Aug 2026· International Journal of Molecular Sciences· Vol 27· 0 citations· 33 references
Medicine
Abstract
Ambient fine particulate matter (PM2.5) is associated with oxidative stress, metabolic dysregulation, and cardiometabolic disease. However, systemic metabolic responses to contrasting real-world ambient air pollution exposure environments remain poorly characterized. In this cross-sectional study, untargeted proton nuclear magnetic resonance (1H-NMR)-based urinary metabolomics was used to investigate metabolic signatures associated with contrasting ambient air pollution exposure environments in Thailand. Adults residing in Chiang Mai (high-exposure region; n = 51) and Songkhla (low-exposure region; n = 52) were recruited during a period of elevated regional air pollution, with long-term residence serving as a proxy for differential exposure to ambient air pollution environments. Partial least squares-discriminant analysis (PLS-DA) demonstrated separation between exposure groups (R2 = 0.873, Q2 = 0.447), indicating good model fit but only modest predictive ability. Eight urinary metabolites differed significantly (p < 0.05), implicating pathways related to tryptophan metabolism, nucleotide metabolism, energy metabolism, and host–microbial co-metabolism. L-arginine and L-cystathionine showed lower relative abundance in the high-exposure group, and six metabolites remained significant after Benjamini–Hochberg false discovery rate correction. Following covariate adjustment, L-tryptophan, hippuric acid, xanthine, and 5-hydroxyindoleacetic acid (5-HIAA) remained significantly associated with the high-exposure group. Contrasting ambient air pollution exposure environments, indexed by regional PM2.5 concentrations, were associated with coordinated urinary metabolic alterations. Because long-term regional residence served as a proxy for individual-level exposure and diet and lifestyle differences between regions were not fully controlled, these findings should be interpreted as associations with contrasting regional exposure environments. Metabolite annotations remain putative and require validation in longitudinal studies with comprehensive pollutant characterization and individual-level exposure assessment.
Background/Objectives: Ambient fine particulate matter (PM2.5) poses significant health risks to older adult populations, yet the specific contributions of its chemical constituents, particularly non-phthalate and non-organophosphate ester compounds, remain poorly understood. This study aimed to elucidate the mechanistic links between PM2.5-bound ester exposures and metabolic pathway alterations in elderly individuals. Methods: A total of 258 elderly residents aged 60 years or older from Fuzhou, China, were recruited. Personal PM2.5 exposure was monitored over 72 h using UPAS V2 samplers, with chemical components analyzed via gas chromatography–mass spectrometry (GC–MS). Plasma metabolomic profiling was conducted using liquid chromatography–mass spectrometry (LC–MS), and metabolic pathway enrichment was performed using MetaboAnalyst 5.0. Linear regression models adjusted for covariates (age, sex, BMI, lifestyle factors) assessed associations between ester exposures and metabolite abundance. Results: The mean PM2.5 concentration was 38.06 μg/m3, with ester compounds dominating the chemical composition. Twenty high-concentration non-target esters were prioritized for analysis. PM2.5 ester exposure was associated with alterations in key metabolic pathways, including steroid biosynthesis, glycolysis/gluconeogenesis, glycerophospholipid metabolism, and purine/pyrimidine metabolism. When interpreted alongside prior epidemiological evidence, these alterations represent putative links to increased risks of insulin resistance, cardiovascular dysfunction, and metabolic syndrome—relationships that require confirmation in prospective cohort studies and controlled toxicological experiments. Conclusions: Putatively annotated PM2.5-bound ester compounds, particularly non-regulated subclasses, are associated with systemic metabolic alterations in older adults, coincident with perturbations in steroid and lipid metabolism. While these findings are exploratory and hypothesis-generating, they highlight the need to incorporate specific ester profiles into PM2.5 risk assessments and develop targeted interventions for vulnerable aging populations.
Shilin Chen, Ruoyu Li, Wenli Wang et al.· Metabolites· 0 citations
Introduction Ambient air pollutants have been increasingly implicated in immune-mediated disorders, yet the metabolic perturbations through which long-term exposure may contribute to rheumatoid arthritis (RA) remain insufficiently characterized. Methods We used data from 403,332 RA-free participants in the UK Biobank cohort to investigate the associations among long-term ambient air pollution exposure, plasma metabolic signatures, and incident RA risk. Participants were followed for a median of 14.01 years. Residential annual average concentrations of PM2.5, PM10, NO2, and NOx were linked to participants' addresses, and a composite air pollution score (APS) was calculated to reflect overall exposure burden. Plasma metabolomics data were used to characterize metabolic perturbations related to each pollutant. A machine learning model was applied to identify air pollutant-associated metabolites and construct corresponding metabolic signatures. We then examined the relationships of air pollutants and derived metabolic signatures with RA risk using Cox proportional hazards models. Generalized propensity score analyses were performed to assess whether the findings persisted after covariate balancing, and mediation analyses were conducted to estimate the contribution of metabolic signatures to the relationship of air pollutants and RA. Results Each standard deviation increase in the PM2.5-, NO2-, NOx-, and APS-related metabolic signatures was associated with elevated RA risk, with hazard ratios of 1.208 (95% CI: 1.180, 1.236), 1.141 (95% CI: 1.109, 1.173), 1.174 (95% CI: 1.148, 1.201), and 1.184 (95% CI: 1.156, 1.212), respectively. Similar estimates were observed in generalized propensity score analyses. Metabolic signatures accounted for 15.7% to 21.1% of the associations between air pollution exposure and RA risk. Conclusion These findings suggest that long-term air pollution exposure is associated with incident RA risk and that systemic metabolic perturbations may represent potential biological pathways underlying this association.
