Outcome Of Drug-induced Liver Injury Research Articles

Drug-induced liver injury from selective androgen receptor modulators, anabolic-androgenic steroids and bodybuilding supplements in Australia.

Reports of DILI due to herbal and dietary supplements have been increasing over time. To characterise clinical, laboratory and histopathological phenotypes and outcomes of drug-induced liver injury (DILI) due to anabolic-androgenic steroids (AAS), selective androgen receptor modulators (SARMs), and bodybuilding supplements (BBS) in Australia. Retrospective case series. Patients presented to nine Australian tertiary hospitals, 2017-2023. DILI was defined biochemically and patients were included if their treating physician attributed DILI to preceding use of AAS, SARMs or BBS. Primary endpoint was time to normalisation of liver biochemistry. Secondary endpoints were hospitalisation for investigation or management of DILI, death attributable to liver injury, and liver transplantation. Twenty-three cases of DILI were identified, involving 40 drugs: 18 AAS, 14 SARMs and eight BBS. Patients were predominantly male (22/23), with median age 30 years (IQR 26-42). Most were symptomatic (21/23). Median latency of onset was 58 days (IQR 28-112 days) from drug commencement. Most patients (17/23) were admitted to hospital. Based on updated Roussel Uclaf Causality Assessment Method, DILI was possible in 17/23, probable in 2/23 and unlikely in 4/23. Median time to normalisation of liver biochemistry was 175 days (IQR 70-292 days) from presentation. Three (3/23) were treated with corticosteroids, 14/23 were treated for itch, and one (1/23) underwent liver transplantation. There were no deaths. The prognosis of DILI from AAS, SARMs and BBS is good although liver transplantation may rarely be required. A detailed drug history is important in uncovering DILI due to these supplements.

Computational models for predicting liver toxicity in the deep learning era.

Drug-induced liver injury (DILI) is a severe adverse reaction caused by drugs and may result in acute liver failure and even death. Many efforts have centered on mitigating risks associated with potential DILI in humans. Among these, quantitative structure-activity relationship (QSAR) was proven to be a valuable tool for early-stage hepatotoxicity screening. Its advantages include no requirement for physical substances and rapid delivery of results. Deep learning (DL) made rapid advancements recently and has been used for developing QSAR models. This review discusses the use of DL in predicting DILI, focusing on the development of QSAR models employing extensive chemical structure datasets alongside their corresponding DILI outcomes. We undertake a comprehensive evaluation of various DL methods, comparing with those of traditional machine learning (ML) approaches, and explore the strengths and limitations of DL techniques regarding their interpretability, scalability, and generalization. Overall, our review underscores the potential of DL methodologies to enhance DILI prediction and provides insights into future avenues for developing predictive models to mitigate DILI risk in humans.

Systematic review and meta-analysis: Comparing hepatocellular and cholestatic patterns of drug-induced liver injury

Drug-induced liver injury (DILI) is a leading cause of death from acute liver failure (ALF). Hy's law warns that a hepatocellular pattern of injury accompanied by jaundice and normal alkaline phosphatase (ALP) levels is associated with a 10% or greater chance of progression to transplant or liver-related death. This meta-analysis of DILI studies evaluates acute and chronic outcomes of DILI according to clinical pattern of injury. We conducted a systematic search using electronic databases PubMed and EMBASE through to 8 March 2022. Our primary outcome was to compare acute outcomes including ALF, liver-related death, and liver transplant between patients experiencing hepatocellular, cholestatic, and mixed patterns of DILI. Our secondary outcome was to compare the rate of DILI chronicity between patients of these three differing patterns of injury. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using a random-effects model. Overall, 12 studies comprising 4290 patients were included. Patients with cholestatic DILI demonstrated similar rates of ALF (OR: 0.80, 95% CI: 0.46–1.40, p = 0.429) and liver-related death (OR: 0.92, 95% CI: 0.50–1.69, p = 0.792) compared to patients with hepatocellular DILI. Patients with cholestatic DILI were significantly more likely to experience chronicity compared to patients with hepatocellular DILI (OR: 2.53, 95% CI: 1.34–4.79, p = 0.004). Hy's law conceives severe DILI as an exclusive consequence of hepatocellular pattern of injury. Our results demonstrate that cholestatic injury can be associated with similarly poor rates of ALF and liver-related fatality, as well as higher rates of chronic DILI.

