Neal L Benowitz1, Katherine M Dains, Delia Dempsey, Lisa Yu, Peyton Jacob. 1. Division of Clinical Pharmacology and Experimental Therapeutics, Medical Service, San Francisco General Hospital Medical Center, and Department of Medicine, University of California, San Francisco, Box 1220, San Francisco, CA 94143-1220, USA. NBenowitz@MedSFGH.ucsf.edu
Abstract
BACKGROUND: We sought to determine the optimal plasma and urine nicotine metabolites, alone or in combination, to estimate the systemic dose of nicotine after low-level exposure. METHODS: We dosed 36 nonsmokers with 100, 200, or 400 microg p.o. of deuterium-labeled nicotine (doses similar to exposure to secondhand smoke) daily for 5 days and then measured plasma and urine nicotine metabolites at various intervals over 24 hours. RESULTS: The strongest correlations with nicotine dose were seen for the sum of four (cotinine+cotinine-glucuronide+trans-3'-hydroxycotinine+3HC-glucuronide) or six (including also nicotine+nicotine-glucuronide) of the major nicotine metabolites in 24-hour urine collection (r=0.96), with lesser correlations for these metabolites using spot urines corrected for creatinine at various times of day (r=0.72-0.80). The sum of plasma cotinine+trans-3'-hydroxycotine was more highly correlated with nicotine dose than plasma cotinine alone (r=0.82 versus 0.75). CONCLUSIONS: Our results provide guidance for the selection of biomarkers to estimate the dose of nicotine taken in low-level (secondhand smoke) tobacco exposure. IMPACT: This is probably relevant to active smoking as well. Copyright (c) 2010 AACR
BACKGROUND: We sought to determine the optimal plasma and urine nicotine metabolites, alone or in combination, to estimate the systemic dose of nicotine after low-level exposure. METHODS: We dosed 36 nonsmokers with 100, 200, or 400 microg p.o. of deuterium-labeled nicotine (doses similar to exposure to secondhand smoke) daily for 5 days and then measured plasma and urine nicotine metabolites at various intervals over 24 hours. RESULTS: The strongest correlations with nicotine dose were seen for the sum of four (cotinine+cotinine-glucuronide+trans-3'-hydroxycotinine+3HC-glucuronide) or six (including also nicotine+nicotine-glucuronide) of the major nicotine metabolites in 24-hour urine collection (r=0.96), with lesser correlations for these metabolites using spot urines corrected for creatinine at various times of day (r=0.72-0.80). The sum of plasma cotinine+trans-3'-hydroxycotine was more highly correlated with nicotine dose than plasma cotinine alone (r=0.82 versus 0.75). CONCLUSIONS: Our results provide guidance for the selection of biomarkers to estimate the dose of nicotine taken in low-level (secondhand smoke) tobacco exposure. IMPACT: This is probably relevant to active smoking as well. Copyright (c) 2010 AACR
Authors: Neal L Benowitz; Gary E Swan; Peyton Jacob; Christina N Lessov-Schlaggar; Rachel F Tyndale Journal: Clin Pharmacol Ther Date: 2006-11 Impact factor: 6.875
Authors: Anne M Joseph; Stephen S Hecht; Sharon E Murphy; Steven G Carmella; Chap T Le; Yan Zhang; Shaomei Han; Dorothy K Hatsukami Journal: Cancer Epidemiol Biomarkers Prev Date: 2005-12 Impact factor: 4.254
Authors: Neal L Benowitz; Katherine M Dains; Delia Dempsey; Brenda Herrera; Lisa Yu; Peyton Jacob Journal: Nicotine Tob Res Date: 2009-06-12 Impact factor: 4.244
Authors: Kaisu Keskitalo-Vuokko; Janne Pitkäniemi; Ulla Broms; Markku Heliövaara; Arpo Aromaa; Markus Perola; Samuli Ripatti; Outi Salminen; Veikko Salomaa; Anu Loukola; Jaakko Kaprio Journal: Nicotine Tob Res Date: 2011-04-16 Impact factor: 4.244
Authors: Taraneh Taghavi; Maria Novalen; Caryn Lerman; Tony P George; Rachel F Tyndale Journal: Cancer Epidemiol Biomarkers Prev Date: 2018-05-31 Impact factor: 4.254
Authors: Lanqing Wang; John T Bernert; Neal L Benowitz; June Feng; Peyton Jacob; Ernest McGahee; Samuel P Caudill; Gerhard Scherer; Max Scherer; Nikola Pluym; Mira V Doig; Kirk Newland; Sharon E Murphy; Nicolas J Caron; Lane C Sander; Makiko Shimizu; Hiroshi Yamazaki; Sung Kim; Loralie J Langman; Jeanita S Pritchett; Lorna T Sniegoski; Yao Li; Benjamin C Blount; James L Pirkle Journal: Cancer Epidemiol Biomarkers Prev Date: 2018-05-31 Impact factor: 4.254
Authors: Suzaynn F Schick; Benjamin C Blount; Peyton Jacob; Najat A Saliba; John T Bernert; Ahmad El Hellani; Peter Jatlow; R Steven Pappas; Lanqing Wang; Jonathan Foulds; Arunava Ghosh; Stephen S Hecht; John C Gomez; Jessica R Martin; Clementina Mesaros; Sanjay Srivastava; Gideon St Helen; Robert Tarran; Pawel K Lorkiewicz; Ian A Blair; Heather L Kimmel; Claire M Doerschuk; Neal L Benowitz; Aruni Bhatnagar Journal: Am J Physiol Lung Cell Mol Physiol Date: 2017-05-18 Impact factor: 5.464
Authors: Taraneh Taghavi; Christopher A Arger; Sarah H Heil; Stephen T Higgins; Rachel F Tyndale Journal: Addiction Date: 2018-07-23 Impact factor: 6.526
Authors: Noah R Gubner; Aleksandra Kozar-Konieczna; Izabela Szoltysek-Boldys; Ewa Slodczyk-Mankowska; Jerzy Goniewicz; Andrzej Sobczak; Peyton Jacob; Neal L Benowitz; Maciej L Goniewicz Journal: Drug Alcohol Depend Date: 2016-04-14 Impact factor: 4.492
Authors: Nicole L Nollen; Matthew S Mayo; Lauren Clark; Lisa Sanderson Cox; Samir S Khariwala; Kim Pulvers; Neal L Benowitz; Jasjit S Ahluwalia Journal: Drug Alcohol Depend Date: 2017-08-16 Impact factor: 4.492
Authors: Ian A Jones; Gideon St Helen; Matthew J Meyers; Delia A Dempsey; Christopher Havel; Peyton Jacob; Amanda Northcross; S Katharine Hammond; Neal L Benowitz Journal: Tob Control Date: 2013-01-24 Impact factor: 7.552