Macrophages are cells with remarkable plasticity. They integrate signals from their microenvironment leading to context-dependent polarization into classically (M1) or alternatively (M2) activated macrophages, representing two extremes of a broad spectrum of divergent phenotypes. Thereby, macrophages deliver protective and pro-regenerative signals towards injured tissue but, depending on the eliciting damage, may also be responsible for the generation and aggravation of tissue injury. Although incompletely understood, there is emerging evidence that macrophage polarization is critical for these antagonistic roles. To identify activation-specific expression patterns of chemokines and cytokines that may confer these distinct effects a systems biology approach was applied. A comprehensive literature-based Boolean model was developed to describe the M1 (LPS-activated) and M2 (IL-4/13-activated) polarization types. The model was validated using high-throughput transcript expression data from murine bone marrow derived macrophages. By dynamic modeling of gene expression, the chronology of pathway activation and autocrine signaling was estimated. Our results provide a deepened understanding of the physiological balance leading to M1/M2 activation, indicating the relevance of co-regulatory signals at the level of Akt1 or Akt2 that may be important for directing macrophage polarization.
Macrophages are essential cells of the immune system and indispensable for a defense against bacterial infection. They reside as resting, immune modulatory cells in several tissues of the human body where they continuously sense inputs from their local environment. They react to stimuli such as toxins, injury or bacterial products in a process termed macrophage activation or polarization. For example, the bacterial component lipopolysaccharide induces so-called classical activation of macrophages into the M1 phenotype that secretes a number of inflammatory cytokines and chemokines leading to killing of bacteria and resolution of inflammation. Another prominent phenotype of macrophages is the M2 polarization state that is associated with wound healing and tissue regeneration. Unbalanced activation of macrophages is implicated in a number of diseases. An improved knowledge and extensive characterization of these macrophages as well as the factors determining their phenotypes will improve the understanding of the role of macrophages in disease progression.
The cytochrome P450, CYP2C8, metabolizes more than 60 clinically used drugs as well as endogenous substances including retinoic acid and arachidonic acid. However, predictive factors for interindividual variability in the efficacy and toxicity of CYP2C8 drug substrates are essentially lacking. Recently we demonstrated that peroxisome proliferator-activated receptor alpha (PPARα), a nuclear receptor primarily involved in control of lipid and energy homeostasis directly regulates the transcription of CYP3A4. Here we investigated the potential regulation of CYP2C8 by PPARα. Two linked intronic SNPs in PPARα (rs4253728, rs4823613) previously associated with hepatic CYP3A4 status showed significant association with CYP2C8 protein level in human liver samples (N = 150). Furthermore, siRNA-mediated knock-down of PPARα in HepaRG human hepatocyte cells resulted in up to ∼60 and ∼50% downregulation of CYP2C8 mRNA and activity, while treatment with the PPARα agonist WY14,643 lead to an induction by >150 and >100%, respectively. Using chromatin immunoprecipitation scanning assay we identified a specific upstream gene region that is occupied in vivo by PPARα. Electromobility shift assay demonstrated direct binding of PPARα to a DR-1 motif located at positions –2762/–2775 bp upstream of the CYP2C8 transcription start site. We further validated the functional activity of this element using luciferase reporter gene assays in HuH7 cells. Moreover, based on our previous studies we demonstrated that WNT/β-catenin acts as a functional inhibitor of PPARα-mediated inducibility of CYP2C8 expression. In conclusion, our data suggest direct involvement of PPARα in both constitutive and inducible regulation of CYP2C8 expression in human liver, which is further modulated by WNT/β-catenin pathway. PPARA gene polymorphism could have a modest influence on CYP2C8 phenotype.
chromatin immunoprecipitation; diet–drug interaction; drug metabolism; genotype–phenotype correlation; HepaRG cells; nuclear receptors; transcriptional regulation; WNT/β-catenin
Fluourouracil (FU) is a mainstay of chemotherapy, although toxicities are common. Genetic biomarkers have been used to predict these adverse events, but their utility is uncertain.
Patients and Methods
We tested candidate polymorphisms identified from a systematic literature search for associations with capecitabine toxicity in 927 patients with colorectal cancer in the Quick and Simple and Reliable trial (QUASAR2). We then performed meta-analysis of QUASAR2 and 16 published studies (n = 4,855 patients) to examine the polymorphisms in various FU monotherapy and combination therapy regimens.
Global capecitabine toxicity (grades 0/1/2 v grades 3/4/5) was associated with the rare, functional DPYD alleles 2846T>A and *2A (combined odds ratio, 5.51; P = .0013) and with the common TYMS polymorphisms 5′VNTR2R/3R and 3′UTR 6bp ins-del (combined odds ratio, 1.31; P = 9.4 × 10−6). There was weaker evidence that these polymorphisms predict toxicity from bolus and infusional FU monotherapy. No good evidence of association with toxicity was found for the remaining polymorphisms, including several currently included in predictive kits. No polymorphisms were associated with toxicity in combination regimens.
A panel of genetic biomarkers for capecitabine monotherapy toxicity would currently comprise only the four DPYD and TYMS variants above. We estimate this test could provide 26% sensitivity, 86% specificity, and 49% positive predictive value—better than most available commercial kits, but suboptimal for clinical use. The test panel might be extended to include additional, rare DPYD variants functionally equivalent to *2A and 2846A, though insufficient evidence supports its use in bolus, infusional, or combination FU. There remains a need to identify further markers of FU toxicity for all regimens.
