TY - JOUR
T1 - Metabolomic profiling identifies signatures and biomarkers linking air pollution to dementia risk
T2 - A prospective cohort study
AU - Tian, Fei
AU - Wang, Yuhua
AU - Huang, Zhenhe
AU - Qian, Aaron M.
AU - Wang, Chongjian
AU - Tan, Lei
AU - McMillin, Stephen Edward
AU - Abresch, Chad
AU - Zhang, Zilong
AU - Lin, Hualiang
N1 - Publisher Copyright:
© 2024 Elsevier B.V.
PY - 2024/12/5
Y1 - 2024/12/5
N2 - 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 2592 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.
AB - 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 2592 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.
KW - Air pollution
KW - Cohort study
KW - Dementia
KW - Elastic net regression
KW - Metabolic signature
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U2 - 10.1016/j.jhazmat.2024.136498
DO - 10.1016/j.jhazmat.2024.136498
M3 - Article
C2 - 39547039
AN - SCOPUS:85209107957
SN - 0304-3894
VL - 480
JO - Journal of Hazardous Materials
JF - Journal of Hazardous Materials
M1 - 136498
ER -