Cardiovascular and inflammatory mechanisms in healthy humans exposed to air pollution in the vicinity of a steel mill.

There is a paucity of mechanistic information that is central to the understanding of the adverse health effects of source emission exposures. To identify source emission-related effects, blood and saliva samples from healthy volunteers who spent five days near a steel plant (Bayview site, with and without a mask that filtered many criteria pollutants) and at a well-removed College site were tested for oxidative stress, inflammation and endothelial dysfunction markers. Biomarker analyses were done using multiplexed protein-array, HPLC-Fluorescence, EIA and ELISA methods. Mixed effects models were used to test for associations between exposure, biological markers and physiological outcomes. Heat map with hierarchical clustering and Ingenuity Pathway Analysis (IPA) were used for mechanistic analyses. Mean CO, SO2 and ultrafine particles (UFP) levels on the day of biological sampling were higher at the Bayview site compared to College site. Bayview site exposures "without" mask were associated with increased (p < 0.05) pro-inflammatory cytokines (e.g IL-4, IL-6) and endothelins (ETs) compared to College site. Plasma IL-1β, IL-2 were increased (p < 0.05) after Bayview site "without" compared to "with" mask exposures. Interquartile range (IQR) increases in CO, UFP and SO2 were associated with increased (p < 0.05) plasma pro-inflammatory cytokines (e.g. IL-6, IL-8) and ET-1(1-21) levels. Plasma/saliva BET-1 levels were positively associated (p < 0.05) with increased systolic BP. C-reactive protein (CRP) was positively associated (p < 0.05) with increased heart rate. Protein network analyses exhibited activation of distinct inflammatory mechanisms after "with" and "without" mask exposures at the Bayview site relative to College site exposures. These findings suggest that air pollutants in the proximity of steel mill site can influence inflammatory and vascular mechanisms. Use of mask and multiple biomarker data can be valuable in gaining insight into source emission-related health impacts.