申请人长期致力于空气污染致机体早期遗传损伤和肺癌的分子流行病学研究，系统探讨了多种污染物(如多环芳烃、金属等)、基因遗传变异及其交互作用在机体早期遗传损伤和肺癌发生和预后中的作用和机制。在J Clin Oncol、Gut、Cancer Res、Environ Sci Technol、Environ Res、Nat Genet等发表SCI论文63篇，被引1153次，其中第一通讯作者13篇，第一和共同第一作者9篇，H因子15。曾获全国百篇优秀博士学位论文奖，入选“万人计划”青年拔尖人才支持计划。本项目以焦炉工职业队列和东风-同济队列人群为研究对象，结合体内外功能学研究，探讨表观遗传学因素(DNA甲基化、lncRNA和miRNA)在环境污染物暴露致机体早期遗传损伤和肺癌发生中的作用和生物学机制，在此基础上研究环境-基因交互作用，为建立肺癌风险预测模型和筛选肺癌高危人群提供科学依据。

My major research interest is the molecular epidemiological studies on the associations of air pollutants exposure with early genetic damage and lung cancer. We have investigated the effects of many environmental pollutants [e.g., polycyclic aromatic hydrocarbons (PAHs), metals, smoking, and coke-oven emissions], genetic variations (e.g., heat shock protein genes, DNA repair genes, and CYP450 genes), and their interactions on the individual’s genetic damage levels, lung cancer risk and prognosis, and also explored the potential underlying mechanisms. I am an author and co-author of 63 SCI papers, which were cited 1153 times by the other publications. I am the first corresponding author of 13 SCI papers (Environ Sci Technol, Environ Res, Sci Rep, Mol carcinogen, Int J cardiol, etc), and the first or co-first author of 9 SCI papers (J Clin Oncol, Gut, Cancer Res, Carcinogenesis, etc). My current H index in web of science is 15. I was awarded Top 100 National Excellent Doctoral Dissertations Award in 2012, and was sponsored by the Program for New Century Excellent Talents in University of the Ministry of Education in 2012 and by the Youth Top Talent Support Program in 2015. In this proposal, we aim to investigate the target epigenetic changes (e.g., DNA methylation, lncRNA, and miRNA) those were caused by environmental PAHs and metals exposure and were dose-related to the individual’s early genetic damage levels and lung cancer risk. The biological functions and deep mechanisms of these epigenetic biomarkers will further be conducted by in vivo and in vitro biological studies. The goal of the present study is to establish scientific risk prediction models and provide new insight into high-risk population screening of lung cancer.