Effects of lifestyle on micronuclei frequency in human lymphocytes in Japanese hard-metal workers

Effects of lifestyle on micronuclei frequency in human lymphocytes in Japanese hard-metal workers

Preventive Medicine 48 (2009) 383–388 Contents lists available at ScienceDirect Preventive Medicine j o u r n a l h o m e p a g e : w w w. e l s ev ...

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Preventive Medicine 48 (2009) 383–388

Contents lists available at ScienceDirect

Preventive Medicine j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / y p m e d

Effects of lifestyle on micronuclei frequency in human lymphocytes in Japanese hard-metal workers Peixin Huang a,b, Bin Huang c, Huachun Weng b, Kunio Nakayama b, Kanehisa Morimoto b,⁎ a b c

Department of Toxicology, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, P.R. China Department of Social and Environmental Medicine, Osaka University Graduate School of Medicine, Yamada-Oka 2-2, Suita, Osaka 565-0871, Japan Center for Epidemiology and Biostatistics, Children's Hospital Medical Center, Cincinnati, OH 45229-3039, USA

a r t i c l e

i n f o

Available online 23 January 2009 Keywords: Lifestyle Micronuclei (MN) frequency Chromosome damage Lymphocytes

a b s t r a c t Objective. The risks of cardiovascular disease, cancer, and other major causes of mortality are largely attributable to lifestyle factors such as smoking, alcohol drinking, hours of working and sleeping, physical activity, diet, and stress. Earlier studies have suggested that an unhealthy lifestyle is also associated with increased lymphocyte sensitivity to mutagens, oxidative DNA damage level, and leukocyte DNA damage. In order to explore the genotoxicity of unhealthy lifestyle, we evaluated the effect of overall lifestyle as well as some individual lifestyle factors on micronuclei (MN) frequency in cultured human lymphocytes. Method. The study was conducted among 208 healthy adult (19 to 59 years) male Japanese hard-metal workers. The subjects were divided into groups according to their self-reported good, moderate, and poor lifestyles based on their responses to a questionnaire regarding eight health practices (cigarette smoking, alcohol consumption, sleeping hours, working hours, physical exercise, eating breakfast, balanced nutrition, and mental stress), the presence or absence of each of which was summed to obtain a health practice index (HPI: range 0–8). Peripheral blood was taken and the cytokinesis-block micronuclei (CBMN) assay was performed. Results. Total lifestyle quality as measured by the HPI was strongly negatively associated with MN frequency in cultured human lymphocytes (p b 0.01). Nutritional imbalance, lack of regular exercise (b2 times per week), insufficient sleep ( ≤ 6 h per day), and overtime working (≥ 9 h per day) each contributed significantly to higher MN frequency (all p b 0.05). In the smoker group, a significantly higher MN frequency was only found in heavy smokers (p b 0.05). On the other hand, mental stress, eating breakfast, and alcohol drinking had no effect on MN frequency. Conclusions. Taken together, these findings indicate that poor lifestyle habits significantly increase MN frequency in human lymphocytes. © 2009 Published by Elsevier Inc.

Introduction Unhealthy lifestyle factors such as cigarette smoking, excessive alcohol drinking, long working hours, less time sleeping, physical inactivity, obesogenic diet, and psychological stress have been shown to contribute to cardiovascular diseases, cancers, and other major causes of mortality in industrialized countries (Breslow and Enstrom, 1980; Willett, 2002; Mascie-Taylor and Karim, 2003; Johnson and Lipscomb, 2006; Metcalfe et al., 2007). Studies investigating underlying mechanisms of unhealthy lifestyle factors and disease have been attracting more and more attention. Considering the complexity of lifestyle, Breslow and Enstrom (1980) selected seven health practices (never smoking cigarettes, regular physical activity, moderate or no use of alcohol, 7–8 h sleep/day regularly, maintaining proper weight, eating breakfast, and not eating between meals) and calculated a ⁎ Corresponding author. E-mail address: [email protected] (K. Morimoto). 0091-7435/$ – see front matter © 2009 Published by Elsevier Inc. doi:10.1016/j.ypmed.2008.12.023

