Biomarkers of drug-induced liver injury

Changing Trajectories of Alanine Aminotransferase and Risk of Antituberculosis Drug-Induced Liver Injury in Chinese Patients: A Cohort Study

Antituberculosis drug-induced liver injury (ATLI) is a major adverse effect during antituberculosis treatment. Early detection or prediction is essential to prevent ATLI in antituberculosis treatment patients. The purpose of this work is to explore the relationship between alanine aminotransferase (ALT) trajectories within 15 days of initial treatment and the risk of ATLI. Based on a historical cohort of patients hospitalized for antituberculosis treatment and group-based trajectory modeling analysis, ALT trajectories within 15 days of initial treatment were determined. Conditional logistic regression model was used to estimate the association between different ALT trajectories and the risk of ATLI, and the corresponding odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated with covariates. Based on the ALT levels within 15 days of initial treatment, a total of 853 patients were divided into four ALT trajectories. The incidence of ATLI significantly increased with the increase of ALT trajectories (2.33%, 4.38%, 5.90%, and 2.44%, respectively). Compared with trajectory 1, the adjusted OR for ATLI in trajectory 2, trajectory 3, and trajectory 4 were 2.448 (95% CI: 0.302-19.856, P = 0.402), 5.373 (95% CI: 0.636-45.411, P = 0.123), 11.010 (95% CI: 0.720-168.330, P = 0.085), respectively, and there was an increasing trend of ATLI risk (Ptrend = 0.015). Different ALT trajectories within 15 days of initial treatment were associated with different risk of ATLI, and it is necessary to pay attention to the ALT trajectory within 15 days of initial treatment to predict the occurrence of ATLI.

Susceptibility to Hepatotoxic Drug-Induced Liver Injury Increased After Traumatic Brain Injury in Mice

The early stages of brain injury can induce acute liver injury, which can be recovered in the short term. Continued medication treatment during hospitalization for brain injury alleviates the prognosis and contributes to a high incidence of drug-induced liver injury (DILI). We hypothesize that there is an interaction between changes in the hepatic environment after brain injury and liver injury produced by intensive drug administration, leading to an upregulation of the organism's sensitivity to DILI. In this study, mice models of TBI were established by controlled cortical impact (CCI) and models of DILI were constructed by acetaminophen (APAP). All mice were divided into four groups: Sham, TBI, APAP, and TBI+APAP, and related liver injury indicators in liver and serum were detected by Western blot, Quantitative real-time PCR (qRT-PCR), and immunohistochemical staining. The results suggested that liver injury induced in the early stages of brain injury recovered in 3 days, but this state could still significantly aggravate DILI, represented by higher liver enzymes (aspartate aminotransferase [AST] and alanine aminotransferase [ALT]), oxidative stress (increase in malondialdehyde [MDA] concentration and deregulation of glutathione [GSH] and superoxide dismutase [SOD] activities), inflammatory response (activation of the HMGB1/TLR4/NF-κB signaling pathway, and increased messenger RNA [mRNA] and protein levels of pro-inflammatory cytokines including tumor necrosis factor alpha [TNF-α], interleukin [IL]-6, and IL-1β), and apoptosis (TUNEL assay, upregulation of Bax protein and deregulation of Bcl-2 protein). In summary, our results suggested that TBI is a potential susceptibility factor for DILI and exacerbates DILI.

Future Perspectives on Radiomics in Acute Liver Injury and Liver Trauma

Background: Acute liver injury occurs most frequently due to trauma, but it can also occur because of sepsis or drug-induced injury. This review aims to analyze artificial intelligence (AI)'s ability to detect and quantify liver injured areas in adults and pediatric patients. Methods: A literature analysis was performed on the PubMed Dataset. We selected original articles published from 2018 to 2023 and cohorts with ≥10 adults or pediatric patients. Results: Six studies counting 564 patients were collected, including 170 (30%) children and 394 adults. Four (66%) articles reported AI application after liver trauma, one (17%) after sepsis, and one (17%) due to chemotherapy. In five (83%) studies, Computed Tomography was performed, while in one (17%), FAST-UltraSound was performed. The studies reported a high diagnostic performance; in particular, three studies reported a specificity rate > 80%. Conclusions: Radiomics models seem reliable and applicable to clinical practice in patients affected by acute liver injury. Further studies are required to achieve larger validation cohorts.

Contributing roles of mitochondrial dysfunction and hepatocyte apoptosis in liver diseases through oxidative stress, post-translational modifications, inflammation, and intestinal barrier dysfunction

