Reduction in oxidatively generated DNA damage following smoking cessation
© Box et al; licensee BioMed Central Ltd. 2011
Received: 3 March 2011
Accepted: 12 May 2011
Published: 12 May 2011
Cigarette smoking is a known cause of cancer, and cancer may be in part due to effects of oxidative stress. However, whether smoking cessation reverses oxidatively induced DNA damage unclear. The current study sought to examine the extent to which three DNA lesions showed significant reductions after participants quit smoking.
Participants (n = 19) in this study were recruited from an ongoing 16-week smoking cessation clinical trial and provided blood samples from which leukocyte DNA was extracted and assessed for 3 DNA lesions (thymine glycol modification [d(TgpA)]; formamide breakdown of pyrimidine bases [d(TgpA)]; 8-oxo-7,8-dihydroguanine [d(Gh)]) via liquid chromatography tandem mass spectrometry (LC-MS/MS). Change in lesions over time was assessed using generalized estimating equations, controlling for gender, age, and treatment condition.
Overall time effects for the d(TgpA) (χ2(3) = 8.068, p < 0.045), d(PfpA) (χ2(3) = 8.477, p < 0.037), and d(Gh) (χ2(3) = 37.599, p < 0.001) lesions were seen, indicating levels of each decreased significantly after CO-confirmed smoking cessation. The d(TgpA) and d(PfpA) lesions show relatively greater rebound at Week 16 compared to the d(Gh) lesion (88% of baseline for d(TgpA), 64% of baseline for d(PfpA), vs 46% of baseline for d(Gh)).
Overall, results from this analysis suggest that cigarette smoking contributes to oxidatively induced DNA damage, and that smoking cessation appears to reduce levels of specific damage markers between 30-50 percent in the short term. Future research may shed light on the broader array of oxidative damage influenced by smoking and over longer durations of abstinence, to provide further insights into mechanisms underlying carcinogenesis.
A commonality in the etiology of cancers may be DNA damage arising from oxidative stress [1, 2]. There are multiple reasons to associate oxidative stress with cancer. Oxidative DNA damage can cause transcription errors, replication errors, and genomic instability, which are all associated with carcinogenesis [3–7]. Over 100 oxidative DNA damage products are known, and reactive oxygen species (ROS) can induce DNA breaks, purine, pyrimidine, or deoxyribose lesions, and even cross links among these .
Oxidative stress in cells and organisms is caused by the presence of ROS, including hydroxyl radicals, superperoxide, hydrogen peroxide, and singlet oxygen. Cells or organisms having an inordinately high level of ROS are said to be under oxidative stress. ROS are generated inadvertently in the mitochondria of all cells concomitant with the synthesis of ATP. ROS arise due to oxygen that escapes complete reduction. Other in-vivo sources of ROS include inflammatory responses and detoxification processes. Cigarette smoking is an important cause of cancer  and it is well established that tobacco smoke contains thousands of chemicals and causes inflammation. It is also known that ROS are generated during the combustion of tobacco products [9–11]. Cancer risk associated with oxidative stress may be explained in that ROS can cause oxidative DNA damage that lead to mutations that lead to cancer.
The connection between environmental exposures like cigarette smoking and cancer may be better understood by characterizing the DNA damage involved in the carcinogenic process. Prior work in examining environmental sources of oxidative damage has generally focused on the 8-oxo-7,8-dihydroguanine [d(Gh)] lesion. Findings on cigarette smoke exposure have been decidedly mixed . Priemé and colleagues  reported a decrease of about 20% in d(Gh) among those quitting smoking up to 26 weeks. Lodovici et al.,  as well as Asami et al.,  reported a significantly lower mean value of d(Gh) in leukocyte DNA of non-smokers compared with smokers while Nia et al.,  and Van Zeeland et al.  reported a lower average value for d(Gh) in lymphocyte DNA of smokers compared with non-smokers. Lodovici et al.,  also demonstrated that d(Gh) was elevated in those exposed to secondhand smoke, similar to an earlier finding by Howard et al.  showing elevated levels in those occupationally exposed to SHS. However, Collier and colleagues  have shown that men and women differed in their oxidative damage levels due to SHS exposure, with a more prominent dose-response effect seen in men.
The current study sought to examine the extent to which these three DNA lesions would show measurable change upon cessation of smoking in a longitudinal fashion. Our study is notable in two respects: longitudinal measurements were a component of an on-going smoking cessation study and study subjects served as their own controls.
Blood samples were drawn with EDTA as anticoagulant, centrifuged, and the buffy coat collected. DNA was extracted from the cells using a kit designed to minimize spurious oxidation reactions (ZeptoMetrix, Inc., Buffalo, NY). The kit employs chaotropic precipitation of the DNA together with desferol in the extraction procedure. One hundred μg of DNA was hydrolyzed and dephosphorylated using nuclease P1 and alkaline phosphatase. A solution containing 15 μl sodium acetate buffer (0.25 M, pH 5.2), 50 μl 3.0 mM Zn Cl2, 50 μL water and 1.0 U nuclease P1 (Sigma N8630) together with the DNA and isotopically labeled internal standards was incubated at 37°C for 2 h at pH 5.2. After addition of 25 μl of Tris-HCl (1 M, pH 9.0) and 70 U of alkaline phosphatase, the sample was incubated for an additional 2 h at pH 8.2. Samples were analyzed using liquid chromatography tandem mass spectrometry (LC-MS/MS). The methodology and internal standards used for measuring oxidative DNA damage at the dimer level have been described previously [20–23].
Since the use of the d(PfpA) and d(TgpA) base modifications as measures of oxidatively generated DNA damage is relatively new, we examined repeatability of these measurements. Pairs of samples from the same participant were prepared and analyzed in parallel. The average values for the two set differed by 6% for the d(TgpA) modification (12 pairs; r = 0.89) and 5% for the d(PfpA) modification (36 pairs; r = 0.74).