cumulative health practice score (range: 0–7) to evaluate the overall individual lifestyle. They found a significant inverse association of health practice score with age-adjusted mortality after 9.5 years of follow-up in California, USA. In Japan, Morimoto added mental stress as an eighth health practice, and developed another Health Practice Index (HPI) to summarize the overall lifestyle habits of individuals (Hirayama and Morimoto, 1990). The HPI was found to be associated with mortality and morbidity from cancers in Japan (Hirayama and Morimoto, 1990). Furthermore, HPI was significantly associated with DNA damage in human leukocytes (Lu et al., 2006), NK cell activity (Kusaka et al., 1992), mutagens in urine (Mure et al., 1996), and total IgE level (Shirakawa and Morimoto, 1991). It has been recognized that an increased frequency of chromosome breaks was an initial event in assessing oncogene risk, thus suggesting that these alterations may play a significant role in carcinogenesis (Tucker and Preston, 1996; Bonassi et al., 2000). Micronuclei (MN) appear in cytoplasm of daughter cells as small additional nuclei and contain whole chromosomes or acentromeric chromosome fragments,

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left behind during nuclear division. Higher MN frequency reflects chromosomal damage and may thus provide a marker for cancer risk (Hagmar et al., 1998; Bonassi et al., 2000) and cardiovascular disease (Andreassi and Botto, 2003). The measurement of MN in peripheral blood lymphocytes (PBL) by cytokinesis-block micronuclei (CBMN) is a well-established tool for evaluating chromosome breaks (Fenech et al., 1999; Fenech, 2005) and MN frequency in PBL was proved to be a predictive biomarker of cancer risk within a population of healthy subjects (Bonassi et al., 2007). A number of studies were designed to investigate the effects of lifestyle factors such as smoking (Bonassi et al., 2003; Minozzo et al., 2004), alcohol drinking (Ramirez and Saldanha, 2002; Ishikawa et al., 2007), nutritional factors (Kazimirova et al. 2006; Fenech et al., 2005) on MN frequency. Unlike these studies which focused on single lifestyle factors, the aim of the current study was to evaluate the effect of overall lifestyle as well as individual lifestyle factors on MN frequency in human lymphocytes in healthy populations. Materials and methods Study design and procedure This was a cross-sectional study that took place in a hard-metal factory (700 total employees, 81% male (mean (SEM) age 43.7(0.6) years) in Osaka, Japan. We deliberately chose to study hard-metal factory workers in order to allow for a higher incidence of poor lifestyle factors such as smoking. Some of the factory workers had the possibility of exposure to various metal dusts, including tungsten, titanium, cobalt, and carbon, however, there is a local ventilation system for their grinding machines in the factory, the concentrations of those metal dusts in air of workplaces were continued to be kept in very low concentrations (under the occupational exposure limits of the Japan Society for Occupational Health). These chemicals were measured every 6 months according to Japanese law for occupational health. Additionally, workers used protective equipment such as dust protective mask and protective gloves. On the other hand, there was no exposure to organic solvent in the workplaces. Therefore, an excessive exposure to genotoxic compounds in the workplace is unlikely. Because 81% workers were male and in order to avoid any possible effects of gender, we chose only male workers. All workers from the factory that met the following inclusion criteria were eligible for the study: (a) male; (b) between 19 and 59 years of age; (c) no obvious diseases or under medical treatment; and (d) able and willing to sign informed consent. The study was approved by the Ethics Committee of the Osaka University Medical School. Study recruitment began at the end of June 2005. After they agreed and provided informed consent, the study questionnaires concerning demographics and lifestyle factors were handed to them in the factory. The questionnaires were collected two weeks later and blood samples (5 ml) were taken while the study participants were receiving their annual health check-up at the factory clinic. As a result, 231 workers (mean (SEM) age 44.0 (0.7) years) were recruited (41% whole male workers in the factory); among them, 208 slides of the samples (90% of the whole samples) were successfully prepared for MN scoring. Cell cultures, slide preparation, and MN scoring were performed by persons who were blinded to personal information about the study participants.