The effect of rifampin on the in vivo metabolism of the antiretroviral drug efavirenz was evaluated in healthy volunteers. In a cross-over placebo control trial, healthy subjects (n = 20) were administered a single 600 mg oral dose of efavirenz after pretreatment with placebo or rifampin (600 mg/day for 10 days). Plasma and urine concentrations of efavirenz, 8-hydroxyefavirenz and 8,14-dihydroxyefavirenz were measured by LC–MS/MS. Compared to placebo treatment, rifampin increased the oral clearance (by ~2.5-fold) and decreased maximum plasma concentration (Cmax) and area under the plasma concentration–time curve (AUC0–∞) of efavirenz (by ~1.6- and ~2.5-fold respectively) (p < 0.001). Rifampin treatment substantially increased the Cmax and AUC0–12h of 8-hydroxyefavirenz and 8,14-dihydroxyefavirenz, metabolic ratio (AUC0–72h of metabolites to AUC0–72h efavirenz) and the amount of metabolites excreted in urine (Ae0–12hr) (all, p < 0.01). Female subjects had longer elimination half-life (1.6–2.2-fold) and larger weight-adjusted distribution volume (1.6– 1.9-fold) of efavirenz than male subjects (p < 0.05) in placebo and rifampin treated groups respectively. In conclusion, rifampin enhances CYP2B6-mediated efavirenz 8-hydroxylation in vivo. The metabolism of a single oral dose of efavirenz may be a suitable in vivo marker of CYP2B6 activity to evaluate induction drug interactions involving this enzyme.
Rifampin; Efavirenz; 8-Hydroxylalion; CYP2B6; Induction; In vivo probe
MicroRNAs (miRNA) are small non-coding RNA molecules of ∼22 nucleotides which regulate large numbers of genes by binding to seed sequences at the 3′-untranslated region of target gene transcripts. The target mRNA is then usually degraded or translation is inhibited, although thus resulting in posttranscriptional down regulation of gene expression at the mRNA and/or protein level. Due to the bioinformatic difficulties in predicting functional miRNA binding sites, several publically available databases have been developed that predict miRNA binding sites based on different algorithms. The parallel use of different databases is currently indispensable, but highly uncomfortable and time consuming, especially when working with numerous genes of interest. We have therefore developed a new stand-alone program, termed MIRNA-DISTILLER, which allows to compile miRNA data for given target genes from public databases. Currently implemented are TargetScan, microCosm, and miRDB, which may be queried independently, pairwise, or together to calculate the respective intersections. Data are stored locally for application of further analysis tools including freely definable biological parameter filters, customized output-lists for both miRNAs and target genes, and various graphical facilities. The software, a data example file and a tutorial are freely available at http://www.ikp-stuttgart.de/content/language1/html/10415.asp
database; gene expression; gene regulation; microRNA; non-coding RNA; stand-alone software
During various inflammatory processes circulating cytokines including IL-6, IL-1β, and TNFα elicit a broad and clinically relevant impairment of hepatic detoxification that is based on the simultaneous downregulation of many drug metabolizing enzymes and transporter genes. To address the question whether a common mechanism is involved we treated human primary hepatocytes with IL-6, the major mediator of the acute phase response in liver, and characterized acute phase and detoxification responses in quantitative gene expression and (phospho-)proteomics data sets. Selective inhibitors were used to disentangle the roles of JAK/STAT, MAPK, and PI3K signaling pathways. A prior knowledge-based fuzzy logic model comprising signal transduction and gene regulation was established and trained with perturbation-derived gene expression data from five hepatocyte donors. Our model suggests a greater role of MAPK/PI3K compared to JAK/STAT with the orphan nuclear receptor RXRα playing a central role in mediating transcriptional downregulation. Validation experiments revealed a striking similarity of RXRα gene silencing versus IL-6 induced negative gene regulation (rs = 0.79; P<0.0001). These results concur with RXRα functioning as obligatory heterodimerization partner for several nuclear receptors that regulate drug and lipid metabolism.
During inflammation, circulating proinflammatory cytokines such as TNFα, IL-1ß, and IL-6, which are produced by, e.g., Kupffer cells, macrophages, or tumor cells, play important roles in hepatocellular signaling pathways and in the regulation of cellular homeostasis. In particular, these cytokines are responsible for the acute phase response (APR) but also for a dramatic reduction of drug detoxification capacity due to impaired expression of numerous genes coding for drug metabolic enzymes and transporters. Here we used high-throughput (phospho-)proteomic and gene expression data to investigate the impact of canonical signaling pathways in mediating IL-6-induced downregulation of drug metabolism related genes. We performed chemical inhibition perturbations to show that most of the IL-6 effects on gene expression are mediated through the MAPK and PI3K/AKT pathways. We constructed a prior knowledge network as basis for a fuzzy logic model that was trained with extensive gene expression data to identify critical regulatory nodes. Our results suggest that the nuclear receptor RXRα plays a central role, which was convincingly validated by RXRα gene silencing experiments. This work shows how computational modeling can support identifying decisive regulatory events from large-scale experimental data.
