Protein expression of various hepatic uridine 5′‐diphosphate glucuronosyltransferase (UGT) enzymes and their inter‐correlations: a meta‐analysis

Abstract

Avoiding cytochrome P450 (CYP) related drug interactions in the development of new drug candidates means that glucuronidation by uridine 5'-diphosphate glucuronosyltransferase (UGT) enzymes is expected to become a more prominent pathway in the metabolism of new drug candidates designed by pharmaceutical companies. Therefore, determining the abundance and activity of these enzymes is of value in the process of scaling in vitro data to in vivo metabolic parameters. Many of the studies involving the measurement of UGTs were conducted with too few samples, which did not provide a good indication of population values and the level of variability. Meta-analysis is used in the current study to combine all reported values (eight studies that used LC-MS isotope-labelled standard targeted quantitative methods), detect inconsistencies between the various datasets and describe correlations of expression between the quantified UGT enzymes. Some heterogeneity was observed between studies, especially in the UGT1A4, 2B7 and 2B10 datasets. However, in the absence of information on the inter-laboratory consistency of assays, it is difficult to assign these differences to the heterogeneity of the samples. Large inter-individual variability was observed in the collated data across this family of enzymes. Positive correlations between the expression levels of certain UGT enzymes were found in the collated data. These included the pairs: UGT1A4/2B4 (rs=0.71, p<0.0001, n=82), UGT2B4/2B15 (rs=0.63, p<0.0001, n=83), UGT2B7/2B15 (rs=0.81, p<0.0001, n=99). These correlations can be explained by common regulatory mechanisms involved in the expression of these proteins.

Quantitative Characterization of Major Hepatic UDP-Glucuronosyltransferase Enzymes in Human Liver Microsomes: Comparison of Two Proteomic Methods and Correlation with Catalytic Activity

“…However, spurious correlations in relation to the activities of UGTs 1A4, 2B7, and 2B15 were also uncovered, which were not as strong as true correlations and could be explained by natural correlation of expression between UGT1A4/2B4 and UGT2B7/2B15, shown to be strong and significant in both SIL-based and QconCAT-based datasets and corroborated by recent literature (Achour et al, 2014c, Margaillan et al, 2015b. A possible ramification of such apparent relationships can be compromised reaction phenotyping of substrates of such enzymes if phenotyping is carried out using correlation of activity with enzyme content in an in vitro system, such as human liver microsomes.…”

“…Particularly, with recent advances in proteomic methods, robust analyses of the protein expression patterns of UGT enzymes in different tissues and in vitro systems Fallon et al, 2013b) made it possible to derive reliable relative expression factors (REFs) essential to these drug-related simulation exercises (Knights et al, 2016). More recent reports have, however, highlighted significant levels of interlaboratory discrepancy between abundance measurements of drugmetabolizing enzymes and drug transporters (Achour et al, 2014c;Badée et al, 2015), even when matched samples were analyzed (Harwood et al, 2016a), necessitating further investigations into the factors contributing to these discrepancies. To illustrate this point, the present study reports comparative analysis of a set of eight UGT enzymes quantified by two distinct proteomic methodologies (SIL and QconCAT-based approaches) in matching samples, with correlation of these abundances against rates of glucuronidation for seven UGT substrates, highlighting large interlaboratory discrepancies between the reported protein levels of these enzymes.…”

“…For example, the abundance of hepatic organic anion transporting polypeptide 1B1 showed a wide variation (up to 10-fold) in sets of nonmatched samples measured using two different methodological workflows Vildhede et al, 2014). Meta-analyses of abundance measurements of drug-metabolizing P450 enzymes (Achour et al, 2014b), UGT enzymes (Achour et al, 2014c), and drug transporters (Badée et al, 2015) revealed up to 600-, 250-, and 100-fold differences in collated data, respectively, with a large level of interstudy heterogeneity (Higgins and Thompson's index of up to 99%), suggesting that variability in data used in pharmacokinetic extrapolation and simulation cannot be attributed to biologic interindividual variation in expression alone.…”

Expression of Hepatic Drug-Metabolizing Cytochrome P450 Enzymes and Their Intercorrelations: A Meta-Analysis

“…We attribute this difference to the cross-reactivity of antibodies (early antibodies to CYP3A4 were rather nonspecific). The major difference between this work and earlier work, however, is the sheer number of individual enzymes detected; 15 individual enzymes have now been quantified, allowing a much more detailed human liver "pie" to be created and complementing our recent UGT liver pie (Achour et al, 2014b).…”

Characterization of Contributing Factors to Variability in Morphine Clearance Through PBPK Modeling Implemented With OCT1 Transporter

“…Previously, we showed the impact of OCT1 genotype on morphine clearance (CL) in pediatric patients 7. After the uptake of morphine into hepatocytes, morphine is metabolized by uridine 5′‐diphosphate glucuronosyltransferase (UGT)2B7 8, 9, 10. Because UGT2B7 is also expressed in the kidneys,11 the kidneys could also contribute to morphine metabolism.…”