Liver cirrhosis is
a chronic disease that affects the liver structure,
protein expression, and overall metabolic function. Abundance data
for drug-metabolizing enzymes and transporters (DMET) across all stages
of disease severity are scarce. Levels of these proteins are crucial
for the accurate prediction of drug clearance in hepatically impaired
patients using physiologically based pharmacokinetic (PBPK) models,
which can be used to guide the selection of more precise dosing. This
study aimed to experimentally quantify these proteins in human liver
samples and assess how they can impact the predictive performance
of the PBPK models. We determined the absolute abundance of 51 DMET
proteins in human liver microsomes across the three degrees of cirrhosis
severity (
n
= 32; 6 mild, 13 moderate, and 13 severe),
compared to histologically normal controls (
n
= 14),
using QconCAT-based targeted proteomics. The results revealed a significant
but non-uniform reduction in the abundance of enzymes and transporters,
from control, by 30–50% in mild, 40–70% in moderate,
and 50–90% in severe cirrhosis groups. Cancer and/or non-alcoholic
fatty liver disease-related cirrhosis showed larger deterioration
in levels of CYP3A4, 2C8, 2E1, 1A6, UGT2B4/7, CES1, FMO3/5, EPHX1,
MGST1/3, BSEP, and OATP2B1 than the cholestasis set. Drug-specific
pathways together with non-uniform changes of abundance across the
enzymes and transporters under various degrees of cirrhosis necessitate
the use of PBPK models. As case examples, such models for repaglinide,
dabigatran, and zidovudine were successful in recovering disease-related
alterations in drug exposure. In conclusion, the current study provides
the biological rationale behind the absence of a single dose adjustment
formula for all drugs in cirrhosis and demonstrates the utility of
proteomics-informed PBPK modeling for drug-specific dose adjustment
in liver cirrhosis.