A Unique In Vitro Assay to Investigate ABCB4 Transport Function

ABCB4 is almost exclusively expressed in the liver, where it plays an essential role in bile formation by transporting phospholipids into the bile. ABCB4 polymorphisms and deficiencies in humans are associated with a wide spectrum of hepatobiliary disorders, attesting to its crucial physiological function. Inhibition of ABCB4 by drugs may lead to cholestasis and drug-induced liver injury (DILI), although compared with other drug transporters, there are only a few identified substrates and inhibitors of ABCB4. Since ABCB4 shares up to 76% identity and 86% similarity in the amino acid sequence with ABCB1, also known to have common drug substrates and inhibitors, we aimed to develop an ABCB4 expressing Abcb1-knockout MDCKII cell line for transcellular transport assays. This in vitro system allows the screening of ABCB4-specific drug substrates and inhibitors independently of ABCB1 activity. Abcb1KO-MDCKII-ABCB4 cells constitute a reproducible, conclusive, and easy to use assay to study drug interactions with digoxin as a substrate. Screening a set of drugs with different DILI outcomes proved that this assay is applicable to test ABCB4 inhibitory potency. Our results are consistent with prior findings concerning hepatotoxicity causality and provide new insights for identifying drugs as potential ABCB4 inhibitors and substrates.

COVID-19-related liver injury: Focus on genetic and drug-induced perspectives.

Empirical use of potentially hepatotoxic drugs in the management of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is considered as one of the major etiopathogenetic factors for liver injury. Recent evidence has shown that an underlying genetic factor may also occur. Hence, it is important to understand the host genetics and iatrogenic-based mechanisms for liver dysfunction to make timely remedial measures. To investigate drug-induced and genetic perspectives for the development of coronavirus disease 2019 (COVID-19)-related liver injury. Reference Citation Analysis, PubMed, Google Scholar and China National Knowledge Infrastructure were searched by employing the relevant MeSH keywords and pertaining data of the duration, site and type of study, sample size with any subgroups and drug-induced liver injury outcome. Genetic aspects were extracted from the most current pertinent publications. In all studies, the hepatic specific aminotransferase and other biochemical indices were more than their prescribed upper normal limit in COVID-19 patients and were found to be significantly related with the gravity of disease, hospital stay, number of COVID-19 treatment drugs and worse clinical outcomes. In addition, membrane bound O-acyltransferase domain containing 7 rs641738, rs11385942 G>GA at chromosome 3 gene cluster and rs657152 C>A at ABO blood locus was significantly associated with severity of livery injury in admitted SARS-CoV-2 patients. Hepatic dysfunction in SARS-CoV-2 infection could be the result of individual drugs or due to drug-drug interactions and may be in a subset of patients with a genetic propensity. Thus, serial estimation of hepatic indices in hospitalized SARS-CoV-2 patients should be done to make timely corrective actions for iatrogenic causes to avoid clinical deterioration. Additional molecular and translational research is warranted in this regard.

Characteristics of Drug-induced Liver Injury in Chronic Liver Disease: Results from the Thai Association for the Study of the Liver (THASL) DILI Registry.

The impact of drug-induced liver injury (DILI) on patients with chronic liver disease (CLD) is unclear. There are few reports comparing DILI in CLD and non-CLD patients. In this study, we aimed to determine the incidence and outcomes of DILI in patients with and without CLD. We collected data on eligible individuals with suspected DILI between 2018 and 2020 who were evaluated systematically for other etiologies, causes, and the severity of DILI. We compared the causative agents, clinical features, and outcomes of DILI among subjects with and without CLD who were enrolled in the Thai Association for the Study of the Liver DILI registry. Subjects with definite, or highly likely DILI were included in the analysis. A total of 200 subjects diagnosed with DILI were found in the registry. Of those, 41 had CLD and 159 had no evidence of CLD in their background. Complementary and alternative medicine (CAM) products were identified as the most common class of DILI agents. Approximately 59% of DILI in the CLD and 40% in non-CLD group were associated with CAM use. Individuals with pre-existing CLD had similar severity including mortality. Twelve patients (6%) developed adverse outcomes related to DILI including seven (3.5%) deaths and five (2.5%) with liver failure. Mortality was 4.88% in CLD and 3.14% in non-CLD subjects over median periods of 58 (8-106) days and 22 (1-65) days, respectively. In this liver disease registry, the causes, clinical presentation, and outcomes of DILI in subjects with CLD and without CLD patients were not different. Further study is required to confirm our findings.

