Child serum metabolome and traffic-related air pollution exposure in pregnancy

• Published in: Environmental research Vol. 203; p. 111907
• Main Authors: Ritz, Beate, Yan, Qi, He, Di, Wu, Jun, Walker, Douglas I., Uppal, Karan, Jones, Dean P., Heck, Julia E.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01-01-2022
• Subjects: abrHigh resolution metabolomics; Adult; Air Pollutants - adverse effects; Air Pollutants - analysis; Air pollution; Air Pollution - adverse effects; Air Pollution - analysis; Case-Control Studies; Exposome; Female; Humans; Infant, Newborn; Inflammation; Metabolome; Oxidative stress; Pregnancy; Traffic-Related Pollution; Oxidative stress; Air pollution; Inflammation; Exposome; abrHigh resolution metabolomics
• ISSN: 0013-9351; 1096-0953
• DOI: 10.1016/j.envres.2021.111907

Maternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and childhood disorders. High-resolution metabolomics (HRM) has previously been employed to identify metabolic responses to traffic-related air pollution in adults, including pregnant women. Thus far, no studies have examined metabolic effects of air pollution exposure in utero on neonates.
We retrieved stored neonatal blood spots for 241 children born in California between 1998 and 2007. These children were randomly selected from all California birth rolls to serve as birth-year matched controls for children with retinoblastoma identified from the California cancer registry for a case control study of childhood cancer. We estimated prenatal traffic-related air pollution exposure (particulate matter less than 2.5 μm (PM2.5)) during the third-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We employed untargeted HRM to obtain metabolic profiles, and metabolites associated with air pollution exposure were identified using partial least squares (PLS) regression and linear regressions. Biological effects were characterized using pathway enrichment analyses adjusting for potential confounders including maternal age, race/ethnicity, and education.
In total we extracted 4038 and 4957 metabolite features from neonatal blood spots in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 reverse phase columns (negative ion mode), respectively. After controlling for confounding factors, partial least square regression (Variable Importance in Projection (VIP) ≥ 2) selected 402 HILIC positive and 182 C18 negative features as statistically significantly associated with increasing third trimester PM2.5 exposure. Using pathway enrichment analysis, we identified metabolites in oxidative stress and inflammation pathways as being altered, primarily involving lipid metabolism.
The metabolite features and pathways associated with air pollution exposure in neonates suggest that maternal exposure during late pregnancy contributes to oxidative stress and inflammation in newborn children.