Yang-Chang Zhang, Tian Liang, Yang Pu et al.· Frontiers in Public Health· 0 citations
It is suggested that air pollution might contribute to T2D risk through inflammation-related proteins, highlighting the potential of proteomics as a tool for precision public health.
Shenghao Yuan, Yongxuan Li, Yujia Bao et al.· Ecotoxicology and Environmen...· 0 citations
It is suggested that air pollution may promote lung cancer partly through metabolic pathways related to inflammatory and oxidative processes, providing key insights into potential mechanisms and targets for prevention.
Sabrina S. Chow, Ying Wang, J. Sarnat et al.· Nature Communications· 0 citations
Summary Background The plasma metabolome represents a valuable molecular readout of a person’s physiological state, yet its relation to health, stress and lifestyle remains underexplored collectively. Methods Here, we conducted an untargeted metabolomics analysis using 3804 paired samples from 1902 participants of the observational Netherlands Study of Depression and Anxiety at baseline and six-year follow-up, quantifying 680 plasma metabolites. We characterised five metabolome principal components, three with distinct biochemical enrichments related to transmembrane transport, sphingolipid, and amino acid metabolism. Findings Metabolite levels showed moderate intrapersonal correlation between baseline and six-year follow-up (ICCmedian = 0.482), and 22% of metabolites showed standardised mean differences >0.2. Multivariate linear modelling on 18 baseline determinants across demographics, psychosocial environment, lifestyle, somatic and mental health explained a maximum of 35% of baseline metabolome PC variance and 12% of six-year change ΔPC variance. Demographic (e.g., sex, age), somatic health (e.g., BMI, medication) and lifestyle factors (e.g., smoking, alcohol intake) demonstrated strong associations both cross-sectionally and longitudinally, while psychosocial factors and mental health contributed minor explained variance in comparison. Interpretation Altogether, our study provides hierarchical insights into the cross-sectional and longitudinal implications of health, stress, and lifestyle exposures for the plasma metabolome. Funding Geestkracht program of the Netherlands Organisation for Health Research and Development, the Dutch Research Council and the Dutch Ministry of Education, Culture and Science, Stress in Action, Amsterdam Neuroscience, ImmunoMIND, the National Institute of Mental Health, National Institute on Ageing and the Foundation for the National Institutes of Health.
D. Klose, Y. Milaneschi, Laura K. M. Han et al.· EBioMedicine· 0 citations
Occupational dust is a widespread environmental contaminant associated with cardiovascular disease risk, yet its underlying molecular mechanisms remain insufficiently elucidated. This study investigated the associations between occupational respirable dust exposure (CDE) and early indicators of cardiovascular risk in 8662 participants from the China-Northern Anhui Coal Workers Cohort (C-NACWC). To explore potential mechanisms, we employed an integrative multi-omics approach, combining serum lipidomics from these participants with publicly available single-cell RNA sequencing data (GSE159677) from human atherosclerotic plaques. Higher levels of CDE were associated with an elevated cardiovascular risk score (CVRS) and adverse lipid profiles. Lipidomics analysis revealed that glycerophospholipid metabolism and insulin resistance mediated 8-21% of the associations between CDE and both CVRS and triglyceride. Single-cell RNA sequencing analysis showed that differentially expressed genes were significantly enriched in glycerophospholipid metabolism and inflammation-related pathways within the atherosclerotic microenvironment. Multi-omics integration suggested interleukin-6 (IL-6) as a potential hub gene in endothelial cells, highlighting a potential link between metabolic dysregulation and inflammatory signaling. Consistently, CDE was positively associated with serum IL-6 concentrations in these miners. Our findings suggest a potential pathway whereby occupational dust exposure is associated with increased early cardiovascular risk via glycerophospholipid metabolism and insulin resistance, which is linked to IL-6- related endothelial inflammation. These findings provide a scientific basis for integrating inflammatory biomarkers into routine occupational screenings. Furthermore, they advocate for a shift in occupational health policy toward comprehensive cardiovascular risk monitoring and personalized health management in dust-exposed populations.
