Mutagenesis Advance Access published online on June 27, 2008
Mutagenesis, doi:10.1093/mutage/gen034
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Exposure level to cigarette tar or nicotine is associated with leukocyte DNA damage in male Japanese smokers
Department of Social and Environmental Medicine, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Osaka 565-0871, Japan
We investigated the number of cigarettes smoked daily, years of smoking, cigarette pack-years, levels of daily exposure to cigarette tar (LECT, mg/day) or nicotine (LECN, mg/day) in 53 male Japanese smokers using a questionnaire and measured each participant's baseline leukocyte DNA damage using the alkaline comet assay. The results showed that the baseline value of peripheral leukocyte DNA strand breaks was significantly associated with LECT (P < 0.05), LECN (P < 0.05), years of smoking or cigarette pack-years (P < 0.05) but not with the number of cigarettes smoked per day. Stepwise multiple regression analyses of factors including age, occupation, years of employment, alcohol drinking behaviour, physical activity, nutritional balance and cigarette smoking parameters showed that LECT was a positively significant predictor (Partial r = 0.0005, P < 0.05) of the comet tail moment. In consideration of the high correlation between LECT and LECN (Ytar = 12.53 Xnicotine –7.23, r = 0.995, P < 0.0001), these results suggest that levels of exposure to cigarette tar or nicotine (mg/day) would be a sensitive parameter in appreciation of genotoxicity of cigarette smoking in these male Japanese smokers.
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Introduction |
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In 1985, Nakayama et al. (1
) reported that cigarette smoke could induce DNA single-strand breaks in cultured human cells as assessed by an alkaline elution assay. After the development of the alkaline single-cell gel electrophoresis assay (comet assay) by Singh et al. in 1988 (2), many scientists used this technique to assess the influence of cigarette smoking on DNA in human peripheral blood leukocytes or lymphocytes (3). However, results varied greatly. Some studies suggested that cigarette smoking could induce DNA strand breaks in human leukocytes or lymphocytes (4–6) while others did not (7–11). We reviewed the published literature and noticed that previous investigators have traditionally categorized their subjects into smokers and non-smokers and generally focused on the number of cigarettes smoked per day or years of smoking but paid little attention to the tar or nicotine content of cigarettes.
In the present study, we investigated lifestyles including the number of cigarettes smoked per day, years of smoking and tar or nicotine content of cigarettes; we estimated the levels of daily exposure to cigarette tar (LECT) or nicotine (LECN) in a group of male Japanese smokers and we measured the baseline level of DNA strand breaks in the subjects’ peripheral blood leukocytes. The results show that LECT, LECN, cigarette pack-years and years of smoking correlate significantly with the level of DNA strand breaks as assessed by the alkaline comet assay. In contrast, the number of cigarettes smoked per day do not show a statistical relationship with the level of DNA strand breaks.
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Materials and methods |
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Subjects
This study was approved by the Ethics Committee of the Osaka University, and informed consent was obtained from each subject. We recruited 53 smokers from a hard-metal factory in Osaka, Japan using the following inclusion criteria: (i) male, (ii) smoker, (iii) between 20 and 60 years of age, (iv) no obvious diseases or under medical treatment and (v) able and willing to give informed consent. Employees were categorized into two main groups, one being office staff or technicians and the other being manufacturing workers. The manufacturing work was hard-metal tooling processing that was physically laborious relative to the work of the office staff and technicians. All subjects included in our study had no obvious history of occupational exposure to any toxic substances.
Estimation of the levels of exposure to cigarette tar or nicotine
Questionnaires on cigarette smoking, alcohol drinking, physical activity, nutritional balance, medication, mental stress, sleeping hour, age and occupation (office and technical work or manufacturing work) were distributed at the end of June 2006 and were collected before taking blood samples in early July 2006. The following data were extracted from the questionnaires: (i) number of cigarettes smoked per day, (ii) brand of cigarette currently consumed, (iii) tar and nicotine contents per cigarette (as marked on the cigarette packet) and (iv) years of smoking. Questions on demographic background, strenuous physical activity in the previous 3 days and cigarette smoking before taking blood samples were also included in the questionnaire.
The estimated level of exposure to cigarette tar per day was calculated as the ‘LECT (mg/day) = number of cigarettes smoked per day x milligram of tar per cigarette’. The estimated level of exposure to cigarette nicotine per day was calculated as the ‘LECN (mg/day) = number of cigarettes smoked per day x milligram of nicotine per cigarette’.
Blood sampling
A 5-ml blood sample was taken from fasting subjects via a peripheral vein between 8:30 and 10:30 in the morning using coded heparinized vacuum tubes (VENOJECT®II VP-H100, Terumo, Tokyo, Japan). Blood samples were placed on ice, taken to the laboratory within 3 h and kept in a 4°C refrigerator until use. All 53 samples were analysed by the alkaline comet assay within 60 h (12) at Osaka University Graduate School of Medicine.
