Metabolomic signature and prediction of incident lung cancer from air pollution exposure in a national cohort: Unraveling the link and underlying role

Air pollution exposure has been identified as a pathogenic factor of lung cancer, whereas the metabolic profile disturbance involved and its underlying role remain unclear while attract much attention. Metabolomic profiling in plasma was conducted among 205,974 participants in the UK Biobank. Particulate matter (PM) with aerodynamic diameter ≤ 10 μm (PM 10 ), PM 2.5 , PM 2.5–10 , nitrogen dioxide (NO 2 ), and nitrogen oxides (NO x ) were assessed by land-use regression models. Mediation roles of metabolic features involved in air pollution and incident lung cancer, and performance of the lung cancer prediction model incorporating crucial metabolite features identified by least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression, were evaluated. During a median follow-up period of 13.1 years, 1,536 incident lung cancer cases were recorded. Among the 143 metabolite features, 66 overlapped in PM 2.5 , NO 2 , or NO x exposure-associated incident lung cancer after multivariate adjustment (false discovery rate P < 0.05). The highest mediation proportions were observed for Albumin (percentage mediated: 4.02 %), Phospholipids in Medium Very-Low-Density Lipoproteins (M-VLDL) (6.38 %), and M-VLDL (6.42 %) in incident lung cancer from PM 2.5 , NO 2 , and NO x exposure, respectively. LASSO and multivariate Cox regression identified 15 metabolite features associated with lung cancer, and inclusion of these metabolite features significantly improved the prediction of lung cancer (C statistic: 0.851; Net reclassification improvement index: 0.144; Integrated discrimination improvement index: 0.005). Disturbance and mediation role of circulating metabolic features in air pollution exposure and incident lung cancer were identified, and metabolite profiling may well improve early prediction of lung cancer. • Metabolic features associated with air pollution exposure were identified. • Metabolic disturbance was associated with lung cancer risk. • Mediation role of metabolites in air pollution and lung cancer was unveiled. • Metabolite profiling may well improve early prediction of lung cancer.

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Journal
Environmental Chemistry and Ecotoxicology
Published
2025-10-31
DOI
https://doi.org/10.1016/j.enceco.2025.10.033
Citations
2
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
1.61
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article

Metabolomic signature and prediction of incident lung cancer from air pollution exposure in a national cohort: Unraveling the link and underlying role

Hao Wang, Jiahao Song, Bin Wang, Sinan Wu et al.
2 citations
Environmental Chemistry and Ecotoxicology
Metabolomics and Mass Spectrometry Studies
1.61
article

Metabolomic signature and prediction of incident lung cancer from air pollution exposure in a national cohort: Unraveling the link and underlying role

Hao Wang, Jiahao Song, Bin Wang, Sinan Wu, Le Huynh Thi Cam Hong, Da Shi, Qing Liu, Wei Liu, Shuhui Wan, Wendi Shi, Zhiying Huo, Weihong Chen, Xuefeng Lai, Yongfang Zhang, Yueru Yang
article en
2 citations

Abstract

Air pollution exposure has been identified as a pathogenic factor of lung cancer, whereas the metabolic profile disturbance involved and its underlying role remain unclear while attract much attention. Metabolomic profiling in plasma was conducted among 205,974 participants in the UK Biobank. Particulate matter (PM) with aerodynamic diameter ≤ 10 μm (PM 10 ), PM 2.5 , PM 2.5–10 , nitrogen dioxide (NO 2 ), and nitrogen oxides (NO x ) were assessed by land-use regression models. Mediation roles of metabolic features involved in air pollution and incident lung cancer, and performance of the lung cancer prediction model incorporating crucial metabolite features identified by least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression, were evaluated. During a median follow-up period of 13.1 years, 1,536 incident lung cancer cases were recorded. Among the 143 metabolite features, 66 overlapped in PM 2.5 , NO 2 , or NO x exposure-associated incident lung cancer after multivariate adjustment (false discovery rate P < 0.05). The highest mediation proportions were observed for Albumin (percentage mediated: 4.02 %), Phospholipids in Medium Very-Low-Density Lipoproteins (M-VLDL) (6.38 %), and M-VLDL (6.42 %) in incident lung cancer from PM 2.5 , NO 2 , and NO x exposure, respectively. LASSO and multivariate Cox regression identified 15 metabolite features associated with lung cancer, and inclusion of these metabolite features significantly improved the prediction of lung cancer (C statistic: 0.851; Net reclassification improvement index: 0.144; Integrated discrimination improvement index: 0.005). Disturbance and mediation role of circulating metabolic features in air pollution exposure and incident lung cancer were identified, and metabolite profiling may well improve early prediction of lung cancer. • Metabolic features associated with air pollution exposure were identified. • Metabolic disturbance was associated with lung cancer risk. • Mediation role of metabolites in air pollution and lung cancer was unveiled. • Metabolite profiling may well improve early prediction of lung cancer.

Environmental Chemistry and EcotoxicologyVol. 8
University of Alberta (CA), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Ministry of Ecology and Environment (CN), University of Cambridge (GB), China-Japan Friendship Hospital (CN), First Affiliated Hospital of Gannan Medical University (CN), Wuhan University of Science and Technology (CN), Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 14%
Metabolomics and Mass Spectrometry Studies
1.61
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