Use of the Tail Moment of the Lymphocytes to Evaluate DNA Damage in Human Biomonitoring Studies

Eunil Lee, Eunha Oh, Joohyun Lee, Donggeun Sul and Juneyoung Lee1

Department of Preventive Medicine, Medical Research Center for Environmental Toxico-Genomics and Proteomics, College of Medicine, Korea University, Seoul 136–705, Korea

Received March 11, 2004; accepted May 27, 2004


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 Materials and Methods
 RESULTS
 DISCUSSION
 REFERENCES
 
The Comet assay has gained increasing popularity for use in human biomonitoring or epidemiologic studies; however, one of the shortcomings of the Comet assay is a lack of agreement on a single appropriate Comet parameter that is capable of adequately describing observed DNA damages. Among the tail parameters of Comet features, the most frequently used are the tail moments (both the Olive tail moment and the extent tail moment), the tail DNA, and the tail length. Some studies comparing Comet parameters have been found in cell toxicity research, but there are few comparative studies that use human biomonitoring or epidemiologic data. In this study, we evaluate those four tail parameters in both high and low DNA damaged cells with the use of epidemiologic data. To do this, a new graphical approach, the so-called quantile dispersion graphs (QDGs) are used. In a comparison of an exposed group and a control group, either the tail moment or tail DNA is preferable to the tail length. With respect to providing smaller variability in quantiles for the amount of DNA damage, however, the tail moment is the preferred parameter for both groups. Moreover, the tail moment provides the most stable estimates for DNA damage because it has a larger degree of uniformity in quantile dispersions. To study high degrees of damage from toxic exposure using B cells or G cells, however, the tail DNA showed more significant discrepancies than the other parameters, in terms of both the mean differences and the graphical differences between the two groups. In view of this result, it is suggested that both the tail moment and the tail DNA be presented as tail parameters in human biomonitoring studies.

Key Words: Comet assay; quantile dispersion graphs; tail moment; Olive tail moment; extent tail moment; tail DNA; tail length; lymphocytes; DNA damage.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 Materials and Methods
 RESULTS
 DISCUSSION
 REFERENCES
 
Since its introduction by Ostling and Johanson (1984)Go and its independent modification by Singh et al. (1988)Go, the Comet assay has been widely used for genotoxic studies and cell biological studies, and even in human biomonitoring studies. Among the many parameters of Comet features, the tail parameters that are the most frequently used are those of the tail moment, the tail DNA, and the tail length (De Boeck et al., 2000Go). The concepts of comet length or tail length as migrations of DNA have been developed by Singh et al. (1988)Go and Olive et al. (1990aGo, 1990b)Go. The tail moment and the percentage of DNA in the tail (i.e., the tail DNA) were introduced by Olive et al. (1990aGo, 1992)Go and Muller et al. (1994)Go, and these parameters have been used by many researchers for genotoxic studies (Anderson et al., 2003Go; Bajpayee et al., 2002Go; Garaj-Vrhovac and Zeljezic, 2002Go; Kim et al., 2002Go; Schabath et al., 2003Go). In addition, a metric based on the percentage of migrated DNA, such as the tail moment, has become popular with the increased use of computerized image analysis systems used to collect Comet data (Tice et al., 2000Go).

Although the popularity of the Comet assay in biomonitoring studies has increased (Moller et al., 2000Go), one of its shortcomings is a lack of agreement on a single appropriate Comet parameter that adequately describes DNA damage (Kassie et al., 2000Go). Although there have been a few studies related to cell toxicity research, studies that compare Comet parameters in human biomonitoring studies are rare. Bocker et al. (1997)Go reported that the tail moment and tail DNA showed more sensitivity than the tail length on the basis of an X-irradiation dose–response experiment. De Boeck et al. (2000)Go showed that tail DNA was a more appropriate parameter than tail length to analyze induced DNA damage because of its smaller variation, based on their internal standard. Olive et al. (1992)Go have suggested that the tail DNA was more accurate for detecting DNA damages than the tail moment.