This review provides an update on recent findings from basic, translational, and clinical studies on the molecular mechanisms of mitochondrial dysfunction and apoptosis of hepatocytes in multiple liver diseases, including but not limited to alcohol-associated liver disease (ALD), metabolic dysfunction-associated steatotic liver disease (MASLD), and drug-induced liver injury (DILI). While the ethanol-inducible cytochrome P450-2E1 (CYP2E1) is mainly responsible for oxidizing binge alcohol via the microsomal ethanol oxidizing system, it is also responsible for metabolizing many xenobiotics, including pollutants, chemicals, drugs, and specific diets abundant in n-6 fatty acids, into toxic metabolites in many organs, including the liver, causing pathological insults through organelles such as mitochondria and endoplasmic reticula. Oxidative imbalances (oxidative stress) in mitochondria promote the covalent modifications of lipids, proteins, and nucleic acids through enzymatic and non-enzymatic mechanisms. Excessive changes stimulate various post-translational modifications (PTMs) of mitochondrial proteins, transcription factors, and histones. Increased PTMs of mitochondrial proteins inactivate many enzymes involved in the reduction of oxidative species, fatty acid metabolism, and mitophagy pathways, leading to mitochondrial dysfunction, energy depletion, and apoptosis. Unique from other organelles, mitochondria control many signaling cascades involved in bioenergetics (fat metabolism), inflammation, and apoptosis/necrosis of hepatocytes. When mitochondrial homeostasis is shifted, these pathways become altered or shut down, likely contributing to the death of hepatocytes with activation of inflammation and hepatic stellate cells, causing liver fibrosis and cirrhosis. This review will encapsulate how mitochondrial dysfunction contributes to hepatocyte apoptosis in several types of liver diseases in order to provide recommendations for targeted therapeutics.

iPSCs as a groundbreaking tool for the study of adverse drug reactions: A new avenue for personalized therapy

Induced pluripotent stem cells (iPSCs), obtained by reprogramming different somatic cell types, represent a promising tool for the study of drug toxicities, especially in the context of personalized medicine. Indeed, these cells retain the same genetic heritage of the donor, allowing the development of personalized models. In addition, they represent a useful tool for the study of adverse drug reactions (ADRs) in special populations, such as pediatric patients, which are often poorly represented in clinical trials due to ethical issues. Particularly, iPSCs can be differentiated into any tissue of the human body, following several protocols which use different stimuli to induce specific differentiation processes. Differentiated cells also maintain the genetic heritage of the donor, and therefore are suitable for personalized pharmacological studies; moreover, iPSC-derived differentiated cells are a valuable tool for the investigation of the mechanisms underlying the physiological differentiation processes. iPSCs-derived organoids represent another important tool for the study of ADRs. Precisely, organoids are in vitro 3D models which better represent the native organ, both from a structural and a functional point of view. Moreover, in the same way as iPSC-derived 2D models, iPSC-derived organoids are appropriate personalized models since they retain the genetic heritage of the donor. In comparison to other in vitro models, iPSC-derived organoids present advantages in terms of versatility, patient-specificity, and ethical issues. This review aims to provide an updated report of the employment of iPSCs, and 2D and 3D models derived from these, for the study of ADRs. This article is categorized under: Cancer > Stem Cells and Development.

Biomarker discovery in acetaminophen hepatotoxicity: leveraging single-cell transcriptomics and mechanistic insight

INTRODUCTION

Acetaminophen (APAP) overdose is the leading cause of drug-induced liver injury and can cause a rapid progression to acute liver failure (ALF). Therefore, the identification of prognostic biomarkers to determine which patients will require a liver transplant is critical for APAP-induced ALF.

AREAS COVERED

We begin by relating the mechanistic investigations in mouse models of APAP hepatotoxicity to the human APAP overdose pathophysiology. We draw insights from the established sequence of molecular events in mice to understand the progression of events in the APAP overdose patient. Through this mechanistic understanding, several new biomarkers, such as CXCL14, have recently been evaluated. We also explore how single-cell RNA sequencing, spatial transcriptomics, and other omics approaches have been leveraged for identifying novel biomarkers and how these approaches will continue to push the field of biomarker discovery forward.

EXPERT OPINION

Recent investigations have elucidated several new biomarkers or combination of markers such as CXCL14, a regenerative miRNA signature, a cell death miRNA signature, hepcidin, LDH, CPS1, and FABP1. While these biomarkers are promising, they all require further validation. Larger cohort studies analyzing these new biomarkers in the same patient samples, while adding these candidate biomarkers to prognostic models will further support their clinical utility.

Network Pharmacology Prediction and Experimental Validation of Ferulic Acid’s Protective Effects against Diclofenac‐Induced Liver Injury

Despite being one of the most consumed analgesics worldwide, liver injury is an adverse effect of diclofenac (DF). In pursuit of reliable hepatoprotective natural remedies, this study aimed to investigate the potential protective effect of ferulic acid (FA) and its mechanism against DF‐induced liver injury. Various network databases and datasets were used to collect targets corresponding to FA and DF‐induced liver injury. Enrichment analyses of common targets were performed, a protein‐protein interaction (PPI) network was constructed, the hub genes were identified, and the upstream miRNA interacting with the top hub gene was later predicted. A DF‐induced liver injury rat model was established to verify FA’s protective effects, and the selected hub gene expression level with its upstream regulatory miRNA and a downstream set of targets was examined to elucidate the underlying mechanism. A total of 18 genes were identified as potential targets of FA to protect against DF‐induced liver injury. Data from the enrichment and PPI analyses and the prediction of the upstream miRNAs indicated that the most worthwhile pair to study was miR‐296‐5p/Jun. In vivo findings showed that coadministration of FA significantly reduced the DF‐induced alterations in the liver function indices, oxidative stress, and liver histology. Mechanistically, FA downregulated the expression of Jun, Bim, Bax, Casp3, IL‐1β, IL‐6, and TNF‐α, whereas it upregulated the expression of rno‐miR‐296‐5p and Bcl2. In conclusion, combining network pharmacology and an in vivo study revealed that miR‐296‐5p/Jun axis could mediate the mitigative effect of FA against DF‐induced liver injury.

