DNA strand breaks in peripheral blood leucocytes of Polish blood donors

DNA strand breaks in peripheral blood leucocytes of Polish blood donors Abstract Knowledge about the basal level of DNA damage in leucocytes of healthy control populations is essential before estimation of the effects of exposure to external agents in biomonitoring studies. The aim of this study was to analyse the effects of some lifestyle factors on baseline DNA damage in leucocytes of humans. The material consisted of the peripheral blood from 276 healthy volunteer blood donors. In addition to the standard blood donation questionnaire, they were asked about age, gender, occupation, radiological history, smoking habit, alcohol consumption, medicine use and pet ownership. The results showed marked intra-individual variability. Significant differences in DNA damage levels were observed between individuals in different age and sex groups, between smokers and non-smokers and between samples taken in different seasons of the year, with the highest DNA damage in those obtained in the summer. Significantly higher levels of DNA damage were noted in leucocytes of donors older than 29 years, in men compared with women and in male smokers. Significantly higher DNA strand breaks were observed in heavy smokers. A non-significantly higher level of DNA damage was observed in individuals subjected to radiological investigation and in those drinking alcohol, whereas lower levels were observed in leucocytes of pet owners and in donors taking medicines. Pet ownership influences the level of DNA damage and there is an interaction between this effect and that of smoking. The smoker/pet owners showed almost half the level of DNA damage of smokers without pets. The current results confirmed high intra-individual variability between the levels of DNA damage of individuals. The significant factors that influence the DNA damage in leucocytes are age, sex and smoking habit, especially in men and in heavy smokers. The finding of reduced DNA damage in the leucocytes of pet owners suggests the tendency towards a beneficial effect of such company. Introduction The comet assay, also called single-cell gel electrophoresis assay, is used to detect DNA single- and double-strand breaks and kinetics of their repair. The alkaline method, developed by Singh et al. (1), allows the detection of DNA denaturation and alkali-label sites. DNA strand breaks in single cells are visualised by the increased migration of DNA segments. This helps in the estimation of intercellular disparity. The mechanism of formation of comets is best understood by analogy with nucleotides. The chromatin loops containing a break loose their supercoiling and became free to be pulled towards the anode under the electrophoresis field.(2) The comet assay is a sensitive, fast and relatively cheap method, so it is widely used. It is used among others for detection of the genotoxic exposure of different chemical and physical agents in different, including occupationally exposed populations. This method might be useful in comparative studies regarding the difference in sensitivity and repair capacity of healthy and ill persons. The comet assay was recommended as a marker of exposure to genotoxic agents, indicating early biological effects in human biomonitoring studies (3–7). In recent years, there have been numerous papers published where the comet assay has been used to assess DNA damage in different populations (8–13). DNA is susceptible to damage from different endogenous and exogenous sources. Such damage can cause cell death and eliminate potentially dangerous cells, or lead to either erroneous or correct DNA repair. Cells have repair systems that may delete or repair damage. Misrepaired damage may result in chromosomal damage or mutations, or cause acute adverse effects within hours to weeks or delayed effects within months to years after exposure. There are many agents that can cause DNA damage, such as chemical agents (14,15), environmental pollutants (16,17), ionising radiation (12,18), ultraviolet radiation (19,20), physical exercise (21,22) and diet (23,24). The level of DNA damage may be higher in older people (25) and in smokers (23,26). Moreover, DNA damage has been associated with a number of illnesses, for example infections (27), and with neurodegenerative disorders such as Parkinson’s and Alzheimer’s diseases (28,29). As there are few studies describing the basal level of DNA damage in white blood cells of healthy control populations, which is essential before the estimation of the effects of exposure to external agents in biomonitoring studies, we decided to investigate a large population of healthy blood donors in order to extend knowledge on this topic. The aim of the present study was to analyse the effects of some selected lifestyle factors on the baseline DNA damage in leucocytes of peripheral blood of humans. Although the majority of factors studied here have already been investigated, it is very important to study again confounding factors, for example smoking habit and age. Moreover, we have studied the effects of different kinds of radiological investigations and of taking different kinds of medicines. For the first time, we investigated the association between DNA damage in leucocytes and pet ownership. Materials and methods The study was performed in accordance with standards of ethics, with the authors having obtained the agreement of the Bioethical Commission on the conducting current research. Collection of samples All blood donors were volunteers entering the Blood Donation Unit in Warsaw. They were informed about the use of their blood also for scientific purpose and they agreed. Donors were also informed about the aim of the experiment and experimental details. All donors filled the standard questionnaire for blood donation designed to obtain relevant details and current health status and illness history. In addition, they were asked about employment, medicine use, pet ownership, smoking habit, alcohol consumption and radiological investigation within the past year. These factors were chosen with the consideration that they need to be easy to describe by donors. We did not ask about factors that would have needed an exact description, such as exercises and sun exposure, in order to avoid donors opting out for reason of excessive questionnaire length. All donors were healthy at the time of blood donation. Samples consisting of 1 ml of whole venous blood were collected from blood donors by venepuncture under sterile conditions, drawn into heparinised tubes and coded. Preparation of slides Whole blood was diluted in RPMI 1640 medium with l-glutamine in relation 1:10. The cells were checked for their viability using trypan blue dye. Then, diluted blood (50 µl) was mixed with 0.5% low melting point agarose (LMPA) and dropped on each of two microscope slides covered with normal melting point agarose. After solidifying the agarose at 4°C, another layer of LMPA was added and allowed to solidify at 4°C again. For further steps, the basic method described by Singh et al. (1) was used. The slides were immersed in freshly prepared cold lysing solution (2.5 M NaCl, 100 mM Na2EDTA, 10 mM Tris, pH 10, 1% sodium sarcosinate), with 1% Triton X-100 and 10% dimethylsulphoxide added just before use, overnight at 4°C. Electrophoresis After lysis, the slides were drained and placed in a horizontal gel electrophoresis tank side-by-side avoiding spaces. Freshly prepared and chilled electrophoresis solution (1 mM Na2EDTA and 300 mM NaOH, pH >13) was poured in the electrophoresis tank to a level ~0.25 cm above the slides. The slides were incubated in this solution for 20 min to allow DNA unwinding and expression of alkali labile sites as DNA breaks. Alkaline electrophoresis was conducted for 20 min at 4°C, 24 V (0.96 V/cm) and 300 mA. All these steps were performed under dimmed light to avoid additional DNA damage. The slides were then washed three times for 5 min with neutralising Tris buffer (0.4 M Tris, pH7.5) to neutralise excess alkali. Staining and slide scoring After neutralisation, the slides were stained with ethidium bromide. Slides were placed in a humidified airtight container to prevent drying of the gel and analysed within 3–4 h. Slides were examined using a fluorescence microscope. Images of 200 randomly selected leucocytes (100 cells from each of 2 replicate slides) were analysed from each donor. According to the procedure described earlier(30), cells were graded by eye into five categories based on the distance of migration and perceived proportion of DNA in the tail: (0) no damage, <5%; (A) low-level damage, 5–20%; (B) medium-level damage, 