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Metabolomics identifying biomarkers of PM2.5 exposure for vulnerable population: based on a prospective cohort study
Authors:Chu  Haiyan  Huang  Feng-Qing  Yuan  Qi  Fan  Yuanming  Xin  Junyi  Du  Mulong  Wang  Meilin  Zhang  Zhengdong  Ma  Gaoxiang
Institution:1.Department of Environmental Genomics, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China
;2.Department of Genetic Toxicology, Center for Global Health, School of Public Health, Nanjing Medical Universty, Nanjing, China
;3.State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, No. 639 Longmian Road, Nanjing, 211198, China
;
Abstract:

Long-term exposure to particular matter (PM), especially fine PM (< 2.5 μm in the aerodynamic diameter, PM2.5), is associated with increased risk of cardiovascular disorders. This study aimed to evaluate the association between long-term exposure to PM2.5/PM10 and the metabolic change in the plasma. Specifically, using metabolomics, we sought to identify the biomarkers for the vulnerable subgroup to PM2.5 exposure. A total of 78 college student volunteers were recruited into this prospective cohort study. All participants received 8 rounds of physical examinations at twice quarterly. Air purifiers were placed in 40 of 78 participants’ dormitories for 14 days. Before and after intervention, physical examinations were performed and the peripheral blood was collected. Plasma metabolomics was determined by ultra-performance liquid chromatography-mass spectrometry. During the follow-up, the average concentrations of PM2.5 and PM10 were 53 μg/m3 and 93 μg/m3, respectively. Totally, 42 and 120 differential metabolic features were detected for PM10 and PM2.5 exposure, respectively. In total, 25 differential metabolites were identified for PM2.5 exposure, most of which were phospholipids. No distinctive metabolites were found for PM10 exposure. A total of 6 differential metabolites (lysoPC (P-20:0), lysoPC (P-18:1(9z)), lysoPC (20:1), lysoPC (O-16:0), choline, and found 1,3-diphenylprop-2-en-1-one) were characterized and confirmed for sensitive individuals. Importantly, we found LysoPC (P-20:0) and LysoPC (P-18:1(9z)) changed significantly before and after air purifier intervention. Our results indicated that the phospholipid catabolism was involved in long-term PM2.5 exposure. LysoPC (P-20:0) and LysoPC (P-18:1(9z)) may be the biomarkers of PM2.5 exposure.

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