Clinical characteristics and outcomes of drug-induced liver injury in Taiwan: With emphasis on the impact of chronic hepatitis B infection.

Whether hepatitis B virus (HBV) infection can affect the outcomes of drug-induced liver injury (DILI) is controversial. This study aimed to evaluate the characteristics and outcomes of DILI in Taiwan, with an emphasis on the impact of HBV infection. We prospectively recruited patients with DILI from multiple centers in Taiwan from 2010 to 2018. A total of 1,014 patients were enrolled. The leading culprit drug category was antimicrobials (481, 47.4%), followed by nonsteroidal anti-inflammatory drugs, anticonvulsants, and statins. Among the antimicrobials, antituberculosis agents were most likely to induce liver injury (257, 25.3%), followed by antibacterial, antifungal, and antiviral agents. The liver-related mortality rate was 8.2% (83/1,014). The patients who died had higher rates of hepatocellular-type liver injury, elevated liver biochemical tests, preexisting liver cirrhosis, jaundice, chronic HBV infection, and antituberculosis drug-induced liver injury (ATDILI) than the survivors. A total of 131 patients (12.9%) with DILI were HBV carriers, of whom 23 (17.6%) died of hepatic failure. The rate of HBV-DNA > 2000 IU/mL was higher in the patients who died (47.8% vs. 26.9%, p = 0.047) than in the survivors. After adjusting for possible risk factors, active HBV infection with HBV-DNA > 2000 IU/mL was the most significant risk factor for liver-related mortality (adjusted HR, 4.40, 95% CI, 2.31%-8.38%, p < 0.001). The other independent risk factors for mortality were ATDILI and albumin-bilirubin (ALBI) score (adjusted HR, 1.25 and 4.09, respectively, p < 0.003). Antituberculosis agents were the leading cause of DILI in Taiwanese, and they were associated with poorer outcomes than other drug categories. Active HBV infection, ATDILI and ALBI score were independent risk factors for fatal DILI. Close monitoring of liver tests and timely antiviral therapy should be implemented in HBV carriers during the administration of high-risk drugs, such as antituberculosis agents.

Drug-induced liver injury in Australia, 2009-2020: the increasing proportion of non-paracetamol cases linked with herbal and dietary supplements.

To compare the characteristics and outcomes of drug-induced liver injury (DILI) caused by paracetamol and non-paracetamol medications, particularly herbal and dietary supplements. Retrospective electronic medical record data analysis. Adults admitted with DILI to the Gastroenterology and Liver Centre at the Royal Prince Alfred Hospital, Sydney (a quaternary referral liver transplantation centre), 2009-2020. 90-day transplant-free survival; drugs implicated as causal agents in DILI. A total of 115 patients with paracetamol-related DILI and 69 with non-paracetamol DILI were admitted to our centre. The most frequently implicated non-paracetamol medications were antibiotics (19, 28%), herbal and dietary supplements (15, 22%), anti-tuberculosis medications (six, 9%), and anti-cancer medications (five, 7%). The number of non-paracetamol DILI admissions was similar across the study period, but the proportion linked with herbal and dietary supplements increased from 2 of 13 (15%) during 2009-11 to 9 of 19 (47%) during 2018-20 (linear trend: P=0.011). Despite higher median baseline model for end-stage liver disease (MELD) scores, 90-day transplant-free survival for patients with paracetamol-related DILI was higher than for patients with non-paracetamol DILI (86%; 95% CI, 79-93% v 71%; 95% CI, 60-82%) and herbal and dietary supplement-related cases (59%; 95% CI, 34-85%). MELD score was an independent predictor of poorer 90-day transplant-free survival in both paracetamol-related (per point increase: adjusted hazard ratio [aHR], 1.19; 95% CI, 1.09-3.74) and non-paracetamol DILI (aHR, 1.24; 95% CI, 1.14-1.36). In our single centre study, the proportion of cases of people hospitalised with DILI linked with herbal and dietary supplements has increased since 2009. Ninety-day transplant-free survival for patients with non-paracetamol DILI, especially those with supplement-related DILI, is poorer than for those with paracetamol-related DILI.

