Asbestos exposure, which still represents an important health problem worldwide, is known to be associated with the development of asbestos-related diseases, including benign pleural diseases (e.g. pleural plaques), asbestosis, lung cancer, malignant mesothelioma (MM) and other types of cancer.1, 2 The pathogenesis of asbestos-related diseases is complicated and not entirely elucidated. Nevertheless, numerous studies have suggested that in addition to a direct mechanical injury, asbestos may stimulate the production of reactive oxygen and nitric species (ROS and RNS) that were shown to have an important role in the pathogenesis of these diseases. ROS and RNS may cause asbestos-related lung injury, DNA strand breaks in mesothelial cells and may increase the risk for developing malignancy.3, 4, 5
To detoxify ROS and consequently prevent the adverse effects of oxidative stress, the human organism possesses antioxidant defence systems. Glutathione (GSH), a tripeptide composed from glutamic acid, cysteine and glycine, is an abundant cellular antioxidant which has a major role in the protection against oxidative injury in cells. It serves as a substrate of many antioxidative enzymes.6, 7 The antioxidant capacity of the glutathione system depends on enzymes involved in its biosynthesis, such as glutamate cysteine ligase (GCL), also known as gamma glutamylcysteine synthetase, as well as on detoxification enzymes, such as glutathione S-transferases (GSTs).6,8, 9, 10
GCL is the rate limiting enzyme of the GSH synthesis and it is suggested to be the major factor that determines GSH level in healthy subjects. The enzyme consists of two subunits: a heavy catalytic subunit (GCLC) and a light modifier subunit (GCLM).6,10 High GSH concentration levels found in many tumors have been associated with the increased GCL activity.11, 12
GSTs are phase II detoxifying enzymes involved in the inactivation of the electrophiles produced by ROS and RNS by catalyzing the conjugation of electrophilic compounds with reduced glutathione.8, 9 In mammals, seven classes of cytosolic GST isoenzymes have been recognized: Alpha, Mu, Pi, Sigma, Theta, Omega and Zeta.13 The crucial GST enzyme in the human lung, which belongs to the Pi class, is GSTP1.14, 15 Two other important polymorphic GSTs are GSTM1 (Mu class) and GSTT1 (Theta class).15, 16
Genes coding for GSH related enzymes are polymorphic. Among the most commonly investigated promoter polymorphisms of the
Regarding
The present study aimed to investigate the influence of
The cross sectional study included all together 940 asbestos-exposed subjects, among them 390 subjects with pleural plaques, 147 subjects with asbestosis, 225 subjects with MM and 178 subjects with no asbestos-related disease. Subjects with pleural plaques, asbestosis and MM were considered as cases, and those with no asbestos-related disease as controls.
Additionally, comparison was made between subjects with MM and subjects with pleural plaques.
Subjects with pleural plaques, asbestosis and subjects with no asbestos-related disease were presented at the State Board for the Recognition of Occupational Asbestos Diseases in the period from 1 January 1998 to 31 December 2007 and were all occupationally exposed to asbestos. The information on all the subjects included was revised in 2018 to verify the latest diagnoses of asbestos-related diseases. Subjects with MM were recruited at the Institute of Oncology Ljubljana, where they were treated in the period between 1 February 2004 and 31 December 2018. The study was approved by the Slovenian Ethics Committee for Research in Medicine and was carried out according to the Declaration of Helsinki.
The diagnosis of pleural plaques, asbestosis or “no asbestos-related disease” was verified by two groups of experts of the State Board for the Recognition of Occupational Asbestos Diseases, each group consisting of a specialist of occupational medicine, a pulmonologist, and a radiologist. Subjects with pleural MM were diagnosed by ultrasound-guided biopsy or thoracoscopy and those with peritoneal MM by laparoscopy. The diagnosis of MM was proved histopathologically by a pathologist experienced in diagnosing this malignant disease.
Data on smoking were collected during an interview based on a standardized questionnaire. The number of pack-years of smoking was calculated from the duration of smoking and the number of cigarettes smoked per day.
