Personal airborne chemical exposure and epigenetic ageing biomarkers in healthy Chinese elderly individuals: Evidence from mixture approaches

Wanying Shi; Xu Gao; Yaqiang Cao; Yuanyuan Chen; Qian Cui; Fuchang Deng; Bo Yang; Elizabeth Z Lin; Jianlong Fang; Tiantian Li; Song Tang; Krystal J Godri Pollitt; Xiaoming Shi

doi:10.1016/j.envint.2022.107614

Personal airborne chemical exposure and epigenetic ageing biomarkers in healthy Chinese elderly individuals: Evidence from mixture approaches

Environ Int. 2022 Dec:170:107614. doi: 10.1016/j.envint.2022.107614. Epub 2022 Nov 3.

Authors

Wanying Shi¹, Xu Gao², Yaqiang Cao³, Yuanyuan Chen⁴, Qian Cui⁵, Fuchang Deng⁴, Bo Yang⁶, Elizabeth Z Lin⁷, Jianlong Fang⁴, Tiantian Li³, Song Tang³, Krystal J Godri Pollitt⁸, Xiaoming Shi⁹

Affiliations

¹ China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
² Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China.
³ China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
⁴ China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
⁵ China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; School of Ecology and Environment, Inner Mongolia University, Hohhot, China.
⁶ China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; School of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China.
⁷ Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA.
⁸ Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA. Electronic address: krystal.pollitt@yale.edu.
⁹ China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China. Electronic address: shixm@chinacdc.cn.

PMID: 36375280
DOI: 10.1016/j.envint.2022.107614

Abstract

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.

Keywords: Ageing biomarker; Airborne chemical mixture; Bayesian kernel machine regression (BKMR); Weighted quantile sum (WQS) regression.

MeSH terms

Aged
Aging
Air Pollution* / adverse effects
Bayes Theorem
Biomarkers
East Asian People
Epigenomics
Humans
Polycyclic Aromatic Hydrocarbons* / toxicity

Substances

Biomarkers
Polycyclic Aromatic Hydrocarbons
phthalic acid