BACKGROUND: Prednisolone and other glucocorticoids (GCs) are potent anti-inflammatory and immunosuppressive drugs. However, prolonged use at a medium or high dose is hampered by side effects of which the metabolic side effects are most evident. Relatively little is known about their effect on gene-expression in vivo, the effect on cell subpopulations and the relation to the efficacy and side effects of GCs.AIM: To identify and compare prednisolone-induced gene signatures in CD4⁺ T lymphocytes and CD14⁺ monocytes derived from healthy volunteers and to link these signatures to underlying biological pathways involved in metabolic adverse effects.MATERIALS & METHODS: Whole-genome expression profiling was performed on CD4⁺ T lymphocytes and CD14⁺ monocytes derived from healthy volunteers treated with prednisolone. Text-mining analyses was used to link genes to pathways involved in metabolic adverse events.RESULTS: Induction of gene-expression was much stronger in CD4⁺ T lymphocytes than in CD14⁺ monocytes with respect to fold changes, but the number of truly cell-specific genes where a strong prednisolone effect in one cell type was accompanied by a total lack of prednisolone effect in the other cell type, was relatively low. Subsequently, a large set of genes was identified with a strong link to metabolic processes, for some of which the association with GCs is novel.CONCLUSION: The identified gene signatures provide new starting points for further study into GC-induced transcriptional regulation in vivo and the mechanisms underlying GC-mediated metabolic side effects.
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BACKGROUND: Glucocorticoids (GCs) control expression of a large number of genes via binding to the GC receptor (GR). Transcription may be regulated either by binding of the GR dimer to DNA regulatory elements or by protein-protein interactions of GR monomers with other transcription factors. Although the type of regulation for a number of individual target genes is known, the relative contribution of both mechanisms to the regulation of the entire transcriptional program remains elusive. To study the importance of GR dimerization in the regulation of gene expression, we performed gene expression profiling of livers of prednisolone-treated wild type (WT) and mice that have lost the ability to form GR dimers (GRdim).RESULTS: The GR target genes identified in WT mice were predominantly related to glucose metabolism, the cell cycle, apoptosis and inflammation. In GRdim mice, the level of prednisolone-induced gene expression was significantly reduced compared to WT, but not completely absent. Interestingly, for a set of genes, involved in cell cycle and apoptosis processes and strongly related to Foxo3a and p53, induction by prednisolone was completely abolished in GRdim mice. In contrast, glucose metabolism-related genes were still modestly upregulated in GRdim mice upon prednisolone treatment. Finally, we identified several novel GC-inducible genes from which Fam107a, a putative histone acetyltransferase complex interacting protein, was most strongly dependent on GR dimerization.CONCLUSIONS: This study on prednisolone-induced effects in livers of WT and GRdim mice identified a number of interesting candidate genes and pathways regulated by GR dimers and sheds new light onto the complex transcriptional regulation of liver function by GCs.
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Synthetic glucocorticoids are potent anti-inflammatory drugs but show dose-dependent metabolic side effects such as the development of insulin resistance and obesity. The precise mechanisms involved in these glucocorticoid-induced side effects, and especially the participation of adipose tissue in this are not completely understood. We used a combination of transcriptomics, antibody arrays and bioinformatics approaches to characterize prednisolone-induced alterations in gene expression and adipokine secretion, which could underlie metabolic dysfunction in 3T3-L1 adipocytes. Several pathways, including cytokine signalling, Akt signalling, and Wnt signalling were found to be regulated at multiple levels, showing that these processes are targeted by prednisolone. These results suggest that mechanisms by which prednisolone induce insulin resistance include dysregulation of wnt signalling and immune response processes. These pathways may provide interesting targets for the development of improved glucocorticoids.