Modulation of the HIF-1α-NCOA4-FTH1 Signaling Axis Regulating Ferroptosis-induced Hepatic Stellate Cell Senescence to Explore the Anti-hepatic Fibrosis Mechanism of Curcumol

INTRODUCTION

Senescence of activated hepatic stellate cells (HSC) reduces extracellular matrix expression to reverse liver fibrosis. Ferroptosis is closely related to cellular senescence, but its regulatory mechanisms need to be further investigated. The iron ions weakly bound to ferritin in the cell are called labile iron pool (LIP), and together with ferritin, they maintain cellular iron homeostasis and regulate the cell's sensitivity to ferroptosis.

METHODS

We used lipopolysaccharide (LPS) to construct a pathological model group and divided the hepatic stellate cells into a blank group, a model group, and a curcumol 12.5 mg/L group, a curcumol 25 mg/L group, and a curcumol 50 mg/L group. HIF-1α-NCOA4- FTH1 signalling axis, ferroptosis and cellular senescence were detected by various cellular molecular biology experiments.

RESULT

We found that curcumol could induce hepatic stellate cell senescence by promoting iron death in hepatic stellate cells. Curcumol induced massive deposition of iron ions in hepatic stellate cells by activating the HIF-1α-NCOA4-FTH1 signalling axis, which further led to iron overload and lipid peroxidation-induced ferroptosis. Interestingly, our knockdown of HIF-1α rescued curcumol-induced LIP and iron deposition in hepatic stellate cells, suggesting that HIF-1α is a key target of curcumol in regulating iron metabolism and ferroptosis. We were able to rescue curcumol-induced hepatic stellate cell senescence when we reduced LIP and iron ion deposition using iron chelators.

CONCLUSION

Overall, curcumol induces ferroptosis and cellular senescence by increasing HIF-1α expression and increasing NCOA4 interaction with FTH1, leading to massive deposition of LIP and iron ions, which may be the molecular biological mechanism of its anti-liver fibrosis.

Screening of Prospective Antiallergic Compound as FcεRI Inhibitors and Its Antiallergic Efficacy Through Immunoinformatics Approaches

The occurrence of allergy, a type I hypersensitivity reaction, is rising exponentially all over the world. Sometimes, allergy proves to be fatal for atopic patients, due to the occurrence of anaphylaxis. This study is aimed to find an anti-allergic agent that can inhibit the binding of IgE to Human High Affinity IgE Receptor (FCεRI), thereby preventing the degranulation of mast cells. A considerable number of potential anti-allergic compounds were assessed for their inhibitory strength through ADMET studies. AUTODOCK was used for estimating the binding energy between anti-allergic compounds and FCεRI, along with the interacting amino acids. The docked pose showing favorable binding energy was subjected to molecular dynamics simulation study. Marrubiin, a diterpenoid lactone from Lamiaceae, and epicatechin-3-gallate appears to be effective in blocking the Human High Affinity IgE Receptor (FCεRI). This in-silico study proposes the use of marrubiin and epicatechin-3-gallate, in the downregulation of allergic responses. Due to the better inhibition constant, future direction of this study is to analyze the safety and efficacy of marrubiin in anti-allergic activities through in-vivo clinical human trials.

Drug induced liver injury - a 2023 update

Drug-Induced Liver Injury (DILI) constitutes hepatic damage attributed to drug exposure. DILI may be categorized as hepatocellular, cholestatic or mixed and might also involve immune responses. When DILI occurs in dose-dependent manner, it is referred to as intrinsic, while if the injury occurs spontaneously, it is termed as idiosyncratic. This review predominately focused on idiosyncratic liver injury. The established molecular mechanisms for DILI include (1) mitochondria dysfunction, (2) increased reactive oxygen species levels, (3) presence of elevated apoptosis and necrosis, (4) and bile duct injuries associated with immune mediated pathways. However, it should be emphasized that the underlying mechanisms responsible for DILI are still unknown. Prevention strategies are critical as incidences occur frequently, and treatment options are limited once the injury has developed. The aim of this review was to utilize retrospective cohort studies from across the globe to gain insight into epidemiological patterns. This review considers (1) what is currently known regarding the mechanisms underlying DILI, (2) discusses potential risk factors and (3) implications of the coronavirus pandemic on DILI presentation and research. Future perspectives are also considered and discussed and include potential new biomarkers, causality assessment and reporting methods.

Glutamate dehydrogenase combined with ferrochelatase as a biomarker of liver injury induced by antituberculosis drugs

AIMS

To explore the potential value of serum glutamate dehydrogenase (GLDH), ferrochelatase (FECH), heme oxygenase-1 (HO-1) and glutathione-S-transferase-α (GST-α) as diagnostic biomarkers for liver injury caused by antituberculosis drugs.

METHODS

We established a rat model of isoniazide-induced liver injury and recruited 122 hospitalized tuberculosis patients taking antituberculosis drugs. We detected the concentration of GLDH, FECH, HO-1 and GST-α by enzyme-linked immunosorbent assay. GraphPad Prism8 and SPSS 26.0 were used for statistical analysis.

