montelukast and Chemical-and-Drug-Induced-Liver-Injury

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

Topics: Acetates; Anaphylaxis; Chemical and Drug Induced Liver Injury; Chromones; Cyclopropanes; Drug Interactions; Enzyme Inhibitors; Hematologic Diseases; Humans; Indoles; Leukotriene Antagonists; Lipoxygenase Inhibitors; Lung Diseases, Interstitial; Membrane Proteins; Phenylcarbamates; Quinolines; Receptors, Leukotriene; Sulfides; Sulfonamides; Tosyl Compounds

Topics: Acetates; Adult; Anti-Asthmatic Agents; Chemical and Drug Induced Liver Injury; Cyclopropanes; Humans; Leukotriene Antagonists; Liver; Liver Function Tests; Male; Quinolines; Sulfides

Montelukast (MNK) has prominent anti-inflammatory and antioxidant activities. It can protect the liver in different hepatotoxic models in animals. Simvastatin (SMV) is one of commonly used lipid lowering drugs for treatment of dyslipidemia in order to reduce cardiovascular disease. It has severe side effects such as myopathy and hepatotoxicity. The aim of the present study is to investigate the possible effect of MNK on SMV-induced myopathy and hepatotoxicity. Four groups of male rats: control group which received saline via stomach tube, MNK treated group (received 10 mg/kg/day MNK via stomach tube), SMV treated group (received 30 mg/kg/day SMV via stomach tube), and MNK + SMV (combination) group which received both MNK and SMV. All animals were treated for 14 days before obtaining blood and tissue samples. SMV has both hepatotoxic effects and myopathy. SMV caused a significant increase in myoglobin, creatinine kinase, ALT, AST, ALP, and bilirubin but, it decreased total proteins, globulin and albumin levels. Co-treatment of SMV and MNK increased the antioxidant activity significantly. MNK modifies partially the myopathic changes and hepatotoxic effect of SMV. Co-administration of MNK and SMV decreased their toxic potentials on the liver, skeletal muscles, and kidney. They have antioxidant activities when given together that produce muscle and hepatic protective effects.

Topics: Acetates; Albumins; Animals; Bilirubin; Chemical and Drug Induced Liver Injury; Creatine Kinase; Cyclopropanes; Drug Interactions; Globulins; Liver Function Tests; Male; Muscular Diseases; Myoglobin; Quinolines; Rats; Simvastatin; Sulfides

This study aims to investigate the acute protective effect of montelukast sodium in hepatic injury secondary to acetaminophen (APAP) intoxication. This study used 60 rats. The rats were grouped into 6 groups. The control group was administered oral distilled water 10 ml/kg, the APAP group oral APAP 1 g/kg, the montelukast sodium (MK) group oral MK 30 mg/kg, the acetaminophen+N-acetylcysteine (APAP+NAC) group oral APAP 1 g/kg, followed by a single dose of intraperitoneal NAC 1.5 g/kg three hours later, the acetaminophen+montelukast sodium (APAP+MK) group oral APAP 1 g/kg, followed by oral MK 30 mg/kg 3 h later, the acetaminophen+N-acetylcysteine+montelukast sodium (APAP+NAC+MK) group oral APAP 1 g/kg, followed by a single intraperitoneal NAC 1.5 g/kg plus oral MK 30 mg/kg 3 h later. Blood and liver tissue samples were taken 24h after drug administration. Aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), and total bilirubin were studied from the blood samples. Liver tissue samples were used for histopathological examination. Compared with the control group, serum AST and ALT activities were higher in the APAP and APAP+NAC groups. APAP+NAC, APAP+MK, and APAP+NAC+MK groups had reduced serum ALT and AST activities than the group administered APAP alone. APAP+MK and APAP+NAC+MK groups had a lower serum ALP activity than the control group. Histopathologically, there was a difference between the group administered APAP alone and the APAP+MK and APAP+NAC+MK groups. MK is as protective as NAC in liver tissue in APAP intoxication in rats.