Drug-induced liver injury associated with severe cutaneous adverse drug reactions: A nationwide study in Taiwan.

Severe cutaneous adverse drug reactions (SCARs) including Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), drug reaction with eosinophilia and systemic symptoms (DRESS) and acute generalized exanthematous pustulosis (AGEP) are high-mortality adverse drug reactions. The risk factors and prognosis of drug-induced liver injury (DILI) concomitant with SCAR warrant clarification. We aimed to evaluate the characteristics and outcomes of DILI with SCAR. We analysed the database of a 10-year multi-centre prospective study in Taiwan from 2011 to 2020. A total of 1415 patients with DILI were enrolled, including 81 cases combined with SJS/TEN, 74 with DRESS, 3 with AGEP and 1257 with pure DILI. Approximated 11.2% of patients had SCAR, of which allopurinol was the leading incriminated drug, followed by sulphonamides and carbamazepine. The SJS/TEN group had the highest mortality (34.6%). Jaundice, acute kidney injury and SJS/TEN were independent risk factors of mortality (odds ratio: 29.54, 4.43 and 4.86, respectively, P<.003). Chronic kidney disease with high-dose allopurinol also contributed to high mortality (78.9%) in cases of allopurinol-induced DILI with SCAR. The HLA-B*5801 was associated with a high risk and mortality of allopurinol-induced DILI with SCAR. Likewise, the HLA-B*1502 was closely related to carbamazepine-induced DILI with SCAR. DILI patients combined with SCAR are common and have a high mortality in Taiwan. Allopurinol is the leading incriminated drug. Jaundice, acute kidney injury and SJS/TEN are risk factors of mortality. HLA-B*5801, chronic kidney disease and high drug dosage also contribute to high mortality in allopurinol-induced DILI with SCAR.

DeepDILI: Deep Learning-Powered Drug-Induced Liver Injury Prediction Using Model-Level Representation.

Drug-induced liver injury (DILI) is the most frequently reported single cause of safety-related withdrawal of marketed drugs. It is essential to identify drugs with DILI potential at the early stages of drug development. In this study, we describe a deep learning-powered DILI (DeepDILI) prediction model created by combining model-level representation generated by conventional machine learning (ML) algorithms with a deep learning framework based on Mold2 descriptors. We conducted a comprehensive evaluation of the proposed DeepDILI model performance by posing several critical questions: (1) Could the DILI potential of newly approved drugs be predicted by accumulated knowledge of early approved ones? (2) is model-level representation more informative than molecule-based representation for DILI prediction? and (3) could improved model explainability be established? For question 1, we developed the DeepDILI model using drugs approved before 1997 to predict the DILI potential of those approved thereafter. As a result, the DeepDILI model outperformed the five conventional ML algorithms and two state-of-the-art ensemble methods with a Matthews correlation coefficient (MCC) value of 0.331. For question 2, we demonstrated that the DeepDILI model's performance was significantly improved (i.e., a MCC improvement of 25.86% in test set) compared with deep neural networks based on molecule-based representation. For question 3, we found 21 chemical descriptors that were enriched, suggesting a strong association with DILI outcome. Furthermore, we found that the DeepDILI model has more discrimination power to identify the DILI potential of drugs belonging to the World Health Organization therapeutic category of 'alimentary tract and metabolism'. Moreover, the DeepDILI model based on Mold2 descriptors outperformed the ones with Mol2vec and MACCS descriptors. Finally, the DeepDILI model was applied to the recent real-world problem of predicting any DILI concern for potential COVID-19 treatments from repositioning drug candidates. Altogether, this developed DeepDILI model could serve as a promising tool for screening for DILI risk of compounds in the preclinical setting, and the DeepDILI model is publicly available through https://github.com/TingLi2016/DeepDILI.

Development of a Battery of In Silico Prediction Tools for Drug-Induced Liver Injury from the Vantage Point of Translational Safety Assessment.

