Metabolomic approaches in the discovery of potential urinary biomarkers of drug-induced liver injury (DILI)

Protective effects of Huang-Qi-Ge-Gen decoction against diabetic liver injury through regulating PI3K/AKT/Nrf2 pathway and metabolic profiling

ETHNOPHARMACOLOGICAL RELEVANCE

Huang-Qi-Ge-Gen decoction (HGD) is a traditional Chinese medicine prescription that has been used for centuries to treat "Xiaoke" (the name of diabetes mellitus in ancient China). However, the ameliorating effects of HGD on diabetic liver injury (DLI) and its mechanisms are not yet fully understood.

AIM OF THE STUDY

To elucidate the ameliorative effect of HGD on DLI and explore its material basis and potential hepatoprotective mechanism.

MATERIALS AND METHODS

A diabetic mice model was induced by feeding a high-fat diet and injecting intraperitoneally with streptozotocin (40 mg kg-1) for five days. After the animals were in confirmed diabetic condition, they were given HGD (3 or 12 g kg-1, i. g.) for 14 weeks. The effectiveness of HGD in treating DLI mice was evaluated by monitoring blood glucose and blood lipid levels, liver function, and pathological conditions. Furthermore, UPLC-MS/MS was used to identify the chemical component profile in HGD and absorption components in HGD-treated plasma. Network pharmacology and molecular docking were performed to predict the potential pathway of HGD intervention in DLI. Then, the results of network pharmacology were validated by examining biochemical parameters and using western blotting. Lastly, urine metabolites were analyzed by metabolomics strategy to explore the effect of HGD on the metabolic profile of DLI mice.

RESULTS

HGD exerted therapeutic potential against the disorders of glucose metabolism and lipid metabolism, liver dysfunction, liver steatosis, and fibrosis in a DLI model mice induced by HFD/STZ. A total of 108 chemical components in HGD and 18 absorption components in HGD-treated plasma were preliminarily identified. Network pharmacology and molecular docking results of the absorbed components in plasma indicated PI3K/AKT as a potential pathway for HGD to intervene in DLI mice. Further experiments verified that HGD markedly reduced liver oxidative stress in DLI mice by modulating the PI3K/AKT/Nrf2 signaling pathway. Moreover, 19 differential metabolites between normal and DLI mice were detected in urine, and seven metabolites could be significantly modulated back by HGD.

CONCLUSIONS

HGD could ameliorate diabetic liver injury by modulating the PI3K/AKT/Nrf2 signaling pathway and urinary metabolic profile.

Kynurenic Acid Plays a Protective Role in Hepatotoxicity Induced by HFPO-DA in Male Mice

Following its introduction as an alternative to perfluorooctanoic acid, hexafluoropropylene oxide dimer acid (HFPO-DA) has been extensively detected in various environmental matrices. Despite this prevalence, limited information is available regarding its hepatotoxicity biomarkers. In this study, toxicokinetic simulations indicated that under repeated treatment, HFPO-DA in mice serum reached a steady state by the 4th day. To assess its subacute hepatic effects and identify potential biomarkers, mice were administered HFPO-DA orally at doses of 0, 0.1, 0.5, 2.5, 12.5, or 62.5 mg/kg/d for 7 d. Results revealed that the lowest observed adverse effect levels were 0.5 mg/kg/d for hepatomegaly and 2.5 mg/kg/d for hepatic injury. Serum metabolomics analysis identified 34, 58, and 118 differential metabolites in the 0.1, 0.5, and 2.5 mg/kg/d groups, respectively, compared to the control group. Based on weighted gene coexpression network analysis, eight potential hepatotoxicity-related metabolites were identified; among them, kynurenic acid (KA) in mouse serum exhibited the highest correlation with liver injury. Furthermore, liver-targeted metabolomics analysis demonstrated that HFPO-DA exposure induced metabolic migration of the kynurenine pathway from KA to nicotinamide adenine dinucleotide, resulting in the activation of endoplasmic reticulum stress and the nuclear factor kappa-B signaling pathway. Notably, pretreatment with KA significantly attenuated liver injury induced by HFPO-DA exposure in mice, highlighting the pivotal roles of KA in the hepatotoxicity of HFPO-DA.