Disrupted bile secretion leads to liver damage characterized by inflammation, fibrosis, eventually cirrhosis, and hepatocellular cancer. As obstructive cholestasis often progresses insidiously, markers for the diagnosis and staging of the disease are urgently needed. To this end, we compiled a comprehensive data set of serum markers, histological parameters and transcript profiles at 8 time points of disease progression after bile duct ligation (BDL) in mice, aiming at identifying a set of parameters that could be used as robust biomarkers for transition of different disease progression phases.
Statistical analysis of the more than 6,000 data points revealed distinct temporal phases of disease. Time course correlation analysis of biochemical, histochemical and mRNA transcript parameters (=factors) defined 6 clusters for different phases of disease progression. The number of CTGF-positive cells provided the most reliable overall measure for disease progression at histological level, bilirubin at biochemical level, and metalloproteinase inhibitor 1 (Timp1) at transcript level. Prominent molecular events exhibited by strong transcript peaks are found for the transcriptional regulator Nr0b2 (Shp) and 1,25-dihydroxyvitamin D(3) 24-hydroxylase (Cyp24a1) at 6 h. Based on these clusters, we constructed a decision tree of factor combinations potentially useful as markers for different time intervals of disease progression. Best prediction for onset of disease is achieved by fibronectin (Fn1), for early disease phase by Cytochrome P450 1A2 (Cyp1a2), passage to perpetuation phase by collagen1α-1 (Col1a1), and transition to the progression phase by interleukin 17-a (Il17a), with early and late progression separated by Col1a1. Notably, these predictions remained stable even for randomly chosen small sub-sets of factors selected from the clusters.
Our detailed time-resolved explorative study of liver homogenates following BDL revealed a well-coordinated response, resulting in disease phase dependent parameter modulations at morphological, biochemical, metabolic and gene expression levels. Interestingly, a small set of selected parameters can be used as diagnostic markers to predict disease stages in mice with cholestatic liver disease.
Electronic supplementary material
The online version of this article (doi:10.1186/s12918-015-0229-0) contains supplementary material, which is available to authorized users.
Liver injury; Mouse; Systems biology; Fibrosis; Cell proliferation; Bile duct ligation; Cholestasis; Morphological profiling; Virtual liver network
Cytochrome P450 2B6 (CYP2B6) belongs to the minor drug metabolizing P450s in human liver. Expression is highly variable both between individuals and within individuals, owing to non-genetic factors, genetic polymorphisms, inducibility, and irreversible inhibition by many compounds. Drugs metabolized mainly by CYP2B6 include artemisinin, bupropion, cyclophosphamide, efavirenz, ketamine, and methadone. CYP2B6 is one of the most polymorphic CYP genes in humans and variants have been shown to affect transcriptional regulation, splicing, mRNA and protein expression, and catalytic activity. Some variants appear to affect several functional levels simultaneously, thus, combined in haplotypes, leading to complex interactions between substrate-dependent and -independent mechanisms. The most common functionally deficient allele is CYP2B6*6 [Q172H, K262R], which occurs at frequencies of 15 to over 60% in different populations. The allele leads to lower expression in liver due to erroneous splicing. Recent investigations suggest that the amino acid changes contribute complex substrate-dependent effects at the activity level, although data from recombinant systems used by different researchers are not well in agreement with each other. Another important variant, CYP2B6*18 [I328T], occurs predominantly in Africans (4–12%) and does not express functional protein. A large number of uncharacterized variants are currently emerging from different ethnicities in the course of the 1000 Genomes Project. The CYP2B6 polymorphism is clinically relevant for HIV-infected patients treated with the reverse transcriptase inhibitor efavirenz, but it is increasingly being recognized for other drug substrates. This review summarizes recent advances on the functional and clinical significance of CYP2B6 and its genetic polymorphism, with particular emphasis on the comparison of kinetic data obtained with different substrates for variants expressed in different recombinant expression systems.
bupropion; cyclophosphamide; cytochrome P450; drug metabolism; drug–drug interaction; efavirenz; pharmacogenetics; pharmacogenomics
Gene expression analysis is an essential part of biological and medical investigations. Quantitative real-time PCR (qPCR) is characterized with excellent sensitivity, dynamic range, reproducibility and is still regarded to be the gold standard for quantifying transcripts abundance. Parallelization of qPCR such as by microfluidic Taqman Fluidigm Biomark Platform enables evaluation of multiple transcripts in samples treated under various conditions. Despite advanced technologies, correct evaluation of the measurements remains challenging. Most widely used methods for evaluating or calculating gene expression data include geNorm and ΔΔCt, respectively. They rely on one or several stable reference genes (RGs) for normalization, thus potentially causing biased results. We therefore applied multivariable regression with a tailored error model to overcome the necessity of stable RGs.
We developed a RG independent data normalization approach based on a tailored linear error model for parallel qPCR data, called LEMming. It uses the assumption that the mean Ct values within samples of similarly treated groups are equal. Performance of LEMming was evaluated in three data sets with different stability patterns of RGs and compared to the results of geNorm normalization. Data set 1 showed that both methods gave similar results if stable RGs are available. Data set 2 included RGs which are stable according to geNorm criteria, but became differentially expressed in normalized data evaluated by a t-test. geNorm-normalized data showed an effect of a shifted mean per gene per condition whereas LEMming-normalized data did not. Comparing the decrease of standard deviation from raw data to geNorm and to LEMming, the latter was superior. In data set 3 according to geNorm calculated average expression stability and pairwise variation, stable RGs were available, but t-tests of raw data contradicted this. Normalization with RGs resulted in distorted data contradicting literature, while LEMming normalized data did not.
