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Malondialdehyde in exhaled breath condensate and urine as a biomarker of air pollution induced oxidative stress

Journal of Exposure Science & Environmental Epidemiology volume 23, pages 322–327 (2013)Cite this article

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Abstract

Underlying mechanisms by which air pollutants adversely affect human health remain poorly understood. Oxidative stress has been considered as a potential mechanism that may promote lipid peroxidation by reactive oxygen species, leading to the formation of malondialdehyde (MDA) that is excreted in biofluids (e.g., urine and exhaled breath condensate (EBC)). A panel study was conducted to examine whether concentrations of MDA in EBC and urine were associated, respectively, with changes in air pollution levels brought by the Beijing Olympic air pollution control measures. EBC and urine samples from 125 healthy adults were collected twice in each of the pre-, during-, and post-Olympic periods. Period-specific means of MDA and changes in MDA levels associated with increases in 24-h average pollutant concentrations were estimated using linear mixed-effects models. From the pre- to the during-Olympic period, when concentrations of most pollutants decreased, EBC MDA and urinary MDA significantly decreased by 24% (P<0.0001) and 28% (P=0.0002), respectively. From the during-Olympic to the post-Olympic period, when concentrations of most pollutants increased, EBC MDA and urinary MDA increased by 28% (P=0.094) and 55% (P=0.046), respectively. Furthermore, the largest increases in EBC MDA associated with one interquartile range (IQR) increases in all pollutants but ozone ranged from 10% (95% CI: 2%, 18%) to 19% (95% CI: 14%, 25%). The largest increases in urinary MDA associated with IQR increases in pollutant concentration ranged from 9% (95%: 0.3%, 19%) to 15% (95% CI: 3%, 28%). These findings support the utility of EBC MDA as a biomarker of oxidative stress in the respiratory tract and urinary MDA as a biomarker of systemic oxidative stress in relation to air pollution exposure in healthy young adults. Both EBC and urine samples can be collected noninvasively in the general population.

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Acknowledgements

We thank all the students and staff from Dr Tong Zhu and Dr Min Hu’s labs for their assistance in air pollution monitoring. This research was jointly funded by NIEHS (1R01 ES0158640, P30 ES05022, and 5P30ES007048) and the Health Effects Institute (4760-RPFA05-3). T.Z. is partly funded by Beijing Environmental Protection Agency (OITC-G08026056). The views expressed in this manuscript are solely of the authors and do not necessarily reflect those of the funding agencies.

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Authors and Affiliations

  1. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA

    Jicheng Gong & Junfeng (Jim) Zhang

  2. College of Environmental Sciences and Engineering, and the Center for Environmental Health, Peking University, Beijing, China

    Tong Zhu, Min Hu & Wei Huang

  3. Environmental and Occupational Health Sciences Institute and UMDNJ-Robert Wood Johnson Medical School, Piscataway, New Jersey, USA

    Howard Kipen

  4. Department of Pulmonary Medicine, Peking University First Hospital, Beijing, China

    Guangfa Wang

  5. University of Medicine and Dentistry of New Jersey, School of Public Health, Piscataway, New Jersey, USA

    Pamela Ohman-Strickland, Shou-En Lu, Lin Zhang & Junfeng (Jim) Zhang

  6. Department of Immunology, Peking University Health Sciences Center, Beijing, China

    Yuedan Wang

  7. Department of Hematology, Peking University First Hospital, Beijing, China

    Ping Zhu

  8. University of Rochester, School of Medicine and Dentistry, Rochester, New York, USA

    David Q Rich

  9. University of Medicine and Dentistry of New Jersey, School of Dentistry, Newark, New Jersey, USA

    Scott R Diehl

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  1. Jicheng Gong
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Correspondence to Junfeng (Jim) Zhang.

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Gong, J., Zhu, T., Kipen, H. et al. Malondialdehyde in exhaled breath condensate and urine as a biomarker of air pollution induced oxidative stress. J Expo Sci Environ Epidemiol 23, 322–327 (2013). https://doi.org/10.1038/jes.2012.127

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  • DOI: https://doi.org/10.1038/jes.2012.127

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