Molecularly Engineered Room-Temperature Phosphorescence for Biomedical Application: From the Visible toward Second Near-Infrared Window

Phosphorescence, characterized by luminescent lifetimes significantly longer than that of biological autofluorescence under ambient environment, is of great value for biomedical applications. Academic evidence of fluorescence imaging indicates that virtually all imaging metrics (sensitivity, resolution, and penetration depths) are improved when progressing into longer wavelength regions, especially the recently reported second near-infrared (NIR-II, 1000-1700 nm) window. Although the emission wavelength of probes does matter, it is not clear whether the guideline of "the longer the wavelength, the better the imaging effect" is still suitable for developing phosphorescent probes. For tissue-specific bioimaging, long-lived probes, even if they emit visible phosphorescence, enable accurate visualization of large deep tissues. For studies dealing with bioimaging of tiny biological architectures or dynamic physiopathological activities, the prerequisite is rigorous planning of long-wavelength phosphorescence, being aware of the cooperative contribution of long wavelengths and long lifetimes for improving the spatiotemporal resolution, penetration depth, and sensitivity of bioimaging. In this Review, emerging molecular engineering methods of room-temperature phosphorescence are discussed through the lens of photophysical mechanisms. We highlight the roles of phosphorescence with emission from visible to NIR-II windows toward bioapplications. To appreciate such advances, challenges and prospects in rapidly growing studies of room-temperature phosphorescence are described.

Recent developments and applications of ambient mass spectrometry imaging in pharmaceutical research: an overview

The application of ambient mass spectrometry imaging "MSI" is expanding in the areas of fundamental research on drug delivery and multiple phases of the process of identifying and developing drugs. Precise monitoring of a drug's pharmacological workflows, such as intake, distribution, metabolism, and discharge, is made easier by MSI's ability to determine the concentrations of the initiating drug and its metabolites across dosed samples without losing spatial data. Lipids, glycans, and proteins are just a few of the many phenotypes that MSI may be used to concurrently examine. Each of these substances has a particular distribution pattern and biological function throughout the body. MSI offers the perfect analytical tool for examining a drug's pharmacological features, especially in vitro and in vivo effectiveness, security, probable toxic effects, and putative molecular pathways, because of its high responsiveness in chemical and physical environments. The utilization of MSI in the field of pharmacy has further extended from the traditional tissue examination to the early stages of drug discovery and development, including examining the structure-function connection, high-throughput capabilities in vitro examination, and ex vivo research on individual cells or tumor spheroids. Additionally, an enormous array of endogenous substances that may function as tissue diagnostics can be scanned simultaneously, giving the specimen a highly thorough characterization. Ambient MSI techniques are soft enough to allow for easy examination of the native sample to gather data on exterior chemical compositions. This paper provides a scientific and methodological overview of ambient MSI utilization in research on pharmaceuticals.

Metabolomic Analysis of Pediatric Patients with Idiosyncratic Drug-Induced Liver Injury According to the Updated RUCAM

Hepatotoxicity, a common adverse drug effect, has been extensively studied in adult patients. However, it is equally important to investigate this condition in pediatric patients to develop personalized treatment strategies for children. This study aimed to identify plasma biomarkers that characterize hepatotoxicity in pediatric patients through an observational case-control study. Metabolomic analysis was conducted on 55 pediatric patients with xenobiotic liver toxicity and 88 healthy controls. The results revealed clear differences between the two groups. Several metabolites, including hydroxydecanoylcarnitine, octanoylcarnitine, lysophosphatidylcholine, glycocholic acid, and taurocholic acid, were identified as potential biomarkers (area under the curve: 0.817; 95% confidence interval: 0.696-0.913). Pathway analysis indicated involvement of primary bile acid biosynthesis and the metabolism of taurine and hypotaurine (p < 0.05). The findings from untargeted metabolomic analysis demonstrated an increase in bile acids in children with hepatotoxicity. The accumulation of cytotoxic bile acids should be further investigated to elucidate the role of these metabolites in drug-induced liver injury.