If RGs are coexpressed but are not independent of the experimental conditions the stability criteria based on inter- and intragroup variation fail. The linear error model developed, LEMming, overcomes the dependency of using RGs for parallel qPCR measurements, besides resolving biases of both technical and biological nature in qPCR. However, to distinguish systematic errors per treated group from a global treatment effect an additional measurement is needed. Quantification of total cDNA content per sample helps to identify systematic errors.
We characterized relationships between 22 polymorphisms in CYP2B6, ABCB1 and CYP3A5, plasma efavirenz exposure, and/or treatment responses in AIDS Clinical Trials Group protocols 384, A5095, and A5097s. A stepwise logistic regression procedure selected polymorphisms associated with reduced drug clearance adjusted for body mass index and composite CYP2B6 516/983 genotype. Competing risk methodology characterized relationships between selected polymorphisms and treatment responses. Association analyses involved 821 individuals (317 for pharmacokinetics, 643 for treatment response). Models that included CYP2B6 516/983 genotype best predicted pharmacokinetics. Slow metabolizer genotypes were associated with increased central nervous system events among whites, and decreased virologic failure among blacks.
pharmacogenetics; efavirenz; CYP2B6; HIV therapy
Atorvastatin δ-lactone, a major, pharmacologically inactive metabolite, has been associated with toxicity. In a previous study we showed that polymorphisms of UGT1A3 influence atorvastatin δ-lactone formation. Here we investigated the reverse reaction, atorvastatin δ-lactone hydrolysis, in a human liver bank. Screening of microarray data revealed paraoxonases PON1 and PON3 among 17 candidate esterases. Microsomal δ-lactone hydrolysis was significantly correlated to PON1 and PON3 protein (rs = 0.60; rs = 0.62, respectively; P < 0.0001). PON1 and PON3 were strongly correlated to each other (rs = 0.60) but PON1 was shown to be more extensively glycosylated than PON3. In addition a novel splice-variant of PON3 was identified. Genotyping of 40 polymorphisms within the PON-locus identified PON1 promoter polymorphisms (−108T > C, −832G > A, −1741G > A) and a tightly linked group of PON3 polymorphisms (−4984A > G, −4105G > A, −1091A > G, −746C > T, and F21F) to be associated with changes in atorvastatin δ-lactone hydrolysis and expression of PON1 but not PON3. However, carriers of the common PON1 polymorphisms L55M or Q192R showed no difference in δ-lactone hydrolysis or PON expression. Haplotype analysis revealed decreased δ-lactone hydrolysis in carriers of the most common haplotype *1 compared to carriers of haplotypes *2, *3, *4, and *7. Analysis of non-genetic factors showed association of hepatocellular and cholangiocellular carcinoma with decreased PON1 and PON3 expression, respectively. Increased C-reactive protein and γ-glutamyl transferase levels were associated with decreased protein expression of both enzymes, and increased bilirubin levels, cholestasis, and presurgical exposure to omeprazole or pantoprazole were related to decreased PON3 protein. In conclusion, PON-locus polymorphisms affect PON1 expression whereas non-genetic factors have an effect on PON1 and PON3 expression. This may influence response to therapy or adverse events in statin treatment.
atorvastatin-lactone; myopathy; rhabdomyolysis; paraoxonase; PON1; PON3; SNP; pharmacogenetics
The peroxisome proliferator-activated receptor alpha (PPARα) controls lipid/energy homeostasis and inflammatory responses. The truncated splice variant PPARα-tr was suggested to exert a dominant negative function despite being unable to bind consensus PPARα DNA response elements.
The distribution and variability factor of each PPARα variant were assessed in the well-characterized cohort of human liver samples (N = 150) on the mRNA and protein levels. Specific siRNA-mediated downregulation of each transcript as well as specific overexpression with subsequent qRT-PCR analysis of downstream genes was used for investigation of specific functional roles of PPARα-wt and PPARα-tr forms in primary human hepatocytes.
Bioinformatic analyses of genome-wide liver expression profiling data suggested a possible role of PPARα-tr in downregulating proliferative and pro-inflammatory genes. Specific gene silencing of both forms in primary human hepatocytes showed that induction of metabolic PPARα-target genes by agonist WY14,643 was prevented by PPARα-wt knock-down but neither prevented nor augmented by PPARα-tr knock-down. WY14,643 treatment did not induce proliferative genes including MYC, CDK1, and PCNA, and knock-down of PPARα-wt had no effect, while PPARα-tr knock-down caused up to 3-fold induction of these genes. Similarly, induction of pro-inflammatory genes IL1B, PTGS2, and CCL2 by IL-6 was augmented by knock-down of PPARα-tr but not of PPARα-wt. In contrast to human proliferative genes, orthologous mouse genes were readily inducible by WY14,643 in PPARα-tr non-expressing AML12 mouse hepatocytes. Induction was augmented by overexpression of PPARα-wt and attenuated by overexpression of PPARα-tr. Pro-inflammatory genes including IL-1β, CCL2 and TNFα were induced by WY14,643 in mouse and human cells and both PPARα forms attenuated induction. As potential mechanism of PPARα-tr inhibitory action we suggest crosstalk with WNT/β-catenin pathway. Finally, treatment with WY14,643 in the presence of PPARα-tr resulted in the significant reduction of cell viability of AML12 and human ovarian cancer cell line, SKOV3.
