Wu Yanjuan, Zhang Yuting, Wang Jingcun, Gan Qiming, Su Xiaofen, Zhang Sun, Ding Yutong, Yang Xinyan, Zhang Nuofu, Wu Kang
Sleep Medicine Center, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, National Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510160, China.
Sleep Medicine Center, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, National Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510160, China.
Ecotoxicol Environ Saf. 2025 Jan 15;290:117602. doi: 10.1016/j.ecoenv.2024.117602. Epub 2024 Dec 30.
Epidemiological studies have consistently demonstrated a robust association between long-term exposure to air pollutants and respiratory diseases. However, establishing causal relationships remains challenging due to residual confounding in observational studies. In this study, Mendelian randomization (MR) analysis was used to explore the causal and epigenetic relationships between various air pollutants and common respiratory diseases.
We utilized a two-sample Mendelian randomization (TSMR) approach to explore the impact of PM, PM, PM, NO, and NO on the incidence of nine respiratory diseases using data from large-scale European GWAS datasets (N = 423,796-456,380 for exposures; N = 162,962-486,484 for outcomes). The primary analytical method was inverse variance weighting (IVW), which explored the exposure-outcome relationship using single nucleotide polymorphisms (SNPs) associated with air pollution. Sensitivity analyses, including MR-Egger regression and leave-one-out analyses, were employed to ensure result consistency. Multivariate MR (MVMR) was performed to adjust for potential smoking-related confounders, such as cigarettes per day, household smoking, exposure to tobacco smoke at home, ever smoked, second-hand smoke, smoking initiation, and age at smoking initiation, as well as the independent effects of each air pollutant. Additionally, methylation and enrichment analyses were conducted to further elucidate the potential effects of air pollution on respiratory diseases.
TSMR analysis revealed that exposure to PM increased the risk of early-onset chronic obstructive pulmonary disease (COPD), pneumonia, pulmonary embolism and lung cancer. PM exposure was associated with an increased risk of lung cancer, while PM exposure increased the risk of pneumonia and bronchiectasis. NO exposure was associated with increased risks of lung cancer and adult asthma. Importantly, these associations remained robust even after controlling for potential tobacco-related confounders in the MVMR analyses. In the MVMR analysis adjusting for other pollutants, significant associations persisted between PM and early-onset COPD, and between PM and pneumonia. Genetic co-localization analyses confirmed that methylation of PM-associated CpG loci (cg11386376 near c1orf175, cg11846064 near rfx2, cg18612040 near rptor, and cg19765378 near c7orf50) was associated with an increased risk of early-onset COPD. Finally, SNPs significantly associated with exposure and outcome were selected for enrichment analysis.
Our findings suggest that exposure to air pollutants may play a causal role in the development of respiratory diseases, with a potential role of epigenomic modifications emphasized. Strengthening comprehensive air pollution regulations by relevant authorities could potentially mitigate the risk of these diseases.
流行病学研究一致表明，长期暴露于空气污染物与呼吸道疾病之间存在密切关联。然而，由于观察性研究中存在残余混杂因素，确定因果关系仍然具有挑战性。在本研究中，采用孟德尔随机化（MR）分析来探讨各种空气污染物与常见呼吸道疾病之间的因果关系和表观遗传关系。
我们利用两样本孟德尔随机化（TSMR）方法，使用来自大规模欧洲全基因组关联研究（GWAS）数据集的数据（暴露组N = 423,796 - 456,380；结局组N = 162,962 - 486,484），探讨PM、PM、PM、NO和NO对九种呼吸道疾病发病率的影响。主要分析方法是逆方差加权（IVW），它使用与空气污染相关的单核苷酸多态性（SNP）来探索暴露 - 结局关系。采用敏感性分析，包括MR - Egger回归和留一法分析，以确保结果的一致性。进行多变量MR（MVMR）以调整潜在的吸烟相关混杂因素，如每日吸烟量、家庭吸烟情况、在家中接触烟草烟雾、曾经吸烟、二手烟、开始吸烟情况以及开始吸烟时的年龄，以及每种空气污染物的独立影响。此外，进行甲基化和富集分析以进一步阐明空气污染对呼吸道疾病的潜在影响。
TSMR分析显示，暴露于PM会增加早发型慢性阻塞性肺疾病（COPD）、肺炎、肺栓塞和肺癌的风险。暴露于PM与肺癌风险增加相关，而暴露于PM会增加肺炎和支气管扩张的风险。暴露于NO与肺癌和成人哮喘风险增加相关。重要的是，即使在MVMR分析中控制了潜在的烟草相关混杂因素后，这些关联仍然很强。在调整其他污染物的MVMR分析中，PM与早发型COPD之间以及PM与肺炎之间仍存在显著关联。基因共定位分析证实，与PM相关的CpG位点（c1orf175附近的cg11386376、rfx2附近的cg11846064、rptor附近的cg18612040和c7orf50附近的cg19765378）的甲基化与早发型COPD风险增加相关。最后，选择与暴露和结局显著相关的SNP进行富集分析。
我们的研究结果表明，暴露于空气污染物可能在呼吸道疾病的发生中起因果作用，强调了表观基因组修饰的潜在作用。相关当局加强全面的空气污染法规可能会降低这些疾病的风险。