Spatiotemporal pharmacometabolomics based on ambient mass spectrometry imaging to evaluate the metabolism and hepatotoxicity of amiodarone in HepG2 spheroids

Three-dimensional (3D) cell spheroid models combined with mass spectrometry imaging (MSI) enables innovative investigation of in vivo-like biological processes under different physiological and pathological conditions. Herein, airflow-assisted desorption electrospray ionization-MSI (AFADESI-MSI) was coupled with 3D HepG2 spheroids to assess the metabolism and hepatotoxicity of amiodarone (AMI). High-coverage imaging of >1100 endogenous metabolites in hepatocyte spheroids was achieved using AFADESI-MSI. Following AMI treatment at different times, 15 metabolites of AMI involved in N-desethylation, hydroxylation, deiodination, and desaturation metabolic reactions were identified, and according to their spatiotemporal dynamics features, the metabolic pathways of AMI were proposed. Subsequently, the temporal and spatial changes in metabolic disturbance within spheroids caused by drug exposure were obtained via metabolomic analysis. The main dysregulated metabolic pathways included arachidonic acid and glycerophospholipid metabolism, providing considerable evidence for the mechanism of AMI hepatotoxicity. In addition, a biomarker group of eight fatty acids was selected that provided improved indication of cell viability and could characterize the hepatotoxicity of AMI. The combination of AFADESI-MSI and HepG2 spheroids can simultaneously obtain spatiotemporal information for drugs, drug metabolites, and endogenous metabolites after AMI treatment, providing an effective tool for in vitro drug hepatotoxicity evaluation.

Urine metabolomics and microbiome analyses reveal the mechanism of anti-tuberculosis drug-induced liver injury, as assessed for causality using the updated RUCAM: A prospective study

Background

Anti-tuberculosis drug-induced liver injury (ATB-DILI) is one of the most common adverse reactions that brings great difficulties to the treatment of tuberculosis. Thus, early identification of individuals at risk for ATB-DILI is urgent. We conducted a prospective cohort study to analyze the urinary metabolic and microbial profiles of patients with ATB-DILI before drug administration. And machine learning method was used to perform prediction model for ATB-DILI based on metabolomics, microbiome and clinical data.

Methods

A total of 74 new TB patients treated with standard first-line anti-TB treatment regimens were enrolled from West China Hospital of Sichuan University. Only patients with an updated RUCAM score of 6 or more were accepted in this study. Nontargeted metabolomics and microbiome analyses were performed on urine samples prior to anti-tuberculosis drug ingestion to screen the differential metabolites and microbes between the ATB-DILI group and the non-ATB-DILI group. Integrating electronic medical records, metabolomics, and microbiome data, four machine learning methods was used, including random forest algorithm, artificial neural network, support vector machine with the linear kernel and radial basis function kernel.

Results

Of all included patients, 69 patients completed follow-up, with 16 (23.19%) patients developing ATB-DILI after antituberculosis treatment. Finally, 14 ATB-DILI patients and 30 age- and sex-matched non-ATB-DILI patients were subjected to urinary metabolomic and microbiome analysis. A total of 28 major differential metabolites were screened out, involving bile secretion, nicotinate and nicotinamide metabolism, tryptophan metabolism, ABC transporters, etc. Negativicoccus and Actinotignum were upregulated in the ATB-DILI group. Multivariate analysis also showed significant metabolic and microbial differences between the non-ATB-DILI and severe ATB-DILI groups. Finally, the four models showed high accuracy in predicting ATB-DILI, with the area under the curve of more than 0.85 for the training set and 1 for the validation set.

Conclusion

This study characterized the metabolic and microbial profile of ATB-DILI risk individuals before drug ingestion for the first time. Metabolomic and microbiome characteristics in patient urine before anti-tuberculosis drug ingestion may predict the risk of liver injury after ingesting anti-tuberculosis drugs. Machine learning algorithms provides a new way to predict the occurrence of ATB-DILI among tuberculosis patients.

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.

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.

Capillary ultrahigh-pressure liquid chromatography-mass spectrometry for fast and high resolution metabolomics separations