Data on cumulative asbestos exposure in fibres/ cm3-years were available for the subjects with pleural plaques, asbestosis, “no asbestos-related disease” and for 28 patients with MM. Based on the data on cumulative asbestos exposure, the asbestos exposures in these subjects were divided into three groups: low (< 11 fibres/cm3-years), medium (11–20 fibres/cm3-years) and high (> 20 fibres/cm3-years) asbestos exposure. For the subjects with MM who lacked the data on cumulative asbestos exposure, asbestos exposures were assessed based on the precise work history and comparison with exposures of the group of subjects with known cumulative asbestos exposure. Accordingly, their asbestos exposures were divided into three groups with presumed low, medium or high asbestos exposure.
Genomic DNA was extracted from peripheral blood samples using Qiagen FlexiGene Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions.
Standard descriptive statistics was used to describe central tendency and variability of investigated variables. Chi-square test and Kruskal-Wallis test were used to compare categorical and continuous variables among different groups, respectively. Deviation from Hardy-Weinberg equilibrium (HWE) was also evaluated using chi-square test. Dominant and additive genetic models were used in the analysis. To compare genotype frequencies among groups, univariable and multivariable logistic regression models were used and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Characteristics used for adjustment in multivariable analysis were selected using stepwise forward-conditional logistic regression. The possible interactions between genotypes as well as between genetic polymorphisms, and between genetic polymorphisms and asbestos exposure were tested by logistic regression models using dummy variables.
Statistical analysis was carried out with IBM SPSS Statistics version 21.0 (IBM Corporation, Armonk, NY, USA). All statistical tests were two-sided and the level of significance was set at 0.05.
The characteristics of the groups of subjects with pleural plaques, asbestosis, MM and subjects without asbestos-related disease are presented in Table 1. A statistically significant difference between the groups was observed for the age (p < 0.001), pack-years of smoking (p = 0.024) and asbestos exposure (p < 0.001). The mean age was the highest for subjects with MM (65 ± 10.7 years), followed by subjects with asbestosis (58.7 ± 9.1 years).
Characteristics of subjects without asbestos-related disease, subjects with pleural plaques, asbestosis or malignant mesothelioma
Characteristic | No disease (N = 178) | Pleural plaques (N = 390) | Asbestosis (N = 147) | Malignant mesothelioma (N = 225) | P | |
---|---|---|---|---|---|---|
Male, N (%) | 119 (66.9) | 277 (71.0) | 110 (74.8) | 164 (72.9) | 0.407 | |
Gender | Chi-square = 2.905, | |||||
Female, N (%) | 59 (33.1) | 113 (29.0) | 37 (25.2) | 61 (27.1) | df = 3 | |
Mean ± SD | 57.6 ± 9.5 | 55.8 ± 9.5 | 58.7 ± 9.1 | 65.0 ± 10.7 | ||
Age (years) | Median (25%–75%) | 56.6 (49.6–65.1) | 55.0 (48.8–62.7) | 59.1 (51.4–65.3) | 66 (58–73) | Test-statistic < 0.001 = 115.390 |
Min–max | 38.2–79.9 | 34.4–85.8 | 37.2–79.2 | 19–95 | ||
No, N (%) | 95 (53.4) | 193 (49.5) | 72 (49.0) | 117 (53.7) [7] | 1.614 | |
Smoking | Chi-square = 0.656, | |||||
Yes, N (%) | 83 (46.6) | 197 (50.5) | 75 (51.0) | 101 (46.3) | df = 3 | |
Mean ± SD | 21.0 ± 15.8 [4] | 18.1 ± 15.6 [22] | 24.4 ± 18.6 [2] | 23.2 ± 17.2 [14] | ||
Pack-(smokers years of only) smoking | Median (25%–75%) | 20 (9–30) | 15 (5–28) | 22.8 (10–32.7) | 20 (8–35) | Test-statistic 0.024 = 9.474 |
Min–max | 0.1–65.3 | 0.05–96.6 | 0.15–90 | 1–69 | ||
Low, N (%) | 138 (77.5) | 277 (72.3) [7] | 75 (51.7) [2] | 34 (45.9) [151] | ||
< 0.001 | ||||||
Asbestos exposure | Middle, N (%) | 13 (7.3) | 38 (9.9) | 28 (19.3) | 23 (31.1) | Chi-square = 53.864, |
High, N (%) | 27 (15.2) | 68 (17.8) | 42 (29.0) | 17 (23.0) | df = 6 |
Number of missing data is presented in [] brackets. P-values were calculated using chi-square test for categorical or Kruskal-Wallis test for continuous variables. SD = standard deviation
The mean values of pack-years of smoking were the highest in subjects with asbestosis (24.4 ± 18.6) and in subjects with MM (23.2 ± 17.2). Regarding asbestos exposure, the percent of subjects with low asbestos exposure was the highest for the group of subject with no asbestos-related disease (77.5%), followed by the group of subjects with pleural plaques (72.3%) (Table 1).
