Abstract

The quantification of tobacco exposure biomarkers is relevant to follow the patients’ tobacco use. They allow to discriminate between tobacco users, non-users, passive smokers, and nicotine products users, such as in nicotine replacement therapy. The aim of this study was to develop and validate a quantification method of tobacco biomarkers of choice – nicotine, cotinine, trans-3′-hydroxycotinine, anatabine and anabasine – in urine. The challenge was to develop an easy and rapid liquid chromatography method requiring only one extraction step and allowing simultaneous detections. Some methods are described in the literature but need specific investment in terms of instrumentation and users training. Here, the developed method had to be carried out with instrumentation easily accessible for medical laboratories. The extraction of the analytes was performed by Supported Liquid Extraction (SLE), which consists in liquid–liquid extraction but supported by a sorbent. It allows to insure efficient neutrals extraction with less organic solvent and without any emulsion formation. 200 µl of basified urine – analytes of interest are neutral in this condition – were loaded on Novum SLE 96-Well Plates (Phenomenex) and analytes were eluted with 1 % formic acid in dichloromethane/propan-2-ol (95/5). After solvent evaporation, samples were reconstituted with 100 µl of water for injection. A mass detector (QDa, Waters) was used to detect analytes, this pre-optimised quadrupole mass analyser being less expensive and requiring less adjustments than traditional mass spectrometers while benefiting of the reliability of mass spectral data. This detector was integrated after an Ultra-high performance liquid chromatography (UHPLC) separation on a BEH C18 column (Waters) at a flow rate of 0.5 ml/min. A gradient elution of H2O (pH 10 with NH4OH) and CH3CN was used. Finally, the developed method was validated. This new method is conclusive to assess the patients’ tobacco exposure and is easy to implement in medical laboratories.

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