Topics: Acetaminophen; Acetates; Acetylcysteine; Analgesics, Non-Narcotic; Animals; Chemical and Drug Induced Liver Injury; Cyclopropanes; Cytochrome P-450 CYP1A2 Inducers; Disease Models, Animal; Free Radical Scavengers; Male; Quinolines; Rats; Rats, Wistar; Sulfides

Many carboxylic acid-containing drugs are associated with idiosyncratic drug toxicity (IDT), which may be caused by reactive acyl glucuronide metabolites. The rate of acyl migration has been earlier suggested as a predictor of acyl glucuronide reactivity. Additionally, acyl Coenzyme A (CoA) conjugates are known to be reactive. Here, 13 drugs with a carboxylic acid moiety were incubated with human liver microsomes to produce acyl glucuronide conjugates for the determination of acyl glucuronide half-lives by acyl migration and with HepaRG cells to monitor the formation of acyl CoA conjugates, their further conjugate metabolites, and trans-acylation products with glutathione. Additionally, in vitro cytotoxicity and mitochondrial toxicity experiments were performed with HepaRG cells to compare the predictability of toxicity. Clearly, longer acyl glucuronide half-lives were observed for safe drugs compared to drugs that can cause IDT. Correlation between half-lives and toxicity classification increased when "relative half-lives," taking into account the formation of isomeric AG-forms due to acyl migration and eliminating the effect of hydrolysis, were used instead of plain disappearance of the initial 1-O-β-AG-form. Correlation was improved further when a daily dose of the drug was taken into account. CoA and related conjugates were detected primarily for the drugs that have the capability to cause IDT, although some exceptions to this were observed. Cytotoxicity and mitochondrial toxicity did not correlate to drug safety. On the basis of the results, the short relative half-life of the acyl glucuronide (high acyl migration rate), high daily dose and detection of acyl CoA conjugates, or further metabolites derived from acyl CoA together seem to indicate that carboxylic acid-containing drugs have a higher probability to cause drug-induced liver injury (DILI).

Topics: Acetates; Acyl Coenzyme A; Acylation; Carboxylic Acids; Chemical and Drug Induced Liver Injury; Chromatography, Liquid; Cyclopropanes; Gemfibrozil; Humans; Mass Spectrometry; Microsomes, Liver; Molecular Structure; Quinolines; Sulfides; Tolmetin

Drug-induced liver injury is the most common cause of market withdrawal of pharmaceuticals, and thus, there is considerable need for better prediction models for DILI early in drug discovery. We present a study involving 223 marketed drugs (51% associated with clinical hepatotoxicity; 49% non-hepatotoxic) to assess the concordance of in vitro bioactivation data with clinical hepatotoxicity and have used these data to develop a decision tree to help reduce late-stage candidate attrition. Data to assess P450 metabolism-dependent inhibition (MDI) for all common drug-metabolizing P450 enzymes were generated for 179 of these compounds, GSH adduct data generated for 190 compounds, covalent binding data obtained for 53 compounds, and clinical dose data obtained for all compounds. Individual data for all 223 compounds are presented here and interrogated to determine what level of an alert to consider termination of a compound. The analysis showed that 76% of drugs with a daily dose of <100 mg were non-hepatotoxic (p < 0.0001). Drugs with a daily dose of ≥100 mg or with GSH adduct formation, marked P450 MDI, or covalent binding ≥200 pmol eq/mg protein tended to be hepatotoxic (∼ 65% in each case). Combining dose with each bioactivation assay increased this association significantly (80-100%, p < 0.0001). These analyses were then used to develop the decision tree and the tree tested using 196 of the compounds with sufficient data (49% hepatotoxic; 51% non-hepatotoxic). The results of these outcome analyses demonstrated the utility of the tree in selectively terminating hepatotoxic compounds early; 45% of the hepatotoxic compounds evaluated using the tree were recommended for termination before candidate selection, whereas only 10% of the non-hepatotoxic compounds were recommended for termination. An independent set of 10 GSK compounds with known clinical hepatotoxicity status were also assessed using the tree, with similar results.