about how many years they had been smoking, and the years since smoking cessation (for ex-smokers). Alcohol drinking habits were assessed by asking about drinking frequency and alcohol consumption per occasion. Eating breakfast habits were classified into almost eating everyday, and not/seldom eating. The physical exercise of the subjects was assessed by asking them about the frequency of doing physical exercise and the minutes they exercised per time. Nutritional balance was classified into three categories: eating a good balanced diet, eating a moderately balanced diet, or not eating a balanced diet, as self-evaluated by the participants. Eating a good balanced nutritional diet was defined as follows: subjects paid much attention to nutritional balance in their daily life; eat various vegetables and fruits, meat, and fish with a good (approximately eating no less than 300 g of various fresh vegetables and fruits, 300–400 g of rice or wheat as main food, 100–200 g of meat or fish per day) balance. Mental stress was also classified into three categories: feel excessive, mild, or slight stress by self-assessment. We assigned 1 point each to: (1) never smoking; (2) not drinking alcohol often; (3) eating breakfast almost every morning; (4) sleeping 7 or 8 h/day; (5) working 8 h or less per day; (6) undertaking physical activity at least twice a week; (7) eating a good or moderately balanced diet; and (8) maintaining a moderate or low level of mental stress; all other responses were assigned 0 points. We calculated the HPI by summing the points for each subject and defined good health practice as an HPI of 6–8 points, moderate health practice as an HPI of 4 or 5 points, and poor health practice as an HPI of 0–3 points. This method of classification has been verified to be useful for the evaluation of personal lifestyle among Japanese persons (Hagihara and Morimoto, 1991; Kusaka et al., 1992; Inoue et al., 1996; Morimoto et al., 2001). Lymphocyte culture and CBMN assay A 5-mL sample of blood was taken from each study participant via a peripheral vein between 8:30 AM and 10:30 AM, using coded heparinized vacuum tubes (VENOJECT(R) IIVP-H100, Terumo, Tokyo, Japan). Blood samples were placed in an ice box and underwent CBMN assay using 300 μL of blood within 4–6 h at the Osaka University Graduate School of Medicine. Whole blood cultures were then set up according to our standard culture protocol (Ogura et al., 1996). Briefly, whole blood (0.3 ml) was added to 4.7 ml of RPMI 1640 tissue culture medium containing 10% fetal bovine serum, 1% antibiotics, and 5% (w/v) phytohaemaglutinin (PHA). Cells were arrested from performing cytokinesis with cytochalasin-B (4.5 μg/ml, sigma) at 44 h and then were harvested at 72 h according to the CBMN standard protocol. The cells were

Health practice index (HPI) The same questionnaire used by Morimoto et al. (1993) was employed in this study. Subjects were asked about smoking status and were classified into smokers, which included current smokers (including those stopping smoking no more than one year), and exsmokers (stopping smoking more than one year) and non-smokers. Smokers were asked about the number of cigarettes smoked each day,

Fig. 1. Association of age and MN/C-MN frequencies (n = 208 male hard-metal workers in Osaka, Japan, July 2005). Data are presented as mean (SEM). ⁎ p b 0.05, ⁎⁎p b 0.01, comparison with next youngest 10-year age group by LSD method. MN: number of micronuclei per 1000 binucleated cells; C-MN: number of micronucleated cells per 1000 binucleated cells; LSD: least significant difference.

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each of the eight separate lifestyle factors. Study participants were divided into four age groups (20–29, 30–39, 40–49 and 50–59 years); three HPI groups according to their summary HPI score (good: 6–8; moderate: 4 or 5; poor: 0–3). One-way analyses of variance (ANOVA) were used to compare the C-MN and MN frequencies among these groups. Analyses of covariance (ANCOVA) with adjustment for age were also performed. All analyses were performed using SPSS version 10.0 (SPSS Inc. Chicago, Illinois). A 2-tailed p b 0.05 was considered statistically significant. Results

Fig. 2. Association of HPI and MN/C-MN frequencies (n = 208 male hard-metal workers in Osaka, Japan, July 2005). Data presented as mean (SEM). HPI groups: good (6–8), moderate (4 or 5), poor (0–3). ⁎p b 0.05, ⁎⁎p b 0.01, comparison with the good group by LSD method. HPI: Health Practice Index; MN: number of micronuclei per 1000 binucleated cells; C-MN: number of micronucleated cells per 1000 binucleated cells; LSD: least significant difference.

