@article {Ladumordmd.119.086462, author = {Mayur K. Ladumor and Deepak Kumar Bhatt and Andrea Gaedigk and Sheena Sharma and Aarzoo Thakur and Robin E. Pearce and J. Steven Leeder and Michael B. Bolger and Saranjit Singh and Bhagwat Prasad}, title = {Ontogeny of Hepatic Sulfotransferases (SULTs) and Prediction of Age-Dependent Fractional Contribution of Sulfation in Acetaminophen Metabolism}, elocation-id = {dmd.119.086462}, year = {2019}, doi = {10.1124/dmd.119.086462}, publisher = {American Society for Pharmacology and Experimental Therapeutics}, abstract = {Cytosolic sulfotransferases (SULTs), including SULT1A, SULT1B, SULT1E and SULT2A isoforms, play noteworthy roles in xenobiotic and endobiotic metabolism. We quantified the protein abundance of SULT1A1, SULT1A3, SULT1B1 and SULT2A1 in human liver cytosol samples (n=194) by LC-MS/MS proteomics. The data were analyzed for association with 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 abundance of SULT1A1, SULT1B1, and SULT2A1 in neonatal samples was 24, 19 and 38\% of the adult levels. Interestingly, unlike UDP-glucuronosyltransferases (UGTs) and cytochrome P450 enzymes (CYPs), SULT1A1 and SULT2A1 showed the highest abundance during early childhood (1 to \<6 years), which gradually decreased by ~40\% in adolescents and adults. SULT1A3 and SULT1B1 abundances were significantly lower in African Americans as compared to Caucasians. Multiple linear regression analysis further confirmed the association of abundance of SULTs with age, ethnicity, and genotype. To demonstrate clinical application of the characteristic SULT ontogeny profiles, we developed and validated a proteomics-informed physiologically based pharmacokinetic (PBPK) model. The PBPK model confirmed the higher fractional contribution of sulfation over glucuronidation in the metabolism of acetaminophen in children. The ontogeny-based age-dependent fractional contribution (fm) of individual drug metabolizing enzymes thus has better potential in prediction of drug-drug interactions and the effect of genetic polymorphisms in the pediatric population.SIGNIFICANCE STATEMENT N/A}, issn = {0090-9556}, URL = {https://dmd.aspetjournals.org/content/early/2019/05/17/dmd.119.086462.1}, eprint = {https://dmd.aspetjournals.org/content/early/2019/05/17/dmd.119.086462.1.full.pdf}, journal = {Drug Metabolism and Disposition} }