20–40%; (C) high-level damage 40–95%; (D) total damage, >95% and given a value 0, 1, 2, 3, 4 (from undamaged—0 to maximally damaged—4). The same person categorised DNA damage in all samples. To obtain a semi-quantitative analysis of the data, the score of DNA damage (the migration of DNA) was calculated as follows: percentage of cells with category A, plus percentage of cells with category Bx2, plus percentage of cells with category Cx3 and plus percentage of cell with category Dx4. The score may range from 0 (all undamaged) to 400 (all totally damaged). Statistical analysis Our data violated the normality test and equal variance test required for the parametric analysis of variance statistics. The non-parametric the Kruskal–Wallis test by ranks and the median test were used for multiple one factor analysis. Comparisons between groups were done using the Mann–Whitney U test as post-hoc test. P-values <0.05 were considered significant. In addition, multifactor analysis of variance was used to compare some factors. Similarly, P < 0.05 were considered significant. Results There were 276 samples collected from blood donors of mixed occupation (students, administrative employees, blue-collar workers, doctors, nurses, technicians, teachers, policemen and saleswomen from food department) aged from 18 to 58 years, including 118 females and 158 males. Among blue-collar workers, there were construction workers, electricians, painters, horticultural workers, laboratory workers, stockmen, mechanics and plumbers. Young persons prevailed among donors. The majority of them (165 persons, i.e. 55%) were aged from 18 to 29 years. Among them, there were 87 females and 78 males. Moreover, there were 45 persons (8 females and 37 males) aged from 30 to 39 years, 40 individuals (13 females and 27 males) aged from 40 to 49 years and 26 individuals (10 females and 16 males) older than 50 years (Table 1). Table 1. Demographic characteristic of donors   Total  Females  Males  Donors, n  276  118 (42.8%)  158 (57.2%)  Age (years) ± SD  30.2 ± 11.6  27.3 ± 11.2  32.3 ± 11.6  No 18- to 29-year-old donors  165  87  78  No 30- to 39-year-old donors  45  8  37  No 40- to 49-year-old donors  40  13  27  No 50+ donors  26  10  16    Total  Females  Males  Donors, n  276  118 (42.8%)  158 (57.2%)  Age (years) ± SD  30.2 ± 11.6  27.3 ± 11.2  32.3 ± 11.6  No 18- to 29-year-old donors  165  87  78  No 30- to 39-year-old donors  45  8  37  No 40- to 49-year-old donors  40  13  27  No 50+ donors  26  10  16  View Large The characteristics of donor groups are shown in Table 2. Among blood donors there were 45.6% of smokers and 54.4% of non-smokers, among men 49.7% and 50.3% and among women 41% and 59%, respectively. The majority of donors (75%) declared consumption of alcohol compared with 25% abstinence. Simultaneously, the majority of donors (70%) had taken medicines (antibiotics, pain killers, calmants, cardiac, sleep-inducing, antiallergic and hormonal) and had pets (dog, cat, parrot, hamster, rat, fishes, chinchilla, canary bird, turtle and guinea pig) at home (59%) within the past year. There were 60.5% donors with radiological history. Table 2. Characteristics of donor group with regard to investigated factors Number (Percent) of donors  Yes  No  Smoking habit  127 (46.0)  149 (54.0)  Female smokers/non-smokers  48 (41.0)  69 (58.9)  Male smokers/non-smokers  79 (49.7)  80 (93.3)  Alcohol consumption  207 (75.0)  69 (25.0)  Medicinal usage  213 (77.2)  63 (22.8)  Pets at home  163 (59.0)  113 (41.0)  Radiological investigations  167 (60.5)  109 (39.5)  Number (Percent) of donors  Yes  No  Smoking habit  127 (46.0)  149 (54.0)  Female smokers/non-smokers  48 (41.0)  69 (58.9)  Male smokers/non-smokers  79 (49.7)  80 (93.3)  Alcohol consumption  207 (75.0)  69 (25.0)  Medicinal usage  213 (77.2)  63 (22.8)  Pets at home  163 (59.0)  113 (41.0)  Radiological investigations  167 (60.5)  109 (39.5)  View Large Cell viability always exceeded 92%. The mean of scored DNA damage in peripheral blood leucocytes of investigated donors was 24.07 ± 22.36, with median 16.25; however, there was marked intra-individual variability (Figure 1). DNA damage varied between 0.5 in the blood of a 20-year-old female non-smoker student to 186 in the leucocytes of a 40-year-old male smoker employed as an electrician. The DNA damage levels in peripheral blood leucocytes in different subgroups of blood donors are shown in Table 3. Generally, the mean level of DNA damage was significantly lower in leucocytes from women (21.05 ± 20.74), when compared with men (26.12 ± 23.38). Considering the age groups, the results showed that DNA damage was higher in older groups compared with younger groups. The highest level of DNA damage was noted in the leucocytes of individuals aged from 40 to 49 years (mean 39.23 ± 35.40, median 33.75), whereas the lowest in the subgroup of the youngest donors aged from 18 to 29 years donors (mean 18.49 ± 14.90, median 13.00). DNA damage in the groups of donors aged 30–39, 40–49 and >50 years was significantly higher compared with the group of the youngest donors (P < 0.05 by Mann–Whitney U test). Higher levels of DNA damage were noted in the blood of smokers (mean 25.41 ± 25.06) than that of non-smokers (mean 19.84 ± 17.69). Such differences were higher in the peripheral blood leucocytes of men. DNA damage levels in male smokers were significantly higher (27.99 ± 26.10, with median value 22.00) compared with male non-smokers, where mean DNA damage was 21.38 ± 19.54 with median 16.00 (P < 0.05 by Mann–Whitney U test). The differences were much larger when smokers were divided into two subgroups: heavy smokers (over 20 cigarettes daily) and moderate smokers (1–17 cigarettes daily). There were no subjects declaring smoking 18 or 19 cigarettes daily. The mean level of DNA damage in the subgroup of heavy smokers was significantly higher (34.44 ± 24.12 with median 31.00) compared with the subgroup of moderate smokers (23.23 ± 25.51, with median 14.50) and non-smokers (P < 0.05 by Mann–Whitney U test). The level of DNA damage in the leucocytes of moderate smokers was not significantly higher compared with non-smokers. Subjecting to radiological investigation or consumption of alcohol induced slightly higher levels of DNA damage in white blood cells, 23.64 ± 21.93 vs. 19.10 ± 14.68 or 21.90 ± 21.51 vs. 19.71 ± 16.92, respectively. In turn, medicine use or pet ownership was associated with low levels of DNA damage, 21.57 ± 19,76 vs. 23.02 ± 15.92 or 19.37 ± 16.67 vs. 26.04 ± 26.60, respectively. Among radiological investigations, the highest level of DNA damage was induced by chest imaging in combination with other imaging (30.81 ± 33.59) and investigations of the hand, leg or vertebral column (27.00 ± 22.32), whereas the lowest levels of damage were induced by teeth or sinuses imaging (17.90 ± 10.64). The above results were not statistically significant compared with the leucocytes of subjects without radiological investigations. In the case of medicine use, the lowest level of DNA damage was induced by antiallergic (15.04 ± 9.41) and hormonal (18.13 ± 23.50) medicines, but only the results of the last subgroup were significantly different compared with the blood of subjects not having used medicines by Mann–Whitney U test. The level of DNA damage was similar in subgroups owing different pets. Fig. 1. View largeDownload slide Mean DNA migration in individual blood samples Fig. 1. View largeDownload slide Mean DNA migration in individual blood samples Table 3. DNA damage in different subgroups of blood donors Name of subgroup  Individuals (n)  Comet score mean ± SD, median  Total  276  24.07 ± 22.36, 16.25  Women  118  21.05 ± 20.74, 12.50  Men  158  26.12 ± 23.38,a 19.50  18–29 years old  165  18.49 ± 14.90, 13.00  30–39 years old  45  29.23 ± 20.60,b 24.00  40–49 years old  40  39.23 ± 35.40,b 33.75  Over 50 years old  26  32.81 ± 26.65,b 31.00  Smokers  127  25.41 ± 25.06, 16.00  Non-smokers  149  19.84 ± 17.69, 15.25  Men smokers  78  27.92 ± 26.10,c 22.00  Men non-smokers  80  21.38 ± 19.54, 16.00  Women smokers  49  20.88 ± 23.73, 10.50  Women non-smokers  69  17.29 ± 14.30, 12.50  Heavy smokers  33  34.44 ± 24.12,d, e 31.00  Moderate smokers  94  23.23 ± 25.51, 14.50  Non-smokers  149  19.84 ± 17.69, 15.25  Radiological investigation (+)  167  23.64 ± 21.93, 16.00   Chest only  63  21.57 ± 18.86, 15.50   Chest + other  21  30.81 ± 33.59, 15.50   Teeth or sinuses  24  17.90 ± 10.64, 16.50   Hand, leg or vertebral  column  23  27.00 ± 22.32, 18.25   Three different or more  20  22.65 ± 26.88, 11.75  Radiological investigation (−)  109  19.10 ± 14.68, 14.25  Pets (+)  163  19.37 ± 16.67, 13.50   Cat  29  18.21 ± 14.21, 