harvested and the slides for scoring MN were prepared and stained with Giemsa as described before (Ogura et al., 1996). The scoring criteria of MN and binucleated cells were based on that of Fenech et al. (2003). The scoring and calculating nuclear division index (NDI), which provides a measure of the proliferative status of the viable cell fraction, was according to Fenech (2007). Micronuclei were scored by one scorer and NDI were scored by the other scorer. The two frequently used endpoints in MN analysis (Bonassi et al., 2001) were used for all statistical analyses in the study: the number of micronucleated cells per 1000 binucleated cells (C-MN), and the number of micronuclei per 1000 binucleated cells (MN). Statistical methods Data were summarized as mean (SEM). The distributions of MN, CMN, age and HPI were assessed and considered to follow approximate Gaussian (normal) distributions (data not shown). Independent sample Student's t-tests were used to compare C-MN and MN frequencies between the groups of participants who had good/ somewhat good practice with those who had poor health practice on

Of the 208 participants in the study, the mean (SEM) MN frequency was 7.2 (0.3), and the mean C-MN frequency was 6.1 (0.2) per thousand binucleated lymphocytes. The mean age was 44.0 (0.7) years, the mean HPI score was 4.1 (0.6), and the mean NDI was 2.6 (0.1). Age and MN frequency Fig. 1 shows the mean MN and C-MN frequencies in each of the 10year age groups. One-way analyses of variance showed MN and C-MN frequencies increased with age (both p b 0.001). Subjects in their twenties had the lowest MN frequency (MN: 3.2 (0.5); C-MN: 3.1 (0.4)). There was a significant increase in MN and C-MN frequencies for participants in their forties compared to those in their thirties (MN p = 0.004; C-MN p = 0.002), and for those in their fifties compare to those in their forties (MN p = 0.014; C-MN p = 0.047). HPI and MN frequency Our data also suggested that the MN frequency in lymphocytes decreased with the total lifestyle index based on the HPI (Fig. 2). Compared to the poor lifestyle group, both the moderate (MN p = 0.046; C-MN p = 0.024) and good (MN p = 0.042; C-MN p = 0.009) groups had significantly lower MN frequencies. As MN and C-MN frequencies were shown above to increase with age, we also conducted ANCOVA, and the results showed MN/C-MN frequency of the moderate group (MN p = 0.048; C-MN p = 0.031) and the good group (MN p = 0.044; C-MN p = 0.014) were significantly lower than the poor lifestyle group after adjustment for the effect of age.

Table 1 Summary of statistical significance of MN/C-MN frequency (mean (SEM)) of good or somewhat good health practice group vs poor health practice group in the study in Osaka, Japan, July 2005 Total Smoking Alcohol drinking Nutritional balance⁎ Exercise⁎⁎ Sleeping hours⁎ Working hours⁎⁎ Mental stress Breakfast

Smokers Non-smokers Often No or moderate Poor Good or moderate No or seldom ≥2 times per week b7 h ≥7 h ≥9 h b9 h Excessive Slight or mild No eating Eating

n

Age

NDI

C-MN

208

44.0(0.7)

2.6(0.1)

6.1(0.2)

133 75 125 83 25 183 165 43 153 55 47 161 71 137 42 166

45.3(1.0) 41.7(1.9) 45.7(0.8) 41.4(1.1) 41.6(0.4) 44.2(0.3) 44.0(0.8) 44.0(1.5) 43.4(0.9) 44.9(1.0) 45.4(1.0) 43.4(0.8) 42.1(1.3) 45.0(1.0) 41.7(1.6) 44.5(0.8)

2.7(0.2) 2.4(0.2) 2.6(0.3) 2.5(0.1) 2.6(0.2) 2.6(0.1) 2.6(0.3) 2.4(0.2) 2.7(0.1) 2.4(0.3) 2.6(0.4) 2.5(0.2) 2.5(0.1) 2.7(0.3) 2.5(0.3) 2.7(0.2)

6.3(0.3) 5.9(0.4) 6.2(0.3) 6.0(0.4) 5.9(0.2) 7.8(0.9) 6.6(0.3) 4.6(0.4) 6.3(0.3) 5.6(0.4) 7.1(0.5) 5.8(0.2) 6.2(0.4) 6.1(0.3) 6.5(0.7) 6.0(0.3)

95% CI of the group difference for C-MN#

MN

(− 1.36, 1.27)NS

7.4(0.4) 6.8(0.5) 7.3(0.4) 7.0(0.5) 6.9(0.3) 9.2(1.1) 7.7(0.4) 5.1(0.5) 7.4(0.4) 6.5(0.4) 8.5(0.7) 6.9(0.3) 7.2(0.5) 7.1(0.4) 7.6(0.9) 7.1(0.3)