Topics: Chemical and Drug Induced Liver Injury; Cytochrome P-450 Enzyme Inhibitors; Cytochrome P-450 Enzyme System; Decision Trees; Drug Evaluation, Preclinical; Drug-Related Side Effects and Adverse Reactions; Glutathione; Humans; Liver; Pharmaceutical Preparations; Protein Binding

The effects of montelukast against methotrexate-induced liver damage were investigated. 35 Wistar albino female rats were divided into 5 groups as follows: group I: control; group II: montelukast (ML); group III: methotrexate (Mtx); group IV: montelukast treatment after methotrexate application (Mtx + ML); group V: montelukast treatment before methotrexate application (ML + Mtx). At the end of the experiment, the liver tissues of rats were removed. Malondialdehyde (MDA), myeloperoxidase (MPO), and reduced glutathione levels were determined from liver tissues. In addition, the liver tissues were examined histologically. MDA and MPO levels of Mtx group were significantly increased when compared to control group. In Mtx + ML group, these parameters were decreased as compared to Mtx group. Mtx injection exhibited major histological alterations such as eosinophilic staining and swelling of hepatocytes. The glycogen storage in hepatocytes was observed as decreased by periodic acid schiff staining in Mtx group as compared to controls. ML treatment did not completely ameliorate the lesions and milder degenerative alterations as loss of the glycogen content was still present. It was showed that montelukast treatment after methotrexate application could reduce methotrexate-induced experimental liver damage.

Topics: Acetates; Animals; Chemical and Drug Induced Liver Injury; Cyclopropanes; Drug Evaluation, Preclinical; Female; Glutathione; Glycogen; Hepatocytes; Liver; Malondialdehyde; Methotrexate; Oxidative Stress; Periodic Acid-Schiff Reaction; Peroxidase; Quinolines; Rats; Rats, Wistar; Sulfides

Drug-induced liver injury (DILI) is a leading cause of drugs failing during clinical trials and being withdrawn from the market. Comparative analysis of drugs based on their DILI potential is an effective approach to discover key DILI mechanisms and risk factors. However, assessing the DILI potential of a drug is a challenge with no existing consensus methods. We proposed a systematic classification scheme using FDA-approved drug labeling to assess the DILI potential of drugs, which yielded a benchmark dataset with 287 drugs representing a wide range of therapeutic categories and daily dosage amounts. The method is transparent and reproducible with a potential to serve as a common practice to study the DILI of marketed drugs for supporting drug discovery and biomarker development.

Topics: Animals; Benchmarking; Biomarkers, Pharmacological; Chemical and Drug Induced Liver Injury; Drug Design; Drug Labeling; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmaceutical Preparations; Reproducibility of Results; United States; United States Food and Drug Administration

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 is a major issue of concern and has led to the withdrawal of a significant number of marketed drugs. An understanding of structure-activity relationships (SARs) of chemicals can make a significant contribution to the identification of potential toxic effects early in the drug development process and aid in avoiding such problems. This process can be supported by the use of existing toxicity data and mechanistic understanding of the biological processes for related compounds. In the published literature, this information is often spread across diverse sources and can be varied and unstructured in quality and content. The current work has explored whether it is feasible to collect and use such data for the development of new SARs for the hepatotoxicity endpoint and expand upon the limited information currently available in this area. Reviews of hepatotoxicity data were used to build a structure-searchable database, which was analyzed to identify chemical classes associated with an adverse effect on the liver. Searches of the published literature were then undertaken to identify additional supporting evidence, and the resulting information was incorporated into the database. This collated information was evaluated and used to determine the scope of the SARs for each class identified. Data for over 1266 chemicals were collected, and SARs for 38 classes were developed. The SARs have been implemented as structural alerts using Derek for Windows (DfW), a knowledge-based expert system, to allow clearly supported and transparent predictions. An evaluation exercise performed using a customized DfW version 10 knowledge base demonstrated an overall concordance of 56% and specificity and sensitivity values of 73% and 46%, respectively. The approach taken demonstrates that SARs for complex endpoints can be derived from the published data for use in the in silico toxicity assessment of new compounds.