Drug-induced liver injury (DILI) remains a challenge when translating knowledge from the preclinical stage to human use cases. Attempts to model human DILI directly based on the information from drug labels have had some success; however, the approach falls short of providing insights or addressing uncertainty due to the difficulty of decoupling the idiosyncratic nature of human DILI outcomes. Our approach in this comparative analysis is to leverage existing preclinical and clinical data as well as information on metabolism to better translate mammalian to human DILI. The human DILI knowledge base from the United States Food and Drug Administration (U.S. FDA) National Center for Toxicology Research contains 1036 pharmaceuticals from diverse therapeutic categories. A human DILI training set of 305 oral marketed drugs was prepared and a binary classification scheme applied. The second knowledge base consists of mammalian repeated dose toxicity with liver toxicity data from various regulatory sources. Within this knowledge base, we identified 278 pharmaceuticals containing 198 marketed or withdrawn oral drugs with data from the U.S. FDA new drug application and 98 active pharmaceutical ingredients from ToxCast. From this collection, a set of 225 oral drugs was prepared as the mammalian hepatotoxicity training set with particular end points of pathology findings in the liver and bile duct. Both human and mammalian data sets were processed using various learning algorithms, including artificial intelligence approaches. The external validations for both models were comparable to the training statistics. These data sets were also used to extract species-differentiating chemotypes that differentiate DILI effects on humans from mammals. A systematic workflow was devised to predict human DILI and provide mechanistic insights. For a given query molecule, both human and mammalian models are run. If the predictions are discordant, both metabolites and parents are investigated for quantitative structure-activity relationship and species-differentiating chemotypes. Their results are combined using the Dempster-Shafer decision theory to yield a final outcome prediction for human DILI with estimated uncertainty. Finally, these tools are implementable within an in silico platform for systematic evaluation.

Drugs-Herbs-Dietary Supplements-induced Liver Injury: A Hidden but Emerging Clinical Problem

Background: Drug-induced liver injury (DILI) is becoming increasingly common. Additionally, there have also been worldwide increases in herbal-induced liver injury (HILI) and supplement-induced liver injury (SILI). Studies on DILI, HILI, and SILI have shown that liver injury is the result of an idiosyncratic reaction and was geographically distinct. Objective: To describe the clinical characteristics and outcomes of DILI, HILI, and SILI in a Thai population. Materials and Methods: We retrospectively included patients (both outpatients and inpatients) who were diagnosed with DILIHILI-SILI at a tertiary care university hospital setting from January 2014 to December 2019. The Roussel Uclaf Causality Assessment Method (RUCAM) score was used to assess causality in suspected cases with a cut-off score of &gt;3. R ratio was used to identify the 3 types of liver injury: hepatocellular, cholestasis, or mixed type. Results: Seventy patients were suspected to have DILI during the study period. Twenty-three patients were excluded due to incomplete data or RUCAM score &lt;3. The remaining 47 patients were included. Of these, 26 cases (55.3%) were due to herbs or supplements and 17 (36.2%) were admitted for a high degree of liver injury. Chinese traditional complementary (12.7%) and multi-herbal products (12.7%) were the common causes of HILI and SILI, respectively. Antimicrobial agents (19.1%) and analgesics (10.6%) were the common causes of conventional drug-induced liver damage. The liver injury patterns in DILI from conventional drugs were hepatocellular (R&gt;5) in 47.6% and cholestatic pattern (R&lt;2) in 33.3%, which was not significantly different (p&gt;0.05). For the HILI and SILI groups, the liver injury patterns were hepatocellular in 46.2% and cholestatic pattern in 15.4% (p = ns). The duration of exposure to diagnosis was similar between the DILI and HILI-SILI groups (3.7 vs. 5.6 months, p = 0.42). The DILI group had longer hospital stay than the HILI and SILI groups (13.5 vs. 7 days; p = 0.63). The overall mortality rate was 2.9%, with one death in each group. Conclusion: Herbal and dietary supplements played an important role in DILI and showed a trend of shorter hospital stays. Hepatocellular liver injury pattern was the most common clinical finding in patients with DILI, HILI, and SILI. Keywords: Drug-induced liver injury, DILI-HILI-SILI, Hepatitis, R pattern

S1011 Etiology and Outcomes of Drug-Induced Liver Injury in a Multi-Ethnic United States Population

S1011 Etiology and Outcomes of Drug-Induced Liver Injury in a Multi-Ethnic United States Population