The genotype frequencies for all studied genetic polymorphisms are shown in Table 2. Genotype frequencies for all investigated SNPs were concordant with HWE.
Genotype frequencies in all subjects, subjects without asbestos-related disease, subjects with pleural plaques, asbestosis and malignant mesothelioma
Polymorphism | Genotype | All subjects (N = 940) | No disease (N = 178) | Pleural plaques (N = 416) | Asbestosis (N = 160) | Malignant mesothelioma (N = 154) |
---|---|---|---|---|---|---|
CC | 772 (82.1) | 149 (83.7) | 310 (79.5) | 124 (84.4) | 189 (84) | |
CT | 162 (17.2) | 29 (16.3) | 78 (20) | 23 (15.6) | 32 (14.2) | |
TT | 6 (0.6) | 0 (0) | 2 (0.5) | 0 (0) | 4 (1.8) | |
CC | 581 (61.8) | 114 (64) | 233 (59.7) | 87 (59.2) | 147 (65.3) | |
CT | 306 (32.6) | 54 (30.3) | 135 (34.6) | 51 (34.7) | 66 (29.3) | |
TT | 53 (5.6) | 10 (5.6) | 22 (5.6) | 9 (6.1) | 12 (5.3) | |
present | 384 (40.9) | 74 (41.6) | 159 (40.8) | 64 (43.5) | 87 (38.7) | |
null genotype | 556 (59.1) | 104 (58.4) | 231 (59.2) | 83 (56.5) | 138 (61.3) | |
present | 782 (83.2) | 138 (77.5) | 330 (84.6) | 128 (87.1) | 186 (82.7) | |
null genotype | 158 (16.8) | 40 (22.5) | 60 (15.4) | 19 (12.9) | 39 (17.3) | |
AA | 454 (78.3) | 78 (43.8) | 202 (51.8) | 76 (51.7) | 98 (43.6) | |
AG | 394 (41.9) | 81 (45.5) | 155 (39.7) | 55 (37.4) | 103 (45.8) | |
GG | 92 (9.8) | 19 (10.7) | 33 (8.5) | 16 (10.9) | 24 (10.7) | |
CC | 785 (83.5) | 141 (79.2) | 334 (85.6) | 121 (82.3) | 189 (84) | |
CT | 146 (15.5) | 34 (19.1) | 54 (13.8) | 23 (15.6) | 35 (15.6) | |
TT | 9 (1.0) | 3 (1.7) | 2 (0.5) | 3 (2) | 1 (0.4) |
In univariate logistic regression analysis, no association was found between
The association between different asbestos-related diseases and genotypes in univariate analysis
Asbestos-related disease | Pleural plaques | Asbestosis | MM | MM | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Polymorphism | Genotype | ||||||||||
OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | ||
CC | Reference | Reference | Reference | Reference | Reference | ||||||
rs17883901 | CT+TT | 1.15 (0.74–1.78) | 0.541 | 1.33 (0.83–2.12) | 0.237 | 0.95 (0.52–1.73) | 0.874 | 0.98 (0.57–1.67) | 0.937 | 0.74 (0.48–1.14) | 0.169 |
