GSH plays a vital role in the lung, defending airway epithelium from damage in response to oxidants and inflammation (1
). However, little is known about the role of glutathione, or about the genes that regulate it, with respect to normal lung function development in children exposed to air pollution. In this study, we observed that variation in the glutathione synthesis gene, GSS
, was associated with differences in susceptibility to the harmful effects of ambient air pollution on children's lung function growth.
We have previously demonstrated a negative association between air pollutants and lung function growth (16
). Whereas the average levels of ozone were not significantly correlated across communities with any other study pollutant, the correlations between other pairs of pollutants were all significant. Thus, nitrogen dioxide and the particulate matter pollutants can be regarded as a correlated suite of pollutants with a similar pattern relative to each other across the 12 communities. In this study, we observed that the negative effects of this suite of air pollutants on children's lung function growth largely occurred in children with the “0100000” haplotype (prevalence of 48%) but not in children with other GSS
haplotypes. In single-pollutant models, an opposite trend was observed for ozone. The effects of ozone on lung function growth were most detrimental in children who did not have the “0100000” haplotype. Results remained consistent in models that jointly adjusted for O3
(as a surrogate for our correlated pollutants).
gene, which encodes human glutathione synthetase, contains 12 coding and 1 noncoding exon and is located at chromosome 20q11.2 (10
). Mutations in GSS
have been shown to affect stability, catalytic capacity, and substrate affinity of the enzyme (10
). The substrate of GSS
can be used for two different reactions, making GSH and making γ-glutamylcyclotransferase. Variation in GSS
could alter the enzymatic reactions in vivo
in favor of creating γ-glutamylcyclotransferase, thereby decreasing availability of the antioxidant GSH. A wide-scale reduction in available GSH would have long-term implications for antioxidant defense in the developing lungs of children under normal conditions, which would be magnified only under conditions of higher oxidative stress, such as when exposed to higher air pollutant levels.
Exposure to air pollutants has been associated with an initial depletion of intracellular GSH followed by a later rebound increase in GSH as an adaptive response to oxidant stress (2
). Genetic variation in GSH genes that diminishes GSH synthesis might exacerbate air pollutant–induced lung injury by delaying this ability to rebound in response to stimuli. The “0100000” haplotype is the most common haplotype of GSS
, occurring in 48% of the children. In our population, this haplotype can be distinguished from all others by evaluating the SNP RS1801310. However, the RS1801310 SNP is an intronic tag SNP whose functionality is currently unknown. Further investigation of genetic variation in GSS
in relation to this haplotype may shed light on which particular regions of the gene or nearby genes in linkage disequilibrium are most relevant in association with air pollution–induced deficits in lung function.
The observed association in our data that haplotype “0100000” appears protective against the effects of ozone on MMEF is puzzling. The biological mechanisms through which air pollutants trigger oxidative stress pathways are not well characterized. Ozone and other pollutants may trigger different biological responses to exposure that are reflected, in part, by our observed differences in lung function effects by GSS
haplotype. In support of our ozone results, an experiment in mice known to be deficient in GSH demonstrated that these mice had less ozone-induced lung injury than did wild-type mice (22
). Although the mouse model involved knockout of GCLM
rather than the GSS
gene, genetic variation in GSS
that reduces GSH may also lead to similar results, as our data suggest.
A strength of this study was the long-term, prospective nature of the data with consistent follow-up and measurement of exposure and outcome data. However, certain limitations should also be considered. Given the complex modeling framework for these analyses, we are limited in our power to detect significant interactions because we are, in effect, testing a three-way interaction between air pollutant, age (for growth curve of lung function), and haplotype.
Confounding by population admixture is often a concern with genetic studies. We controlled for admixture by adjusting for ancestry variables in addition to typical adjustment for self-reported race and ethnicity. The ancestry variables provided better control for genetic descent of four distinct groups: African, European, American Indian, and East Asian. Adjusting for these variables did not appreciably change our results. In addition, a sensitivity analysis of our main results only among non-Hispanic white subjects supported our main results.
The observed effects could also be explained by underlying associations of the exposures and outcome to unmeasured confounding variables. Although we adjusted for known potential confounders including personal characteristics, the possibility of confounding by other factors still exists. For example, dietary intake of antioxidants may modulate effects of air pollution (23
). However, we do not have information about dietary supplementation. Thus, if supplementation with antioxidants differed both by community (and thus air pollution level) as well as by lung function, residual confounding of our association may be present.
Use of residential address to assess air pollution exposure may result in misclassification of exposure, because activity patterns outside the home were not explicitly monitored. However, for the age range (10
–18 yr) of our participants, we and others have found use of residential address to be a reasonable proxy for overall exposure. The catchment areas for the respective elementary schools participating in our study tended to represent small and well-defined neighborhood-scale areas in generally suburban areas. Written questionnaires documented their respective general patterns of activity, including how subjects got from home to school and whether weekday and weekend mornings and afternoons were spent indoors or outdoors. On the basis of these limited responses, exposure assignments based on home locations were judged to be generally representative of subjects' cumulative exposure.
Over the 8-year follow-up period, approximately 10% of study subjects were lost to follow-up each year. Attrition is a potential source of bias in a cohort study if loss to follow-up is related to both exposure and outcome. However, we did not see evidence that the loss of subjects was related to either baseline lung function or exposure to air pollution (16