Associations between long-term PM2.5 exposure and metabolomic signatures: A retrospective cohort study
Abstract
BACKGROUND
Long-term exposure to fine particulate matter (PM2.5) has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood.
OBJECTIVE
To identify the blood metabolome and metabolic pathways associated with long-term PM2.5 exposure.
METHODS
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 PM2.5 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 PM2.5 exposure were defined as long-term PM2.5 exposure. We used one-way Analysis of Variance (ANOVA) and multiple linear regression model to analyze the associations between long-term exposure to PM2.5 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.
RESULTS
Long-term exposure to PM2.5 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…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 1,930 participants or records.
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