Background: Air pollution is associated with accelerated biological ages determined by DNA methylation (DNAm) patterns, imposing further risks of age-related adverse effects. However, little is known about the independent and joint effects of exposure to gaseous organic chemicals that may share a common source.
Methods: We conducted a panel study with the 3-day exposure assessment monthly among 73 Chinese healthy elderly people aged 60 to 69 years in Jinan, Shandong province during September 2018 to January 2019.Exposure to 26 ambient organic chemical contaminants were measured by wearable passive samplers, including volatile organic compounds, polycyclic aromatic hydrocarbons (PAHs), phthalates (PAEs), nitroaromatics (NIs), polybrominated diphenyl ethers, chlorinated hydrocarbons, and organophosphate esters. The Illumina MethylationEPIC BeadChip was used to measure DNA methylation levels in blood samples, and based on which, epigenetic ageing biomarkers, including Hannum clock, Horvath clock, DNAm PhenoAge, DNAm GrimAge, and DNAm estimator of telomere length (DNAmTL) were calculated. Linear mixed effect models were used to estimate the linear associations between 3-day personal chemical exposure and the epigenetic biomarkers, Weighted quantile sum (WQS) regression and the Bayesian kernel machine regression (BKMR) model were further used to evaluate the effect of chemical mixtures.
Results: Multiple linear mixed effects regression models showed that DNAmPhenoAge acceleration was significantly and positively associated with exposure to PAEs, NIs, and PAHs in healthy elderly individuals. Both WQS regression and BKMR models showed a significant positive association with DNAmPhenoAge acceleration with chemical exposures, in which the effect of di-n-butyl phthalate exposure showed the greatest importance.
Conclusion: These findings suggest that exposure to a mixture of airborne chemicals significantly increase the acceleration of the epigenetic biomarker of phenotypic age. These findings serve to identify toxic chemicals in the air and facilitate the evaluation of their potentially severe health effects.
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http://dx.doi.org/10.1016/j.envint.2022.107614 | DOI Listing |
Arch Toxicol
January 2025
Department of Ecotoxicology, Helmholtz Centre for Environmental Research-UFZ, Permoserstraβe 15, 04318, Leipzig, Germany.
Testing for developmental toxicity is an integral part of chemical regulations. The applied tests are laborious and costly and require a large number of vertebrate test animals. To reduce animal numbers and associated costs, the zebrafish embryo was proposed as an alternative model.
View Article and Find Full Text PDFArch Toxicol
January 2025
Department of Medicine, University of California, San Diego, CA, 92093, USA.
E-cigarettes (E.cigs) cause inflammation and damage to human organs, including the lungs and heart. In the gut, E.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
Nicholas School of the Environment, Duke University, Durham, North Carolina 27708, United States.
Pet dogs offer valuable models for studying environmental impacts on human health due to shared environments and a shorter latency period for cancer development. We assessed environmental chemical exposures in a case-control study involving dogs at high risk of urothelial carcinoma, identified by a BRAF V595E mutation in urinary epithelial cells. Cases ( = 25) exhibited low-level BRAF mutations, while controls ( = 76) were matched dogs without the mutation.
View Article and Find Full Text PDFBackground: There is growing interest in the role of environmental factors (i.e., exposome) in the pathogenesis of Alzheimer's diseases.
View Article and Find Full Text PDFBackground: It is now widely acknowledged that diet, lifestyle, and environmental exposures largely affect an individual's metabolic state in health and disease, including the brain. Metabolomics has demonstrated its potential to enable exciting discoveries in brain health, facilitated by advances in analytical and informatics techniques. Here, we highlighted the use of MS/MS-based untargeted metabolomics to study the diet and medication exposure of cognitively declined cohorts through the newly developed FoodMASST and DrugMASST tools.
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