mobic and Chemical-and-Drug-Induced-Liver-Injury

Topics: Chemical and Drug Induced Liver Injury; Databases, Factual; Drug Labeling; Humans; Pharmaceutical Preparations; Risk

Meloxicam is a thiazole-containing NSAID that was approved for marketing with favorable clinical outcomes despite being structurally similar to the hepatotoxic sudoxicam. Introduction of a single methyl group on the thiazole results in an overall lower toxic risk, yet the group's impact on P450 isozyme bioactivation is unclear. Through analytical methods, we used inhibitor phenotyping and recombinant P450s to identify contributing P450s, and then measured steady-state kinetics for bioactivation of sudoxicam and meloxicam by the recombinant P450s to determine relative efficiencies. Experiments showed that CYP2C8, 2C19, and 3A4 catalyze sudoxicam bioactivation, and CYP1A2 catalyzes meloxicam bioactivation, indicating that the methyl group not only impacts enzyme affinity for the drugs, but also alters which isozymes catalyze the metabolic pathways. Scaling of relative P450 efficiencies based on average liver concentration revealed that CYP2C8 dominates the sudoxicam bioactivation pathway and CYP2C9 dominates meloxicam detoxification. Dominant P450s were applied for an informatics assessment of electronic health records to identify potential correlations between meloxicam drug-drug interactions and drug-induced liver injury. Overall, our findings provide a cautionary tale on assumed impacts of even simple structural modifications on drug bioactivation while also revealing specific targets for clinical investigations of predictive factors that determine meloxicam-induced idiosyncratic liver injury.

Topics: Activation, Metabolic; Anti-Inflammatory Agents, Non-Steroidal; Chemical and Drug Induced Liver Injury; Cytochrome P-450 CYP1A2; Cytochrome P-450 CYP2C8; Cytochrome P-450 CYP2C9; Data Mining; Deep Learning; Drug Interactions; Electronic Health Records; Female; Humans; Inactivation, Metabolic; Kinetics; Male; Meloxicam; Microsomes, Liver; Middle Aged; Substrate Specificity; Thiazines

Thiazoles are biologically active aromatic heterocyclic rings occurring frequently in natural products and drugs. These molecules undergo typically harmless elimination; however, a hepatotoxic response can occur due to multistep bioactivation of the thiazole to generate a reactive thioamide. A basis for those differences in outcomes remains unknown. A textbook example is the high hepatotoxicity observed for sudoxicam in contrast to the relative safe use and marketability of meloxicam, which differs in structure from sudoxicam by the addition of a single methyl group. Both drugs undergo bioactivation, but meloxicam exhibits an additional detoxification pathway due to hydroxylation of the methyl group. We hypothesized that thiazole bioactivation efficiency is similar between sudoxicam and meloxicam due to the methyl group being a weak electron donator, and thus, the relevance of bioactivation depends on the competing detoxification pathway. For a rapid analysis, we modeled epoxidation of sudoxicam derivatives to investigate the impact of substituents on thiazole bioactivation. As expected, electron donating groups increased the likelihood for epoxidation with a minimal effect for the methyl group, but model predictions did not extrapolate well among all types of substituents. Through analytical methods, we measured steady-state kinetics for metabolic bioactivation of sudoxicam and meloxicam by human liver microsomes. Sudoxicam bioactivation was 6-fold more efficient than that for meloxicam, yet meloxicam showed a 6-fold higher efficiency of detoxification than bioactivation. Overall, sudoxicam bioactivation was 15-fold more likely than meloxicam considering all metabolic clearance pathways. Kinetic differences likely arise from different enzymes catalyzing respective metabolic pathways based on phenotyping studies. Rather than simply providing an alternative detoxification pathway, the meloxicam methyl group suppressed the bioactivation reaction. These findings indicate the impact of thiazole substituents on bioactivation is more complex than previously thought and likely contributes to the unpredictability of their toxic potential.