(− 0.77, 1.16)NS (− 3.36, − 0. 50)⁎ (0.86, 3.14)⁎⁎⁎ (0.03, 1.91)⁎ (0.51, 2.60)⁎⁎ (−0.64, 1.71)

NS

(−1.14, 2.95)NS

7.2(0.3)

95% CI of the group difference for MN# (− 1.14, 0.86)NS (− 0.88, 1.59)NS (− 4.17,− 0.52)⁎ (1.39, 3.75)⁎⁎⁎ (0.17, 2.51)⁎ (0.69, 3.37)⁎⁎ (−1.32, 1.22)NS (−0.86, 2.14)NS

MN: number of micronuclei per 1000 binucleated cells; C-MN: number of micronucleated cells per 1000 binucleated cells; NDI: nuclear division index; NS: no significant difference. # 95% confidence interval from the independent two sample t-test comparing good or somewhat good health practice group vs poor health practice group. ⁎ p b 0.05. ⁎⁎ p b 0.01. ⁎⁎⁎ p b 0.001.

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Table 2 Multiple regression analysis of association of lifestyle factors with MN/C-MN frequency of lymphocytes in 208 subjects in Osaka, Japan, July 2005 Factors Smoking Drinking Sleeping hours⁎ Mental stress Exercise⁎⁎ Breakfast Working time⁎⁎ Nutrition Balance⁎

MN

C-MN

Beta

Std. error

t

p value

Beta

Std. error

t

p value

− 0.698 − 0.174 − 1.288 0.724 − 2.315 0.142 − 2.194 − 2.304

0.63 0.615 0.618 0.641 0.727 0.748 0.682 0.916

− 1.11 − 0.28 − 2.08 1.13 − 3.18 0.19 − 3.22 − 2.51

0.27 0.78 0.04 0.26 0.00 0.85 0.00 0.01

− 0.488 − 0.053 − 0.829 0.532 − 1.812 0.104 − 1.77 − 1.884

0.495 0.484 0.486 0.504 0.572 0.588 0.536 0.72

− 0.99 − 0.11 − 1.71 1.06 − 3.17 0.18 − 3.30 − 2.62

0.33 0.91 0.09 0.29 0.00 0.86 0.00 0.01

This table shows results of multiple regression analysis. Categorical variables of eight health practices, including cigarette smoking, alcohol drinking, sleeping hours, mental stress status, regular exercise, eating breakfast, working hours, nutritional balance were used as independent variables in the analysis for total subjects. ⁎ p b 0.05. ⁎⁎ p b 0.01. MN: number of micronuclei per 1000 binucleated cells; C-MN: number of micronucleated cells per 1000 binucleated cells.

HPI and NDI The NDI is a useful parameter for comparing the mitogenic response of lymphocytes and cytostatic effects of agents examined in CBMN assay (Fenech 2007). In this study, Both ANOVA (p = 0.89) and linear regression analysis (p = 0.87) results showed that HPI was not significantly associated with NDI. Effect of individual lifestyle habits on MN and C-MN frequencies The relationships between NDI, MN and C-MN frequencies and each of the eight individual domains of the Health Practice Index were also examined. In these analyses, each individual HPI domain were classified into two groups, such as current smokers and ex-smokers were combined to smokers, and compared to non-smokers. Good and moderate nutritional balance group were combined and compared to poor nutritional balance group as shown in Table 1. Our results showed that NDI was not associated with any of individual HPI domain, while eating poor nutritional balanced diet, not regularly exercising (b2 times/week), inadequate sleeping time (≤6 h/day), and longer working time (≥9 h/day) were associated with significantly increased MN and C-MN frequencies. The twogroup comparisons on the other lifestyle habits, alcohol drinking, higher mental stress, and not eating breakfast, did not show significant difference in MN frequency. Multiple regression analysis was also conducted (Table 2). The results suggested that with adjustment of other HPI domain factors, regular exercise, working hours, and nutritional balance have significant effect on both MN and C-MN frequencies. Sleeping hours

