ramipril and Chemical-and-Drug-Induced-Liver-Injury

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

Ramipril, an inhibitor of the angiotensin-converting enzyme (ACEI), is a drug commonly used in the therapy of hypertension. ACEI-induced hepatotoxicity is rare, and most of the reported cases are associated with captopril. Here, we present the first case of ramipril-induced liver injury proven by positive rechallenge and a review of the literature including the data from the US Food and Drug Administration adverse event reporting system (FAERS).. Patient data were collected in the Berlin Case-Control Surveillance Study for adverse drug reactions. PubMed research on ACEI-induced hepatotoxicity included all ACEIs except captopril; analysis of the FAERS database focused on ramipril-induced hepatotoxicity in the period 2009-2011.. A 40-year-old male patient presented with acute onset jaundice and highly (>20-fold increase of alanine aminotranferase (ALT)) elevated liver enzymes (LEs). Viral or autoimmune hepatitis and biliary etiology were ruled out. Withdrawal of several medications including ramipril resulted in an immediate decrease in LEs, whereas a subsequent re-exposure with ramipril resulted in a striking increase in LEs (>35-fold increase of ALT). After definitely discontinuing ramipril, a rapid decline in LEs was observed, suggesting a certain causal relationship between drug intake and hepatic damage. Analysis of the FAERS database retrieved 65 cases of ramipril-associated hepatotoxicity, with jaundice being the most frequent hepatic adverse event. PubMed research detected 23 relevant publications, with enalapril being the ACEI most commonly reported as being associated with liver injury.. ACEI-induced hepatotoxicity is rare. Our case confirms a hepatotoxic potential of ramipril, highlighting the need for alertness among physicians regarding this matter.

Topics: Adult; Adverse Drug Reaction Reporting Systems; Alanine Transaminase; Angiotensin-Converting Enzyme Inhibitors; Chemical and Drug Induced Liver Injury; Humans; Hypertension; Jaundice; Liver; Male; Ramipril

Drug-induced liver injury (DILI) is a rare side effect of angiotensin-converting enzyme inhibitors (ACEIs). Ramipril is a widely used ACE compound because of its effectiveness in the treatment of hypertension and heart failure, as well as its low risk of adverse effects. However, the clinical features of ramipril, and the risk of DILI, have not been adequately studied. A retrospective cohort study was performed based on data from 3909 inpatients to compare the risk of DILI conferred by ramipril and other ACEIs. A logistic regression model was then constructed and validated against data from 1686 patients using ramipril, of which 117 patients were diagnosed with DILI. The use of ramipril increased the risk of DILI by 2.68 times (odds ratio = 2.68; 95% confident interval (CI):1.96-3.71) compared with the group using other ACEIs. The clinical features of DILI in the ramipril group were similar to those from the ACEI group (P>0.05), except that the ALT level was higher (P<0.05). A logistic regression model including Body mass index (BMI), comorbidity, liver disease, daily dose, alanine aminotransferase (ALT), and alkaline phosphatase (ALP) was built and successfully validated for DILI risk prediction, with the area under the receiver operating characteristic curve of the model of 0.82 (95% CI: 0.752-0.888). We recommend that clinicians should be aware of the levels of ALT and ALP as well as BMI, comorbidities, and liver disease before prescribing ramipril to avoid the risk of DILI in patients.

Topics: Angiotensin-Converting Enzyme Inhibitors; Chemical and Drug Induced Liver Injury; Humans; Inpatients; Logistic Models; Ramipril; Retrospective Studies

Hepatic fibrosis is a common feature of chronic liver injury, and the involvement of angiotensin II in such process has been studied earlier. We hypothesized that anti-angiotensin II agents may be effective in preventing hepatic fibrosis. In this study, Long Evans female rats were used and divided into four groups such as Group-I, Control; Group-II, Control + ramipril; Group-III, CCl4; and Group-IV, CCl4 + ramipril. Group II and IV are treated with ramipril for 14 d. At the end of treatment, the livers were removed, and the level of hepatic marker enzymes (aspartate aminotransferase, Alanine aminotransferase, and alkaline phosphatase), nitric oxide, advanced protein oxidation product , catalase activity, and lipid peroxidation were determined. The degree of fibrosis was evaluated through histopathological staining with Sirius red and trichrome milligan staining. Carbon-tetrachloride (CCl4) administration in rats developed hepatic dysfunction and raised the hepatic marker enzymes activities significantly. CCl4 administration in rats also produced oxidative stress, inflammation, and fibrosis in liver. Furthermore, angiotensinogen-inhibitor ramipril normalized the hepatic enzymes activities and improved the antioxidant enzyme catalase activity. Moreover, ramipril treatment ameliorated lipid peroxidation and hepatic inflammation in CCl4-treated rats. Ramipril treatment also significantly reduced hepatic fibrosis in CCl4-administered rats. In conclusion, our investigation suggests that the antifibrotic effect of ramipril may be attributed to inhibition of angiotensin-II mediated oxidative stress and inflammation in liver CCl4-administered rats.

Topics: Angiotensin-Converting Enzyme Inhibitors; Animals; Carbon Tetrachloride Poisoning; Chemical and Drug Induced Liver Injury; Female; Inflammation; Liver Cirrhosis; Oxidative Stress; Ramipril; Rats; Rats, Long-Evans

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

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