Genetic evidence for the causal effects of air pollution on the risk of respiratory diseases
Background: 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...
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Elsevier
2025-01-01
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| Series: | Ecotoxicology and Environmental Safety |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0147651324016786 |
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| author | Yanjuan Wu Yuting Zhang Jingcun Wang Qiming Gan Xiaofen Su Sun Zhang Yutong Ding Xinyan Yang Nuofu Zhang Kang Wu |
| author_facet | Yanjuan Wu Yuting Zhang Jingcun Wang Qiming Gan Xiaofen Su Sun Zhang Yutong Ding Xinyan Yang Nuofu Zhang Kang Wu |
| author_sort | Yanjuan Wu |
| collection | DOAJ |
| description | Background: 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. Methods: We utilized a two-sample Mendelian randomization (TSMR) approach to explore the impact of PM2.5, PM2.5–10, PM10, NO2, and NOX 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. Results: TSMR analysis revealed that exposure to PM2.5 increased the risk of early-onset chronic obstructive pulmonary disease (COPD), pneumonia, pulmonary embolism and lung cancer. PM2.5–10 exposure was associated with an increased risk of lung cancer, while PM10 exposure increased the risk of pneumonia and bronchiectasis. NO2 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 PM2.5 and early-onset COPD, and between PM10 and pneumonia. Genetic co-localization analyses confirmed that methylation of PM2.5-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. Conclusions: 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. |
| format | Article |
| id | doaj-art-6d641efb86144c6aa43b7d9949c24259 |
| institution | Kabale University |
| issn | 0147-6513 |
| language | English |
| publishDate | 2025-01-01 |
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| series | Ecotoxicology and Environmental Safety |
| spelling | doaj-art-6d641efb86144c6aa43b7d9949c242592025-02-12T05:29:57ZengElsevierEcotoxicology and Environmental Safety0147-65132025-01-01290117602Genetic evidence for the causal effects of air pollution on the risk of respiratory diseasesYanjuan Wu0Yuting Zhang1Jingcun Wang2Qiming Gan3Xiaofen Su4Sun Zhang5Yutong Ding6Xinyan Yang7Nuofu Zhang8Kang Wu9Sleep 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, ChinaSleep 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, ChinaSleep 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, ChinaSleep 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, ChinaSleep 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, ChinaSleep 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, ChinaSleep 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, ChinaSleep 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, ChinaCorrespondence to: Department of Pulmonary and Critical Care Medicine, Sleep Medicine Center, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, No. 28 Qiaozhong Mid Road, 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, ChinaCorrespondence to: Department of Pulmonary and Critical Care Medicine, Sleep Medicine Center, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, No. 28 Qiaozhong Mid Road, 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, ChinaBackground: 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. Methods: We utilized a two-sample Mendelian randomization (TSMR) approach to explore the impact of PM2.5, PM2.5–10, PM10, NO2, and NOX 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. Results: TSMR analysis revealed that exposure to PM2.5 increased the risk of early-onset chronic obstructive pulmonary disease (COPD), pneumonia, pulmonary embolism and lung cancer. PM2.5–10 exposure was associated with an increased risk of lung cancer, while PM10 exposure increased the risk of pneumonia and bronchiectasis. NO2 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 PM2.5 and early-onset COPD, and between PM10 and pneumonia. Genetic co-localization analyses confirmed that methylation of PM2.5-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. Conclusions: 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.http://www.sciencedirect.com/science/article/pii/S0147651324016786Air pollutionParticulate matterRespiratory diseasesMendelian randomizationGeneticsDNA methylation |
| spellingShingle | Yanjuan Wu Yuting Zhang Jingcun Wang Qiming Gan Xiaofen Su Sun Zhang Yutong Ding Xinyan Yang Nuofu Zhang Kang Wu Genetic evidence for the causal effects of air pollution on the risk of respiratory diseases Ecotoxicology and Environmental Safety Air pollution Particulate matter Respiratory diseases Mendelian randomization Genetics DNA methylation |
| title | Genetic evidence for the causal effects of air pollution on the risk of respiratory diseases |
| title_full | Genetic evidence for the causal effects of air pollution on the risk of respiratory diseases |
| title_fullStr | Genetic evidence for the causal effects of air pollution on the risk of respiratory diseases |
| title_full_unstemmed | Genetic evidence for the causal effects of air pollution on the risk of respiratory diseases |
| title_short | Genetic evidence for the causal effects of air pollution on the risk of respiratory diseases |
| title_sort | genetic evidence for the causal effects of air pollution on the risk of respiratory diseases |
| topic | Air pollution Particulate matter Respiratory diseases Mendelian randomization Genetics DNA methylation |
| url | http://www.sciencedirect.com/science/article/pii/S0147651324016786 |
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