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Lirong Liang

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Open access Jul 2026

Association of PM2.5 chemical components with metabolome and peak expiratory flow in patients with stable COPD: a panel study.

OBJECTIVE The component‑specific toxicity of fine particulate matter (PM2.5) and the underlying metabolic pathways driving airflow impairment in chronic obstructive pulmonary disease (COPD) remain unclear. We evaluated how specific PM2.5 constituents alter circulating metabolites and mediate short‑term changes in peak expiratory flow (PEF) among COPD patients. METHODS A panel study was conducted in 32 patients with stable COPD in Beijing (2018-2019). Participants were followed-up across four seasons, yielding 3363 daily PEF measurements and 208 serum samples for untargeted metabolomics. PM2.5 components concentrations were obtained from a high-resolution (1 km) dataset integrating ground observations, satellite retrievals, and model simulations. Linear mixed-effects models were used to estimate the associations between PM2.5 components and PEF, and a meet-in-the-middle strategy was adopted to identify mediating metabolites and pathways. RESULTS PEF declines were associated with interquartile range increase in several PM2.5 components (lag0-7 days moving average), most notably for black carbon [-5.88 (-8.76 ~ -3.01) L/min] and sulfate [-4.78 (-8.82 ~ -0.73) L/min]. Metabolomic analysis identified 12 metabolites significantly linked to PEF (q < 0.05). Pathway enrichment highlighted urea cycle/amino group metabolism (P = 0.041) and bile acid biosynthesis (P = 0.012) as key biological response routes. Five metabolites were identified as mediators of the associations between PM2.5 components and PEF, notably Nb-arachidoyltryptamine and 6-nitrochrysene. CONCLUSION These findings highlight black carbon and sulfate as primary drivers of PM2.5-related lung function impairment in COPD patients, likely acting through systemic metabolic perturbations. Our study supports targeted emission controls and suggests metabolic profiling as a potential approach for targeted prevention in vulnerable populations.

Jiachen Li, Lirong Liang, Y. Cai et al. · 0 citations

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