CC | Reference | Reference | Reference | Reference | Reference | ||||||
CT | 1.14 (0.80–1.63) | 0.476 | 1.22 (0.83–1.80) | 0.308 | 1.24 (0.77–1.99) | 0.378 | 0.95 (0.61–1.46) | 0.809 | 0.77 (0.54–1.11) | 0.164 | |
rs41303970 | TT | 1.05 (0.51–2.15) | 0.895 | 1.08 (0.49–2.35) | 0.853 | 1.18 (0.46–3.03) | 0.732 | 0.93 (0.39–2.23) | 0.872 | 0.86 (0.42–1.80) | 0.697 |
CT+TT | 1.13 (0.80–1.58) | 0.495 | 1.20 (0.83–1.73) | 0.330 | 1.23 (0.78–1.93) | 0.369 | 0.95 (0.63–1.43) | 0.788 | 0.79 (0.56–1.11) | 0.170 | |
present | Reference | Reference | Reference | Reference | Reference | ||||||
null genotype | 1.04 (0.74–1.44) | 0.828 | 1.03 (0.72–1.48) | 0.857 | 0.92 (0.59–1.44) | 0.721 | 1.13 (0.76–1.69) | 0.554 | 1.09 (0.78–1.53) | 0.608 | |
present | Reference | Reference | Reference | Reference | Reference | ||||||
null genotype | 0.63 (0.42–0.95) | 0.63 (0.40–0.98) | 0.51 (0.28–0.93) | 0.72 (0.44–1.18) | 0.198 | 1.15 (0.74–1.79) | 0.527 | ||||
AA | Reference | Reference | Reference | Reference | Reference | ||||||
AG | 0.80 (0.57–1.13) | 0.209 | 0.74 (0.51–1.07) | 0.114 | 0.70 (0.44–1.11) | 0.129 | 1.01 (0.67–1.53) | 0.955 | 1.37 (0.97–1.94) | 0.075 | |
GG | 0.80 (0.45–1.40) | 0.428 | 0.67 (0.36–1.25) | 0.208 | 0.86 (0.41–1.80) | 0.698 | 1.01 (0.51–1.97) | 0.988 | 1.50 (0.84–2.67) | 0.170 | |
AG+GG | 0.80 (0.58–1.11) | 0.185 | 0.73 (0.51–1.04) | 0.078 | 0.73 (0.47–1.13) | 0.157 | 1.01 (0.68–1.5) | 0.958 | 1.39 (1.00–1.94) | ||
CC | Reference | Reference | Reference | Reference | Reference | ||||||
rs1138272 | CT+TT | 0.70 (0.46–1.05) | 0.087 | 0.64 (0.40–1.01) | 0.056 | 0.82 (0.47–1.43) | 0.482 | 0.73 (0.44–1.21) | 0.216 | 1.14 (0.72–1.79) | 0.583 |
Statistically significant results are printed in bold. MM = malignant mesothelioma
Regarding age, no association was found between age and pleural plaques (OR = 0.98; 95% CI = 0.96–1.00; p = 0.032). A slight association was observed between age and MM (OR = 1.07; 95% CI = 1.05–1.10; p < 0.001), as well as between age and MM when compared to pleural plaques (OR = 1.10; 95% CI = 1.08–1.12; p < 0.001).