Our data suggest that the truncated PPARα splice variant functions as an endogenous inhibitor of proliferative and pro-inflammatory genes in human cells and that its absence in mouse may explain species-specific differences in fibrate-induced hepatocarcinogenesis.
Electronic supplementary material
The online version of this article (doi:10.1186/s12885-015-1500-x) contains supplementary material, which is available to authorized users.
Alternative splicing; Fibrates; Hepatocarcinogenesis; PPARA; Primary human hepatocytes; Inflammation; Proliferation; WNT/β-catenin
DNA methylation and histone 3 lysine 9 (H3K9) methylation are considered as epigenetic marks that can be inherited through cell divisions. To explore the functional consequences and stability of these modifications, we employed targeted installment of DNA methylation and H3K9 methylation in the vascular endothelial growth factor A (VEGF-A) promoter using catalytic domains of DNA or H3K9 methyltransferases that are fused to a zinc finger protein which binds a site in the VEGF-A promoter.
Expression of the targeted DNA and H3K9 methyltransferases caused dense deposition of DNA methylation or H3K9 di- and trimethylation in the promoter of VEGF-A and downregulation of VEGF-A gene expression. We did not observe positive feedback between DNA methylation and H3K9 methylation. Upon loss of the targeted methyltransferases from the cells, the epigenetic marks, chromatin environment, and gene expression levels returned to their original state, indicating that both methylation marks were not stably propagated after their installment.
The clear anti-correlation between DNA or H3K9 methylation and gene expression suggests a direct role of these marks in transcriptional control. The lack of maintenance of the transiently induced silenced chromatin state suggests that the stability of epigenetic signaling is based on an epigenetic network consisting of several molecular marks. Therefore, for stable reprogramming, either multivalent deposition of functionally related epigenetic marks or longer-lasting trigger stimuli might be necessary.
Electronic supplementary material
The online version of this article (doi:10.1186/s13072-015-0002-z) contains supplementary material, which is available to authorized users.
Efavirenz is commonly used to treat patients coinfected with human immunodeficiency virus and tuberculosis. Previous clinical studies have observed paradoxically elevated efavirenz plasma concentrations in patients with the CYP2B6*6/*6 genotype (but not the CYP2B6*1/*1 genotype) during coadministration with the commonly used four-drug antituberculosis therapy. This study sought to elucidate the mechanism underlying this genotype-dependent drug-drug interaction. In vitro studies were conducted to determine whether one or more of the antituberculosis drugs (rifampin, isoniazid, pyrazinamide, or ethambutol) potently inhibit efavirenz 8-hydroxylation by CYP2B6 or efavirenz 7-hydroxylation by CYP2A6, the main mechanisms of efavirenz clearance. Time- and concentration-dependent kinetics of inhibition by the antituberculosis drugs were determined using genotyped human liver microsomes (HLMs) and recombinant CYP2A6, CYP2B6.1, and CYP2B6.6 enzymes. Although none of the antituberculosis drugs evaluated at up to 10 times clinical plasma concentrations were found to inhibit efavirenz 8-hydroxylation by HLMs, both rifampin (apparent inhibition constant [Ki] = 368 μM) and pyrazinamide (Ki = 637 μM) showed relatively weak inhibition of efavirenz 7-hydroxylation. Importantly, isoniazid demonstrated potent time-dependent inhibition of efavirenz 7-hydroxylation in both HLMs (inhibitor concentration required for half-maximal inactivation [KI] = 30 μM; maximal rate constant of inactivation [kinact] = 0.023 min−1) and recombinant CYP2A6 (KI = 15 μM; kinact = 0.024 min−1) and also formed a metabolite intermediate complex consistent with mechanism-based inhibition. Selective inhibition of the CYP2B6.6 allozyme could not be demonstrated for any of the antituberculosis drugs using either recombinant enzymes or CYP2B6*6 genotype HLMs. In conclusion, the results of this study identify isoniazid as the most likely perpetrator of this clinically important drug-drug interaction through mechanism-based inactivation of CYP2A6.
Chlorpyrifos (CPF) is a widely used organophosphorus (OP) pesticide. CPF is bioactivated by cytochrome P450s (CYPs) to the potent cholinesterase inhibitor chlorpyrifos oxon (CPF-O) or detoxified to 3,5,6-trichloro-2-pyridinol (TCPy). Human CYP2B6 has the highest reported Vmax/Km (intrinsic clearance - CLint) for bioactivation while CYP2C19 has the highest reported CLint for detoxification of CPF. In this study, 22 human liver microsomes (HLMs) genotyped for common variants of these enzymes (CYP2B6*6 and CYP2C19*2) were incubated with 10μM and 0.5μM CPF and assayed for metabolite production. While no differences in metabolite production were observed in homozygous CYP2C19*2 HLMs, homozygous CYP2B6*6 specimens produced significantly less CPF-O than wild-type specimens at 10μM (mean 144 and 446 pmol/min/mg, respectively). This correlated with reduced expression of CYP2B6 protein (mean 4.86 and 30.1 pmol/mg, for CYP2B6*6 and *1, respectively). Additionally, CYP2B6*1 and CYP2B6*6 were over-expressed in mammalian COS-1 cells to assess for the first time the impact of the CYP2B6*6 variant on the kinetic parameters of CPF bioactivation. The Vmax for CYP2B6*6 (1.05 × 105 pmol/min/nmol CYP2B6) was significantly higher than that of CYP2B6*1 (4.13 × 104 pmol/min/nmol CYP2B6) but the Km values did not differ (1.97 μM for CYP2B6*6 and 1.84 μM for CYP2B6*1) resulting in CLint rates of 53.5 and 22.5 nL/min/nmol CYP2B6 for *6 and *1, respectively. These data suggest that CYP2B6*6 has increased specific activity but reduced capacity to bioactivate CPF in HLMs compared to wild-type due to reduced hepatic protein expression, indicating that individuals with this genotype may be less susceptible to CPF toxicity.
