Compendium of gene expression profiles comprising a baseline model of the human liver drug metabolism transcriptome

Abstract

Oligonucleotide microarrays were used to study the variability of pharmacokinetics and drug metabolism (PKDM)-related gene expression in 75 normal human livers. The objective was to define and use absorption, distribution, metabolism and excretion (ADME) gene expression variability to discern co-regulated genes and potential surrogate biomarkers of inducible gene expression. RNA was prepared from donor tissue and hybridized on Agilent microarrays against an RNA mass balanced pool from all donors. Clustering of PKDM gene sets revealed donors with distinct patterns of gene expression that grouped genes known to be regulated by the nuclear receptor, pregnane X-receptor (PXR). Fold range metrics and frequency distributions from the heterogeneous human population were used to define the variability of individual PKDM genes in the 75 human livers and were placed in context by comparing expression data with basal ADME gene expression variability in an inbred and diet/environment controlled population of 27 Rhesus livers. The most variable genes in the hepatic transcriptome were mainly related to drug metabolism, intermediary metabolism, inflammation and cell cycle control. Unique patterns of expression across 75 individuals of inducible ADME gene expression allowed their expression to be correlated with the expression of many other genes. Correlated genes for AhR, CAR and PXR responsive genes (CYP1A2, CYP2B6 and CYP3A4) were identified that may be co-regulated and, therefore, provide clues to the identity of surrogate gene or protein markers for CYP induction. In conclusion, microarrays were used to define the variable expression of hepatic ADME genes in a diverse human population, the expression variability of ADME genes was compared with the expression variability in an inbred population of Rhesus monkeys, and genes were defined that may be co-regulated with important inducible CYP genes.

Expression of Constitutive Androstane Receptor, Hepatic Nuclear Factor 4α, and P450 Oxidoreductase Genes Determines Interindividual Variability in Basal Expression and Activity of a Broad Scope of Xenobiotic Metabolism Genes in the Human Liver

“…In addition, Kawashima et al (2006) demonstrated binding of HNF4␣ to the CYP2C9 promoter with an immunoprecipitation from human liver. Although recent microarray data did not detect the same correlations between expression levels of HNF4␣ and target genes as the current study, this effect is likely accounted for by the low detection level of HNF4␣ by the microarray used (Slatter et al, 2006). HNF4␣ has been shown to exert a dose-dependent effect upon mRNA expression level of CYP2A6, CYP2B6, CYP2C9, CYP2D6, CYP3A4, and CYP3A5 in primary human hepatocytes when HNF4␣ expression was gradually reduced using antisense RNA (Jover et al, 2001).…”

Systematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liver

“…Three of these genes-EHHADH, SLC10A1, and AKR1D1-were also found to be top hub genes in the P450-correlated turquoise module from the independent coexpression network. In the literature, EHHADH has been found to be responsive to ligands of AHR, NR1I3 (CAR), and NR1I2 (PXR); SLC10A1 is selectively responsive to AHR ligands; AKR1D1 is selectively responsive to PXR ligands (Slatter et al 2006). Thus, these three upstream genes represent novel putative key regulators of P450 genes.…”

“…We obtained consensus compound signatures in mouse and rat livers that are responsive to 26 inducers of AHR, NR1I3 (CAR), and NR1I2 (PXR) (e.g., AHR ligand flutamide, CAR ligand androstenol, and PXR ligand hyperforin) (Slatter et al 2006), and analyzed the overlap between these signatures and our network. Indeed, our P450 subnetwork is significantly enriched not only for mouse genes responsive to ligands of AHR, CAR, PXR, and all three receptors with enrichment P-values of 1.66 3 10 À12 , 1.08 3 10 À14 , 9.74 3 10 À13 , and 6.19 3 10…”

“…As described previously (Schadt et al 2008), a total of 780 liver samples (1-2 g) were obtained from Caucasian individuals from three independent liver collections at tissue resource centers at Vanderbilt University, the University of Pittsburgh, and Merck Research Laboratories (Slatter et al 2006). DNA and RNA were isolated from all liver tissue samples.…”

High-Throughput Screening by RNA Interference: Control of Two Distinct Types of Variance

“…Therefore, in many cases the derived function is no better than a guess. Although true functional genomics studies have been done using complex experimental readouts from known physiological states or positive controls and pattern matching the resulting readouts, [1][2][3][4][5][6] RNAi allows for the first time the direct measurement of gene function in pathways of interest on a genome-wide scale. This approach has been quickly embraced in both academic and industrial research.…”