Bingting Zhuo, Shanshan Ran, Aaron M Qian, Junguo Zhang, Maya Tabet, Steven W Howard, Zilong Zhang, Fei Tian, Hualiang Lin
{"title":"空气污染代谢组特征与慢性呼吸系统疾病风险:一项纵向研究。","authors":"Bingting Zhuo, Shanshan Ran, Aaron M Qian, Junguo Zhang, Maya Tabet, Steven W Howard, Zilong Zhang, Fei Tian, Hualiang Lin","doi":"10.1016/j.chest.2024.06.3809","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Although evidence has documented the associations of ambient air pollution with chronic respiratory diseases (CRDs) and lung function, the underlying metabolic mechanisms remain largely unclear.</p><p><strong>Research question: </strong>How does the metabolomic signature for air pollution relate to CRD risk, respiratory symptoms, and lung function?</p><p><strong>Study design and methods: </strong>We retrieved 171,132 participants free of COPD and asthma at baseline from the UK Biobank, who had data on air pollution and metabolomics. Exposures to air pollutants (particulate matter with diameter ≤ 2.5 μm [PM<sub>2.5</sub>], particulate matter with a diameter ≤ 10 μm, nitrogen oxide [NO<sub>X</sub>], and NO<sub>2</sub>) were assessed for 4 years before baseline considering residential address histories. We used 10-fold cross-validation elastic net regression to identify air pollution-associated metabolites. Multivariable Cox models were used to assess the associations between metabolomic signatures and CRD risk. Mediation and pathway analysis were conducted to explore the metabolic mechanism underlying the associations.</p><p><strong>Results: </strong>During a median follow-up of 12.51 years, 8,951 and 5,980 incident COPD and asthma cases were recorded. In multivariable Cox regressions, air pollution was positively associated with CRD risk (eg, hazard ratio per interquartile range increment in PM<sub>2.5</sub>, 1.09; 95% CI, 1.06-1.13). We identified 103, 86, 85, and 90 metabolites in response to PM<sub>2.5</sub>, particulate matter with a diameter ≤ 10 μm, NO<sub>X</sub>, and NO<sub>2</sub> exposure, respectively. The metabolomic signatures showed significant associations with CRD risk (hazard ratio per SD increment in PM<sub>2.5</sub> metabolomic signature, 1.11; 95% CI, 1.09-1.14). Mediation analysis showed that peripheral inflammatory and erythrocyte-related markers mediated the effects of metabolomic signatures on CRD risk. We identified 14 and 12 perturbed metabolic pathways (energy metabolism and amino acid metabolism pathways, etc) for PM<sub>2.5</sub> and NO<sub>X</sub> metabolomic signatures.</p><p><strong>Interpretation: </strong>Our study identifies metabolomic signatures for air pollution exposure. The metabolomic signatures showed significant associations with CRD risk, and inflammatory- and erythrocyte-related markers partly mediated the metabolomic signatures-CRD links.</p>","PeriodicalId":9782,"journal":{"name":"Chest","volume":" ","pages":"975-986"},"PeriodicalIF":9.5000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Air Pollution Metabolomic Signatures and Chronic Respiratory Diseases Risk: A Longitudinal Study.\",\"authors\":\"Bingting Zhuo, Shanshan Ran, Aaron M Qian, Junguo Zhang, Maya Tabet, Steven W Howard, Zilong Zhang, Fei Tian, Hualiang Lin\",\"doi\":\"10.1016/j.chest.2024.06.3809\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Although evidence has documented the associations of ambient air pollution with chronic respiratory diseases (CRDs) and lung function, the underlying metabolic mechanisms remain largely unclear.</p><p><strong>Research question: </strong>How does the metabolomic signature for air pollution relate to CRD risk, respiratory symptoms, and lung function?</p><p><strong>Study design and methods: </strong>We retrieved 171,132 participants free of COPD and asthma at baseline from the UK Biobank, who had data on air pollution and metabolomics. Exposures to air pollutants (particulate matter with diameter ≤ 2.5 μm [PM<sub>2.5</sub>], particulate matter with a diameter ≤ 10 μm, nitrogen oxide [NO<sub>X</sub>], and NO<sub>2</sub>) were assessed for 4 years before baseline considering residential address histories. We used 10-fold cross-validation elastic net regression to identify air pollution-associated metabolites. Multivariable Cox models were used to assess the associations between metabolomic signatures and CRD risk. Mediation and pathway analysis were conducted to explore the metabolic mechanism underlying the associations.