Topics: Activation, Metabolic; Biotransformation; Chemical and Drug Induced Liver Injury; Electrons; Epoxy Compounds; Humans; Hydroxylation; In Vitro Techniques; Kinetics; Meloxicam; Metabolic Networks and Pathways; Microsomes, Liver; Thiazines; Thiazoles

Nonsteroidal anti-inflammatory (NSAI) drugs are the most commonly used group of drugs today. Increase in the use of standard NSAI for treating pain and inflammation was restricted by the fact that these drugs were proven to possibly cause gastrointestinal and renal toxicity. Meloxicam is a NSAI that has anti-inflammatory, analgesic, and antipyretic effects. This study aims to investigate the effects of meloxicam on stomach, kidney, and liver of rats under light microscopy level. Based on the light microscopic observations, mononuclear cell infiltration and pseudolobular formation was established in liver samples of animals in the experimental group. Metaplasia in surface and glandular epithelia and atrophy were observed in stomach samples. Glomerular stasis-related hypertrophy and focal interstitial nephritis were found in kidneys. It was concluded in this study that meloxicam might cause hepatotoxicity, nephrotoxicity, and gastric metaplasia in rats at a used dose and duration.

Topics: Animals; Anti-Inflammatory Agents, Non-Steroidal; Chemical and Drug Induced Liver Injury; Cyclooxygenase 2; Disease Models, Animal; Dose-Response Relationship, Drug; Inflammation; Kidney; Kidney Diseases; Liver; Meloxicam; Metaplasia; Pain; Rats; Rats, Sprague-Dawley; Stomach; Stomach Diseases; Thiazines; Thiazoles; Toxicity Tests

This study was aimed at investigating the antifibrotic effect of meloxicam in CCl4-induced liver fibrosis and elucidating its underlying mechanism. Forty male rats were equally randomized for 8-week treatment with corn oil (negative control), CCl4 (to induce liver fibrosis), and/or meloxicam. Meloxicam effectively ameliorated the CCl4-induced alterations in liver histology, liver weight to body weight ratio, liver functions, and serum markers for liver fibrosis (hyaluronic acid, laminin, and PCIII). Meloxicam significantly abrogated CCl4-induced elevation of messenger RNA (mRNA) expressions for collagen I and alpha smooth muscle actin (α-SMA) and hepatic contents of hydroxyproline, transforming growth factor beta (TGF-β), and tissue inhibitor of matrix metalloproteases (TIMP-1). Meloxicam mitigated CCl4-induced elevation in hepatic levels of nuclear factor kappa B (NF-κB), tumor necrosis factor alpha (TNF-α), total nitric oxide (NO), interleukin-l beta (IL 1β), and prostaglandin E2 (PGE2). Meloxicam modulated CCl4-induced disturbance of liver cytochrome P450 subfamily 2E1 (CYP2E1) and glutathione-S-transferase (GST). The attenuation of meloxicam to liver fibrosis was associated with suppression of oxidative stress via reduction of lipid peroxides along with induction of reduced glutathione content and enhancement of superoxide dismutase, glutathione peroxidase, and catalase activities. This study provides an evidence for antifibrotic effect of meloxicam against CCl4-induced liver fibrosis in rat. The antifibrotic mechanism of meloxicam could be through decreasing NF-κB level and subsequent proinflammatory cytokine production (TNF-α, NO, IL-1 beta, and PGE2) and, hence, collagen deposition through inhibition of TIMP-1 and TGF-β. Abrogation of oxidative stress and modulation of liver-metabolizing enzymes (CYP2E1 and GST) were also involved.

Topics: Animals; Anti-Inflammatory Agents; Antioxidants; Biomarkers; Carbon Tetrachloride; Chemical and Drug Induced Liver Injury; Cytokines; Cytoprotection; Gene Expression Regulation; Inflammation Mediators; Lipid Peroxidation; Liver; Liver Cirrhosis, Experimental; Male; Meloxicam; NF-kappa B; Oxidative Stress; Rats, Sprague-Dawley; Signal Transduction; Thiazines; Thiazoles

