Interaction Between Occupational Exposures and Antioxidant Genes on Chronic Obstructive Pulmonary Disease in UK Biobank - European Medical Journal

Interaction Between Occupational Exposures and Antioxidant Genes on Chronic Obstructive Pulmonary Disease in UK Biobank

3 Mins
EMJ Respiratory 8.1 2020 Feature Image
*Diana A. van der Plaat,1 Sara De Matteis,1,2 Steven Sadhra,3 Debbie Jarvis,1 Paul Cullinan,1 Cosetta Minelli1

Dr van der Plaat has received funding from the European Respiratory Society (ERS) and the European Union’s (EU) H2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 713406. The other authors have declared no conflicts of interest.

EMJ Respir. ;8[1]:77-78. Abstract Review No. AR8.
Antioxidants, chronic obstructive pulmonary disease (COPD), gene–environment interaction, occupational exposures.

Each article is made available under the terms of the Creative Commons Attribution-Non Commercial 4.0 License.


Occupational exposure to vapours, gases, dusts, and fumes (VGDF) has been associated with lower lung function1 and a higher risk of chronic obstructive pulmonary disease (COPD).2 The proportion of COPD attributable to occupational exposures has been estimated at 14%.3 A proposed mechanism underlying the effect of VGDF on COPD is through oxidative stress. A reduced antioxidant capacity has been found in COPD patients4 and higher levels of oxidative stress biomarkers have been associated with exposure to VGDF.5 The effect of VGDF on the lung might be apparent (or might be substantial) only in the presence of genetic variation (e.g., single nucleotide polymorphisms [SNP]) in antioxidant genes, indicating a gene–environment interaction. The study aimed to identify interactions between variants in well-known antioxidant genes and VGDF exposure on COPD risk.


To assess antioxidant gene–VGDF interactions, the authors included 199,607 working individuals from the large UK Biobank (UKB; aged 39–71; 49% male; 44% never-smoker). Of these, 16,389 individuals had COPD spirometrically defined as forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC)< lower limit of normal (GLI-2012) and 34% were exposed to VGDF estimated using the airborne chemical (ACE) job exposure matrix.6 All independent SNP within 15 antioxidant genes selected based on a recent review were analysed.7 Gene–VGDF interactions were invested using a case-only approach using BOLT-LMM adjusted for sex, age, height, smoking status, genotyping batch, and centre, and accounting for population stratification/relatedness. Analyses were stratified according to smoking status. For significant interacting SNP, the authors assessed effects on gene-expression and DNA methylation levels using the online tool PhenoScanner.8


Overall, subjects exposed to VGDF had a 7% increased risk of COPD (Table 1a). However, this increase in risk was only seen in ever-smokers and was significantly different to never-smokers (interaction p=8.79×10-5). In the SNP–VGDF interaction analyses, the authors identified nine nominally significant interactions (p<0.05) for the antioxidant genes CAT (two SNP), GC (two SNP), GSTP1, GSTT1, NOS1, SOD1, and SOD2. Except for a SNP in GC, none of the SNP had a marginal effect on COPD and would therefore not be found if ignoring the effect modification by VGDF. Of the nine SNP, only two rare SNP with minor allele frequencies <3% in GSTP1(rs8191445) and NOS1 (rs145671209) survived correction for multiple testing (false discovery rate <5%). Subjects exposed to VGDF and carrying a copy of the minor allele of the GSTP1 and NOS1 SNP had a respective 19% and 30% higher risk of COPD compared to subject not exposed to VGDF and not carrying a copy of the minor allele (Table 1b). Although the interactions were only significant in never-smokers, the three-way SNP–VGDF–smoking interactions were not significant (p=0.338 for GSTP1 and p=0.460 for NOS1). The GSTP1 SNP was associated with expression of two nearby genes (DOC2GP/NDUFS8) in whole blood. No association was found with DNA methylation for either SNP.

Table 1: Results of the association analysis of A) VGDF with COPD (marginal effect of VGDF); and B) of the SNP-VGDF interaction analyses for both the GSTP1 and the NOS1 SNP, stratified by smoking.
Significant results are presented in bold.
CI: confidence interval; COPD: chronic obstructive pulmonary disease; OR: odds ratio; SNP: single nucleotide polymorphism; VGDF: vapours, gases, dusts, and fumes.


These results suggest that VGDF exposure is associated with a higher risk of COPD, but that this risk may be confined to smokers. Those with rare variations in the antioxidant genes GSTP1 and NOS1 may be more susceptible to the effects of VGDF on COPD, and this effect might be more apparent in never-smokers. Further work is needed to replicate these results in independent samples and to investigate the possibility of three-way SNP–VGDF–smoking interactions.

Mehta AJ et al. Occupational exposure to dusts, gases, and fumes and incidence of chronic ob-structive pulmonary disease in the Swiss Cohort Study on Air Pollution and Lung and Heart Dis-eases in Adults. Am J Respir Crit Care Med. 2012;185(12):1292-300. de Jong K et al. Pesticides and other occupational exposures are associated with airway ob-struction: the LifeLines cohort study. Occup Environ Med. 2014;71(2):88-96. Blanc PD et al. The occupational burden of nonmalignant respiratory diseases. An official Ameri-can Thoracic Society and European Respiratory Society statement. Am J Respir Crit Care Med. 2019;199(11):1312-34. Kirkham PA, Barnes PJ. Oxidative stress in COPD. Chest. 2013;144(1):266-73. Soleimani E et al. Occupational exposure to chemicals and oxidative toxic stress. Toxicol Environ Health Sci. 2015;7(1):1-24. Sadhra SS et al. Development of an occupational airborne chemical exposure matrix. Occup Med (Lond). 2016;66(5):358-64. Fuertes E et al. Antioxidant genes and susceptibility to air pollution for respiratory and cardio-vascular health. Free Radic Biol Med. 2020;151:88-98. Kamat MA et al. PhenoScanner V2: an expanded tool for searching human genotype-phenotype associations. Bioinformatics. 2019;35(22):4851-3.

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