 2000;21: 551–555. pmid:10753184
- 48. Taylor EM, Broughton BC, Botta E, Stefanini M, Sarasin A, Jaspers NG, et al. Xeroderma pigmentosum and trichothiodystrophy are associated with different mutations in the XPD (ERCC2) repair/transcription gene. Proc Natl Acad Sci U S A. 1997;94: 8658–8663. pmid:9238033
- 49. Hoffmann H, Hogel J, Speit G. The effect of smoking on DNA effects in the comet assay: A meta-analysis. Mutagenesis. 2005;20: 455–466. gei064 [pii]. pmid:16280345
- 50. Wilding CS, Relton CL, Rees GS, Tarone RE, Whitehouse CA, Tawn EJ. DNA repair gene polymorphisms in relation to chromosome aberration frequencies in retired radiation workers. Mutat Res. 2005;570: 137–145. S0027-5107(04)00448-8 [pii]. pmid:15680411
- 51. 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. kwi318 [pii]. pmid:16221808
- 52. Wacholder S, Chanock S, Garcia-Closas M, El Ghormli L, Rothman N. Assessing the probability that a positive report is false: An approach for molecular epidemiology studies. J Natl Cancer Inst. 2004;96: 434–442. pmid:15026468
- 53. Matullo G, Dunning AM, Guarrera S, Baynes C, Polidoro S, Garte S, et al. DNA repair polymorphisms and cancer risk in non-smokers in a cohort study. Carcinogenesis. 2006;27: 997–1007. bgi280 [pii]. pmid:16308313
- 54. Attia J, Ioannidis JP, Thakkinstian A, McEvoy M, Scott RJ, Minelli C, et al. How to use an article about genetic association: C: What are the results and will they help me in caring for my patients? JAMA. 2009;301: 304–308. doi: 10.1001/jama.2008.993. pmid:19155457
- 55. Verde Z, Santiago C, Valle B, Fernandez-Santander A, Bandres F, Calvo E, et al. Pharmacogenetics of acenocoumarol: CYP2C9 *2 and VKORC1 c.-1639G>A, 497C>G, 1173C>T, and 3730G>A variants influence drug dose in anticoagulated patients. Thromb Haemost. 2009;101: 591–593. pmid:19277427