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Prediction of Drug-Induced Cholestasis Caused by Transporter and/or Enzyme Inhibition-Derived Cell Stress


Kastrinou-Lampou, Vlasia. Prediction of Drug-Induced Cholestasis Caused by Transporter and/or Enzyme Inhibition-Derived Cell Stress. 2024, University of Zurich, Faculty of Science.

Abstract

Drug-induced liver injury (DILI) is a life-threatening adverse reaction to drugs or xenobiotics with major concern for the pharmaceutical companies and health providers, as it represents a main cause of drug attrition and market drug withdrawal (1, 2). Drug-induced cholestasis (DIC) is characterized by disruption of bile flow, leading to accumulation of bile acids within the hepatocytes. Despite considered less severe compared to other hepatic adverse reactions, DIC is often chronic and can progress to liver cirrhosis and ultimately end-stage liver disease (3). To date, our ability to predict DIC is limited, mainly due to lack of understanding of the complex regulation of bile acids and the inability of the available in vitro and in vivo models to recapitulate liver function of humans. Inhibition properties of new drug candidates towards the main canalicular transporter of bile acids called adenosine triphosphate (ATP)-dependent bile salt export pump (BSEP), known for its role in DIC development, are routinely evaluated in preclinical studies. However, DIC prediction remains challenging, as BSEP inhibition is not always adequately predictive (4). Considering the complexity of bile acid regulation, mechanisms in addition to or alternative to BSEP inhibition may contribute to DIC. While hepatic transporters involved in the transport of bile acids have been extensively studied, the metabolic mechanisms of hepatic bile acid detoxification are not well established. It was therefore the aim of the present thesis to i) characterize the precise metabolic processes involved in bile acid metabolism in the liver, ii) identify the most relevant transport and metabolism mechanisms, which, when impaired individually or in combination, correlate to DIC concern and, iii) develop a mechanistic and quantitative model for DIC prediction using in vitro inhibition data. At the beginning of this work, cytochrome p450 (CYP) 3A4, well recognized for its role in the metabolism of various drugs and xenobiotics, was identified as the predominant enzyme in bile acid detoxification, shown to metabolize a total of nine primary, secondary, or (un) conjugated human bile acids. Three other enzymes, namely UDP-glucuronosyltransferase (UGT) 1A3, 2B7 and sulfotransferase (SULT) 2A1 were also identified to foster bile acid metabolism, with the lithocholic acid, known as the most toxic bile acid, identified as substrate for all aforementioned processes. Contrary to previous reports proposing CYP2Cs and CYP2Bs as putative bile acid detoxification mechanisms (5, 6), our study suggested that they are likely not involved in the bile acid regulation scheme. Consequently, inhibition of CYP3A4-mediated hydroxylation, UGT1A3/2B7-mediated glucuronidation, and/or SULT2A1-mediated sulfation (e.g., by administered drugs) may disrupt bile acid homeostasis, leading to intracellular bile acid accumulation and cholestasis. In a subsequent step, inhibition data towards multiple hepatic transporters (i.e., the organic anion transporting polypeptide (OATP) 1B1, OATP1B3, the Na+-dependent taurocholate transporter (NTCP), the organic solute transporters (OST) α/OSTβ, the multidrug resistance associated protein-2 (MRP2), MRP3, MRP4, the multidrug resistance protein 3 (MDR3), and BSEP), and enzymes (i.e., the bile acid CoA synthase (BACS), the bile acid CoA-amino acid N-acetyltransferase (BAAT), UGT1A3, UGT2B7, SULT2A1, and CYP3A4) for 47 marketed drugs with various degrees of DILI was generated. Concurrently, considering human exposure information, a comprehensive statistical analysis was performed to improve our overall understanding of the pathogenesis of DIC. Based on this exhaustive dataset, reversible inhibition of OATP1B1 and time-dependent inhibition (TDI) of CYP3A4 were identified as the highest importance factors for DIC anticipation across different DILI classification systems and statistical approaches. The significant correlation between OATP1B1 inhibition and DILI severity could be attributed to the previously speculated bidirectional function of this transporter (7-9). Accordingly, bile acids can traffic in and out of the hepatocytes via OATP1B1, and potent inhibition of this pathway may significantly disrupt bile acid homeostasis. Interestingly, inhibition of BSEP was not highlighted by this analysis, despite extensive literature linking it to cholestasis (10-12), further strengthening the hypothesis that BSEP inhibition alone is not sufficient to cause cholestasis. Finally, to address the unmet need for a quantitative and accurate DIC anticipation, an integral prediction approach was developed based on the principles of the well-known extended clearance model (ECM). The new model, subsequently referred to as the “revised” ECM- based 1/R-value model, was intended to quantitatively describe the intrahepatic bile acid accumulation caused by disruption of bile acid flow upon drug-mediated hepatic enzyme and/or transporter inhibition. Specifically, the following terms were considered in the model: a) the sinusoidal transporters NTCP, OATP1B1, OATP1B3, MRP3, MRP4, and OST α/β, b) the canalicular transporters BSEP, MDR3 and MRP2, and c) the hepatic enzymes CYP3A4 (reversible and irreversible inhibition), UGT1A3, UGT2B7, SULT2A1, BACS and BAAT (conjugation with taurine or glycine). The performance of the model was subsequently evaluated using a variety of statistical methods and yielded satisfactory predictivity scores. Furthermore, the possibility to simplify the model by including less processes (i.e., less experimental measurements) was investigated. A simplified variant of the “revised” ECM- based 1/R-value model, consisting only of two input parameters, namely OATP1B1 reversible inhibition and CYP3A4 TDI, yielded very similar predictive performance score as the comprehensive (i.e., unsimplified) model. Notably, results were only slightly improved with the addition of BSEP to the model. As such, the OATP1B1 and CYP3A4 TDI-based model could effectively be employed in DIC risk prediction strategies in an integral and quantitative manner during early preclinical stages of drug development.

