Fine particulate matter (PM2.5) can promote chronic diseases through the fundamental mechanism of inflammation; however, systemic information is lacking on the inflammatory PM2.5 components. To decipher organic components from personal… Click to show full abstract
Fine particulate matter (PM2.5) can promote chronic diseases through the fundamental mechanism of inflammation; however, systemic information is lacking on the inflammatory PM2.5 components. To decipher organic components from personal PM2.5 exposure that were associated with respiratory and circulatory inflammatory responses in older adults, we developed an exposomic approach using trace amounts of particles and applied it on 424 personal PM2.5 samples collected in a panel study in Beijing. Applying an integrated multivariate and univariate untargeted strategy, a total of 267 organic compounds were filtered and then chemically identified according to their association with exhaled nitric oxide (eNO)/interleukin (IL)-6 or serum IL-1β/IL-6, with monocyclic and polycyclic aromatic compounds (i.e., MACs and PACs) as the representatives. Indoor-derived species with medium volatility including MACs were mainly associated with systemic inflammation, while low-volatile ambient components that originate from combustion sources, such as PACs, were mostly associated with airway inflammation. Following ambient component exposure, we found an inverted U-shaped relationship on change of eNO with insulin resistance, suggesting a higher risk of cardiopulmonary dysfunction for individuals with homeostatic model assessment for insulin resistance (HOMA-IR) levels > 2.3. Overall, this study provided a practical untargeted strategy for the systemic investigation of PM2.5 components and proposed source-specific inflammatory effects.
               
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