Associations between long-term PM_2.5 exposure and metabolomic signatures: A retrospective cohort study

Long-term exposure to fine particulate matter (PM_2.5) has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood.

To identify the blood metabolome and metabolic pathways associated with long-term PM_2.5 exposure.

We conducted a retrospective cohort study among 1930 young adults from the Chinese Undergraduate Cohort (CUC) in 2019 in Shandong Province, China. The 1 km × 1 km PM_2.5 grid data were collected from China High Air Pollutants (CHAP) dataset. Liquid chromatography-mass spectrometry (LC-MS) was used to test the plasma samples' metabolome levels. The 12 months of PM_2.5 exposure were defined as long-term PM_2.5 exposure. We used one-way Analysis of Variance (ANOVA) and multiple linear regression model to analyze the associations between long-term exposure to PM_2.5 and plasma metabolites. The multiple linear regression model was adjusted for age, sex, body mass index (BMI), physical activity, smoking status, passive smoking status, alcohol consumption status, outdoor dwell time, socioeconomic status, average temperature, relative humidity and wind speed. In addition, stratified analysis was conducted based on sex.

Long-term exposure to PM_2.5 was associated with 60 altered metabolites enriched in 3 metabolic pathways, including tyrosine metabolism, arginine biosynthesis and unsaturated fatty acids biosynthesis. In the stratified analysis, it was observed that female-specific pathways were glycine, serine, and threonine metabolism, whereas male-specific pathways were glycerophospholipid metabolism.

Long-term exposure to PM_2.5 could possibly induce inflammation and oxidative stress through disturbing amino acid and unsaturated fatty acid metabolism. Our findings should be integrated into preventive strategies, including enhanced monitoring of high-risk exposure groups and the promotion of an anti-inflammatory diet.