基于定组人群追踪的大气细颗粒物暴露组学及代谢效应标志物研究

Air pollution caused by airborne fine particulate matter (PM2.5) has been one of the most important environmental risks of public health in Chinese cities. At present, the toxic components of PM2.5 are still unclear, and the sensitive biomarkers for assessment of its exposure and health effects are also lacking. Based on the exposomics and system biology approaches, this proposal plans to recruit a panel of healthy university students form different cities, and investigate their personal internal and external exposure level of PM2.5 chemical components, and the contribution of external exposure through breath to internal exposure, aiming to elicit the risk of personal exposure to airborne PM2.5. In addition, by using metabolomics approach, we will analyze the differential metabolomic profiles of the study objects between high-level and low-level PM2.5 pollution area, and the differences of the same population between high-level and low-level exposure season will be also investigated. Based on the differential metabolites, we will screen unique metabolic biomarkers for the health risk assessment of PM2.5 exposure. By further bioinformatics analysis, it is expected to find the disturbed metabolic pathways in response to PM2.5 exposure, and to reveal the potential mode-of-action of PM2.5 on human metabolism. Overall, this study is believed to play important roles in clarifying the PM2.5 exposure characteristics of humans in the regions with frequent occurrence of haze, and uncovering the toxic components (metabolic disturbance) of PM2.5, based on which the dose-effect model of personal exposure will be also built for risk assessment of PM2.5 exposure and its health effects.

大气细颗粒物（PM2.5）导致的空气污染已经成为影响我国城市公众健康的重要环境风险之一。但是，PM2.5的致毒性组份仍不清楚，并且缺乏适当的暴露标志物和特异性效应标志物用于评价其人群健康风险。基于暴露组学的理念和系统生物学的研究方法，本项目拟采用定群追踪的研究设计，通过调查不同城市的健康在校大学生人群，研究不同区域和季节PM2.5及其典型污染组份的个体暴露水平、典型污染组份的体液残留水平和潜在暴露标志物、与PM2.5及其典型污染组份暴露剂量相关的代谢效应标志物和相关代谢通路；在揭示PM2.5毒性（代谢干扰效应）组份的基础上，将进一步建构基于个体暴露的剂量-效应模型，为评价大气细颗粒物暴露与健康风险提供科学依据。

大气细颗粒物（PM2.5）导致的空气污染是我国目前的主要环境问题之一，其人群暴露已对公众健康产生了严重影响。然而，PM2.5诱导肺毒性/疾病的分子机制仍不清楚，并且缺乏敏感的效应生物标志物用于评价其暴露健康风险。因此，本项目首先基于人群研究，利用代谢组学技术探讨了“PM2.5暴露-代谢-COPD”三者的关联，揭示PM2.5暴露加剧COPD风险的作用模式；另外，基于动物模型研究了PM2.5诱导肺毒性的代谢作用机制，希望对人群结果加以验证。通过本研究，取得了如下创新成果：.1. 基于北京人群研究，筛选出7种PM2.5暴露相关的代谢物，这些代谢物主要涉及糖酵解、嘌呤和氨基酸代谢；筛选出10种COPD相关的代谢物，他们主要与氨基酸、脂肪酸和葡萄糖代谢有关。通过分析这两类代谢标志物间的统计学和生物学关联，我们提出PM2.5暴露可能导致肺部的氧化应激和能量供应不足从而加剧COPD风险。.2. 基于泰国人群研究，筛选出与COPD密切相关的代谢物picolinic acid、2-Hydroxyadenine和8-Hydroxyadenine，表明COPD人群肺部可能受到氧化胁迫及炎症反应，从而验证了北京人群研究结果。另外，虽然在本人群中未能直接筛选出与PM2.5暴露相关的代谢标志物，但COPD相关标志物methyluric acid、dopamine 4-sulfate（及DOPA sulfate）亦在北京人群中被鉴定为PM2.5相关标志物，说明PM2.5可能通过干扰咖啡因和酪氨酸代谢而加剧COPD患病风险。.3. 基于动物模型，通过分析PM2.5暴露前后大鼠肺组织代谢组变化，鉴定出多种与脂质和核苷酸代谢有关的差异代谢物，提出PM2.5可能通过扰乱肺组织的氧化/抗氧化平衡，并导致脂质代谢紊乱，从而诱导肺毒性。该结果也进一步验证了上述人群研究中发现的PM2.5可能通过产生氧化胁迫及干扰能量代谢而诱发肺疾病。.本项目研究结果不仅可为揭示PM2.5诱导肺疾病（COPD）的分子作用模式提供一定参考，还有望筛选有效的代谢效应标志物用于大气PM2.5暴露的人群健康风险评估。