Meanwhile, the use of Comet assay for human studies has not shown consistent results. This is so because of its large variability as observed in both exposed and control groups (Rojas et al., 1999Go) or because of the poor dose-response relationship noted in biomonitoring studies (Moller et al., 2000Go). It has also been found that the dose–response correlations between benzene exposure and DNA damage in the exposed group were very differ from those in the control group (Sul et al., 2002Go, 2003Go). In case of B lymphocytes, which showed more significant damage in the exposed group than in the controls, the correlation coefficient between t,t-muconic acid levels and the tail moment was 0.737, and that for the tail DNA was 0.742. In the case of T lymphocytes, which showed a slight significant difference between the exposed group and the control group, the correlation coefficient was 0.345 for the tail moment and 0.319 for the tail DNA. They also reported that statistically significant DNA damage for tail parameters depended on cell types; the damage in B cells was higher than in T cells, G cells, and lymphocytes in the exposed group. These discrepancies imply that comparisons of tail parameters should be made according to the degree of DNA damage.

In this study, a new graphical approach, the so-called quantile dispersion graphs (QDGs), was used to compare tail parameters in both high and low DNA damaged cell types with human biomonitoring data. The QDGs were first introduced by Khuri (1997)Go, and he employed exact quantiles of the distribution of the parameter of interest to compare the statistical estimation methods of variance components for random analysis of variance (ANOVA) models. When an exact distribution of the parameter of interest was unknown, Lee and Khuri (1999Go, 2000)Go suggested the use of empirical quantiles, which produced the so-called empirical quantile dispersion graphs (EQDGs). Such plots have been shown to provide not only a comprehensive assessment of the estimation capability of experimental designs but also an overall evaluation of the quality of statistical estimation methods (Khuri and Lee, 2003Go). We employed this method to compare characteristics among the Comet parameters. The EQDGs consisted of plots of the minimum and maximum values of empirical quantiles of the tail parameters over a parameter space. These plots provided an assessment of overall quality of the tail parameters for a particular cell type in the Comet assay, because the plots utilized all of the human data obtained from Comet studies. Furthermore, the plots could be conveniently used to compare an exposed group with a control group for each of the tail parameters.


    Materials and Methods
 TOP
 ABSTRACT
 INTRODUCTION
 Materials and Methods
 RESULTS
 DISCUSSION
 REFERENCES
 
Study subjects. There were 494 subjects in our study, including 259 workers who had been exposed to benzene, polyaromatic hydrocarbons (PAHs), or dioxin. Details for this exposed group are as follows: the group includes 116 benzene workers from six companies—a printing company, two shoe manufacturers, and three chemical companies. The air concentration of benzene varied from 0.008 ppm to 2.032 ppm, as tested by a personal air-sampling method. Urinary muconic acid levels were 0–2.78 mmol muconic acid/mmol creatinine, as tested by spot urine sampling. The PAH exposure workers were 82 automobile emission inspectors from three offices in Seoul, Korea. Air concentrations of PAH were 0.682–13.457 µg/m3, and levels of urinary 1-hydroxypyrene and 2-naphthol levels were 0–1.012 µmol/mol creatinine and 0.846–20.883 µmol/mol creatinine, respectively. There were 61 incineration workers who were exposed to PAHs and dioxin. Levels of air dioxin were 0.2999–90.45 ng-TEQ/Sm3, and those for air PAH were 0.958–13.457 µg/m3. A total of 235 control subjects were chosen from unexposed healthy donors who had undergone an annual health examination at Soonchunhyang University Hospital in Seoul, Korea.

All subjects are male, and their average age and smoking status are similar to the study population of Sul et al. (2002Go, 2003)Go. Each of sampling times for the exposed and control groups was within a week.