Alkaline comet assay
All steps were performed in the dark or under a fluorescent lamp to filter out UV radiation that will further damage DNA. The alkaline comet assay was performed as described elsewhere (13). Briefly, the frosted side of 76 x 26 mm fully frosted glass slides (Matsunami, Osaka, Japan) was pre-coated with 20 µl 0.75% normal melting agarose (Sigma-Aldrich, Tokyo, Japan) in phosphate-buffered saline (PBS) (pH 6.8), and the slides were then dried. Before loading the blood samples, we sealed the dried gel sides of the pre-coated glass slides with an eight-well CoverWellTM perfusion chamber (Funakoshi, Tokyo, Japan). For each sample, we gently mixed 5 µl whole blood with 145 µl of 0.75% low-melting agarose (Cambrex Bio Science, Rockland, ME, USA) in PBS (pH 6.8) and sandwiched the cell suspension layer (20 µl) between the pre-loaded gel and another layer (20 µl) of 0.75% low-melting agarose. After solidifying the gel and gently removing the perfusion chamber, we denatured the DNA in electrophoresis buffer (pH > 13.0) for 20 min at 4°C as described by Singh et al. (2). Electrophoresis was performed for 20 min at 25 V (0.8 V/cm) and 350 mA using an electrophoresis compact power supply (ATTO Corporation, Tokyo, Japan). Following electrophoresis, the slides were neutralized with two 5-min washes in 0.4 M Tris–HCl (pH 7.4), fixed in 99.9% ethanol for 10 min and stored in the dark at room temperature until use. We quantified DNA damage of 100–120 consecutively selected leukocytes after staining with 2 µg/ml ethidium bromide for 1 min using a DHS-SCG imaging system (Keio Electronic Imaging, Osaka, Japan) attached to a fluorescent microscope (Olympus, Tokyo, Japan). We used the comet tail moment, comet ratio and DNA migration (14) to evaluate the degree of DNA strand breaks in all subjects.
During data analysis, we calculated averages of comet assay parameters for each of the sampling days and for the total. The final 53 data were adjusted according to the difference between the total and each-day average of comet parameters. Comet assay and data analysis were conducted double blindly by a skilled technician. Untreated HL60 cells and those treated with 0.5 µM bleomycin for 10 min at 4°C were included as negative and positive controls, respectively, in the assay.
Statistical analysis
We used the Pearson's correlation test, the Spearman's correlation test, Kruskal–Wallis test, a multiple regression analysis, the odds ratio (OR) and 95% confidence interval (CI) for statistical analysis using the SPSS version 13.0 software (SPSS, Chicago, IL, USA). The level of statistical significance was set at P < 0.05. The Kolmogorov–Smirnov test was used to test for normal distributions. All statistical tests were two sided.
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Results |
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Contents of cigarette tar or nicotine in different brands of cigarettes
Table I summarizes all the cigarette brands reported to be consumed by subjects. The data show that tar content of the cigarette brands varied from 1 to 28 mg per cigarette. Nicotine content varied from 0.1 to 2.3 mg per cigarette. Cigarette tar content was significantly correlated with nicotine content (Ytar = 12.53 Xnicotine –7.23, r = 0.995, P < 0.0001, Pearson's correlation).
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Cigarette brands and smoker profiles
Table II summarizes the association of the cigarette brands and the profiles of the subjects. Of the 53 smokers, 16 persons (30.2%) smoked brand A cigarette that contained 1 mg tar per cigarette. Twenty-six persons (49.0%) smoked brand B through G cigarettes containing 3–9 mg tar per cigarette and 11 persons (20.8%) smoked brand H through K cigarettes that contained 10–28 mg tar per cigarette. Among all the profiles examined, LECT or LECN varied significantly among cigarette brands (both, P < 0.0001, Kruskal–Wallis test).
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Correlations between cigarette smoking and comet assay parameters
Table III shows that LECT was significantly associated with comet tail moment (r = 0.320, P < 0.05) and comet ratio (r = 0.317, P < 0.05); LECN was also significantly associated with comet tail moment (r = 0.313, P < 0.05) and comet ratio (r = 0.313, P < 0.05). In contrast, cigarette pack-years (r = 0.344, P < 0.05) and years of smoking (r = 0.308, P < 0.05) were significantly associated with DNA migration, but the number of cigarettes smoked per day failed to show a statistical correlation with the comet assay parameters of peripheral blood leukocytes.
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LECT, LECN and comet parameters of subjects
Table IV shows the data of LECT, LECN and comet assay parameters for each subject. We divided subjects into quartiles according to LECT and compared comet assay parameters between the first quartile and the rest. Results showed that comet tail moment or comet ratio in the fourth quartile was significantly higher than that in the first quartile (P < 0.05, Student's t-test).
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We categorized the comet assay parameters into two parts at 50 percentile (the cut-off point for tail moment was 1.09; for comet ratio it was 43.57 and for DNA migration it was 27.50) and calculated OR and 95% CIs for each quartile of comet assay parameters. Results showed that the more the subjects were exposed to cigarette tar daily, the more they fell into the upper 50% of comet assay parameters. Among them, the highest OR is 20.50 for the fourth quartile of tail moment with 95% CIs from 2.11 to 240.48 (P < 0.01).
