Background Most sample preparation methods characteristically involve intensive and repetitive labor, which is inefficient when preparing large numbers of samples from population-scale studies. Methods This study presents a robotic system designed to meet the sampling requirements for large population-scale studies. Using this robotic system, we developed and validated a method to simultaneously measure urinary anatabine, anabasine, nicotine and seven major nicotine metabolites: 4-Hydroxy-4-(3-pyridyl)butanoic acid, cotinine-N-oxide, nicotine-N-oxide, trans-3′-hydroxycotinine, norcotinine, cotinine and nornicotine. We analyzed robotically prepared samples using high-performance liquid chromatography (HPLC) coupled with triple quadrupole mass spectrometry in positive electrospray ionization mode using scheduled multiple reaction monitoring (sMRM) with a total runtime of 8.5 min. Results The optimized procedure was able to deliver linear analyte responses over a broad range of concentrations. Responses of urine-based calibrators delivered coefficients of determination (R2) of >0.995. Sample preparation recovery was generally higher than 80%. The robotic system was able to prepare four 96-well plate (384 urine samples) per day, and the overall method afforded an accuracy range of 92–115%, and an imprecision of <15.0% on average. Conclusions The validation results demonstrate that the method is accurate, precise, sensitive, robust, and most significantly labor-saving for sample preparation, making it efficient and practical for routine measurements in large population-scale studies such as the National Health and Nutrition Examination Survey (NHANES) and the Population Assessment of Tobacco and Health (PATH) study.

Introduction The Population Assessment of Tobacco and Health (PATH) Study is a longitudinal cohort study on tobacco use behavior, attitudes and beliefs, and tobacco-related health outcomes, including biomarkers of tobacco exposure in the U.S. population. In this report we provide a summary of urinary nicotine metabolite measurements among adult users and non-users of tobacco from Wave 1 (2013–2014) of the PATH Study. Methods Total nicotine and its metabolites including cotinine, trans-3′-hydroxycotinine (HCTT), and other minor metabolites were measured in more than 11 500 adult participants by liquid chromatography tandem mass spectrometry methods. Weighted geometric means (GM) and least square means from statistical modeling were calculated for non-users and users of various tobacco products. Results Among daily users, the highest GM concentrations of nicotine, cotinine and HCTT were found in exclusive smokeless tobacco users, and the lowest in exclusive e-cigarette users. Exclusive combustible product users had intermediate concentrations, similar to those found in users of multiple products (polyusers). Concentrations increased with age within the categories of tobacco users, and differences associated with gender, race/ethnicity and educational attainment were also noted among user categories. Recent (past 12 months) former users had GM cotinine concentrations that were more than threefold greater than never users. Conclusions These urinary nicotine metabolite data provide quantification of nicotine exposure representative of the entire US adult population during 2013–2014 and may serve as a reference for similar analyses in future measurements within this study. Implications Nicotine and its metabolites in urine provide perhaps the most fundamental biomarkers of recent nicotine exposure. This report, based on Wave 1 of the Population Assessment of Tobacco and Health (PATH) Study, provides the first nationally representative data describing urinary nicotine biomarker concentrations in both non-users, and users of a variety of tobacco products including combustible, e-cigarette and smokeless products. These data provide a urinary biomarker concentration snapshot in time for the entire US population during 2013–2014, and will provide a basis for comparison with future results from continuing, periodic evaluations in the PATH Study.