Comet data and tail parameters. The Comet experiment for blood lymphocytes and granulocytes was performed by two laboratory experts, from July 2000 to October 2002, in the Medical Research Center for Environmental Toxico-Genomics and Proteomics, Korea University. The alkaline version of the Comet assay was performed according to the method of Singh et al. (1988)Go, with only one minor modification (pH > 13). Two slides were prepared, and each of about 50 randomly chosen cells (a total of ≥100 cells, up to 120 cells) was scored manually. For scoring, a strict slide reading manual, which included a starting point for reading, a reading area in the slide, a reading direction, and click numbers to move was used. For sampling and scoring, a single-blind method was used. In brief, cells were mixed with 0.5% low-melting agarose and then placed onto fully frosted slides. After that, the slides were coated with 1% normal agarose. When the agarose had solidified, an additional layer of 0.5% low-melting agarose was added. The slides were submersed in the lysing solution (1.5 M NaCl; 100 mM EDTA-1Na; 10 mM Tris-HCl, pH 10; 1% Triton X-100, and 10% DMS, pH 10) for one hour. The slides were then placed in unwinding buffer (1 mM EDTA and 300 mM NaOH, pH > 13) for 20 min. Electrophoresis was carried out using the same solution for 20 min at 25 V and 300 mA (0.8 V/cm). After electrophoresis, the slides were neutralized by washing three times with neutralization buffer (400 mM Tris-Cl, pH 7.4) for 5 min each, and the cells were stained with 50 µl of 10 µg/ml ethidium bromide.

Tail parameters were then calculated automatically using the Komet 4.0 image analysis system (Kinetic Imaging, Liverpool, UK) fitted with an Olympus BX50 fluorescence microscope that was equipped with an excitation filter of 515–560 nm and a barrier filter of 590 nm. Tail parameters used in this study were the tail moment (TM), the extent tail moment (ETM), the tail DNA % (TD), and the tail length (TL). The TM was defined by the percentage of DNA in the tail multiplied by the length between the center of the head and tail, which was defined by Olive et al. (1990a)Go. The ETM was a product of the tail length and the TD. Note that in some studies the extent tail moment has been expressed as the tail moment (De Boeck et al., 2000Go; Lee and Steinert, 2003Go; Tice et al., 2000Go).

The Comet assay was carried out within 3 h after blood sampling. Mononuclear and polynuclear cells were separated by using two kinds of histopaque solutions (1.077 and 1.119) with centrifugation at 700 g for 30 min at room temperature for the sampling of lymphoctytes and granulocytes. T lymphocytes, B lymphocytes, and granulocytes were positively selected with magnetic beads (magnetic cell sorting (MACS) CD3 or CD19 or CD15 isolation kit; Miltenyi Biotec) according to the manufacturer's instructions. Cell viability was measured by the uptake of trypan blue. The viabilities of lymphocytes were 97.6 ± 0.6% after 2 h of sample preparation, 95.1 ± 0.3% after 3 h, and 94.5 ± 0.7% after 4 h. The methods for the Comet assay and cell preparation have been described in detail elsewhere (Sul et al., 2002Go, 2003Go).

Statistical methods. Noting that the observed values of DNA damage for each subject show a skewed distribution, median values of DNA damage were selected to represent the amount of DNA damage. Comparisons of the averages of the median DNA damages between the exposed and control groups were made using the two-tailed Student's t-test. Quantiles of the observed values of DNA damage for each subject were used for a more comprehensive comparison of the tail parameters, namely, TM, ETM, TD, and TL. This was achieved by noting that the distribution of the amount of DNA damage could be determined in terms of its quantiles (Khuri and Lee, 1998Go). Considering that more than 100, and up to 120 Comet-assayed cells for each of the subjects were used, the use of quantiles of the observed DNA damage for a subject would more appropriately represent the true status of DNA damage, rather than using a single-valued criteria, such as a mean or a median. Furthermore, the pattern of such quantiles over the exposed or control groups would provide overall information about DNA damage for the entire group.

As mentioned earlier, for a given tail parameter, the dependency of the particular empirical quantiles on the value of the true amount of DNA damage can be assessed by computing the minimum and maximum of its empirical quantiles over the study subjects. Plots of the resulting minima and maxima produce the EQDGs (Lee and Khuri, 1999Go). More specifically, let {delta}ijk be an observed extent of DNA damage for an ith parameter of a jth cell in a kth subject, i = TM, ETM, TD, and TL; j = 1, 2, ..., nk; and k = 1, 2, ..., mE (or mC), where nk is the number of cells observed in the kth subject and mE (or mC) is the number of subjects for the exposed (or the control) group. (Note that in our study, mE = 259, mC = 235, nk = 100 ~ 120.) Also, let {delta}ik be a set of such values observed for the kth subject having ith parameter, namely, {delta}ik = {{delta}i1k, {delta}i2k, ..., {delta}i,nk,k}. For the given parameter, i, and the subject, k, let q(p, {delta}ik) denote the pth quantile of {delta}ik, that is, p({delta}ik ≤ q) = p, 0 ≤ p ≤ 1. Define