13.00   Dog  67  18.21 ± 16.28, 13.00   Others  29  17.12 ± 14.56, 11.00   Cat + dog  38  19.96 ± 15.74, 15.50  Pets (−)  113  26.04 ± 26.60, 17.50  Alcohol (+)  207  21.90 ± 21.51, 15.50  Alcohol (−)  69  19.71 ± 16.92, 11.50  Medicines (+)  233  21.57 ± 19.76, 15.00   Antibiotics only  14  19.38 ± 14.36, 15.75   antibiotics + painkillers  41  22.62 ± 21.71, 16.00   Pain killers only  55  20.15 ± 20.98, 12.00   Pain killers + others  26  22.15 ± 19.59, 15.00   Three or more different  27  21.68 ± 22.93, 16.75   Antiallergic  28  15.04 ± 9.41, 12.50   Hormonal  28  18.13 ± 23.50, 9.00f  Medicines (−)  43  23.02 ± 15.92, 19.50  Summer  63  38.82 ± 29.07, 35.00g  Autumn  95  30.54 ± 19.83, 24.00g  Winter  120  10.24 ± 7.22, 9.00g  Name of subgroup  Individuals (n)  Comet score mean ± SD, median  Total  276  24.07 ± 22.36, 16.25  Women  118  21.05 ± 20.74, 12.50  Men  158  26.12 ± 23.38,a 19.50  18–29 years old  165  18.49 ± 14.90, 13.00  30–39 years old  45  29.23 ± 20.60,b 24.00  40–49 years old  40  39.23 ± 35.40,b 33.75  Over 50 years old  26  32.81 ± 26.65,b 31.00  Smokers  127  25.41 ± 25.06, 16.00  Non-smokers  149  19.84 ± 17.69, 15.25  Men smokers  78  27.92 ± 26.10,c 22.00  Men non-smokers  80  21.38 ± 19.54, 16.00  Women smokers  49  20.88 ± 23.73, 10.50  Women non-smokers  69  17.29 ± 14.30, 12.50  Heavy smokers  33  34.44 ± 24.12,d, e 31.00  Moderate smokers  94  23.23 ± 25.51, 14.50  Non-smokers  149  19.84 ± 17.69, 15.25  Radiological investigation (+)  167  23.64 ± 21.93, 16.00   Chest only  63  21.57 ± 18.86, 15.50   Chest + other  21  30.81 ± 33.59, 15.50   Teeth or sinuses  24  17.90 ± 10.64, 16.50   Hand, leg or vertebral  column  23  27.00 ± 22.32, 18.25   Three different or more  20  22.65 ± 26.88, 11.75  Radiological investigation (−)  109  19.10 ± 14.68, 14.25  Pets (+)  163  19.37 ± 16.67, 13.50   Cat  29  18.21 ± 14.21, 13.00   Dog  67  18.21 ± 16.28, 13.00   Others  29  17.12 ± 14.56, 11.00   Cat + dog  38  19.96 ± 15.74, 15.50  Pets (−)  113  26.04 ± 26.60, 17.50  Alcohol (+)  207  21.90 ± 21.51, 15.50  Alcohol (−)  69  19.71 ± 16.92, 11.50  Medicines (+)  233  21.57 ± 19.76, 15.00   Antibiotics only  14  19.38 ± 14.36, 15.75   antibiotics + painkillers  41  22.62 ± 21.71, 16.00   Pain killers only  55  20.15 ± 20.98, 12.00   Pain killers + others  26  22.15 ± 19.59, 15.00   Three or more different  27  21.68 ± 22.93, 16.75   Antiallergic  28  15.04 ± 9.41, 12.50   Hormonal  28  18.13 ± 23.50, 9.00f  Medicines (−)  43  23.02 ± 15.92, 19.50  Summer  63  38.82 ± 29.07, 35.00g  Autumn  95  30.54 ± 19.83, 24.00g  Winter  120  10.24 ± 7.22, 9.00g  aP < 0.05 compared to women by Mann–Whitney U test. bP < 0.05 compared to the group of 18- to 29-year olds by Mann–Whitney U test. cP < 0.05 compared to men non-smokers by Mann–Whitney U test. dP < 0.05 compared to non-smokers by Mann–Whitney U test. eP < 0.05 compared to moderate smokers by Mann–Whitney U test. fP < 0.05 compared to medicines (−). gP < 0.05 compared to two other group of seasons. View Large The levels of DNA damage differ significantly between samples taken in different seasons. The level of DNA damage was highest in the summer (38.82 ± 29.07), lower in the autumn (30.54 ± 19.83) and the lowest in the winter (10.24 ± 7.22). A multifactorial analysis, also for the full model with interactions, showed that only pet ownership affects DNA damage (P = 0.03). Moreover, there was an interaction between pet ownership and smoking (P = 0.008; Table 4). Pet ownership seems to be the factor, which moderates the harmful effects of smoking. The mean level of DNA damage in the group of smoker/no pet was 33.75 ± 33.68, whereas in the group of smoker/pet owner the mean level was 17.83 ± 14.59. For comparison, the mean levels of DNA damage in the groups of non-smoker/pet owner and non-smoker/no pet were 19.74 ± 17.08 and 19.49 ± 16.21, respectively. Table 4. Results of analysis of variance for chosen interactions Source of variation  Degree of freedom  Mean square  F  P-value  Sex (S)  1  166.98  0.58  0.45  Smoking (SM)  1  212,26  0.74  0.39  Radiology (R)  1  868.42  3.04  0.08  Pets ownership(P)  1  1384.72  4.85  0.03  Alcohol (A)  1  39.11  0.14  0.71  Medicines (M)  1  408.55  1.43  0.23  SM + P  1  2608.15  7.18  0.008  SM + M  1  469.72  1.29  0.26  P + M  1  60.90  0.17  0.68  SM + P + M  1  334.05  0.92  0.34  SM + A  1  138.25  0.39  0.53  A + M  1  20.02  0.06  0.81  SM + A + M  1  406.94  1.15  0.28  Source of variation  Degree of freedom  Mean square  F  P-value  Sex (S)  1  166.98  0.58  0.45  Smoking (SM)  1  212,26  0.74  0.39  Radiology (R)  1  868.42  3.04  0.08  Pets ownership(P)  1  1384.72  4.85  0.03  Alcohol (A)  1  39.11  0.14  0.71  Medicines (M)  1  408.55  1.43  0.23  SM + P  1  2608.15  7.18  0.008  SM + M  1  469.72  1.29  0.26  P + M  1  60.90  0.17  0.68  SM + P + M  1  334.05  0.92  0.34  SM + A  1  138.25  0.39  0.53  A + M  1  20.02  0.06  0.81  SM + A + M  1  406.94  1.15  0.28  View Large Discussion Human blood, which is a very convenient source of cells, is very often used for biomonitoring studies. White blood cells are easily obtained in a relatively non-invasive way and are available in large numbers. Leucocytes, including lymphocytes, in contrast to erythrocytes, possess nuclei, they are diploid and are almost all in the same phase (G0) of the cell cycle. They circulate throughout the whole body, and thus can be seen as reflecting the overall state of the organism with regard to exposure towards investigated factors (2,31). The mean level of DNA damage among our volunteers was 24.07, and the intra-individual variability, among 276 samples, was high (SD = 22.36). The highest level of DNA damage of white blood cells exceeded 180 (186), whereas the lowest was <1 (0.5). Other authors have observed intra-individual differences in the level of DNA damage among control populations, however, in a smaller range, but this might be because of a lower number of subjects (12,32–35). Our study (Figure 1) showed that blood samples with lower numbers have much more variation than that with high numbers. The main reason is that samples with higher numbers were taken from younger individuals. The mean age of donors of sample numbers 1–138 is 32.67 ± 11.50, whereas the mean age of donors of sample numbers 139–276 is 27.80 ± 11.25. The basal level of DNA damage might be attributed among others to the occupational exposure and smoking habits. Smoking habit significantly influenced the level of primary DNA damage (35). The current study shows an increase in DNA damage of leucocytes in the blood of smoking individuals, significantly in men and in the case of heavy smokers, that is persons smoking more than 20 cigarettes per day. Tobacco smoking is a factor known to alter the structure of DNA. Although the cigarette smoking was found a most important factor causing DNA damage, numerous studies did not find any differences between DNA damage of cells in smokers and non-smokers (34,36–38), or did not indicate a relationship between DNA damage and the number of cigarette smoked per day (34,38–46). However, other authors showed that smoking was associated with the higher levels of DNA damage (23,47). Significantly higher levels of DNA damage in smokers, but without the influence of the number of cigarettes smoked per day, were noted by Lee et al. (48). In contrast, Fracasso et al. (49) showed that the comet parameters correlated with the number of cigarettes smoked per day. In the present study, very low levels of DNA damage were noted in the group of the youngest donors (18–29 years). With increasing age, the mean level of DNA damage increased significantly up to the age of 49 years, and surprisingly slightly decreased in the oldest group of blood donors (50–58 years). No age-related effects were noted previously by several authors (42,43,50–54), but others observed the changes in DNA damage in different age groups. For instance, Singh et al. (25) reported increased DNA damage in people aged over 60 years. The Greece study showed that men aged 55–60 years had a 14.5% higher level of DNA damage in lymphocytes than 20–25 year olds(47). Significant correlations between age and the level of DNA damage in a control population were also observed by other authors (23,55). Løhr et al. (56) showed an association between age and the level of oxidatively damaged DNA in peripheral blood mononuclear cells, particularly in women, where the results for the youngest (18–29 years) groups was significantly different from the results of those groups aged 54–69 and 70–93 years. Dharwan et al. (23) reported that people over 30 years old had higher DNA damage than those younger. This finding is similar to our results. The