We investigated whether the concomitant use of meloxicam and methotrexate might induce kidney and liver damages in patients with rheumatoid arthritis (RA). We enrolled 101 RA patients with normal kidney and liver functions taking meloxicam and methotrexate concomitantly for more than 6 months. Blood and urine tests were performed. Estimated glomerular filtration rate (eGFR) and liver stiffness measurement (LSM) were used for evaluating silent kidney and liver damages. Ultrasonography was also performed to exclude structural abnormalities. We adopted 90 mL/min/1.73 mm(2) and 5.3 kPa as the cutoff for an abnormal eGFR and LSM. The mean age (85 women) was 51.9 years. The mean eGFR was 97.0 mL/min/1.73 m(2) and the mean LSM was 4.7 kPa. The mean weekly dose of methotrexate was 13.4 mg. The mean weekly dose of methotrexate did not correlate with eGFR or LSM. Neither the cumulative dose of meloxicam or methotrexate nor the mean weekly dose of methotrexate showed the significant odds ratio or relative risk for abnormal eGFR and LSM values. The use of higher-dose MTX, above 15 mg per week, with meloxicam did not significantly increase the risk for abnormal LSM and eGFR (RR = 2.042, p = 0.185; RR = 0.473, p = 0.218). The concomitant use of meloxicam and MTX did not clearly increase the risk of silent kidney or liver damage in RA patients with normal laboratory results taking MTX and meloxicam concurrently for over 6 months.

Topics: Acute Kidney Injury; Adult; Anti-Inflammatory Agents, Non-Steroidal; Antirheumatic Agents; Arthritis, Rheumatoid; Asymptomatic Diseases; Chemical and Drug Induced Liver Injury; Cohort Studies; Drug Therapy, Combination; Elasticity Imaging Techniques; Female; Humans; Liver; Male; Meloxicam; Methotrexate; Middle Aged; Odds Ratio; Prospective Studies; Thiazines; Thiazoles

The bile salt export pump (BSEP) is expressed at the canalicular domain of hepatocytes, where it serves as the primary route of elimination for monovalent bile acids (BAs) into the bile canaliculi. The most compelling evidence linking dysfunction in BA transport with liver injury in humans is found with carriers of mutations that render BSEP nonfunctional. Based on mounting evidence, there appears to be a strong association between drug-induced BSEP interference and liver injury in humans; however, causality has not been established. For this reason, drug-induced BSEP interference is best considered a susceptibility factor for liver injury as other host- or drug-related properties may contribute to the development of hepatotoxicity. To better understand the association between BSEP interference and liver injury in humans, over 600 marketed or withdrawn drugs were evaluated in BSEP expressing membrane vesicles. The example of a compound that failed during phase 1 human trials is also described, AMG 009. AMG 009 showed evidence of liver injury in humans that was not predicted by preclinical safety studies, and BSEP inhibition was implicated. For 109 of the drugs with some effect on in vitro BSEP function, clinical use, associations with hepatotoxicity, pharmacokinetic data, and other information were annotated. A steady state concentration (C(ss)) for each of these annotated drugs was estimated, and a ratio between this value and measured IC₅₀ potency values were calculated in an attempt to relate exposure to in vitro potencies. When factoring for exposure, 95% of the annotated compounds with a C(ss)/BSEP IC₅₀ ratio ≥ 0.1 were associated with some form of liver injury. We then investigated the relationship between clinical evidence of liver injury and effects to multidrug resistance-associated proteins (MRPs) believed to play a role in BA homeostasis. The effect of 600+ drugs on MRP2, MRP3, and MRP4 function was also evaluated in membrane vesicle assays. Drugs with a C(ss)/BSEP IC₅₀ ratio ≥ 0.1 and a C(ss)/MRP IC₅₀ ratio ≥ 0.1 had almost a 100% correlation with some evidence of liver injury in humans. These data suggest that integration of exposure data, and knowledge of an effect to not only BSEP but also one or more of the MRPs, is a useful tool for informing the potential for liver injury due to altered BA transport.