and

Plotting qmin(p, {delta}i) and qmax(p, {delta}i) against selected values of p (0 ≤ p ≤ 1) provides the EQDGs for the ith parameter, i = TM, ETM, TD, and TL. These EQDGs will provide information about the distribution of DNA damage for each of the tail parameters. In a comparison of the exposed group with the control group, the ith parameter is considered to be "efficient" to assess the amount of DNA damage if values of both qmax(p, {delta}i) and qmin(p, {delta}i) for the former group are consistently higher, over the range of p, than those for the latter group.

To compare the tail parameters, however, we have to standardize the values of {delta}ijk, because of its differing ranges for the tail parameters. For each of an ith parameter, i = TM, ETM, TD, and TL, we transformed {delta}ijk's to

where are the observed DNA damages for the exposed group and are those for the control group. These standardized values will have a range of 0 to 100 for each of the ith parameter, so that a comparison of the behavior of the tail parameters can be made. Based on the EQDGs obtained by using {delta}ijk*s, we can use the following guidelines for comparison of the tail parameters. First, the ith parameter is considered to be more "consistent" in assessing the amount of DNA damage than the jth parameter, if values of qmax(p, {delta}i) – qmin(p, {delta}i) for the ith parameter are smaller (i.e., less variable) over the range of p (0 ≤ p ≤ 1) than those for the jth parameter. Second, the ith parameter can also be considered more "stable" in estimating the DNA damage than the jth parameter, if the former EQDGs show a larger degree of uniformity (i.e., more flat) than the latter in both the exposed and the control groups. This approach will provide a comprehensive comparison of four tail parameters.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 Materials and Methods
 RESULTS
 DISCUSSION
 REFERENCES
 
Statistical comparisons of the exposed and control groups for the amount of DNA damage are shown in Table 1. The DNA damage of B cells in the exposed group is significant compared to the control group over all of the tail parameters we considered. The amount of DNA damage of B cells is also greater than that of lymphocytes and T cells. This implies that an evaluation of tail parameters should be made according to high or low DNA damage status in an exposed group. For the TM parameter, the exposed group shows a statistically higher average median value compared to the control group in highly damaged cells such as B cells and G cells (p's < 0.0001), but not for the lymphocytes or the T cells (p = 0.1698 and p = 0.1933, respectively). The ETM of lymphocytes and T cells shows significant p values in the opposite direction, whereas the ETM of B cells shows significantly higher values in the exposed group (p's < 0.0001). For the TD, all of the T cells, B cells, and G cells show a significantly larger average median value in the exposed group than in the control group (p = 0.0271, p < 0.0001, and p = 0.0055, respectively), but not for the lymphocyte cells (p = 0.3549). Regarding the TL, there is statistical significance between the two groups for all cell types (p's < 0.0001); however, the direction is opposite for the lymphocytes and T cells. These results support the earlier findings of Sul et al. (2002Go, 2003)Go that the B cell is a more useful target for genetic biomonitoring of human populations exposed to genotoxic compounds than the T cell or the G cell.


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TABLE 1 Average Median Values (±SD) of the Amount of DNA Damage of Study Subjects

 
We also note that for the cells showing statistical significance in those parameters, the pattern of the TM and the TD are somewhat consistent. Statistically larger values are observed in B cells and G cells with the TM, whereas the larger values observed with the TD are in T cells, B cells, and G cells. The patterns of the ETM and the TL are also similar. Both parameters show statistically higher values in the control group for the lymphocytes and T cells, which are the low-damage cells. Considering that the ETM uses the TL, this may indicate that the use of the TL or the ETM might be inappropriate for detecting DNA damage with low-damage cells.