Fig. 3. Association of cigarette smoking MN/C-MN frequencies (n = 208 male hardmetal workers in Osaka, Japan, July 2005). Data presented as mean (SEM). MN and CMN frequencies of nonsmokers and smokers grouped by pack-years. ⁎p b 0.05, significantly different from nonsmokers by LSD method. MN: number of micronuclei per 1000 binucleated cells; C-MN: number of micronucleated cells per 1000 binucleated cells; LSD: least significant difference.

has significant effect on MN frequency only. The results from the multivariable regression analyses are consistent with the results from separate analyses on each of the eight lifestyle factors. The relationship between tobacco consumption in pack-years and MN frequency is useful for studying dose-response associations (Prignot, 1987; Klein et al., 1998). Thus, we further classified the subjects into non-smokers (0 pack-years), light smokers (0 b packyears ≤ 20), heavy smokers (20 b pack-years ≤ 40), and very heavy smokers (pack-years N 40) as done by Marrero et al (2005). The corresponding results suggested that there was a graded increase in MN and C-MN frequencies with increased exposure to smoking (Fig. 3). Heavy smokers had significantly higher MN/C-MN frequency compared to non-smokers (MN p = 0.041; C-MN p = 0.047) and light smokers (MN p = 0.044; C-MN p = 0.057). Using ANCOVA, the results suggested that heavy smoking significantly increased MN (p = 0.043) and C-MN (p = 0.046) frequencies compared to non-smokers after age adjustment. Discussion For most diseases contributing importantly to mortality in Western populations, lifestyle factors have been shown to have high attributable risks, often at least 80 or 90% (Willett, 2002). Previous studies have demonstrated that poorer lifestyle as a whole could increase lymphocyte sensitivity to mutagens (Morimoto et al. 1993), oxidative DNA damage levels (Irie et al., 2005), and leukocyte DNA damage by comet assay (Lu et al., 2006). Consistent with the previous literature, this study provides further clear evidence that both unhealthy lifestyle as a whole and certain individual lifestyle factors increased the baseline MN frequency in lymphocytes, a marker of risk for cancer (Tucker and Preston, 1996) and cardiovascular disease (Andreassi and Botto, 2003). In 208 workers studied, the mean C-MN and MN frequencies were 6.1 and 7.2 per thousand binucleated lymphocytes. Aging in humans appears to be associated with genetic instability. An age-related decline of efficiency in repair processes and accumulation of mutations due to adverse endo- and exogenous conditions result in increased level of DNA damage, and reflected by an increased frequency of chromosomal aberrations at the cytogenetic level. Numerous reports have shown a significantly increased MN (Hedner et al., 1982; Bender et al., 1988; Bonassi et al., 1995), in particular for chromosome loss (Wojda and Witt, 2003) in peripheral blood lymphocytes in both men and women of advanced age. Consistent with these studies, our data showed age positively associated with MN frequency, indicating strongly that the studies on micronuclei frequency in human PBL must take into account the potential confounding effect of age. The mean HPI score of these study subjects was 4.1 (0.6). Although we found a decreasing trend of HPI score with age, linear regression analysis showed no significant association between HPI and age (data not shown). Furthermore, ANCOVA results showed