Topics: Chemical and Drug Induced Liver Injury; Databases, Factual; Humans; Structure-Activity Relationship; Tetracyclines; Thiophenes

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

This study investigates the effects of montelukast sodium (MK) (CysLTLT1 receptor antagonist) on CCl(4)induced hepatopathy on rat.. We worked on 4 groups of 10 Wistar male rats each. The groups received as follows: group I (control group) - saline, group II - MK 5mg/kg/day i.p. for 5 days, group III - MK 5mg/kg/day i.p., 1 day prior to and 4 days concomitantly with CCl(4) p.o., 0.3ml/Kg/day and group IV - CCl(4), p.o., 0.3ml/Kg/day for 4 days. One day after the last administration, samples of blood were taken and alanine aminotransferase (ALT), total bilirubin (TB), direct bilirubin (DB), malondialdehyde (MDA), catalase (CAT) as well as total antioxidant capacity (TAC) were determined. The histopathological exam was performed. We also determined superoxide dismutase (SOD), MDA, CAT and GSH in liver homogenate.. Compared to group IV, group III exhibited statistically significant lower levels of ALT (318+/-15.75 versus 203.14+/-10.28 UI, p<0.0001), TB (3.16+/-0.30 versus 1.99+/-0.08mg/dl, p<0.0001), MDA in blood and in liver homogenate (4.98+/-1.71 versus 2.15+/-1.18nmol/ml, p=0.0004) and higher levels of SOD and CAT. Histopathologically, group IV presented important macro- and micro-vesicular hepatic steatosis and group III preserved lobular histoarchitecture and had less severe cellular lesions.. MK exhibits a partial hepatoprotective effect on rats treated with CCl(4).

Topics: Acetates; Alanine Transaminase; Animals; Bilirubin; Carbon Tetrachloride; Catalase; Chemical and Drug Induced Liver Injury; Cyclopropanes; Liver; Liver Diseases; Male; Malondialdehyde; Quinolines; Rats; Rats, Wistar; Sulfides; Superoxide Dismutase

High aminotransferases and prolonged prothrombin time on entering our liver unit were revealing parenchymal collapse for this 45-year-old obese woman; treatment failure led her to death. Autoimmunity, paracetamol use, alcoholism, and Wilson's disease were all excluded as causes. Because of chronic asthma, she had been receiving a leukotriene receptor antagonist (montelukast) for 5 years before the current presentation; 1 week before onset she had had 1 week of treatment with two dietary supplements for weight control; one of these included Garcinia Cambogia, a possible cause of two recent cases of hepatitis in the USA; in addition, both formulas contained a citrus derivative that interferes cytochrome functions. We speculate on a causal relationship between the assumption of the additives and the fatal hepatitis and envisage a synergy between the additives and montelukast, which per se has well been studied as a hepatotoxic drug. Despite the speculative nature of this presentation, we believe the warning may serve to focus attention on the uncontrolled escalation of food additives going on in these days.

Topics: Acetates; Anti-Asthmatic Agents; Asthma; Chemical and Drug Induced Liver Injury; Cyclopropanes; Dietary Supplements; Drug Interactions; Fatal Outcome; Female; Humans; Liver Failure, Acute; Middle Aged; Quinolines; Sulfides

Topics: Acetates; Adult; Anti-Asthmatic Agents; Asthma; Chemical and Drug Induced Liver Injury; Cyclopropanes; Female; Humans; Leukotriene Antagonists; Quinolines; Sulfides

Topics: Acetates; Acute Disease; Adult; Anti-Asthmatic Agents; Chemical and Drug Induced Liver Injury; Cyclopropanes; Female; Follow-Up Studies; Humans; Leukotriene Antagonists; Quinolines; Sulfides; Time Factors

Topics: Acetates; Acute Disease; Anti-Asthmatic Agents; Chemical and Drug Induced Liver Injury; Cyclopropanes; Female; Humans; Middle Aged; Quinolines; Sulfides

Topics: Acetates; Acute Disease; Aged; Anti-Asthmatic Agents; Asthma; Chemical and Drug Induced Liver Injury; Cyclopropanes; Humans; Male; Quinolines; Sulfides

Topics: Acetates; Aged; Albuterol; Anti-Asthmatic Agents; Asthma, Exercise-Induced; Bronchodilator Agents; Chemical and Drug Induced Liver Injury; Cyclopropanes; Female; Humans; Indoles; Leukotriene Antagonists; Phenylcarbamates; Quinolines; Salmeterol Xinafoate; Sulfides; Sulfonamides; Tosyl Compounds