4.4 Article

Abundance of Phase 1 and 2 Drug-Metabolizing Enzymes in Alcoholic and Hepatitis C Cirrhotic Livers: A Quantitative Targeted Proteomics Study

期刊

DRUG METABOLISM AND DISPOSITION
卷 46, 期 7, 页码 943-952

出版社

AMER SOC PHARMACOLOGY EXPERIMENTAL THERAPEUTICS
DOI: 10.1124/dmd.118.080523

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资金

  1. UWRAPT - Genentech
  2. UWRAPT - Merck
  3. UWRAPT - Gilead
  4. UWRAPT - BMS
  5. UWRAPT - Ardea Biosciences
  6. UWRAPT - Takeda
  7. UWRAPT - Biogen
  8. Eunice Kennedy Shriver National Institute of Child Health and Human Development [R01HD081299]

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To predict the impact of liver cirrhosis on hepatic drug clearance using physiologically based pharmacokinetic (PBPK) modeling, we compared the protein abundance of various phase 1 and phase 2 drug- metabolizing enzymes (DMEs) in S9 fractions of alcoholic (n = 27) or hepatitis C (HCV, n = 30) cirrhotic versus noncirrhotic (control) livers (n = 25). The S9 total protein content was significantly lower in alcoholic or HCV cirrhotic versus control livers (i.e., 38.3 +/- 8.3, 32.3 +/- 12.8, vs. 51.1 +/- 20.7 mg/g liver, respectively). In general, alcoholic cirrhosis was associated with a larger decrease in the DME abundance than HCV cirrhosis; however, only the abundance of UGT1A4, alcohol dehydrogenase (ADH)1A, and ADH1B was significantly lower in alcoholic versus HCV cirrhotic livers. When normalized to per gram of tissue, the abundance of nine DMEs (UGT1A6, UGT1A4, CYP3A4, UGT2B7, CYP1A2, ADH1A, ADH1B, aldehyde oxidase (AOX) 1, and carboxylesterase (CES) 1) in alcoholic cirrhosis and five DMEs (UGT1A6, UGT1A4, CYP3A4, UGT2B7, and CYP1A2) in HCV cirrhosis was < 25% of that in control livers. The abundance of most DMEs in cirrhotic livers was 25% to 50% of control livers. CES2 abundance was not affected by cirrhosis. Integration of UGT2B7 abundance in cirrhotic livers into the liver cirrhosis (Child Pugh C) model of Simcyp improved the prediction of zidovudine and morphine PK in subjects with Child Pugh C liver cirrhosis. These data demonstrate that protein abundance data, combined with PBPK modeling and simulation, can be a powerful tool to predict drug disposition in special populations.

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