RESULTS

In the rat model, serum GLDH concentration gradually increased during isoniazid (INH) administration, while serum FECH, HO-1 and GST-α concentrations significantly increased after INH administration was stopped. The receiver operating characteristic curve showed that the areas under the curve (AUCs) of serum GLDH and FECH for the diagnosis of anti-tuberculosis (TB) drug-induced liver injury (anti-TB-DILI) were 0.7692 (95% confidence interval [CI] 0.5442-0.9943) and 0.7284 (95% CI 0.4863-0.9705) and the diagnostic accuracies were 81.25% and 78.79%, respectively. In clinical research, the AUCs of GLDH and FECH were 0.9124 (95% CI 0.8380-0.9867) and 0.6634 (95% CI 0.5391-0.7877), and the optimal thresholds were 10.40 mIU/mL and 1.304 ng/mL, respectively. The diagnostic accuracy, specificity and positive predictive value (PPV) of GLDH were 82.61%, 79.38% and 47.22%. We performed a joint diagnostic test for GLDH and FECH. The diagnostic accuracy (90.43%), specificity (91.75%) and PPV (65.21%) of serial tests were better than for GLDH and FECH alone.

CONCLUSIONS

GLDH in the diagnosis of liver injury induced by anti-TB drugs has high sensitivity, but low specificity and low PPV. The combination of GLDH and FECH could significantly improve the specificity, PPV and diagnostic accuracy, and reduce the false-positive rate of anti-TB-DILI.

Serum levels of IL-6/IL-10/GLDH may be early recognition markers of anti-tuberculosis drugs (ATB) -induced liver injury

To explore the potential value of serum glutamate dehydrogenase (GLDH) combined with inflammatory cytokines as diagnostic biomarkers for anti-tuberculosis drug -induced liver injury (ATB-DILI). We collected the residual serum from the patients who met the criteria after liver function tests. We have examined these parameters including GLDH which were determined by enzyme-linked immunosorbent assay and cytokines which were determined by cytokine combination detection kit. Multivariate logistics stepwise forward regression was applied to establish regression models. A total of 138 tuberculosis patients were included in the diagnostic markers study of ATB-DILI, including normal liver function group (n = 108) and ATB-DILI group(n = 30). Serum GLDH, IL-6 and IL-10 levels were significantly increased in the ATB-DILI group. Receiver operating characteristic curve (ROC) curve showed that the area under curve (AUC) of serum GLDH, IL-6 and IL-10 for the diagnosis of ATB-DILI were 0.870, 0.714 and 0.811, respectively. In logistic regression modeling, the AUC of GLDH combined with IL-10 as an ATB-DILI marker is 0.912. Serum IL-6、IL-10 and GLDH levels began to rise preceded the increase in ALT by 7 days, with significant differences in IL-6 compared with 7 days. Serum GLDH, IL-6 and IL-10 levels were correlated with the severity of liver injury. In conclusion, we found that GLDH, IL-6 and IL-10 alone as diagnostic markers of ATB-DILI had good diagnostic efficacy. Logistic regression model established by GLDH and IL-10 had better diagnostic efficacy and IL-6 may be an early predictor of liver injury in the setting of ATB poisoning.

Antioxidant-Based Preventive Effect of Phytochemicals on Anticancer Drug-Induced Hepatotoxicity

Significance: Drug-induced liver injury (DILI) or hepatotoxicity has been a hot issue to overcome on the safety and physiological function of the liver, since it is known to have biochemical, cellular, immunological, and molecular alterations in the liver mainly induced by alcohol, chemicals, drugs, heavy metals, and genetic factors. Recently efficient therapeutic and preventive strategies by some phytochemicals are of interest, targeting oxidative stress-mediated hepatotoxicity alone or in combination with anticancer drugs. Recent Advances: To assess DILI, the variety of in vitro and in vivo animal models has been developed mainly by using carbon tetrachloride, d-galactosamine, acetaminophen, and lipopolysaccharide. Also, the mechanisms on hepatotoxicity by several drugs and herbs have been explored in detail. Recent studies reveal that antioxidants including vitamins and some phytochemicals were reported to prevent against DILI. Critical Issues: Antioxidant therapy with some phytochemicals is noteworthy, since oxidative stress is critically involved in DILI via production of chemically reactive oxygen species or metabolites, impairment of mitochondrial respiratory chain, and induction of redox cycling. Future Directions: For efficient antioxidant therapy, DILI susceptibility, Human Leukocyte Antigen genetic factors, biomarkers, and pathogenesis implicated in hepatotoxicity should be further explored in association with oxidative stress-mediated signaling, while more randomized preclinical and clinical trials are required with optimal safe doses of drugs and/or phytochemicals alone or in combination for efficient clinical practice along with the development of advanced DILI diagnostic tools.

Differentiated modulation of signaling molecules AMPK and SIRT1 in experimentally drug-induced hepatocyte injury

AIM

Currently available medicines have little to offer in terms of supporting the regeneration of injured hepatic cells. Previous experimental studies have shown that resveratrol and metformin, less specific activators of AMP-activated protein kinase (AMPK) and sirtuin 1 (SIRT1), can effectively attenuate acute liver injury. The aim of this experimental study was to elucidate whether modulation of AMPK and SIRT1 activity can modify drug/paracetamol (APAP)-induced hepatocyte damage in vitro.

