Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA.
Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA; Yale Center for Perinatal, Pediatric, and Environmental Epidemiology, Yale School of Public Health, New Haven, CT, USA.
Environ Int. 2019 Sep;130:104872. doi: 10.1016/j.envint.2019.05.066. Epub 2019 Jun 20.
Maternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and neurodevelopmental disorders. By utilizing high-resolution metabolomics (HRM), we investigated perturbations of the maternal serum metabolome in response to traffic-related air pollution to identify biological mechanisms.
We retrieved stored mid-pregnancy serum samples from 160 mothers who lived in the Central Valley of California known for high air particulate levels. We estimated prenatal traffic-related air pollution exposure (carbon monoxide, nitric oxides, and particulate matter <2.5 μm) during first-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We used liquid chromatography-high resolution mass spectrometry to obtain untargeted metabolic profiles and partial least squares discriminant analysis (PLS-DA) to select metabolic features associated with air pollution exposure. Pathway analyses were employed to identify biologic pathways related to air pollution exposure. As potential confounders we included maternal age, maternal race/ethnicity, and maternal education.
In total we extracted 4038 and 4957 metabolic features from maternal serum samples in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 (negative ion mode) columns, respectively. After controlling for confounding factors, PLS-DA (Variable Importance in Projection (VIP) ≥2) yielded 181 and 251 metabolic features (HILIC and C18, respectively) that discriminated between the high (n = 98) and low exposed (n = 62). Pathway enrichment analysis for discriminatory features associated with air pollution indicated that in maternal serum oxidative stress and inflammation related pathways were altered, including linoleate, leukotriene, and prostaglandin pathways.
The metabolomic features and pathways we found to be associated with air pollution exposure suggest that maternal exposure during pregnancy induces oxidative stress and inflammation pathways previously implicated in pregnancy complications and adverse outcomes.
母体在怀孕期间暴露于交通相关的空气污染中已被证明会增加不良出生结局和神经发育障碍的风险。通过利用高分辨率代谢组学(HRM),我们研究了母体血清代谢组对交通相关空气污染的反应变化,以确定生物学机制。
我们从居住在加利福尼亚中央山谷的 160 名母亲中检索了存储的妊娠中期血清样本,该山谷以高空气颗粒物水平而闻名。我们使用基于出生时记录的居住地址的加利福尼亚线源扩散模型版本 4(CALINE4)来估计妊娠早期的产前交通相关空气污染暴露(一氧化碳、氮氧化物和小于 2.5μm 的颗粒物)。我们使用液相色谱-高分辨率质谱法获得非靶向代谢谱,并使用偏最小二乘判别分析(PLS-DA)选择与空气污染暴露相关的代谢特征。通路分析用于确定与空气污染暴露相关的生物学途径。作为潜在的混杂因素,我们包括母亲的年龄、母亲的种族/族裔和母亲的教育程度。
我们从亲水相互作用(HILIC)色谱(正离子模式)和 C18(负离子模式)柱中的母体血清样本中分别提取了 4038 和 4957 个代谢特征。在控制混杂因素后,PLS-DA(变量重要性投影(VIP)≥2)产生了 181 和 251 个代谢特征(HILIC 和 C18,分别),可区分高(n=98)和低暴露(n=62)。与空气污染相关的具有判别力的特征的通路富集分析表明,在母体血清中,氧化应激和炎症相关途径发生改变,包括亚油酸、白三烯和前列腺素途径。
我们发现与空气污染暴露相关的代谢特征和途径表明,母体在怀孕期间的暴露会诱导氧化应激和炎症途径,这些途径先前与妊娠并发症和不良结局有关。