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Nontarget Time Trend Screening in Human Blood
Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry.
Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry.
Number of Authors: 32018 (English)In: Environmental Science and Technology Letters, E-ISSN 2328-8930, Vol. 5, no 6, p. 335-340Article in journal (Refereed) Published
Abstract [en]

Human biomonitoring (HBM) programs monitor exposure to a limited number of prioritized chemicals resulting in some important substances being overlooked. Nontarget analysis shows promise for capturing novel substances, yet the large quantity of data produced by these methods remains challenging to interrogate. Here, we apply a prioritization strategy for temporal nontarget HBM data, which shortlists features with increasing time trends, possibly representing substances which are bioaccumulating or to which humans are increasingly exposed. Human whole blood sampled in Germany between 1983 and 2015 was extracted using a modified QuEChERS method and analyzed by UHPLC-Oribtrap-mass spectrometry. Following alignment, peak detection, grouping, and gap filling, up to 14,460 features were obtained. This number was reduced to <= 716 using time trend ratios and Spearman's rank correlation coefficients to identify features which increased over the 32-year time series. Increasing features were investigated further using the KemI market list database (which prioritizes based on human hazard and/or exposure potential) as well as data-dependent product ion scans, followed by MetFrag and mzCloud database searches. Finally, seven prioritized substances, including one pharmaceutical, two pesticides, and four performance chemicals, were confirmed using standards, demonstrating the potential of time trend screening as a prioritization strategy for nontarget HBM data.

Place, publisher, year, edition, pages
2018. Vol. 5, no 6, p. 335-340
National Category
Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:su:diva-158304DOI: 10.1021/acs.estlett.8b00196ISI: 000435417000007OAI: oai:DiVA.org:su-158304DiVA, id: diva2:1235906
Available from: 2018-07-30 Created: 2018-07-30 Last updated: 2018-07-30Bibliographically approved

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Plassmann, Merle M.Benskin, Jonathan P.
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