TY - JOUR
T1 - Paraben Exposure Related to Purine Metabolism and Other Pathways Revealed by Mass Spectrometry-Based Metabolomics
AU - Zhao, Hongzhi
AU - Zheng, Yuanyuan
AU - Zhu, Lin
AU - Xiang, Li
AU - Zhou, Yanqiu
AU - Li, Jiufeng
AU - Fang, Jing
AU - Xu, Shunqing
AU - Xia, Wei
AU - Cai, Zongwei
N1 - Funding Information:
This work was supported by National Natural Science Foundation of China (21437002) and the General Research Fund (12319716) and Collaborative Research Fund (C4024-16W) from Research Grants Council of Hong Kong. Dr. Simon Wang at the Language Centre of HKBU has improved the linguistic presentation of the manuscript.
Publisher copyright:
© 2020 American Chemical Society
PY - 2020/3/17
Y1 - 2020/3/17
N2 - Parabens are widely used as common preservatives in the pharmaceutical and cosmetic industries. Exposure to parabens has been found to be associated with metabolic alterations of human and an increased risk of metabolic disease, such as diabetes. However, limited information is available about metabolic pathways related to paraben exposure. In this study, three parabens were determined in the urine samples of 88 pregnant women by using ultrahigh-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC-QqQ MS). The samples were divided into different groups based on tertile distribution of urinary paraben concentrations. Metabolic profiling of the 88 urine samples was performed by using UHPLC coupled with Orbitrap high-resolution MS. Differential metabolites were screened by comparing the profiles of urine samples from different paraben-exposure groups. The identified metabolites included purines, acylcarnitines, etc., revealing that metabolic pathways such as purine metabolism, fatty acid β-oxidation, and other pathways were disturbed by parabens. Eighteen and three metabolites were correlated (Spearman correlation analysis, p < 0.05) with the exposure levels of methyparaben and propylparaben, respectively. This is the first MS-based nontargeted metabolomics study on pregnant women with paraben exposure. The findings reveal the potential health risk of exposure to parabens and might help one to understand the link between paraben exposure and some metabolic diseases.
AB - Parabens are widely used as common preservatives in the pharmaceutical and cosmetic industries. Exposure to parabens has been found to be associated with metabolic alterations of human and an increased risk of metabolic disease, such as diabetes. However, limited information is available about metabolic pathways related to paraben exposure. In this study, three parabens were determined in the urine samples of 88 pregnant women by using ultrahigh-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC-QqQ MS). The samples were divided into different groups based on tertile distribution of urinary paraben concentrations. Metabolic profiling of the 88 urine samples was performed by using UHPLC coupled with Orbitrap high-resolution MS. Differential metabolites were screened by comparing the profiles of urine samples from different paraben-exposure groups. The identified metabolites included purines, acylcarnitines, etc., revealing that metabolic pathways such as purine metabolism, fatty acid β-oxidation, and other pathways were disturbed by parabens. Eighteen and three metabolites were correlated (Spearman correlation analysis, p < 0.05) with the exposure levels of methyparaben and propylparaben, respectively. This is the first MS-based nontargeted metabolomics study on pregnant women with paraben exposure. The findings reveal the potential health risk of exposure to parabens and might help one to understand the link between paraben exposure and some metabolic diseases.
UR - http://www.scopus.com/inward/record.url?scp=85081699809&partnerID=8YFLogxK
U2 - 10.1021/acs.est.9b07634
DO - 10.1021/acs.est.9b07634
M3 - Journal article
C2 - 32101413
AN - SCOPUS:85081699809
SN - 0013-936X
VL - 54
SP - 3447
EP - 3454
JO - Environmental Science and Technology
JF - Environmental Science and Technology
IS - 6
ER -