METHODS

Primary rat hepatocytes were pretreated with mutual combinations of specific synthetic activators and inhibitors of SIRT1 and AMPK and followed by a toxic dose of APAP. At the end of cultivation, medium samples were collected for biochemical analysis of alanine-aminotransferase and nitrite levels. Hepatocyte viability, thiobarbituric reactive substances, SIRT1 and AMPK activity and protein expression were also assessed.

RESULTS

The harmful effect of APAP was associated with decreased AMPK and SIRT1 activity and protein expression alongside enhanced oxidative stress in hepatocytes. The addition of AMPK activator (AICAR) or SIRT1 activator (CAY10591) significantly attenuated the deleterious effects of AMPK inhibitor (Compound C) on the hepatotoxicity of APAP. Furthermore, CAY10591 but not AICAR markedly decreased the deleterious effect of APAP in combination with SIRT1 inhibitor (EX-527).

CONCLUSION

Our findings demonstrate that decreased AMPK activity is associated with the hepatotoxic effect of APAP which can be significantly attenuated by the administration of a SIRT1 activator. These findings suggest that differentiated modulation of AMPK and SIRT1 activity could therefore provide an interesting and novel therapeutic opportunity in the future to combat hepatocyte injury.

MicroRNAs: Small molecules with big impacts in liver injury

A type of small noncoding RNAs known as microRNAs (miRNAs) fine-tune gene expression posttranscriptionally by binding to certain messenger RNA targets. Numerous physiological processes in the liver, such as differentiation, proliferation, and apoptosis, are regulated by miRNAs. Additionally, there is growing evidence that miRNAs contribute to liver pathology. Extracellular vesicles like exosomes, which contain secreted miRNAs, may facilitate paracrine and endocrine communication between various tissues by changing the gene expression and function of distal cells. The use of stable miRNAs as noninvasive biomarkers was made possible by the discovery of these molecules in body fluids. Circulating miRNAs reflect the conditions of the liver that are abnormal and may serve as new biomarkers for the early detection, prognosis, and evaluation of liver pathological states. miRNAs are appealing therapeutic targets for a range of liver disease states because altered miRNA expression is associated with deregulation of the liver's metabolism, liver damage, liver fibrosis, and tumor formation. This review provides a comprehensive review and update on miRNAs biogenesis pathways and mechanisms of miRNA-mediated gene silencing. It also outlines how miRNAs affect hepatic cell proliferation, death, and regeneration as well as hepatic detoxification. Additionally, it highlights the diverse functions that miRNAs play in the onset and progression of various liver diseases, including nonalcoholic fatty liver disease, alcoholic liver disease, fibrosis, hepatitis C virus infection, and hepatocellular carcinoma. Further, it summarizes the diverse liver-specific miRNAs, illustrating the potential merits and possible caveats of their utilization as noninvasive biomarkers and appealing therapeutic targets for liver illnesses.

Noninvasive biomarkers for the diagnosis and management of autoimmune hepatitis

Autoimmune hepatitis (AIH) is a rare disease of unclear etiology characterized by loss of self-tolerance that can lead to liver injury, cirrhosis, and acute liver failure. First-line treatment consists of systemic corticosteroids, or budesonide, and azathioprine, to which most patients are initially responsive, although predictors of response are lacking. Relapses are very common, correlate with histological activity despite normal serum transaminases, and increase hepatic fibrosis. Furthermore, current regimens lead to adverse effects and reduced quality of life, whereas medication titration is imprecise. Biomarkers that can predict the clinical course of disease, identify patients at elevated risk for relapse, and improve monitoring and medication dosing beyond current practice would have high clinical value. Herein, we review novel candidate biomarkers in adult and pediatric AIH based on prespecified criteria, including gene expression profiles, proteins, metabolites, and immune cell phenotypes in different stages of AIH. We also discuss biomarkers relevant to AIH from other immune diseases. We conclude with proposed future directions in which biomarker implementation into clinical practice could lead to advances in personalized therapeutic management of AIH.

Illuminating the hepatotoxic mechanism of norcantharidin in rats using metabolomics analysis

Background

Norcantharidin (NCTD) has multiple antitumor effects. However, NCTD can induce significant hepatotoxicity and the mechanism of hepatotoxicity is not clear for now.

Objective

This study aimed to explore the hepatotoxicity of NCTD in rat by ultra-performance liquid chromatography (UPLC) quadrupole time-of-flight (Q-TOF)-MS (UPLC/Q-TOF-MS) metabolomics.

Results

Serum biochemical indices including alanine aminotransferase (ALT) and total bilirubin (T-BIL) were significantly increased. Histopathological and ultrastructure results revealed that hepatocytes were damaged. Furthermore, the metabolomics results showed that 11 metabolites in serum and 8 metabolites in liver were differential metabolites for NCTD hepatotoxicity. Four metabolic pathways including the sphingolipid metabolism, purine metabolism, arachidonic acid metabolism, and glycerophospholipid metabolism were the key metabolic pathways related to NCTD hepatotoxicity.