nuclear DNA damage being correlated with age is associated with declining DNA repair caused by declining efficiency of DNA repair enzymes (57,58). A meta-analysis study confirmed an association between age and DNA damage in humans, which could be connected with DNA damage accumulation (59). The reason for DNA damage accumulating with age may be an increased production of reactive oxygen species (ROS). This may be associated with cellular metabolism involving oxygen, metals and other metabolites, which decrease scavenging of ROS by antioxidants or a failure of cells to repair DNA damage (60–64). Schumacher et al. (65) and Hoeijamakers (66) suggested that accumulation of unrepaired DNA damage, which decreases genomic integrity is a major source of stochastic changes that can influence ageing. The accumulation of DNA damage with age could be mediated by metabolic factors, including plasma lipids, glycosylated hemoglobin and intake of alcohol, which was positively associated with the level of oxidatively induced DNA damage (56). Results of some studies showed that lifestyle also has an important role in the accumulation of damage to DNA (60,67). The following factors may be responsible for the accumulation of DNA damage: smoking, alcohol intake, environmental exposure, psychological stress and physical activity (21,67–69). There are differences between the levels of DNA damage between genders. As previous studies have shown, men may have more DNA damage in leucocytes than women (32) or, in contrast, women’s blood may show higher DNA damage (3). Lam et al. (70) found male gender to be a risk factor for increased genetic damage. Higher level of DNA damage in males than in females was noted in the Indian population (71). Kopjar et al.(35) noted that in the general population of Croatia, there is a little higher, but not significantly higher, level of DNA damage in lymphocytes of men. This observation was confirmed in the current study, where men’s leucocytes had higher level of DNA damage than women’s leucocytes. Diagnostic X-rays exposure most efficiently enhanced the levels of primary DNA damage (35). In the current study, the level of DNA damage in leucocytes of people subjected to radiological investigations was not significantly higher compared with that of non-investigated individuals. The present study showed slightly, but not significantly, lower level of DNA damage in donors taking medicines, except hormonal medicines, which was associated with significantly lower levels of DNA damage. It might be expected that the comet assay would detect more DNA damage in individuals suffering from infectious diseases (3). Betancourt et al. (27) observed that infections in infants were associated with enhanced frequency of DNA damage. Donors taking antibiotics were expected to have higher level of DNA damage. Higher levels of DNA damage were noted in the leucocytes of malnourished children treated with antibiotics (72). Moreover, the anticancer drugs, idarubicin and mitoxantrone, as well as the antibiotic steptozotocin induced DNA damage in normal lymphocytes (73,74). The antibiotic benzathine penicillin G did not induce DNA damage (75). No genotoxic effects of salinomycin in human nasal mucosa and peripheral blood lymphocytes were observed by Scherzad et al. (76) Our study did not confirm the induction of DNA damage in human leucocytes by antibiotics. A higher level of DNA damage was also noted in women using contraceptives(77) and in patients using antiplaque agents (78). Our donors did not report the name of hormonal medicines; however, these reduced the level of DNA damage. Ghosh et al. (79) observed that dexomethosone, deriphyline and furosemide can induce significant DNA damage in human peripheral blood lymphocytes, whereas acetozolamide, ibuprofen and nifedipine showed no genotoxic effect. Metformin (an antihyperglycemic agent) can protect against oxidant-induced DNA damage in lymphocytes from elderly subjects (80). Some medicines or vitamins may have antioxidant properties, so they can prevent or reduce DNA damage. This may indirectly explain why the oldest donors had lower DNA damage. It might be speculated that it is because they take more medicines. The results of our study might be also explained by the occasional taking of medicines by our donors, who were healthy at the moment of donation and free from chronic diseases. Antiallergic medicines showed non-significantly reduced DNA damage in the present study. Although dexamethasone, which induced significant DNA damage, may be used against allergies, other antiallergic medications, which for example have also anti-inflammatory properties, may reduce DNA damage. Our study showed a non-significant difference between alcohol drinkers and abstainers. This may be because donors declared small or moderate consumption of alcohol (1–5 bottles of beer or 1–3 glasses of wine per month). Previous studies reported significant association between alcohol consumption and DNA damage in lymphocytes (56,81) or no effect (39,48). A Japanese study showed that alcohol drinking frequency was a significant predictor of DNA damage for subjects with an aldehyde dehydrogenase 2 (ALDH-2)-deficient genotype, but not for subjects with ALDH-2 proficient genotype (82). Frequent alcohol drinking was significantly associated with a reduced level of DNA damage in peripheral blood leucocytes from ALDH-2-deficient male subjects (82). The current study showed that individuals owning domestic pets had lower levels of DNA damage in leucocytes. This observation was robust in multivariate analysis, indicating that it is not confounded by sex, smoking, diagnostic X-ray exposure, alcohol consumption and intake of medicine. Pet ownership may moderate the harmful effects of smoking. The mean level of DNA damage in the group of smoker/pet owner was almost half that of the group of smoker/no pet. No published studies about the impact of pet ownership on the levels of DNA damage in cells of human are known. The beneficial effect of human health induced by pets (zoocyia) was recently described in several papers (83–86). Pets benefit human health mainly in the following ways: as builders of social capital, as agents of harm reduction, as motivators for healthy behaviour change and as potential participants in treatment plans (84). Contact with animals can confer physiological benefits, relieving symptoms of mental and cognitive illness and loneliness (85). The benefits of companion animals are most likely to be through reduction in depression, anxiety and social isolation. Positive relationship showed measurably higher oxytocin with lower cortisol and alpha-amylase levels (86). The current results showed, depending on the post-hoc test used, a statistically significant or non-significant trend that companion animals might also influence DNA integrity. However, it might also be a ‘healthy pet-owner effect’, that is, people who are adversely affected by pets do not have them in their homes. More investigations into the DNA damage of pet owners is needed to highlight our observation, which might be important. Our results showed significant seasonal variation in the level of DNA damage in the leucocytes of blood donors. This finding may also explain higher level of DNA damage in samples with lower numbers (Figure 1) that were taken in the summer. Similar to our results, higher frequencies of DNA strand breaks in the summer were noted by several groups of investigators (42,43,51,87–89). In contrast, other authors observed the highest DNA damage in the winter (35,90,91). Increased frequency of DNA damage may be caused by higher sunlight exposure in the summer. Ultraviolet radiation, which is a component of sunlight, is a known factor inducing DNA damage (19,20,92,93). Sunlight might penetrate the outer layer of the human epidermis leading to the induction of DNA damage in mononuclear cells circulating in the vessels in the skin(88). In conclusion, the current results confirmed very high intra-individual variability between the levels of DNA damage in human leucocytes and significant seasonal variation. 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( 2014)[ Effect of dimethyl sulfoxide on the extent of DNA single-strand breaks and alkali-labile sites induced by 365 nm UV-radiation in human blood lymphocyte nucleoids]. Radiats. Biol. Radioecol ., 54, 169– 173. Google Scholar PubMed  93. Aristatile, B., Al-Numair, K. S., Al-Assaf, A. H., Veeramani, C. and Pugalendi, K. V. ( 2015) Protective effect of carvacrol on oxidative stress and cellular DNA damage induced by UVB irradiation in human peripheral lymphocytes. J. Biochem. Mol. Toxicol ., 29, 497– 507. Google Scholar CrossRef Search ADS PubMed  © The Author(s) 2017. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Mutagenesis Oxford University Press

