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Human urinary biomarkers of dioxin exposure: analysis by metabolomics and biologically driven data dimensionality reduction.

Abstract：

:Untargeted metabolomic approaches offer new opportunities for a deeper understanding of the molecular events related to toxic exposure. This study proposes a metabolomic investigation of biochemical alterations occurring in urine as a result of dioxin toxicity. Urine samples were collected from Czech chemical workers submitted to severe dioxin occupational exposure in a herbicide production plant in the late 1960s. Experiments were carried out with ultra-high pressure liquid chromatography (UHPLC) coupled to high-resolution quadrupole time-of-flight (QTOF) mass spectrometry. A chemistry-driven feature selection was applied to focus on steroid-related metabolites. Supervised multivariate data analysis allowed biomarkers, mainly related to bile acids, to be highlighted. These results supported the hypothesis of liver damage and oxidative stress for long-term dioxin toxicity. As a second step of data analysis, the information gained from the urine analysis of Victor Yushchenko after his poisoning was examined. A subset of relevant urinary markers of acute dioxin toxicity from this extreme phenotype, including glucuro- and sulfo-conjugated endogenous steroid metabolites and bile acids, was assessed for its ability to detect long-term effects of exposure. The metabolomic strategy presented in this work allowed the determination of metabolic patterns related to dioxin effects in human and the discovery of highly predictive subsets of biologically meaningful and clinically relevant compounds. These results are expected to provide valuable information for a deeper understanding of the molecular events related to dioxin toxicity. Furthermore, it presents an original methodology of data dimensionality reduction by using extreme phenotype as a guide to select relevant features prior to data modeling (biologically driven data reduction).

journal_name

Toxicol Lett

journal_title

Toxicology letters

authors

Jeanneret F,Boccard J,Badoud F,Sorg O,Tonoli D,Pelclova D,Vlckova S,Rutledge DN,Samer CF,Hochstrasser D,Saurat JH,Rudaz S

doi

10.1016/j.toxlet.2013.10.031

subject

Has Abstract

pub_date

2014-10-15 00:00:00

pages

234-43

issue

eissn

0378-4274

issn

1879-3169

pii

S0378-4274(13)01374-X

journal_volume

230

pub_type

杂志文章

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Human urinary biomarkers of dioxin exposure: analysis by metabolomics and biologically driven data dimensionality reduction.