Conclusion

The metabolomics analysis in this study reveal new clues on the hepatotoxicity mechanism of NCTD in rats. These findings have potential applications in the toxicity study of NCTD.

Highlights of the drug-induced liver injury literature for 2021

INTRODUCTION

In 2021, over 3,000 articles on Drug-Induced Liver Injury (DILI) were published, nearly doubling the annual number compared to 2011. This review selected DILI articles from 2021 we felt held the greatest interest and clinical relevance.

AREAS COVERED

A literature search was conducted using PubMed between 1 March 2021 and 28 February 2022. 86 articles were included. This review discusses new and established cases of hepatotoxins, including new FDA approvals and COVID-19 therapeutics. Developments in biomarkers and causality assessment methods are discussed. Updates from registries are also explored.

EXPERT OPINION

DILI diagnosis and prognostication remain challenging. Roussel Uclaf Causality Assessment Method (RUCAM) is the best option for determining causality and has been increasingly accepted by clinicians. Revised Electronic Causality Assessment Method (RECAM) may be more user-friendly and accurate but requires further validation. Quantitative systems pharmacology methods, such as DILIsym, are increasingly used to predict hepatotoxicity. Oncotherapeutic agents represent many newly approved and described causes of DILI. Such hepatotoxicity is deemed acceptable relative to the benefit these drugs offer. Drugs developed for non-life-threatening disorders may not show a favorable benefit-to-risk ratio and will be more difficult to approve. As the COVID-19 landscape evolves, its effect on DILI deserves further investigation.

Screening of Biomarkers and Toxicity Mechanisms of Rifampicin-Induced Liver Injury Based on Targeted Bile Acid Metabolomics

Rifampicin (RIF) is a critical first-line drug for tuberculosis. However, long-term or high-dose treatment with RIF can induce severe liver injury; the underlying mechanism of this effect has not yet been clarified. This study was performed to screen reliable and sensitive biomarkers in serum bile acids (BAs) using targeted BA metabolomics and evaluate the toxicity mechanisms underlying RIF-induced liver injury through the farnesoid x receptor (Fxr)-multidrug resistance-associated proteins (Mrps) signaling pathway. Thirty-two Institute of Cancer Research mice were randomly divided into four groups, and normal saline, isoniazid 75 mg/kg + RIF 177 mg/kg (RIF-L), RIF-L, or RIF 442.5 mg/kg (RIF-H) was orally administered by gavage for 21 days. After treatment, changes in serum biochemical parameters, hepatic pathological conditions, BA levels, Fxr expression, and BA transporter levels were measured. RIF caused notable liver injury and increased serum cholic acid (CA) levels. Decline in the serum secondary BAs (deoxycholic acid, lithocholic acid, taurodeoxycholic acid, and tauroursodeoxycholic acid) levels led to liver injury in mice. Serum BAs were subjected to metabolomic assessment using partial least squares discriminant and receiver operating characteristic curve analyses. CA, DCA, LCA, TDCA, and TUDCA are potential biomarkers for early detection of RIF-induced liver injury. Furthermore, RIF-H reduced hepatic BA levels and elevated serum BA levels by suppressing the expression of Fxr and Mrp2 messenger ribonucleic acid (mRNA) while inducing that of Mrp3 and Mrp4 mRNAs. These findings provide evidence for screening additional biomarkers based on targeted BA metabolomics and provide further insights into the pathogenesis of RIF-induced liver injury.

How to Foster 'New Approach Methodology' Toxicologists

The need to reduce, refine and replace animal experimentation has led to a boom in the establishment of new approach methodologies (NAMs). This promising trend brings the hope that the replacement of animals by using NAMs will become increasingly accepted by regulators, included in legislation, and consequently more-often implemented by industry. The majority of NAMs, however, are still not very well understood, either due to the complexity of the applied approach or the data analysis workflow. A potential solution to this problem is the provision of better educational resources to scientists new to the area - showcasing the added value of NAMs and outlining various ways of overcoming issues associated with knowledge gaps. In this paper, the educational exchange between four institutions - namely, two universities and two SMEs - via a series of video training sessions, is described. The goal of this exchange was to showcase an exemplary event to help introduce scientists to non-animal approaches, and to actively support the development of resources enabling the use of alternatives to laboratory animals.

Targeting tryptophan metabolism reveals Clematichinenoside AR alleviates triptolide-induced hepatotoxicity

Liver toxicity induced by Triptolide (TP) has limited its clinical application on rheumatoid arthritis (RA). Saponins have been proved as an efficacious remedy to mitigate hepatotoxicity. However, the mechanism of reducing hepatotoxicity by saponins intervention remains incompletely characterized. Tryptophan (Trp) metabolites activate transcriptional regulators to mediate host detoxification responses. Our study aimed to investigate whether Clematichinenoside AR (C-AR) could attenuate TP-induced liver damage by regulating Trp metabolism. We used targeted metabolomics to quantify Trp metabolites in the serum and liver samples of collagen-induced arthritis rats treated by TP. Multiple comparison analyses helped the evaluation of promising biomarkers. The pronounced changed levels of Trp, indole acetic acid, and indole-3-carboxaldehyde in the serum and indole acetic acid, indole, and tryptamine in the liver are relevant to TP-induced liver injury. Intervention with C-AR could relieve TP-induced hepatotoxicity evidenced by ameliorative serum parameters and hepatic histology. In addition, C-AR regulated the levels of these indoles biomarker candidates to normal. Therapeutic modulation with natural compounds might be a useful clinical strategy to ameliorate toxicity induced by TP. Deciphering Trp metabolism will facilitate a better understanding of the pathogenesis of diseases and drug responding.

