Literature DB >> 7597257

Modeling human interindividual variability in metabolism and risk: the example of 4-aminobiphenyl.

F Y Bois1, G Krowech, L Zeise.   

Abstract

We investigate, through modeling, the impact of interindividual heterogeneity in the metabolism of 4-aminobiphenyl (ABP) and in physiological factors on human cancer risk: A physiological pharmacokinetic model was used to quantify the time course of the formation of the proximate carcinogen, N-hydroxy-4-ABP and the DNA-binding of the active species in the bladder. The metabolic and physiologic model parameters were randomly varied, via Monte Carlo simulations, to reproduce interindividual variability. The sampling means for most parameters were scaled from values developed by Kadlubar et al. (Cancer Res., 51: 4371, 1991) for dogs; variances were obtained primarily from published human data (e.g., measurements of ABP N-oxidation, and arylamine N-acetylation in human liver tissue). In 500 simulations, theoretically representing 500 humans, DNA-adduct levels in the bladder of the most susceptible individuals are ten thousand times higher than for the least susceptible, and the 5th and 95th percentiles differ by a factor of 160. DNA binding for the most susceptible individual (with low urine pH, low N-acetylation and high N-oxidation activities) is theoretically one million-fold higher than for the least susceptible (with high urine pH, high N-acetylation and low N-oxidation activities). The simulations also suggest that the four factors contributing most significantly to interindividual differences in DNA-binding of ABP in human bladder are urine pH, ABP N-oxidation, ABP N-acetylation and urination frequency.

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Year:  1995        PMID: 7597257     DOI: 10.1111/j.1539-6924.1995.tb00314.x

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  9 in total

Review 1.  Whole body pharmacokinetic models.

Authors:  Ivan Nestorov
Journal:  Clin Pharmacokinet       Date:  2003       Impact factor: 6.447

2.  Urinary pH, cigarette smoking and bladder cancer risk.

Authors:  Juan Alguacil; Manolis Kogevinas; Debra T Silverman; Núria Malats; Francisco X Real; Montserrat García-Closas; Adonina Tardón; Manuel Rivas; Montserrat Torà; Reina García-Closas; Consol Serra; Alfredo Carrato; Ruth M Pfeiffer; Joan Fortuny; Claudine Samanic; Nathaniel Rothman
Journal:  Carcinogenesis       Date:  2011-03-14       Impact factor: 4.944

3.  Toxicity testing in the 21st century: a vision and a strategy.

Authors:  Daniel Krewski; Daniel Acosta; Melvin Andersen; Henry Anderson; John C Bailar; Kim Boekelheide; Robert Brent; Gail Charnley; Vivian G Cheung; Sidney Green; Karl T Kelsey; Nancy I Kerkvliet; Abby A Li; Lawrence McCray; Otto Meyer; Reid D Patterson; William Pennie; Robert A Scala; Gina M Solomon; Martin Stephens; James Yager; Lauren Zeise
Journal:  J Toxicol Environ Health B Crit Rev       Date:  2010-02       Impact factor: 6.393

4.  Age-Related Changes in Pediatric Physiology: Quantitative Analysis of Organ Weights and Blood Flows : Age-Related Changes in Pediatric Physiology.

Authors:  Hsuan Ping Chang; Se Jin Kim; Di Wu; Kushal Shah; Dhaval K Shah
Journal:  AAPS J       Date:  2021-03-31       Impact factor: 4.009

5.  Effect of Increased Water Intake on Urinary DNA Adduct Levels and Mutagenicity in Smokers: A Randomized Study.

Authors:  Inmaculada Buendia Jimenez; Pascaline Richardot; Pascaline Picard; Eve M Lepicard; Michel De Meo; Glenn Talaska
Journal:  Dis Markers       Date:  2015-08-18       Impact factor: 3.434

6.  Urinary pH is an independent predictor of upper tract recurrence in non-muscle-invasive bladder cancer patients with a smoking history.

Authors:  Hiroki Ide; Eiji Kikuchi; Koichiro Ogihara; Naoya Niwa; Keisuke Shigeta; Tsukasa Masuda; Yuto Baba; Ryuichi Mizuno; Mototsugu Oya
Journal:  Sci Rep       Date:  2021-10-19       Impact factor: 4.379

7.  Acidic urine is associated with poor prognosis in patients with bladder cancer undergoing radical cystectomy.

Authors:  Jang Hee Han; Seung-Hwan Jeong; Hyeong Dong Yuk; Chang Wook Jeong; Cheol Kwak; Ja Hyeon Ku
Journal:  Front Oncol       Date:  2022-08-26       Impact factor: 5.738

8.  Addressing human variability in next-generation human health risk assessments of environmental chemicals.

Authors:  Lauren Zeise; Frederic Y Bois; Weihsueh A Chiu; Dale Hattis; Ivan Rusyn; Kathryn Z Guyton
Journal:  Environ Health Perspect       Date:  2012-10-19       Impact factor: 9.031

9.  Considerations for Using Genetic and Epigenetic Information in Occupational Health Risk Assessment and Standard Setting.

Authors:  P A Schulte; C Whittaker; C P Curran
Journal:  J Occup Environ Hyg       Date:  2015       Impact factor: 2.155

  9 in total

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