A large prospective metabolomics study has linked long-term air pollution exposure to circulating metabolic changes associated with later lung cancer risk.
The study analyzed pre-diagnostic plasma samples from 1,357 participants in two American Cancer Society Cancer Prevention Study cohorts. All participants were cancer-free when blood was collected; 671 were later diagnosed with lung cancer. Residential exposure estimates for six ambient air pollutants, including carbon monoxide, nitrogen dioxide, ozone, sulfur dioxide, PM10, and PM2.5, were assigned at the time of blood draw.
To connect exposure, metabolism, and disease risk, the team profiled plasma metabolites using untargeted ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Samples were analyzed under four chromatographic and ionization conditions, including reverse-phase and hydrophilic interaction chromatography methods. After quality control, 1,138 metabolites were included in the final analysis.
The researchers then applied metabolome-wide association studies to identify metabolic features linked to air pollution exposure, followed by high-dimensional mediation analysis to test whether any of those features could statistically mediate associations between pollution and lung cancer risk.
Of the 1,138 metabolites analyzed, 522 were associated with at least one air pollutant. Eight metabolites were associated with both air pollution exposure and subsequent lung cancer risk. Seven were confirmed with level 1 evidence, meaning their accurate mass, retention time, and MS/MS fragmentation spectra matched authentic chemical standards analyzed under the same conditions.
Four metabolites emerged as potential intermediates between air pollution exposure and later lung cancer risk in the mediation analysis. The mediated associations involved PM10, PM2.5, and ozone, with signals linked mainly to peptide and xenobiotic metabolism. These pathways suggest possible roles for oxidative stress, inflammation, combustion-related exposures, and glutathione-related responses.
Several findings were biologically complex. For example, gamma-glutamylglutamine was positively associated with multiple air pollutants but inversely associated with lung cancer risk. The authors suggest that this pattern may reflect compensatory or feedback responses to pollutant-induced oxidative stress or inflammation, rather than a simple harmful exposure signal.
Sensitivity analyses gave similar results after adjustment for baseline comorbidities, use of five-year air pollution averages, and stratification by sex, smoking status, family history, and age. The authors note, however, that the study remains observational and hypothesis-generating.
The findings do not establish causality, but they suggest that blood metabolomics could help identify the inflammatory, oxidative, and xenobiotic-response pathways through which particulate matter and ozone may contribute to lung cancer risk.
The authors note that the analysis was limited by single-time-point exposure and metabolomic measurements, an older and predominantly white study population, and the exploratory statistical threshold used for untargeted metabolomics.
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