Metabolic profiling of lysophosphatidylcholines in chlorpromazine hydrochloride- and N-acetyl-p-amino-phenoltriptolide-induced liver injured rats based on ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry

Chlorpromazine hydrochloride (CH) and N-acetyl-p-amino-phenoltriptolide (APAP) are typical acentral dopamine receptor antagonists and antipyretic analgesics in clinical applications, respectively. However, it has been reported that these 2 drugs could cause liver damage. Lysophosphatidylcholines (LPCs) have multiple physiological functions and are metabolized primarily in the liver, where it undergoes significant changes when the liver is damaged. In the study, 15 LPCs in the rat serum with CH- and APAP-induced liver injury were quantified based on ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry, and multivariate statistical analyses including principal component analysis (PCA) and orthogonal partial least squares discriminate analysis (OPLS-DA) were combined to understand CH- and APAP-induced liver injury from the perspective of LPC metabolic profiling. The quantitative results showed that there were significant changes in 10 LPCs and 5 LPCs after CH- and APAP-administration, separately. The results of PCA and OPLS-DA indicated that CH- and APAP-induced liver injury could be well distinguished by the LPC metabolic profiling, and 7 LPCs and 1 LPC biomarkers that could characterize CH- and APAP-induced liver damage in turn had been screened. This study will not only provide a new perspective for the clinical diagnosis of CH- and APAP-induced liver injury, but also offer a reference for further study of their hepatotoxicity mechanisms.

Redrawing the map to novel DILI biomarkers in circulation: Where are we, where should we go, and how can we get there?

Circulating biomarkers of drug-induced liver injury (DILI) have been a focus of research in hepatology over the last decade, and several novel DILI biomarkers that hold promise for certain applications have been identified. For example, glutamate dehydrogenase holds promise as a specific biomarker of liver injury in patients with concomitant muscle damage. It may also be a specific indicator of mitochondrial damage. In addition, microRNA-122 is sensitive for early detection of liver injury in acetaminophen overdose patients. However, recent events in the field of DILI biomarker research have provided us with an opportunity to step back, consider how biomarker discovery has been done thus far, and determine how to move forward in a way that will optimize the discovery process. This is important because major challenges remain in the DILI field and related areas that could be overcome in part by new biomarkers. In this short review, we briefly describe recent progress in DILI biomarker discovery and development, identify current needs, and suggest a general approach to move forward.

Using an Automated Algorithm to Identify Potential Drug-Induced Liver Injury Cases in a Pharmacovigilance Database

INTRODUCTION

Drug-induced liver injury (DILI) is the most frequent cause of acute liver failure in North America and Europe, but it is often missed because of unstandardized diagnostic methods and criteria. This study aimed to develop and validate an automated algorithm to identify potential DILI cases in routine pharmacovigilance (PV) activities.

METHODS

Post-marketing hepatic adverse events reported for a potentially hepatotoxic drug in a global PV database from 19 March 2017 to 18 June 2018 were assessed manually and with the automated algorithm. The algorithm provided case assessments by applying pre-specified criteria to all case data and narratives simultaneously.

RESULTS

A total of 1456 cases were included for analysis and assessed manually. Sufficient data for algorithm assessment were available for 476 cases (32.7%). Of these cases, manual assessment identified 312 (65.5%) potential DILI cases while algorithm assessment identified 305 (64.1%) potential DILI cases. Comparison of manual and algorithm assessments demonstrated a sensitivity of 97.8% and a specificity of 79.3% for the algorithm. Given the prevalence of potential DILI cases in the population studied, the algorithm was calculated to have positive predictive value 56.3% and negative predictive value 99.2%. The time required for manual review compared to algorithm review suggested that application of the algorithm prior to manual screening would have resulted in a time savings of 42.2%.

CONCLUSION

An automated algorithm to identify potential DILI cases was developed and successfully implemented. The algorithm demonstrated a high sensitivity, a high negative predictive value, along with significant efficiency and utility in a real-time PV database.

Metabolomic analysis to discriminate drug-induced liver injury (DILI) phenotypes

Drug-induced liver injury (DILI) is an adverse toxic hepatic clinical reaction associated to the administration of a drug that can occur both at early clinical stages of drug development, as well after normal clinical usage of approved drugs. Because of its unpredictability and clinical relevance, it is of medical concern. Three DILI phenotypes (hepatocellular, cholestatic, and mixed) are currently recognized, based on serum alanine aminotransferase (ALT) and alkaline phosphatase (ALP) values. However, this classification lacks accuracy to distinguish among the many intermediate mixed types, or even to estimate the magnitude and progression of the injury. It was found desirable to have additional elements for better evaluation criteria of DILI. With this aim, we have examined the serum metabolomic changes occurring in 79 DILI patients recruited and monitored using established clinical criteria, along the course of the disease and until recovery. Results revealed that free and conjugated bile acids, and glycerophospholipids were among the most relevant metabolite classes for DILI phenotype characterization. Using an ensemble of PLS-DA models, metabolomic information was integrated into a ternary diagram to display the disease phenotype, the severity of the liver damage, and its progression. The modeling implemented and the use of such compiled information in an easily understandable and visual manner facilitates a straightforward DILI phenotyping and allow to monitor its progression and recovery prediction, usefully complementing the concise information drawn out by the ALT and ALP classification.