DNA strand breaks in peripheral blood leucocytes of Polish blood donors

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Oxford University Press
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© The Author(s) 2017. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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10.1093/mutage/gex024
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Abstract

Abstract Knowledge about the basal level of DNA damage in leucocytes of healthy control populations is essential before estimation of the effects of exposure to external agents in biomonitoring studies. The aim of this study was to analyse the effects of some lifestyle factors on baseline DNA damage in leucocytes of humans. The material consisted of the peripheral blood from 276 healthy volunteer blood donors. In addition to the standard blood donation questionnaire, they were asked about age, gender, occupation, radiological history, smoking habit, alcohol consumption, medicine use and pet ownership. The results showed marked intra-individual variability. Significant differences in DNA damage levels were observed between individuals in different age and sex groups, between smokers and non-smokers and between samples taken in different seasons of the year, with the highest DNA damage in those obtained in the summer. Significantly higher levels of DNA damage were noted in leucocytes of donors older than 29 years, in men compared with women and in male smokers. Significantly higher DNA strand breaks were observed in heavy smokers. A non-significantly higher level of DNA damage was observed in individuals subjected to radiological investigation and in those drinking alcohol, whereas lower levels were observed in leucocytes of pet owners and in donors taking medicines. Pet ownership influences the level of DNA damage and there is an interaction between this effect and that of smoking. The smoker/pet owners showed almost half the level of DNA damage of smokers without pets. The current results confirmed high intra-individual variability between the levels of DNA damage of individuals. The significant factors that influence the DNA damage in leucocytes are age, sex and smoking habit, especially in men and in heavy smokers. The finding of reduced DNA damage in the leucocytes of pet owners suggests the tendency towards a beneficial effect of such company. Introduction The comet assay, also called single-cell gel electrophoresis assay, is used to detect DNA single- and double-strand breaks and kinetics of their repair. The alkaline method, developed by Singh et al. (1), allows the detection of DNA denaturation and alkali-label sites. DNA strand breaks in single cells are visualised by the increased migration of DNA segments. This helps in the estimation of intercellular disparity. The mechanism of formation of comets is best understood by analogy with nucleotides. The chromatin loops containing a break loose their supercoiling and became free to be pulled towards the anode under the electrophoresis field.(2) The comet assay is a sensitive, fast and relatively cheap method, so it is widely used. It is used among others for detection of the genotoxic exposure of different chemical and physical agents in different, including occupationally exposed populations. This method might be useful in comparative studies regarding the difference in sensitivity and repair capacity of healthy and ill persons. The comet assay was recommended as a marker of exposure to genotoxic agents, indicating early biological effects in human biomonitoring studies (3–7). In recent years, there have been numerous papers published where the comet assay has been used to assess DNA damage in different populations (8–13). DNA is susceptible to damage from different endogenous and exogenous sources. Such damage can cause cell death and eliminate potentially dangerous cells, or lead to either erroneous or correct DNA repair. Cells have repair systems that may delete or repair damage. Misrepaired damage may result in chromosomal damage or mutations, or cause acute adverse effects within hours to weeks or delayed effects within months to years after exposure. There are many agents that can cause DNA damage, such as chemical agents (14,15), environmental pollutants (16,17), ionising radiation (12,18), ultraviolet radiation (19,20), physical exercise (21,22) and diet (23,24). The level of DNA damage may be higher in older people (25) and in smokers (23,26). Moreover, DNA damage has been associated with a number of illnesses, for example infections (27), and with neurodegenerative disorders such as Parkinson’s and Alzheimer’s diseases (28,29). As there are few studies describing the basal level of DNA damage in white blood cells of healthy control populations, which is essential before the estimation of the effects of exposure to external agents in biomonitoring studies, we decided to investigate a large population of healthy blood donors in order to extend knowledge on this topic. The aim of the present study was to analyse the effects of some selected lifestyle factors on the baseline DNA damage in leucocytes of peripheral blood of humans. Although the majority of factors studied here have already been investigated, it is very important to study again confounding factors, for example smoking habit and age. Moreover, we have studied the effects of different kinds of radiological investigations and of taking different kinds of medicines. For the first time, we investigated the association between DNA damage in leucocytes and pet ownership. Materials and methods The study was performed in accordance with standards of ethics, with the authors having obtained the agreement of the Bioethical Commission on the conducting current research. Collection of samples All blood donors were volunteers entering the Blood Donation Unit in Warsaw. They were informed about the use of their blood also for scientific purpose and they agreed. Donors were also informed about the aim of the experiment and experimental details. All donors filled the standard questionnaire for blood donation designed to obtain relevant details and current health status and illness history. In addition, they were asked about employment, medicine use, pet ownership, smoking habit, alcohol consumption and radiological investigation within the past year. These factors were chosen with the consideration that they need to be easy to describe by donors. We did not ask about factors that would have needed an exact description, such as exercises and sun exposure, in order to avoid donors opting out for reason of excessive questionnaire length. All donors were healthy at the time of blood donation. Samples consisting of 1 ml of whole venous blood were collected from blood donors by venepuncture under sterile conditions, drawn into heparinised tubes and coded. Preparation of slides Whole blood was diluted in RPMI 1640 medium with l-glutamine in relation 1:10. The cells were checked for their viability using trypan blue dye. Then, diluted blood (50 µl) was mixed with 0.5% low melting point agarose (LMPA) and dropped on each of two microscope slides covered with normal melting point agarose. After solidifying the agarose at 4°C, another layer of LMPA was added and allowed to solidify at 4°C again. For further steps, the basic method described by Singh et al. (1) was used. The slides were immersed in freshly prepared cold lysing solution (2.5 M NaCl, 100 mM Na2EDTA, 10 mM Tris, pH 10, 1% sodium sarcosinate), with 1% Triton X-100 and 10% dimethylsulphoxide added just before use, overnight at 4°C. Electrophoresis After lysis, the slides were drained and placed in a horizontal gel electrophoresis tank side-by-side avoiding spaces. Freshly prepared and chilled electrophoresis solution (1 mM Na2EDTA and 300 mM NaOH, pH >13) was poured in the electrophoresis tank to a level ~0.25 cm above the slides. The slides were incubated in this solution for 20 min to allow DNA unwinding and expression of alkali labile sites as DNA breaks. Alkaline electrophoresis was conducted for 20 min at 4°C, 24 V (0.96 V/cm) and 300 mA. All these steps were performed under dimmed light to avoid additional DNA damage. The slides were then washed three times for 5 min with neutralising Tris buffer (0.4 M Tris, pH7.5) to neutralise excess alkali. Staining and slide scoring After neutralisation, the slides were stained with ethidium bromide. Slides were placed in a humidified airtight container to prevent drying of the gel and analysed within 3–4 h. Slides were