**8. Gene-environment interactions and asbestosis**

We are presenting the example of an approach to gene-environment interaction research by summarising and building on the results of our studies that aimed to investigate the influence of interactions between different genotypes (*MnSOD*, *ECSOD*, *CAT*, *GSTM1*, *GSTT1*, *GSTP*, *iNOS*), between genotypes and smoking and between genotypes and cumulative asbestos exposure on the risk of developing asbestosis [6, 14, 116–119].

A nested case-control study included 262 cases with asbestosis and 265 controls with no asbestos-related disease. All the subjects included in the study were employed in the asbestos cement manufacturing plant of Salonit Anhovo, Slovenia, and occupationally exposed to asbestos. Data on smoking were obtained from all subjects using a standardised questionnaire [25, 120] and checked during the interview. The data on the cumulative asbestos exposure, expressed in fibres/cm3 -years [intensity in fibres per cm3 of air multiplied by time of exposure expressed in years], were available for all the subjects from the previous study [25]. The diagnosis of asbestosis or 'no asbestos-related disease' was based on the Helsinki Criteria for Diagnosis and Attribution of Asbestos Diseases [121] and on the American Thoracic Society recommendations [122]. Each case was confirmed by an interdisciplinary group of experts (consisting of an occupational physician, a radiologist and a pulmonologist) of the State Board for Recognition of Occupational Asbestos Diseases at the Clinical Institute of Occupational Medicine. Capillary blood samples from the finger tips of all cases and controls have been collected on FTA Mini Cards (Whatman Bioscience) for the isolation of deoxyribonucleic acid (DNA) and genotyping. All the genetic analyses were performed using PCR-based approaches as previously described [6, 14, 116–119].

Before testing interactions, the associations between outcome [in our case asbestosis] and individual variables were assessed using univariate logistic regression analysis. As expected, asbestosis was associated with cumulative asbestos exposure, whereas no association was found with smoking (OR = 0.98, 95%; CI = 0.69–1.39 for ever versus never smoking) [14]. Analysing the association between asbestosis and individual genotypes, an important association was observed between asbestosis and *MnSOD* genotype (OR = 1.50, 95% CI = 1.01– 2.24 for -9Ala/Ala versus combined Ala/Val and Val/Val genotypes) [118]. Only non-significantly elevated risk of asbestosis was observed for the *ECSOD* and *CAT* genotypes (OR = 1.63, 95% CI = 0.62–4.27 for *ECSOD* 213Arg/Gly versus the Arg/Arg genotype and OR = 1.36, 95% CI = 0.70–2.62 for *CAT* −262 TT compared to combined CT and CC genotypes, respectively) [117, 118]. Regarding GSTs, no association was found between asbestosis and *GSTM1*-null genotype (OR = 1.01, 95% CI = 0.71–1.43), while the presence of *GSTT1*-null genotype showed a protective effect for this disease (OR = 0.61, 95% CI = 0.40–0.94) [14]. On the other hand, *GSTP1* genotype coding for an enzyme with a high conjugation capacity versus genotypes resulting in an intermediate or low enzyme activity significantly increases the risk of developing asbestosis (OR = 1.49, 95% CI 1.06–2.10) [116]. A slightly elevated risk of asbestosis was also found for the *iNOS* LL genotype compared to the combined SL and SS genotypes (OR = 1.20, 95% CI = 0.85–1.69) [119]. Based on the above-mentioned results, it could be suggested that the genotypes may increase, decrease or have no effect on the risk of disease, in our case asbestosis.

tandem repeat polymorphisms have been associated with the transcriptional promoter activity, which has been shown to increase with the CCTTT repeat number. Based on that, alleles with 11 or fewer CCTTT repeats are usually defined as short alleles (S) and the ones with 12 or more repeats as long alleles (L). Accordingly, the subjects can have SS, SL or LL

We are presenting the example of an approach to gene-environment interaction research by summarising and building on the results of our studies that aimed to investigate the influence of interactions between different genotypes (*MnSOD*, *ECSOD*, *CAT*, *GSTM1*, *GSTT1*, *GSTP*, *iNOS*), between genotypes and smoking and between genotypes and cumulative asbestos

A nested case-control study included 262 cases with asbestosis and 265 controls with no asbestos-related disease. All the subjects included in the study were employed in the asbestos cement manufacturing plant of Salonit Anhovo, Slovenia, and occupationally exposed to asbestos. Data on smoking were obtained from all subjects using a standardised questionnaire [25, 120] and checked during the interview. The data on the cumulative asbestos exposure,

expressed in years], were available for all the subjects from the previous study [25]. The diagnosis of asbestosis or 'no asbestos-related disease' was based on the Helsinki Criteria for Diagnosis and Attribution of Asbestos Diseases [121] and on the American Thoracic Society recommendations [122]. Each case was confirmed by an interdisciplinary group of experts (consisting of an occupational physician, a radiologist and a pulmonologist) of the State Board for Recognition of Occupational Asbestos Diseases at the Clinical Institute of Occupational Medicine. Capillary blood samples from the finger tips of all cases and controls have been collected on FTA Mini Cards (Whatman Bioscience) for the isolation of deoxyribonucleic acid (DNA) and genotyping. All the genetic analyses were performed using PCR-based approaches