Abstract

Drug-induced liver injury (DILI) is a life-threatening adverse reaction to drugs or xenobiotics with major concern for the pharmaceutical companies and health providers, as it represents a main cause of drug attrition and market drug withdrawal (1, 2). Drug-induced cholestasis (DIC) is characterized by disruption of bile flow, leading to accumulation of bile acids within the hepatocytes. Despite considered less severe compared to other hepatic adverse reactions, DIC is often chronic and can progress to liver cirrhosis and ultimately end-stage liver disease (3). To date, our ability to predict DIC is limited, mainly due to lack of understanding of the complex regulation of bile acids and the inability of the available in vitro and in vivo models to recapitulate liver function of humans. Inhibition properties of new drug candidates towards the main canalicular transporter of bile acids called adenosine triphosphate (ATP)-dependent bile salt export pump (BSEP), known for its role in DIC development, are routinely evaluated in preclinical studies. However, DIC prediction remains challenging, as BSEP inhibition is not always adequately predictive (4). Considering the complexity of bile acid regulation, mechanisms in addition to or alternative to BSEP inhibition may contribute to DIC. While hepatic transporters involved in the transport of bile acids have been extensively studied, the metabolic mechanisms of hepatic bile acid detoxification are not well established. It was therefore the aim of the present thesis to i) characterize the precise metabolic processes involved in bile acid metabolism in the liver, ii) identify the most relevant transport and metabolism mechanisms, which, when impaired individually or in combination, correlate to DIC concern and, iii) develop a mechanistic and quantitative model for DIC prediction using in vitro inhibition data. At the beginning of this work, cytochrome p450 (CYP) 3A4, well recognized for its role in the metabolism of various drugs and xenobiotics, was identified as the predominant enzyme in bile acid detoxification, shown to metabolize a total of nine primary, secondary, or (un) conjugated human bile acids. Three other enzymes, namely UDP-glucuronosyltransferase (UGT) 1A3, 2B7 and sulfotransferase (SULT) 2A1 were also identified to foster bile acid metabolism, with the lithocholic acid, known as the most toxic bile acid, identified as substrate for all aforementioned processes. Contrary to previous reports proposing CYP2Cs and CYP2Bs as putative bile acid detoxification mechanisms (5, 6), our study suggested that they are likely not involved in the bile acid regulation scheme. Consequently, inhibition of CYP3A4-mediated hydroxylation, UGT1A3/2B7-mediated glucuronidation, and/or SULT2A1-mediated sulfation (e.g., by administered drugs) may disrupt bile acid homeostasis, leading to intracellular bile acid accumulation and cholestasis. In a subsequent step, inhibition data towards multiple hepatic transporters (i.e., the organic anion transporting polypeptide (OATP) 1B1, OATP1B3, the Na+-dependent taurocholate transporter (NTCP), the organic solute transporters (OST) α/OSTβ, the multidrug resistance associated protein-2 (MRP2), MRP3, MRP4, the multidrug resistance protein 3 (MDR3), and BSEP), and enzymes (i.e., the bile acid CoA synthase (BACS), the bile acid CoA-amino acid N-acetyltransferase (BAAT), UGT1A3, UGT2B7, SULT2A1, and CYP3A4) for 47 marketed