The analysis of association between asbestos exposure and asbestos-related diseases revealed a positive association between high and medium
In multivariate logistic regression analysis, the risk of
The association between different asbestos-related diseases and genotypes in multivariate analysis
Asbestos-related disease | Pleural plaques | Asbestosis | MM | MM | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Polymorphism | Genotype | ||||||||||
OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | ||
CC | Reference | Reference | Reference | Reference | Reference | ||||||
rs17883901 | CT+TT | 1.18 (0.75–1.86) | 0.466 | 1.33 (0.83–2.12) | 0.240 | 0.96 (0.52–1.78) | 0.893 | 0.66 (0.28–1.57) | 0.344 | 0.57 (0.26–1.23) | 0.154 |
CC | Reference | Reference | Reference | Reference | Reference | ||||||
CT | 1.16 (0.8–1.68) | 0.431 | 1.22 (0.82–1.79) | 0.323 | 1.10 (0.67–1.81) | 0.695 | 0.98 (0.51–1.87) | 0.945 | 0.76 (0.43–1.36) | 0.360 | |
rs41303970 | TT | 1.16 (0.55–2.42) | 0.696 | 1.06 (0.48–2.32) | 0.883 | 1.37 (0.52–3.63) | 0.524 | 1.13 (0.33–3.84) | 0.844 | 1.05 (0.35–3.09) | 0.934 |
CT+TT | 1.16 (0.82–1.64) | 0.406 | 1.19 (0.82–1.72) | 0.351 | 1.14 (0.72–1.83) | 0.576 | 1.00 (0.55–1.84) | 0.994 | 0.80 (0.47–1.38) | 0.429 | |
present | Reference | Reference | Reference | Reference | Reference | ||||||
null genotype | 1.04 (0.74–1.46) | 0.837 | 1.06 (0.74–1.53) | 0.738 | 0.84 (0.53–1.34) | 0.464 | 1.09 (0.60–1.98) | 0.774 | 1.09 (0.63–1.87) | 0.756 | |
present | Reference | Reference | Reference | Reference | Reference | ||||||
null genotype | 0.62 (0.41–0.94) | 0.63 (0.4–0.99) | 0.51 (0.27–0.95) | 1.00 (0.48–2.08) | 0.996 | 1.28 (0.65–2.53) | 0.479 | ||||
AA | Reference | Reference | Reference | Reference | Reference | ||||||
AG | 0.78 (0.54–1.11) | 0.162 | 0.74 (0.51–1.07) | 0.113 | 0.65 (0.40–1.06) | 0.087 | 1.23 (0.66–2.32) | 0.513 | 1.86 (1.04–3.30) | ||
GG | 0.8 (0.45–1.43) | 0.461 | 0.67 (0.36–1.24) | 0.203 | 0.96 (0.45–2.06) | 0.920 | 1.65 (0.65–4.16) | 0.288 | 2.40 (1.04–5.54) | ||
AG+GG | 0.78 (0.56–1.1) | 0.153 | 0.72 (0.51–1.04) | 0.077 | 0.71 (0.45–1.12) | 0.140 | 1.31 (0.72–2.39) | 0.370 | 1.97 (1.14–3.39) | ||
CC | Reference | Reference | Reference | Reference | Reference | ||||||
rs1138272 | CT+TT | 0.68 (0.44–1.04) | 0.078 | 0.64 (0.4–1.02) | 0.059 | 0.84 (0.47–1.51) | 0.565 | 0.73 (0.34–1.60) | 0.433 | 1.02 (0.49–2.13) | 0.965 |
MM = malignant mesothelioma. Statistically significant results are printed in bold.
Adjustments made: Asbestos-related disease
In further logistic regression analysis, the interactions between polymorphisms showed no significant influence on the risk for developing asbestos-related diseases (data not shown).
Testing the influence of interactions between asbestos high and medium
The present study investigated the influence of genetic polymorphisms in GSH related genes, the interactions between these polymorphism, and interactions between polymorphisms and asbestos exposure on the risk of asbestos-related diseases.
The present study revealed a protective effect of
The results of our study showed that
Our study revealed no influence of
Our study confirmed the impact of high and medium
In this study, the interactions between investigated GSH related gene polymorphisms did not influence the risk for developing asbestos-related diseases. On the other hand, we observed that the interaction between
Another interesting finding of this study showed that the interaction between
Considering the potential limitations of the study, the data on asbestos exposure were not available for all subjects, especially not for patients with MM. Consequently, the analyses of the interactions between genetic polymorphisms and asbestos exposure could be performed only for the subgroup of MM patients.
On the other hand, the study also brings novel findings and has some important strengths. Firstly, according to our knowledge, this is the first study to investigate the association between
In conclusion, our findings suggest that among genetic polymorphisms in GSH related genes,