examined using a fluorescence microscope. Images of 200 randomly selected leucocytes (100 cells from each of 2 replicate slides) were analysed from each donor. According to the procedure described earlier(30), cells were graded by eye into five categories based on the distance of migration and perceived proportion of DNA in the tail: (0) no damage, <5%; (A) low-level damage, 5–20%; (B) medium-level damage, 20–40%; (C) high-level damage 40–95%; (D) total damage, >95% and given a value 0, 1, 2, 3, 4 (from undamaged—0 to maximally damaged—4). The same person categorised DNA damage in all samples. To obtain a semi-quantitative analysis of the data, the score of DNA damage (the migration of DNA) was calculated as follows: percentage of cells with category A, plus percentage of cells with category Bx2, plus percentage of cells with category Cx3 and plus percentage of cell with category Dx4. The score may range from 0 (all undamaged) to 400 (all totally damaged). Statistical analysis Our data violated the normality test and equal variance test required for the parametric analysis of variance statistics. The non-parametric the Kruskal–Wallis test by ranks and the median test were used for multiple one factor analysis. Comparisons between groups were done using the Mann–Whitney U test as post-hoc test. P-values <0.05 were considered significant. In addition, multifactor analysis of variance was used to compare some factors. Similarly, P < 0.05 were considered significant. Results There were 276 samples collected from blood donors of mixed occupation (students, administrative employees, blue-collar workers, doctors, nurses, technicians, teachers, policemen and saleswomen from food department) aged from 18 to 58 years, including 118 females and 158 males. Among blue-collar workers, there were construction workers, electricians, painters, horticultural workers, laboratory workers, stockmen, mechanics and plumbers. Young persons prevailed among donors. The majority of them (165 persons, i.e. 55%) were aged from 18 to 29 years. Among them, there were 87 females and 78 males. Moreover, there were 45 persons (8 females and 37 males) aged from 30 to 39 years, 40 individuals (13 females and 27 males) aged from 40 to 49 years and 26 individuals (10 females and 16 males) older than 50 years (Table 1). Table 1. Demographic characteristic of donors   Total  Females  Males  Donors, n  276  118 (42.8%)  158 (57.2%)  Age (years) ± SD  30.2 ± 11.6  27.3 ± 11.2  32.3 ± 11.6  No 18- to 29-year-old donors  165  87  78  No 30- to 39-year-old donors  45  8  37  No 40- to 49-year-old donors  40  13  27  No 50+ donors  26  10  16    Total  Females  Males  Donors, n  276  118 (42.8%)  158 (57.2%)  Age (years) ± SD  30.2 ± 11.6  27.3 ± 11.2  32.3 ± 11.6  No 18- to 29-year-old donors  165  87  78  No 30- to 39-year-old donors  45  8  37  No 40- to 49-year-old donors  40  13  27  No 50+ donors  26  10  16  View Large The characteristics of donor groups are shown in Table 2. Among blood donors there were 45.6% of smokers and 54.4% of non-smokers, among men 49.7% and 50.3% and among women 41% and 59%, respectively. The majority of donors (75%) declared consumption of alcohol compared with 25% abstinence. Simultaneously, the majority of donors (70%) had taken medicines (antibiotics, pain killers, calmants, cardiac, sleep-inducing, antiallergic and hormonal) and had pets (dog, cat, parrot, hamster, rat, fishes, chinchilla, canary bird, turtle and guinea pig) at home (59%) within the past year. There were 60.5% donors with radiological history. Table 2. Characteristics of donor group with regard to investigated factors Number (Percent) of donors  Yes  No  Smoking habit  127 (46.0)  149 (54.0)  Female smokers/non-smokers  48 (41.0)  69 (58.9)  Male smokers/non-smokers  79 (49.7)  80 (93.3)  Alcohol consumption  207 (75.0)  69 (25.0)  Medicinal usage  213 (77.2)  63 (22.8)  Pets at home  163 (59.0)  113 (41.0)  Radiological investigations  167 (60.5)  109 (39.5)  Number (Percent) of donors  Yes  No  Smoking habit  127 (46.0)  149 (54.0)  Female smokers/non-smokers  48 (41.0)  69 (58.9)  Male smokers/non-smokers  79 (49.7)  80 (93.3)  Alcohol consumption  207 (75.0)  69 (25.0)  Medicinal usage  213 (77.2)  63 (22.8)  Pets at home  163 (59.0)  113 (41.0)  Radiological investigations  167 (60.5)  109 (39.5)  View Large Cell viability always exceeded 92%. The mean of scored DNA damage in peripheral blood leucocytes of investigated donors was 24.07 ± 22.36, with median 16.25; however, there was marked intra-individual variability (Figure 1). DNA damage varied between 0.5 in the blood of a 20-year-old female non-smoker student to 186 in the leucocytes of a 40-year-old male smoker employed as an electrician. The DNA damage levels in peripheral blood leucocytes in different subgroups of blood donors are shown in Table 3. Generally, the mean level of DNA damage was significantly lower in leucocytes from women (21.05 ± 20.74), when compared with men (26.12 ± 23.38). Considering the age groups, the results showed that DNA damage was higher in older groups compared with younger groups. The highest level of DNA damage was noted in the leucocytes of individuals aged from 40 to 49 years (mean 39.23 ± 35.40, median 33.75), whereas the lowest in the subgroup of the youngest donors aged from 18 to 29 years donors (mean 18.49 ± 14.90, median 13.00). DNA damage in the groups of donors aged 30–39, 40–49 and >50 years was significantly higher compared with the group of the youngest donors (P < 0.05 by Mann–Whitney U test). Higher levels of DNA damage were noted in the blood of smokers (mean 25.41 ± 25.06) than that of non-smokers (mean 19.84 ± 17.69). Such differences were higher in the peripheral blood leucocytes of men. DNA damage levels in male smokers were significantly higher (27.99 ± 26.10, with median value 22.00) compared with male non-smokers, where mean DNA damage was 21.38 ± 19.54 with median 16.00 (P < 0.05 by Mann–Whitney U test). The differences were much larger when smokers were divided into two subgroups: heavy smokers (over 20 cigarettes daily) and moderate smokers (1–17 cigarettes daily). There were no subjects declaring smoking 18 or 19 cigarettes daily. The mean level of DNA damage in the subgroup of heavy smokers was significantly higher (34.44 ± 24.12 with median 31.00) compared with the subgroup of moderate smokers (23.23 ± 25.51, with median 14.50) and non-smokers (P < 0.05 by Mann–Whitney U test). The level of DNA damage in the leucocytes of moderate smokers was not significantly higher compared with non-smokers. Subjecting to radiological investigation or consumption of alcohol induced slightly higher levels of DNA damage in white blood cells, 23.64 ± 21.93 vs. 19.10 ± 14.68 or 21.90 ± 21.51 vs. 19.71 ± 16.92, respectively. In turn, medicine use or pet ownership was associated with low levels of DNA damage, 21.57 ± 19,76 vs. 23.02 ± 15.92 or 19.37 ± 16.67 vs. 26.04 ± 26.60, respectively. Among radiological investigations, the highest level of DNA damage was induced by chest imaging in combination with other imaging (30.81 ± 33.59) and investigations of the hand, leg or vertebral column (27.00 ± 22.32), whereas the lowest levels of damage were induced by teeth or sinuses imaging (17.90 ± 10.64). The above results were not statistically significant compared with the leucocytes of subjects without radiological investigations. In the case of medicine use, the lowest level of DNA damage was induced by antiallergic (15.04 ± 9.41) and hormonal (18.13 ± 23.50) medicines, but only the results of the last subgroup were significantly different compared with the blood of subjects not having used medicines by Mann–Whitney U test. The level of DNA damage was similar in subgroups owing different pets. Fig. 1. View largeDownload slide Mean DNA migration in individual blood samples Fig. 1. View largeDownload slide Mean DNA migration in individual blood samples Table 3. DNA damage in different subgroups of blood donors Name of subgroup  Individuals (n)  Comet score mean ± SD, median  Total  276  24.07 ± 22.36, 16.25  Women  118  21.05 ± 20.74, 12.50  Men  158  26.12 ± 23.38,a 19.50  18–29 years old  165  18.49 ± 14.90, 13.00  30–39 years old  45  29.23 ± 20.60,b 24.00  40–49 years old  40  39.23 ± 35.40,b 33.75  Over 50 years old  26  32.81 ± 26.65,b 31.00  Smokers  127  25.41 ± 25.06, 16.00  Non-smokers  149  19.84 ± 17.69, 15.25  Men smokers  78  27.92 ± 26.10,c 22.00  Men non-smokers  80  21.38 ± 19.54, 16.00  Women smokers  49  20.88 ± 23.73, 10.50  Women non-smokers  69  17.29 ± 14.30, 12.50  Heavy smokers  33  34.44 ± 24.12,d, e 31.00  Moderate smokers  94  23.23 ± 25.51, 14.50  Non-smokers  149  19.84 ± 17.69, 15.25  