Metal exposure and oxidative stress biomarkers in subway workers

Abstract

Background and aim: Rich in metals, subway particles could induce more oxidative stress (OS) than ambient PM. We aimed at investigating relationships between subway particle exposure and OS biomarkers measured in urine and exhaled breath condensate (EBC). Methods: Nine subway workers (station agents, locomotive operators and security guards) were monitored during their 6-h shifts over two consecutive weeks. Time-weighted average mass concentrations expressed as PM10, PM2.5 and their metal concentrations were determined. Urine and EBC samples were collected pre- and post-shift to measure metals, malondialdehyde, 8-isoprostane, and 8-hydroxy-deoxyguanine concentrations. Associations were first explored using correlation and hierarchical cluster analysis. The identified clusters were then investigated using linear mixed regression models adjusted for age and sex, with participant's ID as random effect. Results: PM concentrations varied significantly between jobs. Locomotive operators had the highest exposure (189 and 137 μg/m3 for PM10 and PM2.5, respectively). The most abundant metals in PM were Fe, Cu, Al and Zn; in EBC, Zn, Cu and Ni; and in urine, Si, Zn, Mo, Ti, and Cu. Regarding OS biomarkers, in EBC, only malondialdehyde was detected. Urinary malondialdehyde and 8-hydroxy-deoxyguanine concentrations varied according to the weekday and workers’ age. Zn or Ni exposure clusters were identified. Modeled urinary Zn concentration was negatively associated with urinary malondialdehyde and positively associated with malondialdehyde in EBC. PM10 Zn was also negatively associated with urinary malondialdehyde and 8-isoprostane, but with borderline significance. PM10 Ni was negatively associated with urinary 8-hydroxy-deoxyguanine. In models adjusted for all exposure metrics of a given metal, associations remained between urinary Zn and malondialdehyde and between urinary Ni and 8-hydroxy-deoxyguanine. Conclusion: These findings suggest Zn and Ni influence in OS reflected by urinary malondialdehyde and 8-hydroxy-deoxyguanine concentrations. Further investigations based on larger datasets and in-depth time-series analysis are needed to understand the underlying mechanism of these associations.