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MN/C-MN frequencies of the moderate lifestyle and the good lifestyle groups were significantly lower than the poor lifestyle group after adjusted for the effect of age. Above results suggested that association of HPI with MN frequency we observed in the study was not cofounded by the age. Previous study results on the effects of smoking on MN frequency have varied greatly. Despite a few reports showing positive results (Cruz et al., 1994; Boeck et al., 2000; Giorgio et al., 1994; Sorsa et al., 1988), the large majority of studies did not find any association between MN frequency and smoking habit (Chang et al., 1997; Bolognesi et al., 1997; Bukvic et al., 1998; Burgaz et al., 1999; Hessel et al., 2001). We noticed that Bonassi et al (2003) found a higher MN frequency only in a subgroup of smokers (N30 cigarettes/day) than non-smokers in a meta-analysis of data from the large HUMN database that was assembled from laboratories in many countries. In this study, we examined the effect of smoking in different ways. Our data showed no significant difference in baseline MN frequency among current smokers, ex-smokers and non-smokers (data not shown). Smoking cessation could decrease the cancer risk to some extent, but even after 10 years since cessation, ex-smokers still have a two fold increased cancer risk as compared to never smokers (Bosetti et al., 2006; Weijenberg et al., 2008). Therefore, we combined current smokers (n = 112) and ex-smokers (n = 21) and compared them with non-smokers, some suggestive but non-statistically increases in MN frequency were observed in smokers (Table 1). However, when considering pack-years, the significances between these subgroups were found (Fig. 3). The significantly higher MN and C-MN frequencies were only found in heavy smokers, suggesting that the smaller portion of heavy smokers (23% of subjects) in the study may be the reason why we could not find obvious differences between smokers and non-smokers in Table 1. Because cigarette smoking is a complex behavior, better measurement of cigarette smoking exposure is needed to better study the association between smoking and chromosome damage. Furthermore, smoking may induce apoptosis more than micronuclei, and the deficiency of MN in the very heavy smokers might be explained by the fact that micronucleated cells are preferentially eliminated by apoptosis (Fig. 3). In fact, some studies have shown smoking greatly decreased NK cell numbers in peripheral blood lymphocytes (Li et al., 2007), and smoking (i.e. nicotine) induces apoptosis in human lymphocytes by enhancing expression of Fas (CD95) death receptor (Suzuki et al., 1999), increases apoptotic T cells by decreasing Bcl-2 and IL-7 receptor expression (Hodge et al., 2005). Smoking also induces apoptosis in rat terminal bronchiole through the p53/Bax and JNK/FasL cascade pathway (Wu et al., 2006). Moreover, inhibition of apoptosis has been demonstrated to increase the proportion of micronucleated cells (Kirsch-Volders and Fenech, 2001). Therefore, it is possible that the genotoxic effects of smoke could be better assessed by scoring not only micronucleated cells, but also apoptotic and necrotic cells, using CBMN cytome assay (Fenech, 2007). Physical inactivity and obesogenic diet were the second leading causes of mortality in the United States in 2000 (Mokdad et al., 2000). We found that these two poor habits also increased MN frequency. Eating a nutritionally balanced diet and performing regular exercise could up-regulate endogenous antioxidant defense and repair systems, and therefore lead to less chromosome damage. In this study, people paying much/more attention to nutritional balance in their daily life, eating more fresh vegetables/fruits, and some fish or other animal meat per day were thought to intake necessary nutrients basically sufficient and balanced, and our results clearly showed a lower MN frequency in these workers than the others. This is consistent with earlier reports; for example, Fenech et al. (2005) demonstrated that low intake of calcium, folate, nicotinic acid, vitamin E, retinol, beta-carotene increased genome instability. But as a limit in this study, we could not investigate the associations of certain nutrients (i.e. vitamins, folate, and calcium) and MN frequency

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because we defined nutritional balance as self-evaluation and did not assess blood status of nutrients quantitatively. Besides lifestyle characteristics, genetic variants could interact host factors (gender, age) and diseases (cancer, coronary artery disease), and as a consequence could affect MN frequencies in humans. For example, A recent pooled analysis by Kirsch-Volders et al. (2006) indicated that the GSTT1 genotype influenced MN frequencies in an age-dependent way. Lower MN frequencies were found in GSTT1-null subjects aged 20, and higher MN frequencies in GSTT1-null subjects aged 60, when compared with GSTT1-positive genotypes. Higher MN frequencies were also consistently reported for ALDH2-deficient habitual drinkers (Ishikawa et al., 2003, 2007) and for GSTM1-null smokers (Palma et al. 2007; Masetti et al., 2003). This study has some limitations. Our study sample did not include any heavy alcohol drinkers because most of them drink small amount of alcohol (one or two cups/glasses of wine/beer) in one session, so we were not able to evaluate the effects of heavy drinking, or effects of the extent to which they drank in one session on MN frequency. Our questionnaires investigating breakfast as eating or not, without the data of breakfast nutritional quality, may cause false negative results in association of breakfast with MN frequency. Furthermore, mental stress was investigated by self-perception, not by any psychological stress biomarkers (e.g. salivary cortisol). That may not accurately reflect the true level of mental stress. Despite these limitations, the results of this study have identified associations between overall and individual lifestyle habits and genome stability in human lymphocytes and further support the importance of maintaining a balanced lifestyle for preventing cancer and other diseases. Role of funding source The study was supported by the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT to support the project). The sponsors did not involve in the study plan and procedure. Conflict of interest statement The authors declare that there are no conflicts of interest.

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