Linked Life Data

17119053

Source:http://linkedlifedata.com/resource/pubmed/id/17119053

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
2006-11-22
pubmed:abstractText
We used natural spline (NS) models to investigate nonlinear relationships between levels of benzene metabolites (E,E-muconic acid, S-phenylmercapturic acid, phenol, hydroquinone, and catechol) and benzene exposure among 386 exposed and control workers in Tianjin, China. After adjusting for background levels (estimated from the 60 control subjects with the lowest benzene exposures), expected mean trends of all metabolite levels increased with benzene air concentrations from 0.03 to 88.9 ppm. Molar fractions for phenol, hydroquinone, and E,E-muconic acid changed continuously with increasing air concentrations, suggesting that competing CYP-mediated metabolic pathways favored E,E-muconic acid and hydroquinone below 20 ppm and favored phenol above 20 ppm. Mean trends of dose-specific levels (micromol/L/ppm benzene) of E,E-muconic acid, phenol, hydroquinone, and catechol all decreased with increasing benzene exposure, with an overall 9-fold reduction of total metabolites. Surprisingly, about 90% of the reductions in dose-specific levels occurred below about 3 ppm for each major metabolite. Using generalized linear models with NS-smoothing functions (GLM + NS models), we detected significant effects upon metabolite levels of gender, age, and smoking status. Metabolite levels were about 20% higher in females and decreased between 1% and 2% per year of life. In addition, levels of hydroquinone and catechol were greater in smoking subjects. Overall, our results indicate that benzene metabolism is highly nonlinear with increasing benzene exposure above 0.03 ppm, and that current human toxicokinetic models do not accurately predict benzene metabolism below 3 ppm. Our results also suggest that GLM + NS models are ideal for evaluating nonlinear relationships between environmental exposures and levels of human biomarkers.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1055-9965
pubmed:author
pubmed:issnType
Print
pubmed:volume
15
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2246-52
pubmed:dateRevised
2007-12-3
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Modeling human metabolism of benzene following occupational and environmental exposures.
pubmed:affiliation
School of Public Health, University of North Carolina, CB 7431, Chapel Hill, NC 27599. smr@unc.edu.
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural, Research Support, N.I.H., Intramural