Avoidability of drug-induced liver injury (DILI) in an elderly hospital cohort with cases assessed for causality by the updated RUCAM score

BackgroundDrug-induced liver injury (DILI) represents an increasing morbidity in the general population, but more so in the elderly cohort of patients. Despite this, the concept of its prevention through prospective analysis has largely remained unexamined. We evaluated the utility of recently validated adverse drug reactions (ADR) avoidability tool in a cohort of elderly patients with DILI.MethodsWe examined 38 DILI-drug pairs from n=38 patients in a prospective cohort of patients presenting with adverse drug reactions to a Weill Cornell-affiliated tertiary hospital between February 2019 and January 2020. DILI outcomes were adjudicated by the updated Roussel Uclaf Causality Assessment Method (RUCAM). Two clinical pharmacologists and two general physicians utilized the Liverpool adverse drug reactions avoidability tool (LAAT) and the modified Hallas tools to rate the preventability of DILI-drug pairs. Inter-rater, exact agreement proportions, as well as intraclass correlation coefficients were generated and expressed as ordinal outcomes.ResultsThe cases examined for the determination of DILI avoidability had probability likelihood of “probable” or “highly probable” by the updated RUCAM scale. Examination of the 38 DILI-drug pairs (n= 38 patients) resulted in a total of 152 ordinal outcome decisions. We found about 32.3% (50/152) and 34.2% (52/152) of DILI-drug pairs were rated as “avoidable” (“probable” or “definite”) by the LAAT and the modified Hallas tools respectively. The overall median Krippendorf’s kappa with the LAAT was 0.61 (SE 0.12, CI 0.36, 0.85) and for modified Hallas tool was 0.53 (SE 0.18; CI 0.16, 0.89). The inter-rater correlation coefficient (ICC) for the LAAT and modified Hallas were 0.50 [0.32, 0.65] and 0.63 [0.48, 0.76] respectively. Exact pairwise agreement was present in 30/38 (IQR 29.5, 34.5), and 28/38 (IQR 27.5-35.5) of DILI-ADR pairs using the LAAT and modified Hallas tools respectively.ConclusionWe found a significant proportion of drug-induced liver injury adjudicated by the updated RUCAM scale in elderly hospitalized cohort of patients were avoidable with significant implication for therapeutic commissioning as well as cost effectiveness interventions in this cohort of patients.

Drug induced liver injury: an update.

Drug induced liver injury (DILI) is a relatively rare hepatic condition in response to the use of medications, illegal drugs, herbal products or dietary supplements. It occurs in susceptible individuals through a combination of genetic and environmental risk factors believed to modify drug metabolism and/or excretion leading to a cascade of cellular events, including oxidative stress formation, apoptosis/necrosis, haptenization, immune response activation and a failure to adapt. The resultant liver damage can present with an array of phenotypes, which mimic almost every other liver disorder, and varies in severity from asymptomatic elevation of liver tests to fulminant hepatic failure. Despite recent research efforts specific biomarkers are not still available for routine use in clinical practice, which makes the diagnosis of DILI uncertain and relying on a high degree of awareness of this condition and the exclusion of other causes of liver disease. Diagnostic scales such as the CIOMS/RUCAM can support the causality assessment of a DILI suspicion, but need refinement as some criteria are not evidence-based. Prospective collection of well-vetted DILI cases in established DILI registries has allowed the identification and validation of a number of clinical variables, and to predict a more severe DILI outcome. DILI is also in need of properly designed clinical trials to evaluate the efficacy of new DILI treatments as well as older drugs such as ursodeoxycholic acid traditionally used to ameliorate cholestasis or corticosteroids now widely tried in the oncology field to manage the emergent type of hepatotoxicity related to immune checkpoint inhibitors.