drugs with various degrees of DILI was generated. Concurrently, considering human exposure information, a comprehensive statistical analysis was performed to improve our overall understanding of the pathogenesis of DIC. Based on this exhaustive dataset, reversible inhibition of OATP1B1 and time-dependent inhibition (TDI) of CYP3A4 were identified as the highest importance factors for DIC anticipation across different DILI classification systems and statistical approaches. The significant correlation between OATP1B1 inhibition and DILI severity could be attributed to the previously speculated bidirectional function of this transporter (7-9). Accordingly, bile acids can traffic in and out of the hepatocytes via OATP1B1, and potent inhibition of this pathway may significantly disrupt bile acid homeostasis. Interestingly, inhibition of BSEP was not highlighted by this analysis, despite extensive literature linking it to cholestasis (10-12), further strengthening the hypothesis that BSEP inhibition alone is not sufficient to cause cholestasis. Finally, to address the unmet need for a quantitative and accurate DIC anticipation, an integral prediction approach was developed based on the principles of the well-known extended clearance model (ECM). The new model, subsequently referred to as the “revised” ECM- based 1/R-value model, was intended to quantitatively describe the intrahepatic bile acid accumulation caused by disruption of bile acid flow upon drug-mediated hepatic enzyme and/or transporter inhibition. Specifically, the following terms were considered in the model: a) the sinusoidal transporters NTCP, OATP1B1, OATP1B3, MRP3, MRP4, and OST α/β, b) the canalicular transporters BSEP, MDR3 and MRP2, and c) the hepatic enzymes CYP3A4 (reversible and irreversible inhibition), UGT1A3, UGT2B7, SULT2A1, BACS and BAAT (conjugation with taurine or glycine). The performance of the model was subsequently evaluated using a variety of statistical methods and yielded satisfactory predictivity scores. Furthermore, the possibility to simplify the model by including less processes (i.e., less experimental measurements) was investigated. A simplified variant of the “revised” ECM- based 1/R-value model, consisting only of two input parameters, namely OATP1B1 reversible inhibition and CYP3A4 TDI, yielded very similar predictive performance score as the comprehensive (i.e., unsimplified) model. Notably, results were only slightly improved with the addition of BSEP to the model. As such, the OATP1B1 and CYP3A4 TDI-based model could effectively be employed in DIC risk prediction strategies in an integral and quantitative manner during early preclinical stages of drug development.

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Additional indexing

Item Type:Dissertation (cumulative)
Referees:Kullak-Ublick Gerd-Achim, Arand Michael, Naegeli Hanspeter, Camenisch Gian
Communities & Collections:04 Faculty of Medicine > Institute of Pharmacology and Toxicology
07 Faculty of Science > Institute of Pharmacology and Toxicology

05 Vetsuisse Faculty > Veterinärwissenschaftliches Institut > Institute of Veterinary Pharmacology and Toxicology
UZH Dissertations
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Language:English
Place of Publication:Zürich
Date:20 March 2024
Deposited On:20 Mar 2024 12:25
Last Modified:21 May 2024 20:47
Number of Pages:173
OA Status:Green
  • Content: Published Version
  • Language: English