Fei Tian, Yuhua Wang, Zhenhe Huang, Aaron M. Qian, Chongjian Wang, Lei Tan, Stephen Edward McMillin, Chad Abresch, Zilong Zhang, Hualiang Lin
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The underlying mechanisms between air pollution and dementia driven by metabolic signature or specific metabolites were also investigated. A total of 2,592 incident dementia cases were documented. We identified the metabolite profiles in response to air pollution exposure, including 87 metabolites for PM<sub>2.5</sub>, 65 metabolites for PM<sub>10</sub>, 76 metabolites for NO<sub>2</sub>, and 71 metabolites for NO<sub>x</sub>. The air pollution-related metabolic signatures were associated with increased risk of dementia, with hazard ratios (HR) of 1.17 (95% CI: 1.12, 1.22), 1.06 (95% CI: 1.02, 1.11), 1.16 (95% CI: 1.10, 1.21), and 1.17 (95% CI: 1.12, 1.22) for PM<sub>2.5</sub>, PM<sub>10</sub>, NO<sub>2</sub> and NO<sub>x</sub>, respectively. The associations persisted using causal models. Metabolic signatures mediated the associations between air pollution exposure and dementia risk, with mediation proportions ranging from 6.57% to 12.71%. Additionally, we observed that a metabolite known as free cholesterol in medium VLDL (M-VLDL-FC) played a crucial mediating role. Our study provides novel insights into the metabolic mechanisms linking air pollution exposure to dementia risk.","PeriodicalId":361,"journal":{"name":"Journal of Hazardous Materials","volume":"35 1","pages":""},"PeriodicalIF":12.2000,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Metabolomic profiling identifies signatures and biomarkers linking air pollution to dementia risk: a prospective cohort study\",\"authors\":\"Fei Tian, Yuhua Wang, Zhenhe Huang, Aaron M. Qian, Chongjian Wang, Lei Tan, Stephen Edward McMillin, Chad Abresch, Zilong Zhang, Hualiang Lin\",\"doi\":\"10.1016/j.jhazmat.2024.136498\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Exposure to air pollution has been associated with increased dementia. However, it remains unknown what specific metabolic mechanisms play a role in this relationship. We included 192,300 dementia-free participants from the UK Biobank cohort study. Annual concentrations of air pollution were assessed based on the residential address. Elastic net regression was performed to identify air pollution-related metabolites, and metabolic score was constructed. Cox regression models and covariate balancing generalized propensity scores (CBGPS) regression models were conducted to explore the longitudinal associations between air pollution/metabolic signatures and dementia risk. The underlying mechanisms between air pollution and dementia driven by metabolic signature or specific metabolites were also investigated. A total of 2,592 incident dementia cases were documented. We identified the metabolite profiles in response to air pollution exposure, including 87 metabolites for PM<sub>2.5</sub>, 65 metabolites for PM<sub>10</sub>, 76 metabolites for NO<sub>2</sub>, and 71 metabolites for NO<sub>x</sub>. The air pollution-related metabolic signatures were associated with increased risk of dementia, with hazard ratios (HR) of 1.17 (95% CI: 1.12, 1.22), 1.06 (95% CI: 1.02, 1.11), 1.16 (95% CI: 1.10, 1.21), and 1.17 (95% CI: 1.12, 1.22) for PM<sub>2.5</sub>, PM<sub>10</sub>, NO<sub>2</sub> and NO<sub>x</sub>, respectively. The associations persisted using causal models. Metabolic signatures mediated the associations between air pollution exposure and dementia risk, with mediation proportions ranging from 6.57% to 12.71%. Additionally, we observed that a metabolite known as free cholesterol in medium VLDL (M-VLDL-FC) played a crucial mediating role. 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Metabolomic profiling identifies signatures and biomarkers linking air pollution to dementia risk: a prospective cohort study
Exposure to air pollution has been associated with increased dementia. However, it remains unknown what specific metabolic mechanisms play a role in this relationship. We included 192,300 dementia-free participants from the UK Biobank cohort study. Annual concentrations of air pollution were assessed based on the residential address. Elastic net regression was performed to identify air pollution-related metabolites, and metabolic score was constructed. Cox regression models and covariate balancing generalized propensity scores (CBGPS) regression models were conducted to explore the longitudinal associations between air pollution/metabolic signatures and dementia risk. The underlying mechanisms between air pollution and dementia driven by metabolic signature or specific metabolites were also investigated. A total of 2,592 incident dementia cases were documented. We identified the metabolite profiles in response to air pollution exposure, including 87 metabolites for PM2.5, 65 metabolites for PM10, 76 metabolites for NO2, and 71 metabolites for NOx. The air pollution-related metabolic signatures were associated with increased risk of dementia, with hazard ratios (HR) of 1.17 (95% CI: 1.12, 1.22), 1.06 (95% CI: 1.02, 1.11), 1.16 (95% CI: 1.10, 1.21), and 1.17 (95% CI: 1.12, 1.22) for PM2.5, PM10, NO2 and NOx, respectively. The associations persisted using causal models. Metabolic signatures mediated the associations between air pollution exposure and dementia risk, with mediation proportions ranging from 6.57% to 12.71%. Additionally, we observed that a metabolite known as free cholesterol in medium VLDL (M-VLDL-FC) played a crucial mediating role. Our study provides novel insights into the metabolic mechanisms linking air pollution exposure to dementia risk.
期刊介绍:
The Journal of Hazardous Materials serves as a global platform for promoting cutting-edge research in the field of Environmental Science and Engineering. Our publication features a wide range of articles, including full-length research papers, review articles, and perspectives, with the aim of enhancing our understanding of the dangers and risks associated with various materials concerning public health and the environment. It is important to note that the term "environmental contaminants" refers specifically to substances that pose hazardous effects through contamination, while excluding those that do not have such impacts on the environment or human health. Moreover, we emphasize the distinction between wastes and hazardous materials in order to provide further clarity on the scope of the journal. We have a keen interest in exploring specific compounds and microbial agents that have adverse effects on the environment.