Outcomes and Predictors of Mortality in Patients With Drug-Induced Liver Injury at a Tertiary Hospital in South India: A Single-Centre Experience

Drug-induced liver injury (DILI) is an important cause of acute liver failure with significant morbidity and mortality. The outcome of DILI varies widely according to the drug implicated and the type of liver injury. Owing to the heterogeneous nature of liver injury, knowledge on clinical course and prognosis of DILI is limited. We had undertaken this study to determine the clinical characteristics, outcomes, and predictors of mortality in patients with DILI. This prospective study was conducted from January 2015 through December 2018. We analyzed the drugs implicated, clinical course, and the outcome. Causality assessment was performed by using Roussel Uclaf Causality Assessment Method scoring. Patients were followed for 6 months until recovery/death or liver transplantation. There were 133 cases with DILI. The mean age was 47.6 years, and 51.9% of them were men. Drugs causing DILI were antitubercular drugs (37.5%) followed by neuropsychiatric drugs (16.5%), antibiotics/antifungals (12%), complementary and alternative medicine (10.5%), immunomodulatory/chemotherapeutic drugs (10.5%), and nonsteroidal antiinflammatory drugs (7.5%). Eighty-two (61.6%) patients were classified as hepatocellular, 30 (22.5%) as mixed and 21 (15.7%) as cholestatic type of injury. There was no significant difference in the mortality and morbidity between the three types of liver injury. There were 18 deaths (13.5%), of which antitubercular drugs constituted the majority (55.5%) followed by neuropsychiatric drugs (27.7%) and complementary and alternative medicine (16.6%). Based on receiver operating characteristic curve analysis, model for end-stage liver disease (MELD) score >28, mean international normalized ratio (INR) >1.97, mean bilirubin level >15.6mg/dl, and creatinine level >1.35mg/dl were associated with mortality. Although DILI is uncommon, it has significant morbidity and mortality. Antitubercular drugs were the most common cause for DILI and DILI-related mortality in our study. Variables such as MELD, INR, bilirubin, albumin, and creatinine helpin predicting severity of liver injury and may help in triaging the patient for referral for liver transplantation.

A High Serum Level of Taurocholic Acid Is Correlated With the Severity and Resolution of Drug-induced Liver Injury

Alterations in the serum levels of bile acids are associated with drug-induced liver injury (DILI). We investigated the association between serum levels of bile acids and the severity and outcome of DILI, along with the potential role of variants in the ATP binding cassette subfamily B member 11 (ABCB11) gene and expression of its product, ABCB11 (also called BSEP). We performed this prospective study of 95 patients (median age, 53 years; 73.7% female) with DILI from August 2018 through August 2019. Patients were matched for age, gender, and body mass index with healthy individuals (n=100; healthy controls) and patients with chronic hepatitis B (n=105; CHB controls). We collected demographic and biochemical data at baseline and 1 week, 1 month, 3 months, and 6 months after DILI onset and at the time of biochemical recovery, liver failure or liver transplantation. Serum levels of bile acids were measured using high-performance liquid-chromatography tandem mass-spectrometry. All 27 exons of ABCB11 were sequenced and expression of BSEP was analyzed by immunohistochemistry in liver biopsy specimens. Levels of 30 of the 37 bile acids analyzed differed significantly between patients with DILI and healthy controls. Changes in levels of taurocholic acid (TCA), glycocholic acid, taurochenodeoxycholate, and glycochenodeoxycholate associated with the increased levels of bilirubin and greater severity of DILI, and were also associated with CHB. Cox regression analysis showed that only change in the levels of TCA independently associated with biochemical resolution of DILI. Combination of TCA level (≥ 1955.41 nmol/L), patient age, and DILI severity was associated with abnormal blood biochemistry at 6 months after DILI onset (area under the curve, 0.81; 95% confidence interval, 0.71-0.88; sensitivity, 0.69; specificity, 0.81). ABCB11 missense variants were not associated with differences in the serum bile acid profiles, DILI severity, or clinical resolution. However, lower levels of BSEP in bile canaliculi in liver biopsies were associated with altered serum levels of bile acids. In this prospective study performed in Chinese patients, we found that the serum levels of TCA were associated with the severity and clinical resolution of DILI. Reduced protein expression of BSEP in liver tissue, rather than variants of the ABCB11 gene were associated with altered serum levels of bile acids.

Isoniazid and Rifampicin Produce Hepatic Fibrosis through an Oxidative Stress-Dependent Mechanism.

