Yao Yueli, Schneider Alexandra, Wolf Kathrin, Zhang Siqi, Wang-Sattler Rui, Peters Annette, Breitner Susanne
Institute for Medical Information Processing, Biometry and Epidemiology - IBE, Ludwig-Maximilians-Universität München, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Environ Int. 2022 Dec;170:107632. doi: 10.1016/j.envint.2022.107632. Epub 2022 Nov 13.
Long-term exposure to air pollution has been associated with cardiopulmonary diseases, while the underlying mechanisms remain unclear.
To investigate changes in serum metabolites associated with long-term exposure to air pollution and explore the susceptibility characteristics.
We used data from the German population-based Cooperative Health Research in the Region of Augsburg (KORA) S4 survey (1999-2001) and two follow-up examinations (F4: 2006-08 and FF4: 2013-14). Mass-spectrometry-based targeted metabolomics was used to quantify metabolites among serum samples. Only participants with repeated metabolites measurements were included in the current analysis. Land-use regression (LUR) models were used to estimate annual average concentrations of ultrafine particles, particulate matter (PM) with an aerodynamic diameter less than 10 μm (PM), coarse particles (PM), fine particles, PM absorbance (a proxy of elemental carbon related to traffic exhaust, PM), nitrogen oxides (NO, NO), and ozone at individuals' residences. We applied confounder-adjusted mixed-effects regression models to examine the associations between long-term exposure to air pollution and metabolites.
Among 9,620 observations from 4,261 KORA participants, we included 5,772 (60.0%) observations from 2,583 (60.6%) participants in this analysis. Out of 108 metabolites that passed stringent quality control across three study points in time, we identified nine significant negative associations between phosphatidylcholines (PCs) and ambient pollutants at a Benjamini-Hochberg false discovery rate (FDR) corrected p-value < 0.05. The strongest association was seen for an increase of 0.27 μg/m (interquartile range) in PM and decreased phosphatidylcholine acyl-alkyl C36:3 (PC ae C36:3) concentrations [percent change in the geometric mean: -2.5% (95% confidence interval: -3.6%, -1.5%)].
Our study suggested that long-term exposure to air pollution is associated with metabolic alterations, particularly in PCs with unsaturated long-chain fatty acids. These findings might provide new insights into potential mechanisms for air pollution-related adverse outcomes.
长期暴露于空气污染与心肺疾病相关，但其潜在机制仍不清楚。
研究与长期暴露于空气污染相关的血清代谢物变化，并探索易感性特征。
我们使用了来自德国奥格斯堡地区基于人群的合作健康研究（KORA）S4调查（1999 - 2001年）以及两次随访检查（F4：2006 - 2008年和FF4：2013 - 2014年）的数据。基于质谱的靶向代谢组学用于定量血清样本中的代谢物。本分析仅纳入了有重复代谢物测量值的参与者。土地利用回归（LUR）模型用于估计个体住所的超细颗粒物、空气动力学直径小于10μm的颗粒物（PM）、粗颗粒物（PM）、细颗粒物、PM吸光度（与交通尾气相关的元素碳的替代指标，PM）、氮氧化物（NO、NO）和臭氧的年平均浓度。我们应用经混杂因素调整的混合效应回归模型来研究长期暴露于空气污染与代谢物之间的关联。
在来自4261名KORA参与者的9620条观测数据中，我们在本分析中纳入了来自2583名（60.6%）参与者的5772条（60.0%）观测数据。在三个时间点通过严格质量控制的108种代谢物中，我们在磷脂酰胆碱（PCs）与环境污染物之间发现了9种显著的负相关，经Benjamini - Hochberg错误发现率（FDR）校正后的p值<0.05。最强的关联是PM每增加0.27μg/m（四分位间距），磷脂酰胆碱酰基 - 烷基C36:3（PC ae C36:3）浓度降低[几何均值的百分比变化：-2.5%（95%置信区间：-3.6%，-1.5%）]。
我们的研究表明，长期暴露于空气污染与代谢改变有关，特别是与具有不饱和长链脂肪酸的PCs有关。这些发现可能为空气污染相关不良后果的潜在机制提供新的见解。