Multiple regression analyses of lifestyle factors and comet tail moment
Table V shows that when age, number of cigarettes smoked per day, years of smoking, cigarette pack-years, LECT, LECN, alcohol drinking frequency (times per month), occupation (office, technical work or manufacturing work), years of employment, physical activity habit (five categories from almost every day to almost no activity) and nutritional balance were taken into account to predict the comet tail moment, then LECT, alcohol drinking frequency and occupation were significant predictors. Of these three predictors, only LECT showed a positive association with comet tail moment (partial r = 0.0005, P < 0.05). Both alcohol drinking frequency and occupation showed a negative association with comet tail moment.
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Discussion |
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TopIntroductionMaterials and methodsResultsDiscussionFundingReferences |
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In the present study, we demonstrated for the first time that the estimated LECT or LECN was significantly associated with the level of peripheral blood leukocyte DNA strand breaks in male Japanese smokers as assessed by the alkaline comet assay. From stepwise multiple linear regression analysis, LECT was shown to be a positive predictor for comet tail moment.
Based on our survey, tar contents varied from 1 mg (including 0.1 mg nicotine) to 28 mg (including 2.3 mg nicotine) per cigarette. As about one-third of smokers reported consuming low-tar (1 mg per cigarette) cigarettes and one-fifth high-tar (10–28 mg per cigarette) ones (Table II), we speculated that LECT could be a valuable parameter to represent levels of exposure to cigarette smoking.
DNA strand breaks induced by cigarette smoking mainly result from the effects of free radicals in smoke (1), which include gas-phase free radicals and particulate (or tar) ones. The half-life of gas-phase free radicals is too short to reach the cell nucleus while the particulate (or tar) free radicals are stable and can easily pass through the cell membrane, therefore adducting to and producing nicks in the DNA (15–18). Thus, we suggest that the level of exposure to cigarette tar might be, at least partially, responsible for DNA strand breaks as assessed by the alkaline comet assay.
DNA strand breaks are reportedly induced by compounds like polycyclic aromatic hydrocarbons, benzene, phenols (19–22), etc. in cigarette smoke. However, some chemicals like formaldehyde and acetaldehyde could cross-link the DNA fragments among DNA strands or to proteins (23), which is proved to hinder the migration of DNA fragments during electrophoresis in comet assay (24). Thus, the influence of different components of cigarette smoke on the comet assay parameters may be complex.
In the present study, some smoking parameters showed an association with some of the comet assay parameters. It is not clear why LECT and LECN are associated with tail moment and comet ratio but not with DNA migration. Because we only studied a group of smokers, we cannot say whether smoking actually induced DNA effects in our study group in comparison with non-smokers. We did not find a significant difference in tail moment between the 30.2% low-tar smokers and the 20.8% high-tar smokers. However, we found that the tail moment and the comet ratio in the fourth quartile of LECT were significantly higher than those in the first quartile of LECT. While LECT showed a positive association with the comet tail moment and alcohol drinking and occupation showed a negative association with the comet tail moment. These findings cannot be explained at present and their biological significance remains unclear.
In the present study, blood samples were kept at 4°C for an average of 
30 h (range 5–60 h). As the single-strand breaks induced by cigarette smoke might be repaired instantly, the DNA strand breaks we detected should be the background levels derived from DNA adducts, apurinic or apyrimidinic sites, uncompleted DNA repair of complicated DNA damage and oxidative stress derived from chronic inflammation in respiratory system associated with long-term exposure to cigarette smoke (25–27). We investigated the cigarette smoking habits and physical activities of all subjects prior to blood sampling but did not find a significant influence of these recent events on the comet assay parameters measured (data not shown).
As the blood samples were kept at 4°C from 5 h up to nearly 60 h, we suggest that the storage time could be an additive factor influencing comet assay results. Although Anderson et al. (12) reported that blood samples could be kept at 4°C or room temperature up to 4 days without significant influence on comet assay results, we noticed that the storage time of the blood samples from cigarette smokers increased variability of comet assay results (data not shown). Although we modified the comet parameters by dates, it is still beyond our knowledge if storage time could exaggerate the difference in comet parameters among subjects exposed to different levels of cigarette tar.
Because of the small sample size, confounding lifestyle factors and the characteristics of the comet assay itself, we cannot completely exclude the possibility of chance in our findings. Nevertheless, the data would suggest that further investigations on the appreciation and application of the levels of exposure to cigarette tar (LECT) in smoking-related epidemiological studies are warranted.
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Funding |
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Japan Society for the Promotion of Science (17590513).
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Acknowledgments |
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We would like to thank the volunteers for their enthusiastic participation, the Association for Preventive Medicine of Japan for their assistance in collecting the blood samples and Dr Kunio Nakayama for his help with the lifestyle investigations.
Conflict of interest statement: None declared.
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Notes |
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* To whom correspondence should be addressed. Tel: +81 6 6879 3920; Fax: +81 6 6879 3923; Email: morimoto{at}envi.med.osaka-u.ac.jp
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Received on February 17, 2008; revised on May 19, 2008; accepted on May 19, 2008.
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