Methods A combined dose of INH (50 mg) and RMP (100 mg) per kg body weight per day was administered to mice by oral gavage, 6 days a week, for 4 to 24 weeks for the assessment of liver injury, oxidative stress, and development of hepatic fibrosis, including demonstration of changes in key fibrogenesis linked pathways and mediators. Results Progressive increase in markers of hepatic stellate cell (HSC) activation associated with changes in matrix turnover was observed between 12 and 24 weeks of INH-RMP treatment along with the elevation of liver collagen content and significant periportal fibrosis. These were associated with concurrent apoptosis of the hepatocytes, increase in hepatic cytochrome P450 2E1 (CYP2E1), NADPH oxidase (NOX) activity, and development of hepatic oxidative stress. Conclusions INH-RMP can activate HSC through generation of NOX-mediated oxidative stress, leading to the development of liver fibrosis.

Presentations, Causes and Outcomes of Drug-Induced Liver Injury in Egypt

Drug-induced liver injury (DILI) is a frequent cause of liver injury and acute liver failure. We aimed to review all hospitalized DILI cases in a tertiary Egyptian center from January 2015 through January 2016. Cases with elevated alanine aminotransferase more than 3-fold and/or alkaline phosphatase more than 2-fold the upper limit of normal value were prospectively recruited and followed for one year. Drug history, liver biopsy whenever feasible and application of Roussel Uclaf Causality Assessment Method (RUCAM) were the diagnostic prerequisites after exclusion of other etiologies of acute liver injury. In order of frequency, the incriminated drugs were: Diclofenac (31 cases, 41.3%), amoxicillin-clavulanate (14 cases, 18.7%), halothane toxicity (8 cases, 10.7%), ibuprofen (4 cases, 5.3%), Khat (3 cases, 4%), tramadol (3 cases, 4%), Sofosbuvir with ribavirin (2 cases, 2.7%), and acetylsalicylic acid (2 cases, 2.7%) with one offending drug in 93.3% of cases. Forty-four cases (58.7%) were males; while 56 cases (74.7%) had HCV related chronic liver disease. Thirty-two cases (42.7%) presented with pattern of hepatocellular injury, while 23 cases (30.7%) were with cholestasis, and 20 cases (20.7%) with a mixed hepatocellular/cholestatic injury. One case received a transplant (0.75%), 7 cases died (9.3%), 23 cases (30.6%) developed liver decompensation (hepatic encephalopathy and ascites), and 44 cases completely resolved (58.7%). In conclusion, Diclofenac is the commonest offender in DILI occurrence in an Egyptian cohort. Age and prothrombin concentration were the only predictors of unfavorable outcomes of DILI.

Development of Prediction Models for Drug-Induced Cholestasis, Cirrhosis, Hepatitis, and Steatosis Based on Drug and Drug Metabolite Structures.

Drug-induced liver injury (DILI) is one of the major reasons for termination of drug development. Due to the importance of predicting DILI in early phases of drug development, diverse in silico models have been developed to filter out DILI-causing candidates before clinical study. However, no computational models have achieved sufficient prediction power for screening DILI in early phases because 1) drugs often cause liver injury through reactive metabolites, 2) different clinical outcomes of DILI have different mechanisms, and 3) the DILI label on drugs is not clearly defined. In this study, we developed binary classification models to predict drug-induced cholestasis, cirrhosis, hepatitis, and steatosis based on the structure of drugs and their metabolites. DILI-positive data was obtained from post-market reports of drugs and DILI-negative data from DILIrank, a database curated by the Food and Drug Administration (FDA). Support vector machine (SVM) and random forest (RF) were used in developing models with nine fingerprints and one 2D molecular descriptor calculated from drug (152 DILI-positives and 102 DILI-negatives) and drug metabolite (192 DILI-positives and 126 DILI-negatives) structures. Models were developed according to Organisation for Economic Co-operation and Development (OECD) guidelines for quantitative structure-activity relationship (QSAR) validation. Internal and external validation was performed with a randomization test in order to thoroughly examine model predictability and avoid random correlation between structural features and adverse outcomes. The applicability domain was defined with a leverage method for reliable prediction of new chemicals. The best models for each liver disease were selected based on external validation results from drugs (cholestasis: 70%, cirrhosis: 90%, hepatitis: 83%, and steatosis: 85%) and drug metabolites (cholestasis: 86%, cirrhosis: 88%, hepatitis: 86%, and steatosis: 83%) with applicability domain analysis. Compiled data sets were further exploited to derive privileged substructures that were more frequent in DILI-positive sets compared to DILI-negative sets and in drug metabolite structures compared to drug structures with a Morgan fingerprint level 2.