Particulate matter 2.5 (PM2.5) is associated with reproductive health and adverse pregnancy outcomes. However, studies evaluating biological markers of PM2.5 are lacking, and identifying biomarkers for estimating prenatal exposure to prevent pregnancy complications is essential. Therefore, we aimed to explore urine metabolites that are easy to measure as biomarkers of exposure. In this matched case-control study based on the PM2.5 exposure, 30 high PM2.5 group (>15 μg/m3) and 30 low PM2.5 group (<15 μg/m3) were selected from air pollution on pregnancy outcome (APPO) cohort study. We used a time-weighted average model to estimate individual PM exposure, which used indoor PM2.5 and outdoor PM2.5 concentrations by atmospheric measurement network based on residential addresses. Clinical characteristics and urine samples were collected from participants during the second trimester of pregnancy. Urine metabolites were quantitatively measured using gas chromatography-mass spectrometry following multistep chemical derivatization. Statistical analyses were conducted using SPSS version 21 and MetaboAnalyst 5.0. Small for gestational age and gestational diabetes (GDM) were significantly increased in the high PM2.5 group, respectively (P = 0.042, and 0.022). Fifteen metabolites showed significant differences between the two groups (P < 0.05). Subsequent pathway enrichment revealed that four pathways, including pentose and glucuronate interconversion with three pentose sugars (ribose, arabinose, and xylose; P < 0.05). The concentration of ribose increased preterm births (PTB) and GDM (P = 0.044 and 0.049, respectively), and the arabinose concentration showed a tendency to increase in PTB (P = 0.044). Therefore, we identified urinary pentose metabolites as biomarkers of PM2.5 and confirmed the possibility of their relationship with pregnancy complications.
Keywords: Arabinose; Gestational diabetes; Particulate matter; Preterm birth; Ribose; Xylose.
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