Topics: Animals; ATP Binding Cassette Transporter, Subfamily B; ATP Binding Cassette Transporter, Subfamily B, Member 11; ATP-Binding Cassette Transporters; Biological Transport; Chemical and Drug Induced Liver Injury; Cluster Analysis; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Male; Multidrug Resistance-Associated Proteins; Pharmacokinetics; Rats; Rats, Sprague-Dawley; Recombinant Proteins; Risk Assessment; Risk Factors; Toxicity Tests

The current study aimed at investigating the potential hepatoprotective property and mechanism of meloxicam (MEL) against carbon tetrachloride (CCl(4))-induced hepatocellular damage in rats. Subcutaneous administration of CCl(4) (2 mL/kg, twice/week for 8 weeks) induced hepatocellular damage substantiated by hematoxylin and eosin staining and significant elevation in serum aspartate transaminase, alanine transaminase, and total bilirubin. In addition, CCL(4) treatment led to elevation in liver contents of lipid peroxidation marker (malondialdehyde), prostaglandin E2, active caspase 3, and Terminal deoxynucleotidyl transferase dUTP nick end labeling-positive cells and reduction in the activities of superoxide dismutase, catalase, glutathione-S-transferase, and reduced glutathione in the liver tissue. Prior oral treatment with MEL (5 mg/kg, twice/week) retained the normal liver histology and significantly restored all of these parameters close to normal values. These results demonstrated the hepatoprotective utility of MEL against the CCl(4)-induced liver injury which might ascribe to its antioxidant, free radical scavenging, antiapoptotic and anti-inflammatory effects.

Topics: Animals; Anti-Inflammatory Agents, Non-Steroidal; Apoptosis; Carbon Tetrachloride; Caspase 3; Chemical and Drug Induced Liver Injury; Cyclooxygenase 2 Inhibitors; Dinoprostone; Glutathione; Male; Malondialdehyde; Meloxicam; Oxidative Stress; Protective Agents; Rats; Rats, Sprague-Dawley; Thiazines; Thiazoles

Drug-induced liver injury (DILI) is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. We then developed in silico predictive models for each of these 13 side effects, which were further combined to construct a DILI prediction system (DILIps). The DILIps yielded 60-70% prediction accuracy for three independent validation sets. To enhance the confidence for identification of drugs that cause severe DILI in humans, the "Rule of Three" was developed in DILIps by using a consensus strategy based on 13 models. This gave high positive predictive value (91%) when applied to an external dataset containing 206 drugs from three independent literature datasets. Using the DILIps, we screened all the drugs in DrugBank and investigated their DILI potential in terms of protein targets and therapeutic categories through network modeling. We demonstrated that two therapeutic categories, anti-infectives for systemic use and musculoskeletal system drugs, were enriched for DILI, which is consistent with current knowledge. We also identified protein targets and pathways that are related to drugs that cause DILI by using pathway analysis and co-occurrence text mining. While marketed drugs were the focus of this study, the DILIps has a potential as an evaluation tool to screen and prioritize new drug candidates or chemicals, such as environmental chemicals, to avoid those that might cause liver toxicity. We expect that the methodology can be also applied to other drug safety endpoints, such as renal or cardiovascular toxicity.

Topics: Animals; Anti-Infective Agents; Anti-Inflammatory Agents; Chemical and Drug Induced Liver Injury; Databases, Factual; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Models, Biological; Predictive Value of Tests

Drug-induced liver injury is one of the main causes of drug attrition. The ability to predict the liver effects of drug candidates from their chemical structures is critical to help guide experimental drug discovery projects toward safer medicines. In this study, we have compiled a data set of 951 compounds reported to produce a wide range of effects in the liver in different species, comprising humans, rodents, and nonrodents. The liver effects for this data set were obtained as assertional metadata, generated from MEDLINE abstracts using a unique combination of lexical and linguistic methods and ontological rules. We have analyzed this data set using conventional cheminformatics approaches and addressed several questions pertaining to cross-species concordance of liver effects, chemical determinants of liver effects in humans, and the prediction of whether a given compound is likely to cause a liver effect in humans. We found that the concordance of liver effects was relatively low (ca. 39-44%) between different species, raising the possibility that species specificity could depend on specific features of chemical structure. Compounds were clustered by their chemical similarity, and similar compounds were examined for the expected similarity of their species-dependent liver effect profiles. In most cases, similar profiles were observed for members of the same cluster, but some compounds appeared as outliers. The outliers were the subject of focused assertion regeneration from MEDLINE as well as other data sources. In some cases, additional biological assertions were identified, which were in line with expectations based on compounds' chemical similarities. The assertions were further converted to binary annotations of underlying chemicals (i.e., liver effect vs no liver effect), and binary quantitative structure-activity relationship (QSAR) models were generated to predict whether a compound would be expected to produce liver effects in humans. Despite the apparent heterogeneity of data, models have shown good predictive power assessed by external 5-fold cross-validation procedures. The external predictive power of binary QSAR models was further confirmed by their application to compounds that were retrieved or studied after the model was developed. To the best of our knowledge, this is the first study for chemical toxicity prediction that applied QSAR modeling and other cheminformatics techniques to observational data generated by the means of automate