CYP2B6; CYP2C19; chlorpyrifos; biotransformation
CYP3A4 is the most important drug metabolizing enzyme in adult humans because of its prominent expression in liver and gut and because of its broad substrate specificity, which includes drugs from most therapeutic categories and many endogenous substances. Expression and function of CYP3A4 vary extensively both intra- and interindividually thus contributing to unpredictable drug response and toxicity. A multitude of environmental, genetic, and physiological factors are known to influence CYP3A4 expression and activity. Among the best predictable sources of variation are drug–drug interactions, which are either caused by pregnane X-receptor (PXR), constitutive androstane receptor (CAR) mediated gene induction, or by inhibition through coadministered drugs or other chemicals, including also plant and food ingredients. Among physiological and pathophysiological factors are hormonal status, age, and gender, the latter of which was shown to result in higher levels in females compared to males, as well as inflammatory processes that downregulate CYP3A4 transcription. Despite the influence of these non-genetic factors, the genetic influence on CYP3A4 activity was estimated in previous twin studies and using information on repeated drug administration to account for 66% up to 88% of the interindividual variation. Although many single nucleotide polymorphisms (SNPs) within the CYP3A locus have been identified, genetic association studies have so far failed to explain a major part of the phenotypic variability. The term “missing heritability” has been used to denominate the gap between expected and known genetic contribution, e.g., for complex diseases, and is also used here in analogy. In this review we summarize CYP3A4 pharmacogenetics/genomics from the early inheritance estimations up to the most recent genetic and clinical studies, including new findings about SNPs in CYP3A4 (*22) and other genes (P450 oxidoreductase (POR), peroxisome proliferator-activated receptor alpha (PPARA)) with possible contribution to CYP3A4 variable expression.
cytochrome P450; CYP3A4; pharmacogenomics; pharmacogenetics; drug metabolism; heritability
Non-alcoholic fatty liver disease (NAFLD), the hepatic manifestation of the metabolic syndrome, is a complex multifactorial disease characterized by metabolic deregulations that include accumulation of lipids in the liver, lipotoxicity, and insulin resistance. The progression of NAFLD to non-alcoholic steatohepatitis and cirrhosis, and ultimately to carcinomas, is governed by interplay of pro-inflammatory pathways, oxidative stress, as well as fibrogenic and apoptotic cues. As the liver is the major organ of biotransformation, deregulations in hepatic signaling pathways have effects on both, xenobiotic and endobiotic metabolism. Several major nuclear receptors involved in the transcription and regulation of phase I and II drug metabolizing enzymes and transporters also have endobiotic ligands including several lipids. Hence, hepatic lipid accumulation in steatosis and NAFLD, which leads to deregulated activation patterns of nuclear receptors, may result in altered drug metabolism capacity in NAFLD patients. On the other hand, genetic and association studies have indicated that a malfunction in drug metabolism can affect the prevalence and severity of NAFLD. This review focuses on the complex interplay between NAFLD pathogenesis and drug metabolism. A better understanding of these relationships is a prerequisite for developing improved drug dosing algorithms for the pharmacotherapy of patients with different stages of NAFLD.
NAFLD; xenobiotic metabolism; nuclear receptors; phase I and II enzymes; transporters
Organic anion transporting polypeptide (OATP) 1B1, OATP1B3, and OATP2B1 (encoded by SLCO1B1, SLCO1B3, SLCO2B1) mediate the hepatic uptake of endogenous compounds like bile acids and of drugs, for example, the lipid-lowering atorvastatin, thereby influencing hepatobiliary elimination. Here we systematically elucidated the contribution of SLCO variants on expression of the three hepatic OATPs under consideration of additional important covariates.
Expression was quantified by RT-PCR and immunoblotting in 143 Caucasian liver samples. A total of 109 rare and common variants in the SLCO1B3-SLCO1B1 genomic region and the SLCO2B1 gene were genotyped by MALDI-TOF mass spectrometry and genome-wide SNP microarray technology. SLCO1B1 haplotypes affecting hepatic OATP1B1 expression were associated with pharmacokinetic data of the OATP1B1 substrate atorvastatin (n = 82).
Expression of OATP1B1, OATP1B3, and OATP2B1 at the mRNA and protein levels showed marked interindividual variability. All three OATPs were expressed in a coordinated fashion. By a multivariate regression analysis adjusted for non-genetic and transcription covariates, increased OATP1B1 expression was associated with the coding SLCO1B1 variant c.388A > G (rs2306283) even after correction for multiple testing (P = 0.00034). This held true for haplotypes harboring c.388A > G but not the functional variant c.521T > C (rs4149056) associated with statin-related myopathy. c.388A > G also significantly affected atorvastatin pharmacokinetics. SLCO variants and non-genetic and regulatory covariates together accounted for 59% of variability of OATP1B1 expression.