To assure a 'clean' sample for assessment of cessation effects on levels of oxidative damage, analyses were limited to those who reported complete cessation and demonstrated CO-confirmed abstinence at 4 weeks and 11 weeks after TQD. The initial approach to analysis was descriptive (Pearson correlations, cross tabulations, t-tests) and focused on patient demographics and base modifications across subjects and weeks. Generalized estimating equations (GEE) were employed to examine the significance of change in biomarkers across time, accounting for the within-subjects dependence of measurements and adjusting for gender, treatment group (Active, Placebo) and age . The GEE models used a normal distribution with log link function, and an exchangeable working correlation matrix for the repeated measurement. Analyses were conduced using SPSS 16.0 (SPSS Inc., Chicago, IL).
Demographic and smoking behavior characteristics of the sample and interrelationships among measures at baseline
t-statistic and p-value for comparison on demographic variables
Pearson correlation and p-value between biomarkers and smoking variables
Cigarettes per Week
Carbon Monoxide (ppm)
Geometric mean thymine glycol (d(TgpA)), formamide (d(PfpA)) and 8-oxo-7,8-dihydroguanine (dGh) lesions (fmol/μg) by week, unadjusted and adjusted for age, gender, and treatment condition
Cigarette per week (SEM)
d(TgpA) fmol/μg (SEM)
d(PfpA) fmol/μg (SEM)
TQD - 4 weeks [baseline] (N = 19)
TQD [week 0] (N = 19)
TQD + 4 weeks [week 4] (N = 13)
TQD +11 [week 11] (N = 10)
Parameter estimates from GEE models for each modification (statistically significant beta weights highlighted in bold)
Wald χ2(df = 1)
Wald χ2(df = 1)
Wald χ2(df = 1)
TQD - 4 weeks [baseline]
TQD [week 0]
TQD + 4 weeks [week 4]
TQD +11 [week 11]
The findings from this study indicate that cigarette smoking appears to be related to oxidatively generated DNA damage, and that smoking cessation may reduce levels of oxidative damage between 30-50 percent in the short term (11 weeks following cessation). This study supports earlier findings [13, 14] that the d(Gh) lesion is associated with smoking, and also supports findings by Nia and colleagues  which reported decreases in d(Gh) after smoking cessation. This study also provides preliminary evidence that smoking may also contribute to formamide [d(PfpA)] DNA lesions, while evidence for a relationship between smoking and the thymine glycol [d(TgpA)] lesion was weaker. Carmella and colleagues  proposed that sensitivity to changes in smoking (e.g., cessation) within-subjects is a strong indicator of the utility of a biomarker, as it allows individuals to serve as their own controls, minimizing the potential role for individual differences in DNA repair or toxicant metabolism as possible explanations for observed variations. By this standard, d(Gh) and d(PfpA) may be promising biomarkers for future evaluation.
We are unable to explain the slight increase in levels of two biomarkers at the final measurement, despite controlling for CO-confirmed abstinence and self-reported cigarette use. One hypothesis is that these markers are sensitive to small exposures to cigarette smoke, including exposure to secondhand smoke (which was not measured) as well as other environmental exposures/sources. Indeed, other research has noted exposure to SHS as a potential source of oxidative damage in nonsmokers, [17, 18] so this remains a plausible explanation. Alternatively, it may reflect the normal range of variability in oxidative damage with an individual over time.
A difficulty associated with assessing oxidative DNA damage caused by a single mechanism, such as smoking, is that a substantial level of damage is always present. Further, other environmental and demographic factors, particularly age, gender and diet, may influence damage levels. The contribution of smoking to oxidative DNA damage must be assessed by the incremental change produced by the behavior relative to background levels. A significant advantage of the present study was the longitudinal assessment of DNA damage among a group of smokers who participated in a smoking cessation trial; with this design individuals served as their own controls. However, this study also had weaknesses, including a small sample size, examination of only three DNA modifications, and lack of data regarding other sources of oxidative stress. For example, smoking appears to influence forms of oxidative stress beyond oxidatively induced DNA damage, such as lipid peroxidation . Recent papers have used other approaches and markers of oxidative stress related to cigarette smoking in addition to d(Gh), including isoprostanes, hydroxyeicosatetraenoic acid products (HETEs), and advanced glycation end-products [27–29]. Future research should look to examine the contribution of smoking to oxidative stress in a broader context, including additional markers, other sources of damage, and individual DNA repair capacity.
Overall, results from this analysis suggest that cigarette smoking contributes to the burden of oxidative DNA damage in smokers, but that the level of such DNA modifications may be reduced by stopping smoking. Future research may shed light on the broader array of oxidative damage influenced by smoking, to provide further insights into mechanisms underlying carcinogenesis.
formamide breakdown product of pyrimidine bases
glycol modification of thymine
Generalized estimating equations
liquid chromatography tandem mass spectrometry
Target quit day
These activities were primarily supported by National Cancer Institute contract HHSN261200644002 (Laboratory Assessment of Tobacco Use Behavior and Exposure to Toxins Among Users of New Tobacco Products Promoted to Reduce Harm; PI: Peter Shields, MD), by grant CA139513 from the National Cancer Institute (PI: Nathalie Zeitouni, MD), and partially supported by a 2008 Pfizer Global Research Award for Nicotine Dependence (PI: Martin C. Mahoney, MD, PhD). The work utilized RPCI shared mass spectrometry facilities supported by CA016056 (Cancer Center Support Grant; PI: Donald L Trump, MD). The funding entities were not involved in the collection or analysis of data, nor the decision to submit the manuscript for publication.
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