Topics: Animals; Chemical and Drug Induced Liver Injury; Cluster Analysis; Databases, Factual; Humans; MEDLINE; Mice; Models, Chemical; Molecular Conformation; Quantitative Structure-Activity Relationship

Drug-induced liver injury (DILI) is one of the most important reasons for drug development failure at both preapproval and postapproval stages. There has been increased interest in developing predictive in vivo, in vitro, and in silico models to identify compounds that cause idiosyncratic hepatotoxicity. In the current study, we applied machine learning, a Bayesian modeling method with extended connectivity fingerprints and other interpretable descriptors. The model that was developed and internally validated (using a training set of 295 compounds) was then applied to a large test set relative to the training set (237 compounds) for external validation. The resulting concordance of 60%, sensitivity of 56%, and specificity of 67% were comparable to results for internal validation. The Bayesian model with extended connectivity functional class fingerprints of maximum diameter 6 (ECFC_6) and interpretable descriptors suggested several substructures that are chemically reactive and may also be important for DILI-causing compounds, e.g., ketones, diols, and α-methyl styrene type structures. Using Smiles Arbitrary Target Specification (SMARTS) filters published by several pharmaceutical companies, we evaluated whether such reactive substructures could be readily detected by any of the published filters. It was apparent that the most stringent filters used in this study, such as the Abbott alerts, which captures thiol traps and other compounds, may be of use in identifying DILI-causing compounds (sensitivity 67%). A significant outcome of the present study is that we provide predictions for many compounds that cause DILI by using the knowledge we have available from previous studies. These computational models may represent cost-effective selection criteria before in vitro or in vivo experimental studies.

Topics: Bayes Theorem; Chemical and Drug Induced Liver Injury; Humans; Ligands

Topics: Actin Cytoskeleton; Alanine Transaminase; Anti-Inflammatory Agents; Anti-Inflammatory Agents, Non-Steroidal; Aspartate Aminotransferases; Azathioprine; Back Pain; Bilirubin; Chemical and Drug Induced Liver Injury; Drug Therapy, Combination; Hepatitis, Autoimmune; Humans; Immunoglobulin G; Immunosuppressive Agents; Male; Meloxicam; Middle Aged; Prednisone; Thiazines; Thiazoles

A 4-year-old female Siberian Husky was diagnosed with pyogranulomatous steatitis at the site of a recurrence of left anal sac rupture (day 1). Carprofen and orbifloxacin were given for 13 days without improvement. A single dose of meloxicam was administered prior to surgical resection of the anal sac, and based on elevated liver enzyme activity, liver supportive therapy was initiated. The dog received carprofen and orbifloxacin orally on the evening of day 14. The dog became anorectic the following morning, and began vomiting. Despite supportive therapy, the dog was unresponsive to treatment and died on day 16. Postmortem examination revealed severe vacuolar change and acute necrosis of hepatocytes consistent with carprofen and meloxicam induced-toxicosis.

Topics: Animals; Anti-Inflammatory Agents, Non-Steroidal; Carbazoles; Chemical and Drug Induced Liver Injury; Dog Diseases; Dogs; Fatal Outcome; Female; Liver; Meloxicam; Steatitis; Thiazines; Thiazoles