Particulate Air Pollution, Oxidative Stress Genes, and Heart Rate Variability in an Elderly Cohort

Table 1 shows the levels and distribution of the variables used in this study, overall, and for the different combinations of GSTM1 genotype and HMOX 1 microsatellite repeat length. The study participants were all male, with average age of 72.8 years (SD = 6.6 years) at the first HRV measurement. No differences among the subpopulations defined by the combinations of GSTM1 genotype [wild-type or null] and HMOX-1 microsatellite repeat length [< 25 (GT)n repeats in both alleles or ≥ 25 (GT)n repeats in at least one allele] were found in age, BMI, systolic blood pressure, diastolic blood pressure, mean arterial pressure, heart rate, fasting blood glucose, total cholesterol, high-density lipoproteins (HDL), triglyceride, smoking status, alcohol intake (≥ 2 drinks/day), history of coronary heart disease (CHD), diabetes, hypertension, or stroke, and use of beta-blockers, calcium channel blockers, or ACE inhibitors (Table 1). The two genes were not associated with each other (p > 0.67).

Table 2 shows the results of the analyses for the association of PM_2.5 with changes inHRV for the entire population (model 1), by GSTM1 genotype (model 2), and by HMOX-1 microsatellite (GT)n repeat length (model 3).

For the entire population, we found that a 10 μg/m³ increase in ambient PM_2.5 in the 48 hr before the HRV measurement was associated with a 6.8% decrease in SDNN [95% confidence interval (CI), −12.9 to −0.2; p = 0.043] and with a 17.3% decrease in HF (95% CI, −30.0 to −2.3; p = 0.026). Ambient PM_2.5 concentrations were also negatively associated with LF (estimated change = −11.2%, 95% CI, −22.8 to 2.2), but the result was not statistically significant (p = 0.10).

The PM_2.5–HRV association was modified by GSTM1 genotype, with PM_2.5 concentrations negatively associated with SDNN, HF, and LF in GSTM1-null subjects, whereas no association between PM_2.5 and HRV was found in GSTM1–wild-type carriers. In subjects with the GSTM1-null deletion, a 10-μg/m³ increase in PM_2.5 was associated with a 10.5% decrease in SDNN (95% CI, −18.2 to −2.2; p = 0.015), a 24.2% decrease in HF (95% CI, −39.2 to −5.5; p = 0.014), and a 17.0% decrease in LF (95% CI, −31.0 to −0.2; p = 0.048). In GSTM1–wild-type subjects, the estimated decreases in HRV for a 10-μg/m³ increase in PM_2.5 were 2.0% (95% CI, −11.3 to 8.3; p = 0.69) for SDNN, 4.0% (95% CI, −24.8 to 22.6; p = 0.74) for HF, and 0.6% (95% CI, −19.0 to 22.0; p = 0.95) for LF. However, the p-values for statistical interactions between PM_2.5 and GSTM1 genotype were not significant.

Similarly, we found that that PM_2.5–HRV association was modified by HMOX-1 genotypes. Ambient PM_2.5 concentrations were negatively associated with all three HRV outcomes in carriers of at least one allele with ≥ 25 microsatellite (GT)n repeats in the HMOX-1 promoter region, whereas no association between PM_2.5 and HRV was present in carriers of < 25 repeats in both alleles. In subjects with at least one allele with ≥ 25 microsatellite (GT)n repeats, a 10-μg/m³ increase in PM_2.5 was associated with a 8.5% decrease in SDNN (95% CI, −14.8 to −1.8; p = 0.014), a 20.1% decrease in HF (95% CI, −32.9 to −5.0; p = 0.012), and a 14.0% decrease in LF (95% CI, −25.7 to −0.5; p = 0.043). The p-value for statistical interactions between PM_2.5 and GSTM1 genotype was marginally significant (p = 0.059) when the SDNN component of HRV was considered but was not significant for HF (p = 0.14) and LF (p = 0.11).

We further evaluated the interrelationship between PM_2.5, GSTM1, and HMOX-1 by estimating the effect of PM_2.5 on HRV within each combination of the GSTM1 genotypes and HMOX-1 microsatellite repeat length categories (Table 3). These results indicate a clear trend of increasingly negative coefficients as we move across gene categories. In carriers of both the GSTM1-null deletion and at least one allele with ≥ 25 HMOX-1 microsatellite (GT)n repeats, PM_2.5 was negatively associated with all three HRV outcomes, whereas no significant association was found in subjects with any other combinations. In subjects carrying the GSTM1-null deletion and at least one allele with ≥ 25 HMOX-1 microsatellite (GT)n repeats, a 10-μg/m³ increase in PM_2.5 in the 48 hr before the HRV measurement was associated with a −12.7% decrease in SDNN (95% CI, −20.6 to −3.9; p = 0.0059), a 27.8% decrease in HF (95% CI, −43.0 to −8.5; p = 0.0073), and a 20.1% decrease in LF (95% CI, −34.5 to −2.7; p = 0.0261). GSTM1 genotypes and HMOX-1 microsatellite repeat lengths had a combined effect on the association between PM_2.5 and HRV, as shown in Table 3 by the significant three-way interaction term between GSTM1, HMOX-1, and PM_2.5 (coded as PM_2.5 × a trend variable that is 1 for GSTM1 present and both short repeats, 2 for GSTM1 null and both short repeats, 2 for one long repeat and GSTM1 present, and 4 for GSTM1 null and at least one long repeat).