The minimum and maximum empirical quantile values of the observed DNA damage for selected probability values for each of the cell types are shown in Tables 2GoGo5. The EQDG plots for the lymphocytes, the T cells, the B cells, and the G cells are given in Figures 1, 2, 3, and 4, respectively. For lymphocyte cells, the exposed group showed consistently higher maximum quantile values [i.e., qmax(p, {delta}i)], over the range of p (0 ≤ p ≤ 1) than did the control group in the TM. In the TD, the maximum quantile values for the exposed group are mostly higher than those for the control group (see Table 2 as well as Figure 1a and 1c). However, the maximum quantiles for the ETM and the TL between the exposed group and the control group are crossed over. For the minimum quantiles [i.e., qmin(p, {delta}i)], the control group shows slightly higher values than the exposed group for most values of p for all parameters (see Fig. 1). For T-cells, most of the maximum quantiles of the TM are larger for the exposed group than for the control group (see Table 3 and Fig. 2a). The exposed group's preference to the control group in producing larger quantiles, however, is unclear for the parameters ETM and TD (see Fig. 2b and 2c). With the TL, consistently higher quantiles are observed, even in the control group (see Fig. 1d, Fig. 2d and Fig. 4d). For B cells, the maximum quantiles in the exposed group are uniformly higher than those for the control group at all tail parameters. This is also true for the minimum quantiles, except for the TL (see Table 4 and Fig. 3). For G cells, the TM, ETM, and TD parameters in the exposed group show larger maximum quantiles than those in the control group, but this pattern is reversed with the TL (see Table 5 and Fig. 4). In conclusion, in a comparison of the exposed and control groups, either the TM or the TD is a more efficient parameter than the others for the lymphocyte, T cells and G cells. For B cells, all parameters, except the TL, are efficient.


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TABLE 2 Minimum and Maximum Empirical Quantile Values of DNA Damage for the Lympocytes from the 259 Subjects of the Exposed Group and the 235 Subjects of the Control Group with Selected Values of Probability

 

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TABLE 3 Minimum and Maximum Empirical Quantile Values of DNA Damage for the T Cells from the 113 Subjects of the Exposed Group and the 48 Subjects of the Control Group with Selected Values of Probability

 

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TABLE 4 Minimum and Maximum Empirical Quantile Values of DNA Damage for the B Cells from the 113 Subjects of the Exposed Group and the 48 Subjects of the Control Group with Selected Values of Probability

 

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TABLE 5 Minimum and Maximum Empirical Quantile Values of DNA Damage for the G Cells from the 113 Subjects of the Exposed Group and the 48 Subjects of the Control Group with Selected Values of Probability

 


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FIG. 1. Empirical quantile dispersion graphs (EQDGs) for the lymphocytes, using the observed values of DNA damage tail moment (TM), extent tail moment (ETM), tail DNA % (TD), and tail length (TL). For each set of solid and broken lines, the upper line represents the maximum quantile values for a given probability, and the lower line is for that of the minimum. Solid lines are for the exposed group, and broken lines are for the control group. The same explanations apply to Figures 2, 3, and 4.

 


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FIG. 2. EQDGs for the T cells, using the observed values of DNA damage.

 


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FIG. 3. EQDGs for the B cells, using the observed values of DNA damage.

 


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FIG. 4. EQDGs for the G cells, using the observed values of DNA damage.

 
In order to compare the capability for assessing DNA damage among the tail parameters, the EQDGs for each of the cell types are obtained using the standardized values ({delta}ijk*, s), and these are shown in Figures 5 through 8. Observations made from these figures are as follows: first, for all cell types, it is apparent that the TM shows the smallest variability in the standardized extents of DNA damage among the tail parameters (see Figs. 5a–5c through 8a–8c). This is true for both the exposed group and the control group. The ETM and the TD also show smaller variability than the TL, and with similar patterns, indicating that the TM provides a more consistent estimate of DNA damage in human biomonitoring studies than the other parameters, regardless of cell type. Second, the degree of uniformity in the quantile values of DNA damage is also larger with the TM than with either the ETM or the TD, and it is much larger than with the TL in the lymphocytes and B cells for both groups (see Figs. 5 and 7), and in the T cells for the control group (see Fig. 6c and 6d). For the exposed group in the T cells and both groups in the G cells, the degree of uniformity with the ETM or the TD is larger than the TM (see Fig. 6a and 6b and Fig. 8). Comparing the ETM or the TD with the TL, the former is more stable than the latter, implying that the TM parameter provides the most consistency in observing DNA damage among the tail parameters. The TM also provides more stable estimates of DNA damage than either the ETM or the TD, but only in the lymphocytes and the B cells.



