Ambient PM2.5 species and ultrafine particle exposure and their differential metabolomic signatures

• Published in: Environment international Vol. 151; p. 106447
• Main Authors: Nassan, Feiby L., Wang, Cuicui, Kelly, Rachel S., Lasky-Su, Jessica A., Vokonas, Pantel S., Koutrakis, Petros, Schwartz, Joel D.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2021; Elsevier
• Subjects: Air pollution; Metabolomics; Particulate matter; SPECIES, Normative Aging Study (NAS); Metabolomics; Air pollution; Particulate matter; SPECIES, Normative Aging Study (NAS)
• ISSN: 0160-4120; 1873-6750
• DOI: 10.1016/j.envint.2021.106447

•Metabolomic profiling is a powerful tool for mechanistic understanding of PM2.5 exposure impact.•PM2.5 exposure has metabolomic signatures related to oxidative stress, immunity, & nucleic acid damage.•Little is known about the specific PM2.5 species (hence sources) that drive these signatures.•Ultrafine particles were the main significant species of short-term PM2.5 exposure followed by Ni and V then Si, Al, and K.•Black carbon, Ni, V, Zn, Cu, Fe, and Se were the main significant species of long-term PM2.5 exposure. The metabolomic signatures of short- and long-term exposure to PM2.5 have been reported and linked to inflammation and oxidative stress. However, little is known about the relative contribution of the specific PM2.5 species (hence sources) that drive these metabolomic signatures. We aimed to determine the relative contribution of the different species of PM2.5 exposure to the perturbed metabolic pathways related to changes in the plasma metabolome. We performed mass-spectrometry based metabolomic profiling of plasma samples among men from the Normative Aging Study to identify metabolic pathways associated with PM2.5 species. The exposure windows included short-term (one, seven-, and thirty-day moving average) and long-term (one year moving average). We used linear mixed-effect regression with subject-specific intercepts while simultaneously adjusting for PM2.5, NO2, O3, temperature, relative humidity, and covariates and correcting for multiple testing. We also used independent component analysis (ICA) to examine the relative contribution of patterns of PM2.5 species. Between 2000 and 2016, 456 men provided 648 blood samples, in which 1158 metabolites were quantified. We chose 305 metabolites for the short-term and 288 metabolites for the long-term exposure in this analysis that were significantly associated (p-value < 0.01) with PM2.5 to include in our PM2.5 species analysis. On average, men were 75.0 years old and their body mass index was 27.7 kg/m2. Only 3% were current smokers. In the adjusted models, ultrafine particles (UFPs) were the most significant species of short-term PM2.5 exposure followed by nickel, vanadium, potassium, silicon, and aluminum. Black carbon, vanadium, zinc, nickel, iron, copper, and selenium were the significant species of long-term PM2.5 exposure. We identified several metabolic pathways perturbed with PM2.5 species including glycerophospholipid, sphingolipid, and glutathione. These pathways are involved in inflammation, oxidative stress, immunity, and nucleic acid damage and repair. Results were overlapped with the ICA. We identified several significant perturbed plasma metabolites and metabolic pathways associated with exposure to PM2.5 species. These species are associated with traffic, fuel oil, and wood smoke. This is the largest study to report a metabolomic signature of PM2.5 species’ exposure and the first to use ICA.