Radiological investigation (+)  167  23.64 ± 21.93, 16.00   Chest only  63  21.57 ± 18.86, 15.50   Chest + other  21  30.81 ± 33.59, 15.50   Teeth or sinuses  24  17.90 ± 10.64, 16.50   Hand, leg or vertebral  column  23  27.00 ± 22.32, 18.25   Three different or more  20  22.65 ± 26.88, 11.75  Radiological investigation (−)  109  19.10 ± 14.68, 14.25  Pets (+)  163  19.37 ± 16.67, 13.50   Cat  29  18.21 ± 14.21, 13.00   Dog  67  18.21 ± 16.28, 13.00   Others  29  17.12 ± 14.56, 11.00   Cat + dog  38  19.96 ± 15.74, 15.50  Pets (−)  113  26.04 ± 26.60, 17.50  Alcohol (+)  207  21.90 ± 21.51, 15.50  Alcohol (−)  69  19.71 ± 16.92, 11.50  Medicines (+)  233  21.57 ± 19.76, 15.00   Antibiotics only  14  19.38 ± 14.36, 15.75   antibiotics + painkillers  41  22.62 ± 21.71, 16.00   Pain killers only  55  20.15 ± 20.98, 12.00   Pain killers + others  26  22.15 ± 19.59, 15.00   Three or more different  27  21.68 ± 22.93, 16.75   Antiallergic  28  15.04 ± 9.41, 12.50   Hormonal  28  18.13 ± 23.50, 9.00f  Medicines (−)  43  23.02 ± 15.92, 19.50  Summer  63  38.82 ± 29.07, 35.00g  Autumn  95  30.54 ± 19.83, 24.00g  Winter  120  10.24 ± 7.22, 9.00g  Name of subgroup  Individuals (n)  Comet score mean ± SD, median  Total  276  24.07 ± 22.36, 16.25  Women  118  21.05 ± 20.74, 12.50  Men  158  26.12 ± 23.38,a 19.50  18–29 years old  165  18.49 ± 14.90, 13.00  30–39 years old  45  29.23 ± 20.60,b 24.00  40–49 years old  40  39.23 ± 35.40,b 33.75  Over 50 years old  26  32.81 ± 26.65,b 31.00  Smokers  127  25.41 ± 25.06, 16.00  Non-smokers  149  19.84 ± 17.69, 15.25  Men smokers  78  27.92 ± 26.10,c 22.00  Men non-smokers  80  21.38 ± 19.54, 16.00  Women smokers  49  20.88 ± 23.73, 10.50  Women non-smokers  69  17.29 ± 14.30, 12.50  Heavy smokers  33  34.44 ± 24.12,d, e 31.00  Moderate smokers  94  23.23 ± 25.51, 14.50  Non-smokers  149  19.84 ± 17.69, 15.25  Radiological investigation (+)  167  23.64 ± 21.93, 16.00   Chest only  63  21.57 ± 18.86, 15.50   Chest + other  21  30.81 ± 33.59, 15.50   Teeth or sinuses  24  17.90 ± 10.64, 16.50   Hand, leg or vertebral  column  23  27.00 ± 22.32, 18.25   Three different or more  20  22.65 ± 26.88, 11.75  Radiological investigation (−)  109  19.10 ± 14.68, 14.25  Pets (+)  163  19.37 ± 16.67, 13.50   Cat  29  18.21 ± 14.21, 13.00   Dog  67  18.21 ± 16.28, 13.00   Others  29  17.12 ± 14.56, 11.00   Cat + dog  38  19.96 ± 15.74, 15.50  Pets (−)  113  26.04 ± 26.60, 17.50  Alcohol (+)  207  21.90 ± 21.51, 15.50  Alcohol (−)  69  19.71 ± 16.92, 11.50  Medicines (+)  233  21.57 ± 19.76, 15.00   Antibiotics only  14  19.38 ± 14.36, 15.75   antibiotics + painkillers  41  22.62 ± 21.71, 16.00   Pain killers only  55  20.15 ± 20.98, 12.00   Pain killers + others  26  22.15 ± 19.59, 15.00   Three or more different  27  21.68 ± 22.93, 16.75   Antiallergic  28  15.04 ± 9.41, 12.50   Hormonal  28  18.13 ± 23.50, 9.00f  Medicines (−)  43  23.02 ± 15.92, 19.50  Summer  63  38.82 ± 29.07, 35.00g  Autumn  95  30.54 ± 19.83, 24.00g  Winter  120  10.24 ± 7.22, 9.00g  aP < 0.05 compared to women by Mann–Whitney U test. bP < 0.05 compared to the group of 18- to 29-year olds by Mann–Whitney U test. cP < 0.05 compared to men non-smokers by Mann–Whitney U test. dP < 0.05 compared to non-smokers by Mann–Whitney U test. eP < 0.05 compared to moderate smokers by Mann–Whitney U test. fP < 0.05 compared to medicines (−). gP < 0.05 compared to two other group of seasons. View Large The levels of DNA damage differ significantly between samples taken in different seasons. The level of DNA damage was highest in the summer (38.82 ± 29.07), lower in the autumn (30.54 ± 19.83) and the lowest in the winter (10.24 ± 7.22). A multifactorial analysis, also for the full model with interactions, showed that only pet ownership affects DNA damage (P = 0.03). Moreover, there was an interaction between pet ownership and smoking (P = 0.008; Table 4). Pet ownership seems to be the factor, which moderates the harmful effects of smoking. The mean level of DNA damage in the group of smoker/no pet was 33.75 ± 33.68, whereas in the group of smoker/pet owner the mean level was 17.83 ± 14.59. For comparison, the mean levels of DNA damage in the groups of non-smoker/pet owner and non-smoker/no pet were 19.74 ± 17.08 and 19.49 ± 16.21, respectively. Table 4. Results of analysis of variance for chosen interactions Source of variation  Degree of freedom  Mean square  F  P-value  Sex (S)  1  166.98  0.58  0.45  Smoking (SM)  1  212,26  0.74  0.39  Radiology (R)  1  868.42  3.04  0.08  Pets ownership(P)  1  1384.72  4.85  0.03  Alcohol (A)  1  39.11  0.14  0.71  Medicines (M)  1  408.55  1.43  0.23  SM + P  1  2608.15  7.18  0.008  SM + M  1  469.72  1.29  0.26  P + M  1  60.90  0.17  0.68  SM + P + M  1  334.05  0.92  0.34  SM + A  1  138.25  0.39  0.53  A + M  1  20.02  0.06  0.81  SM + A + M  1  406.94  1.15  0.28  Source of variation  Degree of freedom  Mean square  F  P-value  Sex (S)  1  166.98  0.58  0.45  Smoking (SM)  1  212,26  0.74  0.39  Radiology (R)  1  868.42  3.04  0.08  Pets ownership(P)  1  1384.72  4.85  0.03  Alcohol (A)  1  39.11  0.14  0.71  Medicines (M)  1  408.55  1.43  0.23  SM + P  1  2608.15  7.18  0.008  SM + M  1  469.72  1.29  0.26  P + M  1  60.90  0.17  0.68  SM + P + M  1  334.05  0.92  0.34  SM + A  1  138.25  0.39  0.53  A + M  1  20.02  0.06  0.81  SM + A + M  1  406.94  1.15  0.28  View Large Discussion Human blood, which is a very convenient source of cells, is very often used for biomonitoring studies. White blood cells are easily obtained in a relatively non-invasive way and are available in large numbers. Leucocytes, including lymphocytes, in contrast to erythrocytes, possess nuclei, they are diploid and are almost all in the same phase (G0) of the cell cycle. They circulate throughout the whole body, and thus can be seen as reflecting the overall state of the organism with regard to exposure towards investigated factors (2,31). The mean level of DNA damage among our volunteers was 24.07, and the intra-individual variability, among 276 samples, was high (SD = 22.36). The highest level of DNA damage of white blood cells exceeded 180 (186), whereas the lowest was <1 (0.5). Other authors have observed intra-individual differences in the level of DNA damage among control populations, however, in a smaller range, but this might be because of a lower number of subjects (12,32–35). Our study (Figure 1) showed that blood samples with lower numbers have much more variation than that with high numbers. The main reason is that samples with higher numbers were taken from younger individuals. The mean age of donors of sample numbers 1–138 is 32.67 ± 11.50, whereas the mean age of donors of sample numbers 139–276 is 27.80 ± 11.25. The basal level of DNA damage might be attributed among others to the occupational exposure and smoking habits. Smoking habit significantly influenced the level of primary DNA damage (35). The current study shows an increase in DNA damage of leucocytes in the blood of smoking individuals, significantly in men and in the case of heavy smokers, that is persons smoking more than 20 cigarettes per day. Tobacco smoking is a factor known to alter the structure of DNA. Although the cigarette smoking was found a most important factor causing DNA damage, numerous studies did not find any differences between DNA damage of cells in smokers and non-smokers (34,36–38), or did not indicate a relationship between DNA damage and the number of cigarette smoked per day (34,38–46). However, other authors showed that smoking was associated with the higher levels of DNA damage (23,47). Significantly higher levels of DNA damage in smokers, but without the influence of the number of cigarettes smoked per day, were noted by Lee et al. (48). In contrast, Fracasso et al. (49) showed that the comet parameters correlated with the number of cigarettes smoked per day. In the present study, very low levels of DNA damage were noted in the group of the youngest donors (18–29 years). With increasing age, the mean level of DNA damage increased significantly up to the age of 49 years, and surprisingly slightly decreased in the oldest group of blood donors (50–58 years). No age-related effects were noted previously by several authors (42,43,50–54), but others observed the changes in DNA damage in different age groups. For instance, Singh et al. (25) reported increased DNA damage in people aged over 60 years. The Greece study showed that men aged 55–60 years had a 14.5% higher level of DNA damage in lymphocytes than 20–25 year olds(47). Significant correlations between age and the level of DNA damage in a control population were also observed by other authors (23,55). Løhr et al. (56) showed an