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Introduction: To reduce continuously increasing costs in drug development, adverse effects of drugs need to be detected as early as possible in the process. In recent years, compound-induced gene expression profiling methodologies have been developed to assess compound toxicity, including Gene Ontology term and pathway over-representation analyses. The objective of this study was to introduce an additional approach, in which literature information is used for compound profiling to evaluate compound toxicity and mode of toxicity. Methods: Gene annotations were built by text mining in Medline abstracts for retrieval of co-publications between genes, pathology terms, biological processes and pathways. This literature information was used to generate compound-specific keyword fingerprints, representing over-represented keywords calculated in a set of regulated genes after compound administration. To see whether keyword fingerprints can be used for assessment of compound toxicity, we analyzed microarray data sets of rat liver treated with 11 hepatotoxicants. Results: Analysis of keyword fingerprints of two genotoxic carcinogens, two nongenotoxic carcinogens, two peroxisome proliferators and two randomly generated gene sets, showed that each compound produced a specific keyword fingerprint that correlated with the experimentally observed histopathological events induced by the individual compounds. By contrast, the random sets produced a flat aspecific keyword profile, indicating that the fingerprints induced by the compounds reflect biological events rather than random noise. A more detailed analysis of the keyword profiles of diethylhexylphthalate, dimethylnitrosamine and methapyrilene (MPy) showed that the differences in the keyword fingerprints of these three compounds are based upon known distinct modes of action. Visualization of MPy-linked keywords and MPy-induced genes in a literature network enabled us to construct a mode of toxicity proposal for MPy, which is in agreement with known effects of MPy in literature. Conclusion: Compound keyword fingerprinting based on information retrieved from literature is a powerful approach for compound profiling, allowing evaluation of compound toxicity and analysis of the mode of action. © 2007 Future Medicine Ltd.
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Glucocorticoids (GCs) such as prednisolone are potent immunosuppressive drugs but suffer from severe adverse effects, including the induction of insulin resistance. Therefore, development of so-called Selective Glucocorticoid Receptor Modulators (SGRM) is highly desirable. Here we describe a non-steroidal Glucocorticoid Receptor (GR)-selective compound (Org 214007-0) with a binding affinity to GR similar to that of prednisolone. Structural modelling of the GR-Org 214007-0 binding site shows disturbance of the loop between helix 11 and helix 12 of GR, confirmed by partial recruitment of the TIF2-3 peptide. Using various cell lines and primary human cells, we show here that Org 214007-0 acts as a partial GC agonist, since it repressed inflammatory genes and was less effective in induction of metabolic genes. More importantly, in vivo studies in mice indicated that Org 214007-0 retained full efficacy in acute inflammation models as well as in a chronic collagen-induced arthritis (CIA) model. Gene expression profiling of muscle tissue derived from arthritic mice showed a partial activity of Org 214007-0 at an equi-efficacious dosage of prednisolone, with an increased ratio in repression versus induction of genes. Finally, in mice Org 214007-0 did not induce elevated fasting glucose nor the shift in glucose/glycogen balance in the liver seen with an equi-efficacious dose of prednisolone. All together, our data demonstrate that Org 214007-0 is a novel SGRMs with an improved therapeutic index compared to prednisolone. This class of SGRMs can contribute to effective anti-inflammatory therapy with a lower risk for metabolic side effects.
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From PLoS website: In general, dietary antigens are tolerated by the gut associated immune system. Impairment of this so-called oral tolerance is a serious health risk. We have previously shown that activation of the ligand-dependent transcription factor aryl hydrocarbon receptor (AhR) by the environmental pollutant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) affects both oral tolerance and food allergy. In this study, we determine whether a common plant-derived, dietary AhR-ligand modulates oral tolerance as well. We therefore fed mice with indole-3-carbinole (I3C), an AhR ligand that is abundant in cruciferous plants. We show that several I3C metabolites were detectable in the serum after feeding, including the high-affinity ligand 3,3´-diindolylmethane (DIM). I3C feeding robustly induced the AhR-target gene CYP4501A1 in the intestine; I3C feeding also induced the aldh1 gene, whose product catalyzes the formation of retinoic acid (RA), an inducer of regulatory T cells. We then measured parameters indicating oral tolerance and severity of peanut-induced food allergy. In contrast to the tolerance-breaking effect of TCDD, feeding mice with chow containing 2 g/kg I3C lowered the serum anti-ovalbumin IgG1 response in an experimental oral tolerance protocol. Moreover, I3C feeding attenuated symptoms of peanut allergy. In conclusion, the dietary compound I3C can positively influence a vital immune function of the gut.
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Glucocorticoids (GCs), such as prednisolone (PRED), are widely prescribed anti-inflammatory drugs, but their use may induce glucose intolerance and diabetes. GC-induced beta cell dysfunction contributes to these diabetogenic effects through mechanisms that remain to be elucidated. In this study, we hypothesized that activation of the unfolded protein response (UPR) following endoplasmic reticulum (ER) stress could be one of the underlying mechanisms involved in GC-induced beta cell dysfunction. We report here that PRED did not affect basal insulin release but time-dependently inhibited glucose-stimulated insulin secretion in INS-1E cells. PRED treatment also decreased both PDX1 and insulin expression, leading to a marked reduction in cellular insulin content. These PRED-induced detrimental effects were found to be prevented by prior treatment with the glucocorticoid receptor (GR) antagonist RU486 and associated with activation of two of the three branches of the UPR. Indeed, PRED induced a GR-mediated activation of both ATF6 and IRE1/XBP1 pathways but was found to reduce the phosphorylation of PERK and its downstream substrate eIF2α. These modulations of ER stress pathways were accompanied by upregulation of calpain 10 and increased cleaved caspase 3, indicating that long term exposure to PRED ultimately promotes apoptosis. Taken together, our data suggest that the inhibition of insulin biosynthesis by PRED in the insulin-secreting INS-1E cells results, at least in part, from a GR-mediated impairment in ER homeostasis which may lead to apoptotic cell death.
