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Autor(en) / Beteiligte
Titel
Ontogeny of Hepatic Sulfotransferases and Prediction of Age-Dependent Fractional Contribution of Sulfation in Acetaminophen Metabolism
Ist Teil von
  • Drug metabolism and disposition, 2019-08, Vol.47 (8), p.818-831
Ort / Verlag
United States: American Society for Pharmacology and Experimental Therapeutics, Inc
Erscheinungsjahr
2019
Quelle
MEDLINE
Beschreibungen/Notizen
  • Cytosolic sulfotransferases (SULTs), including SULT1A, SULT1B, SULT1E, and SULT2A isoforms, play noteworthy roles in xenobiotic and endobiotic metabolism. We quantified the protein abundances of SULT1A1, SULT1A3, SULT1B1, and SULT2A1 in human liver cytosol samples ( = 194) by liquid chromatography-tandem mass spectrometry proteomics. The data were analyzed for their associations by age, sex, genotype, and ethnicity of the donors. SULT1A1, SULT1B1, and SULT2A1 showed significant age-dependent protein abundance, whereas SULT1A3 was invariable across 0-70 years. The respective mean abundances of SULT1A1, SULT1B1, and SULT2A1 in neonatal samples was 24%, 19%, and 38% of the adult levels. Interestingly, unlike UDP-glucuronosyltransferases and cytochrome P450 enzymes, SULT1A1 and SULT2A1 showed the highest abundance during early childhood (1 to <6 years), which gradually decreased by approx. 40% in adolescents and adults. SULT1A3 and SULT1B1 abundances were significantly lower in African Americans compared with Caucasians. Multiple linear regression analysis further confirmed the association of SULT abundances by age, ethnicity, and genotype. To demonstrate clinical application of the characteristic SULT ontogeny profiles, we developed and validated a proteomics-informed physiologically based pharmacokinetic model of acetaminophen. The latter confirmed the higher fractional contribution of sulfation over glucuronidation in the metabolism of acetaminophen in children. The study thus highlights that the ontogeny-based age-dependent fractional contribution (f ) of individual drug-metabolizing enzymes has better potential in prediction of drug-drug interactions and the effect of genetic polymorphisms in the pediatric population.

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