Before testing interactions, the associations between outcome [in our case asbestosis] and individual variables were assessed using univariate logistic regression analysis. As expected, asbestosis was associated with cumulative asbestos exposure, whereas no association was found with smoking (OR = 0.98, 95%; CI = 0.69–1.39 for ever versus never smoking) [14]. Analysing the association between asbestosis and individual genotypes, an important association was observed between asbestosis and *MnSOD* genotype (OR = 1.50, 95% CI = 1.01– 2.24 for -9Ala/Ala versus combined Ala/Val and Val/Val genotypes) [118]. Only non-significantly elevated risk of asbestosis was observed for the *ECSOD* and *CAT* genotypes (OR = 1.63, 95% CI = 0.62–4.27 for *ECSOD* 213Arg/Gly versus the Arg/Arg genotype and OR = 1.36, 95% CI = 0.70–2.62 for *CAT* −262 TT compared to combined CT and CC genotypes, respectively) [117, 118]. Regarding GSTs, no association was found between asbestosis and *GSTM1*-null genotype (OR = 1.01, 95% CI = 0.71–1.43), while the presence of *GSTT1*-null genotype showed

of air multiplied by time of exposure


**8. Gene-environment interactions and asbestosis**

exposure on the risk of developing asbestosis [6, 14, 116–119].

genotype [115].

164 Occupational Health

expressed in fibres/cm3

as previously described [6, 14, 116–119].

Univariate modelling was followed by multivariate analysis and interactions as the genes usually do not act independently, but may interact. To test the interactions, simple categorical models based on stratification were constructed first, followed by logistic regression models using dummy variables. The analysis showed that the association between asbestosis and *MnSOD* Ala-9Val genotypes was modified strongly by *CAT* −262 C>T genotypes. An increased risk of developing asbestosis was observed for the combined *MnSOD* -9Ala/Val and Val/Val genotypes compared to the Ala/Ala genotype only among those subjects who also had *CAT* −262TT genotype, suggesting an interaction, which was further confirmed by logistic regression analysis using dummy variables (OR = 4.49, 95% CI = 1.08–18.61) [6]. Considering that both MnSOD and CAT constitute a part of the primary defence system against ROS and catalyse the consecutive reactions in the detoxification of ROS [48, 74, 80, 82], this interaction could be considered as logical and biologically plausible. Similarly, the association between asbestosis and *iNOS* (CCTTT)n genotypes was also modified by CAT −262 C>T genotypes, where a higher asbestosis risk for the *iNOS* LL genotype versus the combined SL and SS genotypes was observed only among those who had *CAT* −262 TT genotype (OR = 4.78, 95% CI = 1.15–19.81) [6]. Taking into account that reactions between ROS and NO have been proposed to potentiate the cytotoxic and mutagenic effect of asbestos fibres [48, 51, 64, 71] and based on the assumption that NO produced by the catalytic activity of iNOS can function as a protective agent against toxic effects of H2O2 [123], which is detoxified by CAT [48, 74, 80, 82], and vice versa that H2O2 decreases the cytotoxicity of NO [124], this interaction could also be considered as biologically plausible [6].

Next, interactions between different genotypes and an important lifestyle factor—in our case smoking—have been tested. We observed that the *GSTM1*-null polymorphism did modify the association between smoking and asbestosis, although there was no independent association between either *GSTM1*-null polymorphism or smoking and asbestosis risk (OR = 2.67, 95% CI = 1.31–5.46) [6]. We can explain this modifying effect with the observation that both asbestos and smoking increase the production of ROS [46, 125, 126], which are known to be involved in the pathogenesis of asbestosis [23, 30, 46, 48–50]. It has been suggested that cigarette smoke and asbestos increase DNA damage and ROS production in pulmonary cells synergistically [125–127]. In line with these reports and considering the role of *GSTM1* in the defence against ROS [84–87], this observation could also be considered as biologically plausible [6]. Similarly, the association between smoking and asbestosis was modified by *iNOS* (CCTTT)n polymorphism (OR = 2.00, 95% CI = 0.99–4.03) [6]. Knowing that cigarette smoke is the largest source of NO that humans are exposed to and can also increase the expression and activity of iNOS [128, 129] and based on the suggestion that asbestos fibres may upregulate the activity

of iNOS and thus the production of NO, which is thought to play an important role in the initiation and progression of asbestosis [51, 70], this interaction could also be physiologically explained [6].

Finally, we present an example of the interaction between genotypes and environmental exposure, in our case occupational exposure to asbestos. In order to assess the interactions between the genotypes and occupational cumulative asbestos exposure, we have first constructed simple categorical models that included cumulative asbestos exposure categorised as follows: ≤11.23 fibres/cm3 -years and >11.23 fibres/cm3 -years (11.23 fibres/cm3 -years was the average cumulative asbestos exposure for the controls). In our analysis, we have observed that the association between asbestosis and cumulative asbestos exposure was modified by the iNOS (CCTTT)n genotypes (OR = 5.74; 95% CI = 3.30–9.99) [6].