To test whether the effect modification by genotype was driven by a few individuals or represented a more general shifting of the distribution of PM_2.5–HRV slopes, we refit our mixed models, dropping the interaction terms with genotype but allowing for random subject-specific slopes. Figure 1 shows the distribution of subject-specific PM_2.5 slopes for SDNN by three categories of genotype (HMOX-1 < 25 repeats and GSTM1 wt, either HMOX-1 ≥ 25 repeats or GSTM1 null, or both HMOX-1 ≥ 25 repeats and GSTM1 null). The shift to the left of the distributions does not appear to be driven by outliers. The same shift in the distributions was observed also for the HF and LF components (data not shown).

Goodness of fit of the three-way interaction models was evaluated using the Akaike Information Criterion (AIC). AICs for models including the three-way interaction term were lower than those obtained from corresponding models including the main effects of GSTM1, HMOX-1, and PM_2.5, as well as the two-way interactions between GSTM1 and PM_2.5 and HMOX-1 and PM_2.5, thus indicating better goodness of fit.

Our study, based on an elderly population in Boston, showed that functional genetic variations in GSTM1 and HMOX-1, both of which are related to defenses against oxidative stress, modify the effects of PM_2.5 on HRV. In the present work, we have extended our previous results examining the modification of the PM_2.5–HRV association by GSTM1 (Schwartz et al. 2005b) to include other HRV outcomes and repeated measures on subjects, to show effect modification by HMOX-1, and to show a three-way interaction between the two genes and combustion particles.

This work is part of a series of studies seeking to examine the potential pathways by which particles affect HRV. Specifically, we are looking at oxidative stress and endothelial function as potential pathways to this outcome. We hypothesize that if a pathway is important in the effect of PM_2.5 on HRV, then factors that modify that pathway, either genes or drugs, may modify the PM_2.5 response. We are also looking at metal-processing pathways as an indirect test of the hypothesis that metals on the PM_2.5 particles play an important role in the HRV response (Park et al. 2006).

In our previous work on the same population we showed that ambient PM_2.5 concentrations averaged over the 48 hr before the examination were associated with a reduction HF, with negative, albeit nonsignificant, associations were seen with SDNN and LF (Park et al. 2005). In the present work, based on longer follow-up and additional HRV measurements, we were also able to show a significant effect on SDNN, as well as a more pronounced, although still nonsignificant, negative association with LF.

As part of our examination of oxidative stress we have previously shown that particles had no effect on HRV in subjects with the functional GSTM1 polymorphism (GSTM1–wild-type) but had a substantially increased effect in those with the deletion (GSTM1-null) (Schwartz et al. 2005b). Similarly, we showed that statin use and obesity, which both modify ROS production, altered PM_2.5 effects on HRV (Schwartz et al. 2005b), thus confirming the critical role of oxidative stress pathways. In this article, we extend those results by showing a three-way interaction with genetic modifiers of response to oxidative stress.

Although particle exposure has also been linked with activation of inflammatory pathways (Baccarelli et al. 2007b; Liao et al. 2004; Peters et al. 2001), alterations in blood coagulation (Baccarelli et al. 2007a; Liao et al. 2005), endothelial injury and dysfunction (Brook et al. 2002; Ikeda et al. 1998), and alterations in the autonomic control of the heart (Creason et al. 2001; Gold et al. 2000; Liao et al. 2004a), our findings suggest that genetic variations in oxidative stress pathways play a critical role in the cardiovascular effects of airborne particles.

Rodents exposed to concentrated urban particles evinced increased reactive oxygen species in both the lung and the heart (Gurgueira et al. 2002), an effect muted by preadministration of N-acetylcysteine, a glutathione precursor and potent antioxidant (Rhoden et al. 2004). Inhalation of particles produces oxidative stress directly or via acute pulmonary inflammation, thus causing a series of events, such as the production of proinflammatory mediators, an increase of extracellular calcium influx, and the disruption of nitric oxide regulation (Stone et al. 2000; Thomas et al. 2001), that may impair autonomic function and hence HRV. Diesel particles have also been shown to increase oxidative stress in endothelial tissue, inducing the production of HMOX-1 (Furuyama et al. 2006). The viability of cell cultures of microvascular endothelial cells was impaired by diesel particles with an accompanying large increase in induction of HMOX-1 (Hirano et al. 2003); this process was blunted by N-acetylcysteine. Woodsmoke particles have also been shown to deplete intracellular glutathione and upregulate HMOX-1 activity in endothelial cells (Liu et al. 2005). Our results showing interactions of particles with GSTM1 deletion and microsatellite (GT)n repeat length in the gene coding for HMOX-1 are consistent with these laboratory findings that suggest a prominent role of ROS in particle toxicity.

