Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/10946
Title: Time of the day dictates the variability of biomarkers of exposure to disinfection byproducts
Authors: Gängler, Stephanie 
Charisiadis, Pantelis 
Seth, Ratanesh Kumar 
Chatterjee, Saurabh 
Makris, Konstantinos C. 
Major Field of Science: Medical and Health Sciences
Field Category: Other Medical Sciences
Keywords: Circadian;Cosinor;Disinfection;Liver clock;Metabolic activation;Susceptibility;Toxication;Xenobiotics
Issue Date: Mar-2018
Source: Environment International, 2018, vol. 112, pp. 33-40
Volume: 112
Start page: 33
End page: 40
Journal: Environment International 
Abstract: Non-persistent environmental chemicals (NOPEC) are xenobiotics with short half-lives of elimination (< 7 h). Similar to chronopharmacokinetics, NOPEC metabolism may follow diurnal patterns of cytochrome P450 activity. The role of circadian liver clock in shaping NOPEC metabolism and their concomitant measurements of biomarkers of exposure and effect remains poorly understood in real-life human settings. Metabolic activation (toxication) by CYP2E1 converts trihalomethanes (THM) to harmful metabolites. We investigated the diurnal variation of urinary THM exposures and their metabolism patterns as catalyzed by CYP2E1 redox activity, using the surrogate marker of 4-hydroxynonenal (4HNE). We implemented three time-series trials with adult volunteers conducting specific household cleaning activities at predefined times of a day. Circadia variation of 4HNE was assessed with a cosinor model and its mesor levels increased with THM exposure. The time of exposure within the day dictated the magnitude of urinary THM levels and their toxication effect; in all three trials and relative to urinary THM levels before the activity, lower and higher median THM were measured right after the activity in morning and afternoon/night, respectively. This is consistent with higher reported CYP2E1 redox activity in light/active phase. Population health studies should incorporate time-stamped biomarker data to improve the understanding of chronic disease processes.
URI: https://hdl.handle.net/20.500.14279/10946
ISSN: 18736750
DOI: 10.1016/j.envint.2017.12.013
Rights: © Elsevier
Type: Article
Affiliation : Cyprus University of Technology 
University of South Carolina 
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