Our results show that expression of OATP1B1, but not of OATP1B3 and OATP2B1, is significantly affected by genetic variants. The SLCO1B1 variant c.388A > G is the major determinant with additional consequences on atorvastatin plasma levels.
Organic cation transporters (OCTs) determine not only physiological processes but are also involved in the cellular uptake of anticancer agents. Based on microarray analyses in hepatocellular carcinoma (HCC), SLC22A1/OCT1 mRNA seems to be downregulated, but systematic protein expression data are currently missing. Moreover, the underlying molecular mechanisms responsible for altered SLC22A1 expression in HCC are not fully understood. Therefore, we investigated the role of DNA methylation in the transcriptional regulation of the family members SLC22A1/OCT1, SLC22A2/OCT2 and SLC22A3/OCT3 in HCC.
Semiquantitative immunohistochemistry of SLC22A1 protein expression was performed in paired HCC and histological normal adjacent liver tissues (n = 71) using tissue microarray analyses, and the results were correlated with clinicopathological features. DNA methylation, quantified by MALDI-TOF mass spectrometry and gene expression of SLC22A1, SLC22A2 and SLC22A3 were investigated using fresh-frozen HCC (n = 22) and non-tumor adjacent liver tissues as well as histologically normal liver samples (n = 120) from a large-scale liverbank.
Based on tissue microarray analyses, we observed a significant downregulation of SLC22A1 protein expression in HCC compared to normal adjacent tissue (P < 0.0001). SLC22A1 expression was significantly inverse correlated with expression of the proliferation marker MIB1/Ki-67 (rs = -0.464, P < 0.0001). DNA methylation of SLC22A1 was significantly higher in HCC compared with non-tumor adjacent liver tissue and was lowest in histologically normal liver tissue. Methylation levels for SLC22A1 in combination with RASSF1A resulted in a specificity of > 90% and a sensitivity of 82% for discriminating HCC and tumor-free liver tissue.
DNA methylation of SLC22A1 is associated with downregulation of SLC22A1 in HCC and might be a new biomarker for HCC diagnosis and prognosis. Moreover, targeting SLC22A1 methylation by demethylating agents may offer a novel strategy for anticancer therapy of HCC.
Sex-differences in human liver gene expression were characterized on a genome-wide scale using a large liver sample collection, allowing for detection of small expression differences with high statistical power. 1,249 sex-biased genes were identified, 70% showing higher expression in females. Chromosomal bias was apparent, with female-biased genes enriched on chrX and male-biased genes enriched on chrY and chr19, where 11 male-biased zinc-finger KRAB-repressor domain genes are distributed in six clusters. Top biological functions and diseases significantly enriched in sex-biased genes include transcription, chromatin organization and modification, sexual reproduction, lipid metabolism and cardiovascular disease. Notably, sex-biased genes are enriched at loci associated with polygenic dyslipidemia and coronary artery disease in genome-wide association studies. Moreover, of the 8 sex-biased genes at these loci, 4 have been directly linked to monogenic disorders of lipid metabolism and show an expression profile in females (elevated expression of ABCA1, APOA5 and LDLR; reduced expression of LIPC) that is consistent with the lower female risk of coronary artery disease. Female-biased expression was also observed for CYP7A1, which is activated by drugs used to treat hypercholesterolemia. Several sex-biased drug-metabolizing enzyme genes were identified, including members of the CYP, UGT, GPX and ALDH families. Half of 879 mouse orthologs, including many genes of lipid metabolism and homeostasis, show growth hormone-regulated sex-biased expression in mouse liver, suggesting growth hormone might play a similar regulatory role in human liver. Finally, the evolutionary rate of protein coding regions for human-mouse orthologs, revealed by dN/dS ratio, is significantly higher for genes showing the same sex-bias in both species than for non-sex-biased genes. These findings establish that human hepatic sex differences are widespread and affect diverse cell metabolic processes, and may help explain sex differences in lipid profiles associated with sex differential risk of coronary artery disease.
The individual character of pharmacokinetics is of great importance in the risk assessment of new drug leads in pharmacological research. Amongst others, it is severely influenced by the properties and inter-individual variability of the enzymes and transporters of the drug detoxification system of the liver. Predicting individual drug biotransformation capacity requires quantitative and detailed models.
In this contribution we present the de novo deterministic modeling of atorvastatin biotransformation based on comprehensive published knowledge on involved metabolic and transport pathways as well as physicochemical properties. The model was evaluated on primary human hepatocytes and parameter identifiability analysis was performed under multiple experimental constraints. Dynamic simulations of atorvastatin biotransformation considering the inter-individual variability of the two major involved enzymes CYP3A4 and UGT1A3 based on quantitative protein expression data in a large human liver bank (n = 150) highlighted the variability in the individual biotransformation profiles and therefore also points to the individuality of pharmacokinetics.
A dynamic model for the biotransformation of atorvastatin has been developed using quantitative metabolite measurements in primary human hepatocytes. The model comprises kinetics for transport processes and metabolic enzymes as well as population liver expression data allowing us to assess the impact of inter-individual variability of concentrations of key proteins. Application of computational tools for parameter sensitivity analysis enabled us to considerably improve the validity of the model and to create a consistent framework for precise computer-aided simulations in toxicology.