</p><p><strong>Results: </strong>During a median follow-up of 12.51 years, 8,951 and 5,980 incident COPD and asthma cases were recorded. In multivariable Cox regressions, air pollution was positively associated with CRD risk (eg, hazard ratio per interquartile range increment in PM<sub>2.5</sub>, 1.09; 95% CI, 1.06-1.13). We identified 103, 86, 85, and 90 metabolites in response to PM<sub>2.5</sub>, particulate matter with a diameter ≤ 10 μm, NO<sub>X</sub>, and NO<sub>2</sub> exposure, respectively. The metabolomic signatures showed significant associations with CRD risk (hazard ratio per SD increment in PM<sub>2.5</sub> metabolomic signature, 1.11; 95% CI, 1.09-1.14). Mediation analysis showed that peripheral inflammatory and erythrocyte-related markers mediated the effects of metabolomic signatures on CRD risk. We identified 14 and 12 perturbed metabolic pathways (energy metabolism and amino acid metabolism pathways, etc) for PM<sub>2.5</sub> and NO<sub>X</sub> metabolomic signatures.</p><p><strong>Interpretation: </strong>Our study identifies metabolomic signatures for air pollution exposure. 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Air Pollution Metabolomic Signatures and Chronic Respiratory Diseases Risk: A Longitudinal Study.
Background: Although evidence has documented the associations of ambient air pollution with chronic respiratory diseases (CRDs) and lung function, the underlying metabolic mechanisms remain largely unclear.
Research question: How does the metabolomic signature for air pollution relate to CRD risk, respiratory symptoms, and lung function?
Study design and methods: We retrieved 171,132 participants free of COPD and asthma at baseline from the UK Biobank, who had data on air pollution and metabolomics. Exposures to air pollutants (particulate matter with diameter ≤ 2.5 μm [PM2.5], particulate matter with a diameter ≤ 10 μm, nitrogen oxide [NOX], and NO2) were assessed for 4 years before baseline considering residential address histories. We used 10-fold cross-validation elastic net regression to identify air pollution-associated metabolites. Multivariable Cox models were used to assess the associations between metabolomic signatures and CRD risk. Mediation and pathway analysis were conducted to explore the metabolic mechanism underlying the associations.
Results: During a median follow-up of 12.51 years, 8,951 and 5,980 incident COPD and asthma cases were recorded. In multivariable Cox regressions, air pollution was positively associated with CRD risk (eg, hazard ratio per interquartile range increment in PM2.5, 1.09; 95% CI, 1.06-1.13). We identified 103, 86, 85, and 90 metabolites in response to PM2.5, particulate matter with a diameter ≤ 10 μm, NOX, and NO2 exposure, respectively. The metabolomic signatures showed significant associations with CRD risk (hazard ratio per SD increment in PM2.5 metabolomic signature, 1.11; 95% CI, 1.09-1.14). Mediation analysis showed that peripheral inflammatory and erythrocyte-related markers mediated the effects of metabolomic signatures on CRD risk. We identified 14 and 12 perturbed metabolic pathways (energy metabolism and amino acid metabolism pathways, etc) for PM2.5 and NOX metabolomic signatures.
Interpretation: Our study identifies metabolomic signatures for air pollution exposure. The metabolomic signatures showed significant associations with CRD risk, and inflammatory- and erythrocyte-related markers partly mediated the metabolomic signatures-CRD links.
期刊介绍:
At CHEST, our mission is to revolutionize patient care through the collaboration of multidisciplinary clinicians in the fields of pulmonary, critical care, and sleep medicine. We achieve this by publishing cutting-edge clinical research that addresses current challenges and brings forth future advancements. To enhance understanding in a rapidly evolving field, CHEST also features review articles, commentaries, and facilitates discussions on emerging controversies. We place great emphasis on scientific rigor, employing a rigorous peer review process, and ensuring all accepted content is published online within two weeks.