HMOX-1, the inducible heme oxygenase isoform, is expressed in multiple tissues, including vascular smooth muscle and endothelial cells (Exner et al. 2004). HMOX-1 expression has been shown to be upregulated in rat heart microvessel endothelial cells exposed to organic extracts of diesel exhaust particles (Furuyama et al. 2006), an effect that is likely to represent a response directed against ROS production (Morita 2005). Large individual differences in the ability to modulate the quantitative level of HMOX-1 activity in response to a given stimulus have been described, which correlate with differences in the length of a microsatellite (GT)n repeat in the 5′ flanking region of the HMOX-1 gene (Exner et al. 2004; Hirai et al. 2003; Yamada et al. 2000). The purine–pyrimidine alternating sequence in the (GT)n repeat has the potential to assume Z-DNA conformation, a left-handed double-helix structure that is thermodynamically unfavorable compared with B-DNA conformation (Rich et al. 1984) and has been described as negatively affecting transcriptional activity (Delic et al. 1991; Naylor and Clark 1990). Yamada and co-workers demonstrated by transient-transfection assay in cultured cell lines that the larger the number of (GT)n repeats in the HMOX-1 gene promoter, the lower is the HMOX-1 inducibility by ROS (Yamada et al. 2000).

In our study, HMOX-1 microsatellite (GT)n repeat length appeared to modulate the effects of PM_2.5 on autonomic function, as measured by HRV variability. PM_2.5 exhibited a negative correlation with SDNN, HF, and LF in individuals with ≥ 25 repeats, whereas no effect was seen in subjects with < 25 repeats. Furthermore, the strongest effects of PM_2.5 were found in subjects that were lacking efficiency in antioxidant responses due to the combination of the GSTM1 deletion and ≥ 25 microsatellite (GT)n repeats in the HMOX-1 promoter. While the p-values for statistical interaction between PM_2.5 and GSTM1 and between PM_2.5 and HMOX-1 were not significant, the tests for the three-way interaction among PM_2.5, GSTM1, and HMOX-1 were highly significant, confirming that the stronger effect modification of PM_2.5 effects on HRV is seen when both genes are considered. The statistical modeling we used to fit the three-way interaction tested whether the size of PM_2.5 effects in carriers of GSTM1 null and at least one long HMOX-1 repeat was 2 times larger than that observed in subjects carrying either GSTM1 null or one long HMOX-1 repeat. Thus, our data strongly suggest that particle exposure interacts with individual variations in the antioxidant response pathway to determine its effects on HRV.

A potential limitation of this study is that we used ambient PM_2.5 concentrations from a single monitoring site as a surrogate for recent exposure to PM_2.5. A recent study comparing ambient concentrations at this site with personal exposures in Boston has shown a high longitudinal correlation (Sarnat et al. 2005) between the two measurements; the study also reported that PM_2.5 concentrations were spatially homogeneous over the Boston area. This suggests that our use of ambient concentrations is reasonable and the resulting exposure error is likely to be nondifferential. In our analyses, we considered several potential confounding factors that may have influenced HRV measures, as we adjusted our models for age, BMI, mean arterial pressure, fasting blood glucose, cigarette smoking, alcohol consumption, room temperature, outdoor apparent temperature, season, and use of beta-blockers, calcium channel blockers, and ACE inhibitors. Therefore, chances that the observed associations reflected bias due to confounders are minimized.

Our results can be generalized only to an aged population that consists of older males who are almost all white. The effect on women and children as well as different ethnic groups should be addressed in future studies, particularly in relation to the exposure of different population groups to PM_2.5 with varying geographic location, occupation, socioeconomic status, and behavioral characteristics. Other health outcomes including respiratory responses may also be affected by responses to ROS in an interaction with PM_2.5 exposure. Our findings provide new information to guide research on the breadth of the effect of PM_2.5 exposure.

This work was supported by National Institute of Environmental Health Sciences grants RO1ES00002, RO1ES015172-01, PO1ES009825, and U.S. Environmental Protection Agency grants EPAR827353 and R83241601. The VA Normative Aging Study, a component of the Massachusetts Veterans Epidemiology Research and Information Center, Boston, Massachusetts, is supported by the Cooperative Studies Program/Epidemiology Research and Information Center of the U.S. Department of Veterans Affairs.