The human drug metabolizing cytochrome P450 (CYP) 1A2, is one of the major P450 isoforms contributing by about 5–20% to the hepatic P450 pool and catalyzing oxidative biotransformation of up to 10% of clinically relevant drugs including clozapine and caffeine. CYP1A2 activity is interindividually highly variable and although twin studies have suggested a high heritability, underlying genetic factors are still unknown. Here we adopted a pathway-oriented approach using a large human liver bank (n = 150) to elucidate whether variants in candidate genes of constitutive, ligand-inducible, and pathophysiological inhibitory regulatory pathways may explain different hepatic CYP1A2 phenotypes. Samples were phenotyped for phenacetin O-deethylase activity, and the expression of CYP1A2 protein and mRNA was determined. CYP1A2 expression and function was increased in smokers and decreased in patients with inflammation and cholestasis. Of 169 SNPs in 17 candidate genes including the CYP1A locus, 136 non-redundant SNPs with minor allele frequency >5% were analyzed by univariate and multivariate methods. A total of 13 strong significant associations were identified, of which 10 SNPs in the ARNT, AhRR, HNF1α, IL1β, SRC-1, and VDR genes showed consistent changes for at least two phenotypes by univariate analysis. Multivariate linear modeling indicated that the polymorphisms and non-genetic factors together explained 42, 38, and 33% of CYP1A2 variation at activity, protein and mRNA levels, respectively. In conclusion, we identified novel trans-associations between regulatory genes and hepatic CYP1A2 function and expression, but additional genetic factors must be assumed to explain the full extent of CYP1A2 heritability.
candidate gene; cytochrome P450; CYP1A2; multivariate analysis; non-genetic factors; pharmacogenetics; pharmacogenomics; SNP
To characterize the interindividual variability and the individual CYP involved in the formation of α-hydroxy-, N-desmethyl- and N-didesmethyl-tamoxifen from tamoxifen.
Microsomes from 50 human livers were used to characterize the interindividual variability in the α-hydroxylation, N-desmethylation and N-didesmethylation of tamoxifen. Selective inhibitors and recombinant enzymes were used to identify the forms of CYP catalysing these reactions.
The rates of formation of α-hydroxy-, N-desmethyl- and N-didesmethyl-tamoxifen were highly variable, and correlated with each other (P < 0.0001). The respective ranges were 0.7–11.4, 25.7–411, and below the limit of quantification – 4.4 pmol mg−1 protein min−1. Formation of all metabolites was observed with expressed recombinant CYP3A4, inhibited by troleandomycin (65, 77 and 35%, respectively, P < 0.05) and associated with CYP3A4 expression (rs = 0.612, rs = 0.585 and rs = 0.430, P < 0.01, respectively).
Formation of α-hydroxy-, N-desmethyl- and N-didesmethyl-tamoxifen in vitro is highly variable and mediated predominantly by CYP3A4.
α-OH-tam; CYP3A4; N-didesmethyl-tam; tamoxifen
To investigate in a large panel of 50 human liver samples the contribution of CYP2C9, CYP2D6, and CYP3A4 to the overall formation of the potent antioestrogen Z-4-hydroxy-tamoxifen, and how various genotypes affect its formation from tamoxifen.
The formation of Z-4-hydroxy-tamoxifen from 10 µm tamoxifen was studied in human liver microsomes (n = 50), characterized for CYP2B6, CYP2C9, CYP2D6 and CYP3A4 expression, and CYP2B6, CYP2C9 and CYP2D6 genotype. The effect of chemical and monoclonal antibody inhibitors, and the formation in supersomes expressing recombinant CYP isoforms was also investigated. Z-4-hydroxy-tamoxifen was quantified using LC-MS analysis.
Z-4-hydroxy-tamoxifen was formed by supersomes expressing CYP2B6, CYP2C9, CYP2C19 and CYP2D6, but not CYP3A4. In agreement with these data, the mean formation of Z-4-hydroxy-tamoxifen was inhibited 49% by sulphaphenazole (P = 0.001), 38% by quinidine (P<0.05) and 13% by monoclonal antibody against CYP2B6 (MAB-2B6, P<0.05). Furthermore, Z-4-hydroxy-tamoxifen formation significantly correlated with both CYP2C9 expression (rs = 0.256, P<0.05) and CYP2D6 expression (rs = 0.309, P<0.05). Genotypes of CYP2D6, CYP2B6 and CYP2C9 had an effect on metabolite formation in such a way that samples with two nonfunctional CYP2D6, or two variant CYP2C9 or CYP2B6 alleles, showed lower enzyme activity compared with those with two functional or wild-type alleles, (5.0 vs 9.9 pmol mg−1 protein min−1, P = 0.046, 5.1 vs 9.9 pmol mg−1 protein min−1, P = 0.053, and 6.8 vs 9.4 pmol mg−1 protein min−1, P = 0.054, respectively). CYP2D6 and CYP2C9 contribute on average 45 and 46%, respectively, to the overall formation of Z-4-hydroxy-tamoxifen.
CYP2B6, CYP2C9 and CYP2D6 genotypes all affected Z-4-hydroxy-tamoxifen formation and can predict individual ability to catalyse this reaction.
CYP2B6; CYP2C9; CYP2D6; genotype; Z-4-hydroxy-tamoxifen