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FIG. 5. Empirical quantile dispersion graphs (EQDGs) for the lymphocytes, using the standardized values of DNA damage. Each set of lines in each plot represents the maximum and minimum standardized quantile values for a given probability. Two plots are used to show the EQDGs of the four tail parameters, tail moment (TM), extent tail moment (ETM), tail DNA % (TD), and tail length (TL), where (a) and (b) are for the exposed group and (c) and (d) are for the control group. The same explanations apply to Figures 6, 7, and 8.

 


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FIG. 8. EQDGs for the G cells, using the standardized values of DNA damage.

 


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FIG. 7. EQDGs for the B cells, using the standardized values of DNA damage.

 


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FIG. 6. EQDGs for the T cells, using the standardized values of DNA damage.

 

    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 Materials and Methods
 RESULTS
 DISCUSSION
 REFERENCES
 
The Comet assay is a rapid and inexpensive method for measuring DNA single-strand breaks. It also has an advantage over the other DNA damage-detecting methods, such as sister chromatid exchange, alkali elution, and micronucleus assay, because of its high sensitivity (Lee and Steinert, 2003Go). The Comet experiment we used was the alkaline version (pH >13) by Singh's method (1988). At pH >13, increased DNA migration is associated with increased levels of frank single-strand break (SSB) of DNA, and the SSB is associated with incomplete excision repair sites and alkali-labile sites (e.g., apurinic sites) (Kohn, 1991Go; Tice et al., 2000Go). This alkaline version of the Comet assay offers greatly increased sensitivity for identifying genotoxic agents. The first consensus made by an expert panel was that, in terms of a testing strategy for genetic toxicology, the alkaline version of the Comet assay was the methodology of choice (Tice et al., 2000Go).

Several parameters of Comet features have been developed. Bocker et al. (1997)Go summarized 10 measurement methods, and a new parameter, the tail profile, has been introduced by Bowden et al. (2003)Go. However, the TM, TD, and TL remain the most frequently used tail parameters (De Boeck et al., 2000Go). Among them, the TL was reported as the least sensitive parameter in the dose–response curve when compared with the TM and a head-tail ratio (Bocker et al., 1997Go). De Boeck et al. (2000)Go have also reported that the TL showed more inter-electrophoresis and inter-experimenter variation than the TD.

Even for healthy individuals, the variation of tail parameters between studies was considerable (1.2-fold to 26-fold) (Moller et al., 2000Go). The tail moments of the exposed and control groups in this study, however, were relatively similar to other benzene-exposed groups, as measured with Komet 4.0 software (Zhu et al., 2000Go). The average median of the tail moments of exposed workers ranges from 1.17 to 1.27 in our study, whereas the mean of the tail moments in the study of Zhu et al. (2000)Go for lymphocytes ranged from 1.47 to 2.25. For the controls, the values were 1.12–1.22 in our study and 1.39 in Zhu's study. Andreoli et al. (1997)Go have shown similar results; they report that the tail moment of the exposed group was 1.90 and that of the control group was 0.94. Lam et al. (2002)Go, however, showed lower values than ours; 0.74 for exposed subjects and 0.53 for controls.

Previous studies have shown that the parameters of TM and TD were generally highly correlated. The correlation between the TM and the TL of human lymphocytes was relatively lower than between the TM and the head-tail ratio, both in normal subjects and in ataxia telangiectasia patients (Bocker et al., 1997Go). It has also been reported that the second derivatives of the TM and those of the TD in the dose–time–response surface, which quantified DNA damage/repair, were highly correlated (Kim et al., 2002Go). For our data, the correlations among the four parameters are summarized in Table 6. Those between the TM, or the ETM, and the TD are generally higher than those for the TM and the TL, or the TD and the TL, in both the exposed and control groups. Over the cell types considered, the correlation coefficients between the TD and the TL are less than 0.2 in the control group, and between 0.2 and 0.7 in the exposed group. Although the correlation coefficients between the TM, or the ETM, and the TD are similar in both groups, those between the TM and the TL, or between the TD and the TL, are very different in both groups. The correlations between the ETM and the TL are also noted to be higher than those between the TM and the TL, because the ETM uses a tail length, whereas the TM uses a distance between the center of the head and the tail.