Immune-Mediated Drug-Induced Liver Injury: Immunogenetics and Experimental Models

Drug-induced liver injury (DILI) is a challenging clinical event in medicine, particularly because of its ability to present with a variety of phenotypes including that of autoimmune hepatitis or other immune mediated liver injuries. Limited diagnostic and therapeutic tools are available, mostly because its pathogenesis has remained poorly understood for decades. The recent scientific and technological advancements in genomics and immunology are paving the way for a better understanding of the molecular aspects of DILI. This review provides an updated overview of the genetic predisposition and immunological mechanisms behind the pathogenesis of DILI and presents the state-of-the-art experimental models to study DILI at the pre-clinical level.

Oxidative Stress in Drug-Induced Liver Injury (DILI): From Mechanisms to Biomarkers for Use in Clinical Practice

Idiosyncratic drug-induced liver injury (DILI) is a type of hepatic injury caused by an uncommon drug adverse reaction that can develop to conditions spanning from asymptomatic liver laboratory abnormalities to acute liver failure (ALF) and death. The cellular and molecular mechanisms involved in DILI are poorly understood. Hepatocyte damage can be caused by the metabolic activation of chemically active intermediate metabolites that covalently bind to macromolecules (e.g., proteins, DNA), forming protein adducts-neoantigens-that lead to the generation of oxidative stress, mitochondrial dysfunction, and endoplasmic reticulum (ER) stress, which can eventually lead to cell death. In parallel, damage-associated molecular patterns (DAMPs) stimulate the immune response, whereby inflammasomes play a pivotal role, and neoantigen presentation on specific human leukocyte antigen (HLA) molecules trigger the adaptive immune response. A wide array of antioxidant mechanisms exists to counterbalance the effect of oxidants, including glutathione (GSH), superoxide dismutase (SOD), catalase, and glutathione peroxidase (GPX), which are pivotal in detoxification. These get compromised during DILI, triggering an imbalance between oxidants and antioxidants defense systems, generating oxidative stress. As a result of exacerbated oxidative stress, several danger signals, including mitochondrial damage, cell death, and inflammatory markers, and microRNAs (miRNAs) related to extracellular vesicles (EVs) have already been reported as mechanistic biomarkers. Here, the status quo and the future directions in DILI are thoroughly discussed, with a special focus on the role of oxidative stress and the development of new biomarkers.

Comparing Machine Learning Algorithms for Predicting Drug-Induced Liver Injury (DILI)

Drug-induced liver injury (DILI) is one the most unpredictable adverse reactions to xenobiotics in humans and the leading cause of postmarketing withdrawals of approved drugs. To date, these drugs have been collated by the FDA to form the DILIRank database, which classifies DILI severity and potential. These classifications have been used by various research groups in generating computational predictions for this type of liver injury. Recently, groups from Pfizer and AstraZeneca have collated DILI in vitro data and physicochemical properties for compounds that can be used along with data from the FDA to build machine learning models for DILI. In this study, we have used these data sets, as well as the Biopharmaceutics Drug Disposition Classification System data set, to generate Bayesian machine learning models with our in-house software, Assay Central. The performance of all machine learning models was assessed through both the internal 5-fold cross-validation metrics and prediction accuracy of an external test set of compounds with known hepatotoxicity. The best-performing Bayesian model was based on the DILI-concern category from the DILIRank database with an ROC of 0.814, a sensitivity of 0.741, a specificity of 0.755, and an accuracy of 0.746. A comparison of alternative machine learning algorithms, such as k-nearest neighbors, support vector classification, AdaBoosted decision trees, and deep learning methods, produced similar statistics to those generated with the Bayesian algorithm in Assay Central. This study demonstrates machine learning models grouped in a tool called MegaTox that can be used to predict early-stage clinical compounds, as well as recent FDA-approved drugs, to identify potential DILI.

Drug-induced liver injury

Drug-induced liver injury (DILI), including herbal and dietary supplement hepatotoxicity, is often passed lightly; however, it can lead to the requirement of a liver transplant or may even cause death because of liver failure. Recently, the American College of Gastroenterology, Chinese Society of Hepatology and European Association for the Study of the Liver guidelines for the diagnosis and treatment of DILI have been established, and they will be helpful for guiding clinical treatment decisions. Roussel Uclaf Causality Assessment Method scoring is the most commonly used method to diagnose DILI; however, it has some limitations, such as poor validity and reproducibility. Recently, studies on new biomarkers have been actively carried out, which will help diagnose DILI and predict the prognosis of DILI. It is expected that the development of new therapies such as autophagy inducers and various other technologies of the fourth industrial revolution will be applicable to DILI research.