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According to the "membrane sensor" hypothesis, the membrane's physical properties and microdomain organization play an initiating role in the heat shock response. Clinical conditions such as cancer, diabetes and neurodegenerative diseases are all coupled with specific changes in the physical state and lipid composition of cellular membranes and characterized by altered heat shock protein levels in cells suggesting that these "membrane defects" can cause suboptimal hsp-gene expression. Such observations provide a new rationale for the introduction of novel, heat shock protein modulating drug candidates. Intercalating compounds can be used to alter membrane properties and by doing so normalize dysregulated expression of heat shock proteins, resulting in a beneficial therapeutic effect for reversing the pathological impact of disease. The membrane (and lipid) interacting hydroximic acid (HA) derivatives discussed in this review physiologically restore the heat shock protein stress response, creating a new class of "membrane-lipid therapy" pharmaceuticals. The diseases that HA derivatives potentially target are diverse and include, among others, insulin resistance and diabetes, neuropathy, atrial fibrillation, and amyotrophic lateral sclerosis. At a molecular level HA derivatives are broad spectrum, multi-target compounds as they fluidize yet stabilize membranes and remodel their lipid rafts while otherwise acting as PARP inhibitors. The HA derivatives have the potential to ameliorate disparate conditions, whether of acute or chronic nature. Many of these diseases presently are either untreatable or inadequately treated with currently available pharmaceuticals. Ultimately, the HA derivatives promise to play a major role in future pharmacotherapy.
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Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiat- ing event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a standardized way to map and organize toxicological mechanistic information. As such, AOPs inform on key events underlying toxicity, thus supporting the development of New Approach Methodologies (NAMs), which aim to reduce the use of animal testing for toxicology purposes. However, the establishment of a novel AOP relies on the gathering of multiple streams of evidence and infor- mation, from available literature to knowledge databases. Often, this information is in the form of free text, also called unstructured text, which is not immediately digestible by a computer. This information is thus both tedious and increasingly time-consuming to process manually with the growing volume of data available. The advance- ment of machine learning provides alternative solutions to this challenge. To extract and organize information from relevant sources, it seems valuable to employ deep learning Natural Language Processing techniques. We review here some of the recent progress in the NLP field, and show how these techniques have already demonstrated value in the biomedical and toxicology areas. We also propose an approach to efficiently and reliably extract and combine relevant toxicological information from text. This data can be used to map underlying mechanisms that lead to toxicological effects and start building quantitative models, in particular AOPs, ultimately allowing animal-free human-based hazard and risk assessment.
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New approach methodologies predicting human cardiotoxicity are of interest to support or even replace in vivo-based drug safety testing. The present study presents an in vitro–in silico approach to predict the effect of inter-individual and inter-ethnic kinetic variations in the cardiotoxicity of R- and S-methadone in the Caucasian and the Chinese population. In vitro cardiotoxicity data, and metabolic data obtained from two approaches, using either individual human liver microsomes or recombinant cytochrome P450 enzymes (rCYPs), were integrated with physiologically based kinetic (PBK) models and Monte Carlo simulations to predict inter-individual and inter-ethnic variations in methadone-induced cardiotoxicity. Chemical specific adjustment factors were defined and used to derive dose–response curves for the sensitive individuals. Our simulations indicated that Chinese are more sensitive towards methadone-induced cardiotoxicity with Margin of Safety values being generally two-fold lower than those for Caucasians for both methadone enantiomers. Individual PBK models using microsomes and PBK models using rCYPs combined with Monte Carlo simulations predicted similar inter-individual and inter-ethnic variations in methadone-induced cardiotoxicity. The present study illustrates how inter-individual and inter-ethnic variations in cardiotoxicity can be predicted by combining in vitro toxicity and metabolic data, PBK modelling and Monte Carlo simulations. The novel methodology can be used to enhance cardiac safety evaluations and risk assessment of chemicals.
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