On-line solid-phase extraction with ultra performance liquid chromatography and tandem mass spectrometry for the detection of nicotine, cotinine and trans-3′-hydroxycotinine in urine to strengthen human biomonitoring and smoking cessation studies

Abstract

At the time of writing, this work appears to be the first published report on the coupling of on-line solid phase extraction (SPE) with ultra performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) for the simultaneous detection of nicotine, cotinine and trans-3′-hydroxycotinine in human urine. The advantages of both on-line SPE (speed, automation, less labor intensive) coupled with UPLC–MS/MS (speed, sensitivity) offer a viable option for efficient and economical biomonitoring studies for the assessment of active and passive exposure to tobacco smoke and clinical studies focusing on smoke cessation techniques. In a first approach, a 1:100 dilution of the urine was applied to screen for both passive and active exposure. Intra- and inter-batch reproducibility of this fast method (10min) was assessed for three concentration levels and were found to be less than 8% for each analyte while the accuracy was between 89 and 113%. To further improve the sensitivity of this approach when focusing only on passive smokers, the performance of a 1:10 dilution with the on-line SPE UPLC–MS/MS system was also tested. Results indeed show better sensitivity (LOQ's 1.0, 1.0 and 5.0μg/l for respectively cotinine, nicotine and trans-3′-hydroxycotinine) and good analytical performance for all other analytical parameters on the low levels tested here. Both methods were applied to measure the concentration of nicotine, cotinine and trans-3′-hydroxycotinine in the urine of 53 volunteers (smokers and non-smokers) recruited via an internal call at the Scientific Institute of Public Health. For non-smokers and smokers, cotinine levels e.g. were respectively between 1.0–470μg/l and 97–2381μg/l. Both these on-line SPE UPLC–MS/MS methods showed their potential for dedicated future large biomonitoring projects as they made it possible to analyze large series of samples in a fast, sensitive, robust and cost-efficient manner.