association between age and the level of oxidatively damaged DNA in peripheral blood mononuclear cells, particularly in women, where the results for the youngest (18–29 years) groups was significantly different from the results of those groups aged 54–69 and 70–93 years. Dharwan et al. (23) reported that people over 30 years old had higher DNA damage than those younger. This finding is similar to our results. The nuclear DNA damage being correlated with age is associated with declining DNA repair caused by declining efficiency of DNA repair enzymes (57,58). A meta-analysis study confirmed an association between age and DNA damage in humans, which could be connected with DNA damage accumulation (59). The reason for DNA damage accumulating with age may be an increased production of reactive oxygen species (ROS). This may be associated with cellular metabolism involving oxygen, metals and other metabolites, which decrease scavenging of ROS by antioxidants or a failure of cells to repair DNA damage (60–64). Schumacher et al. (65) and Hoeijamakers (66) suggested that accumulation of unrepaired DNA damage, which decreases genomic integrity is a major source of stochastic changes that can influence ageing. The accumulation of DNA damage with age could be mediated by metabolic factors, including plasma lipids, glycosylated hemoglobin and intake of alcohol, which was positively associated with the level of oxidatively induced DNA damage (56). Results of some studies showed that lifestyle also has an important role in the accumulation of damage to DNA (60,67). The following factors may be responsible for the accumulation of DNA damage: smoking, alcohol intake, environmental exposure, psychological stress and physical activity (21,67–69). There are differences between the levels of DNA damage between genders. As previous studies have shown, men may have more DNA damage in leucocytes than women (32) or, in contrast, women’s blood may show higher DNA damage (3). Lam et al. (70) found male gender to be a risk factor for increased genetic damage. Higher level of DNA damage in males than in females was noted in the Indian population (71). Kopjar et al.(35) noted that in the general population of Croatia, there is a little higher, but not significantly higher, level of DNA damage in lymphocytes of men. This observation was confirmed in the current study, where men’s leucocytes had higher level of DNA damage than women’s leucocytes. Diagnostic X-rays exposure most efficiently enhanced the levels of primary DNA damage (35). In the current study, the level of DNA damage in leucocytes of people subjected to radiological investigations was not significantly higher compared with that of non-investigated individuals. The present study showed slightly, but not significantly, lower level of DNA damage in donors taking medicines, except hormonal medicines, which was associated with significantly lower levels of DNA damage. It might be expected that the comet assay would detect more DNA damage in individuals suffering from infectious diseases (3). Betancourt et al. (27) observed that infections in infants were associated with enhanced frequency of DNA damage. Donors taking antibiotics were expected to have higher level of DNA damage. Higher levels of DNA damage were noted in the leucocytes of malnourished children treated with antibiotics (72). Moreover, the anticancer drugs, idarubicin and mitoxantrone, as well as the antibiotic steptozotocin induced DNA damage in normal lymphocytes (73,74). The antibiotic benzathine penicillin G did not induce DNA damage (75). No genotoxic effects of salinomycin in human nasal mucosa and peripheral blood lymphocytes were observed by Scherzad et al. (76) Our study did not confirm the induction of DNA damage in human leucocytes by antibiotics. A higher level of DNA damage was also noted in women using contraceptives(77) and in patients using antiplaque agents (78). Our donors did not report the name of hormonal medicines; however, these reduced the level of DNA damage. Ghosh et al. (79) observed that dexomethosone, deriphyline and furosemide can induce significant DNA damage in human peripheral blood lymphocytes, whereas acetozolamide, ibuprofen and nifedipine showed no genotoxic effect. Metformin (an antihyperglycemic agent) can protect against oxidant-induced DNA damage in lymphocytes from elderly subjects (80). Some medicines or vitamins may have antioxidant properties, so they can prevent or reduce DNA damage. This may indirectly explain why the oldest donors had lower DNA damage. It might be speculated that it is because they take more medicines. The results of our study might be also explained by the occasional taking of medicines by our donors, who were healthy at the moment of donation and free from chronic diseases. Antiallergic medicines showed non-significantly reduced DNA damage in the present study. Although dexamethasone, which induced significant DNA damage, may be used against allergies, other antiallergic medications, which for example have also anti-inflammatory properties, may reduce DNA damage. Our study showed a non-significant difference between alcohol drinkers and abstainers. This may be because donors declared small or moderate consumption of alcohol (1–5 bottles of beer or 1–3 glasses of wine per month). Previous studies reported significant association between alcohol consumption and DNA damage in lymphocytes (56,81) or no effect (39,48). A Japanese study showed that alcohol drinking frequency was a significant predictor of DNA damage for subjects with an aldehyde dehydrogenase 2 (ALDH-2)-deficient genotype, but not for subjects with ALDH-2 proficient genotype (82). Frequent alcohol drinking was significantly associated with a reduced level of DNA damage in peripheral blood leucocytes from ALDH-2-deficient male subjects (82). The current study showed that individuals owning domestic pets had lower levels of DNA damage in leucocytes. This observation was robust in multivariate analysis, indicating that it is not confounded by sex, smoking, diagnostic X-ray exposure, alcohol consumption and intake of medicine. Pet ownership may moderate the harmful effects of smoking. The mean level of DNA damage in the group of smoker/pet owner was almost half that of the group of smoker/no pet. No published studies about the impact of pet ownership on the levels of DNA damage in cells of human are known. The beneficial effect of human health induced by pets (zoocyia) was recently described in several papers (83–86). Pets benefit human health mainly in the following ways: as builders of social capital, as agents of harm reduction, as motivators for healthy behaviour change and as potential participants in treatment plans (84). Contact with animals can confer physiological benefits, relieving symptoms of mental and cognitive illness and loneliness (85). The benefits of companion animals are most likely to be through reduction in depression, anxiety and social isolation. Positive relationship showed measurably higher oxytocin with lower cortisol and alpha-amylase levels (86). The current results showed, depending on the post-hoc test used, a statistically significant or non-significant trend that companion animals might also influence DNA integrity. However, it might also be a ‘healthy pet-owner effect’, that is, people who are adversely affected by pets do not have them in their homes. More investigations into the DNA damage of pet owners is needed to highlight our observation, which might be important. Our results showed significant seasonal variation in the level of DNA damage in the leucocytes of blood donors. This finding may also explain higher level of DNA damage in samples with lower numbers (Figure 1) that were taken in the summer. Similar to our results, higher frequencies of DNA strand breaks in the summer were noted by several groups of investigators (42,43,51,87–89). In contrast, other authors observed the highest DNA damage in the winter (35,90,91). Increased frequency of DNA damage may be caused by higher sunlight exposure in the summer. Ultraviolet radiation, which is a component of sunlight, is a known factor inducing DNA damage (19,20,92,93). Sunlight might penetrate the outer layer of the human epidermis leading to the induction of DNA damage in mononuclear cells circulating in the vessels in the skin(88). In conclusion, the current results confirmed very high intra-individual variability between the levels of DNA damage in human leucocytes and significant seasonal variation. 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MutagenesisOxford University Press

Published: Jan 1, 2018

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