117 Metabolomics experiment among workers exposed to 2, 3, 7, 8-tetrachlorodibenzo-p-dioxin (TCDD)

• Published in: Occupational and environmental medicine (London, England) Vol. 70; no. Suppl 1; pp. A39 - A40
• Main Authors: Saberi Hosnijeh, F, Pechlivanis, Keun, Portengen, Bueno-de-Mesquita, Heederik, Vermeulen
• Format: Journal Article
• Language: English
• Published: London BMJ Publishing Group Ltd 01.09.2013; BMJ Publishing Group LTD
• Subjects: Coefficient of variation; Dioxins; Gas chromatography; High pressure; Liquid chromatography; Lymphoma; Mass spectrometry; Metabolites; Occupational exposure; TCDD
• ISSN: 1351-0711; 1470-7926
• DOI: 10.1136/oemed-2013-101717.117

Objectives Previous occupational studies suggest that 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) exposure may be associated with non-Hodgkin lymphoma (NHL) but findings are inconclusive. Mechanistic studies using global biochemical profiling (metabolomics) could provide supporting evidence for such an association by identifying relevant biological pathways. We applied metabolomics profiling to a cohort of TCDD exposed workers. Methods 81 workers who had been exposed to either high (n = 43) or low (n = 38) TCDD levels more than 30 years before serum collection and 63 non-exposed workers (from a comparable factory but without TCDD exposure) were included in the study. Serum ion metabolites were detected using Ultra high Pressure Liquid Chromatography (UPLC) coupled online to a Q-TOF Premier mass spectrometer with a scan range of 70�’1000 m/z. Current plasma levels of TCDD (TCDDCurrent) were determined by high-resolution gas chromatography/isotope dilution high resolution mass spectrometry. TCDD blood levels at the time of last exposure (TCDDmax) were estimated using a one-compartment first order kinetic model. Differentially expressed metabolites were identified using partial least squares (PLS) regression, and Bayesian stochastic search variable selection with spike-and-slab priors of (nonlinear) generalised additive models. Results Features that were present in all QC samples and had a coefficient of variation CV <30% were included in the present analyses (n = 421 features). PLS and Bayesian stochastic search variable selection regression analyses revealed no obvious metabolic perturbations associated with TCDD serum levels. Conclusions This is the first global metabolomic analysis related to TCDD exposure. No significant features were identified. It is concluded that TCDD exposure at levels present in this study does not lead to significant perturbations of the serum metabolites.