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TABLE 6 Correlations among the Tail Moment (TM), the Extent Tail Moment (ETM), the Tail DNA % (TD), and the Tail Length (TL) for Each of the Cell Types in the Human Exposed and Control Groups, Using the Median DNA Damage for Each Subject

 
The high correlations between the parameters of tail moments (TM or ETM) and the TD indicate that they are better parameters than the TL for expressing the DNA damage in human lymphocytes. Considering the report by Olive et al. (1992)Go that the TD was more accurate than the TM in comparing the sensitivity of the alkaline and neutral assays in an experimental cell study, it is of interest to investigate which parameter is more suitable for measuring DNA damages in a human biomonitoring study. To do this, we may need to use more sophisticated statistical techniques than the standard method such as Student's t-test. In this respect, empirical quantile dispersion graphs (EQDGs), developed by Lee and Khuri (1999Go, 2000)Go can help us not only to understand the shape of the distribution for values of DNA damages for a given tail parameter, but also to compare DNA damage between the exposed group and the control group. This graphical representation can be used satisfactorily to evaluate each parameter's consistency and stability for assessing DNA damage, as well as to determine the efficiency of tail parameters in comparing the two groups. Therefore, with the EQDGs, we can investigate the degree of differences among parameters, which allows us to make comprehensive comparisons of the Comet parameters.

In the EQDGs for all cell types we considered, only the TM shows consistently higher maximum quantile values in the exposed group than in the control group. Moreover, although the minimum quantile values of the TM and the ETM are almost unchanged over the range of probabilities, the values for the TD increase noticeably for large probability values, regardless of cell type. In this respect, the TM is a more efficient parameter than the others in comparing the exposed and control groups. For the B cells, which represent high levels of damage, however, the parameters of ETM and TD are also useful (see Figs. 1GoGo4). When considering the consistency of quantiles for DNA damage, the TM is preferred for human biomonitoring, for all cell types and for both the high and low damage status, because it gives the least variable estimates of DNA damage. As for the degree of uniformity of the observed quantiles, the parameter TM is more stable than the others for the lymphocytes and B cells, whereas the ETM and the TD provide stable estimates in the B cells and G cells (see Figs. 5GoGo8).

In conclusion, this study compared the Comet parameters of TM, ETM, TD, and TL in several ways; a comparison of means between the exposed group and the control group was made using Student's t-test. A relationship among those parameters was established using correlation analysis, and a more comprehensive evaluation of the parameters was done by using the so-called EQDGs. Considering all of the results from these analyses, it was shown that the TM is generally the preferred parameter among the four Comet parameters. Some other recommendations, however, have to be considered at this point. Tice et al. (2000)Go recommended that data on the TL and the TD should be provided when using the TM. De Boeck et al. (2000)Go have also pointed out that the TM should be addressed carefully and always in addition to the TD and/or the TL, because of its masking effect in some cases. In the present study, the TD also showed significant results, but at a different perspective from those of the TM or the ETM (see Table 1). It would therefore be advisable to produce the TM and the TD at the same time by using a computerized image-analysis system, and to present both sets of information as the tail parameters for human biomonitoring studies.


    ACKNOWLEDGMENTS
 
E.L. was supported by a grant from the Medical Research Center for Environmental Toxico-Genomics and Proteomics, funded by the Korea Science and Engineering Foundations and the Ministry of Science & Technology. J.L. was supported by Korea Research Foundation Grant KRF-2003–041-C00059. The authors appreciate the editor's and referees' comments and suggestions that helped to improve the contents of this article.


    NOTES
 

1 To whom correspondence should be addressed at Department of Preventive Medicine, College of Medicine, Korea University, 126-1, 5-ka, Anam-Dong, Sungbuk-Gu, Seoul 136-705, Korea. Fax: + 82-2-927-7220. E-mail: jyleeuf{at}korea.ac.kr.


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 Materials and Methods
 RESULTS
 DISCUSSION
 REFERENCES
 
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