LC-MS is an important tool for metabolomics due its high sensitivity and broad metabolite coverage. The goal of improving resolution and decreasing analysis time in HPLC has led to the use of 5 - 15 cm long columns packed with 1.7 - 1.9 µm particles requiring pressures of 8 - 12 kpsi. We report on the potential for capillary LC-MS based metabolomics utilizing porous C18 particles down to 1.1 µm diameter and columns up to 50 cm long with an operating pressure of 35 kpsi. Our experiments show that it is possible to pack columns with 1.1 µm porous particles to provide predicted improvements in separation time and efficiency. Using kinetic plots to guide the choice of column length and particle size, we packed 50 cm long columns with 1.7 µm particles and 20 cm long columns with 1.1 µm particles, which should produce equivalent performance in shorter times. Columns were tested by performing isocratic and gradient LC-MS analyses of small molecule metabolites and extracts from plasma. These columns provided approximately 100,000 theoretical plates for metabolite standards and peak capacities over 500 in 100 min for a complex plasma extract with robust interfacing to MS. To generate a given peak capacity, the 1.1 µm particles in 20 cm columns required roughly 75% of the time as 1.7 µm particles in 50 cm columns with both operated at 35 kpsi. The 1.1 µm particle packed columns generated a given peak capacity nearly 3 times faster than 1.7 µm particles in 15 cm columns operated at ~10 kpsi. This latter condition represents commercial state of the art for capillary LC. To consider practical benefits for metabolomics, the effect of different LC-MS variables on mass spectral feature detection was evaluated. Lower flow rates (down to 700 nL/min) and larger injection volumes (up to 1 µL) increased the features detected with modest loss in separation performance. The results demonstrate the potential for fast and high resolution separations for metabolomics using 1.1 µm particles operated at 35 kpsi for capillary LC-MS.

Genome-Scale Model-Based Identification of Metabolite Indicators for Early Detection of Kidney Toxicity

Identifying early indicators of toxicant-induced organ damage is critical to provide effective treatment. To discover such indicators and the underlying mechanisms of toxicity, we used gentamicin as an exemplar kidney toxicant and performed systematic perturbation studies in Sprague Dawley rats. We obtained high-throughput data 7 and 13 h after administration of a single dose of gentamicin (0.5 g/kg) and identified global changes in genes in the liver and kidneys, metabolites in the plasma and urine, and absolute fluxes in central carbon metabolism. We used these measured changes in genes in the liver and kidney as constraints to a rat multitissue genome-scale metabolic network model to investigate the mechanism of gentamicin-induced kidney toxicity and identify metabolites associated with changes in tissue gene expression. Our experimental analysis revealed that gentamicin-induced metabolic perturbations could be detected as early as 7 h postexposure. Our integrated systems-level analyses suggest that changes in kidney gene expression drive most of the significant metabolite alterations in the urine. The analyses thus allowed us to identify several significantly enriched injury-specific pathways in the kidney underlying gentamicin-induced toxicity, as well as metabolites in these pathways that could serve as potential early indicators of kidney damage.

Drug-Induced Liver Injury: Highlights of the Recent Literature

Drug-induced liver injury (DILI), herbal-induced liver injury, and herbal and dietary supplement (HDS)-induced liver injury are an important aspect of drug safety. Knowledge regarding responsible drugs, mechanisms, risk factors, and the diagnostic tools to detect liver injury have continued to grow in the past year. This review highlights what we considered the most significant publications from among more than 1800 articles relating to liver injury from medications, herbal products, and dietary supplements in 2017 and 2018. The US Drug-Induced Liver Injury Network (DILIN) prospective study highlighted several areas of ongoing study, including the potential utility of human leukocyte antigens and microRNAs as DILI risk factors and new data on racial differences, the role of alcohol consumption, factors associated with prognosis, and updates on the clinical signatures of autoimmune DILI, thiopurines, and HDS agents. Novel data were also generated from the Spanish and Latin American DILI registries as well as from Chinese and Korean case series. A few new agents causing DILI were added to the growing list in the past 2 years, including sodium-glucose co-transporter-2 inhibitors, as were new aspects of chemotherapy-associated liver injury. A number of cases reported previously described hepatotoxins confirmed via the Roussel Uclaf Causality Assessment Method (RUCAM; e.g., norethisterone, methylprednisolone, glatiramer acetate) and/or the DILIN method (e.g., celecoxib, dimethyl fumarate). Additionally, much work centered on elucidating the pathophysiology of DILI, including the importance of bile salt export pumps and immune-mediated mechanisms. Finally, it must be noted that, while hundreds of new studies described DILI in 2017-2018, the quality of such reports must always be addressed. Björnsson reminds us to remain very critical of the data when addressing the future utility of a study, which is why it is so important to adhere to a standardized method such as RUCAM when determining DILI causality. While drug-induced hepatotoxicity remains a diagnosis of exclusion, the diverse array of publications that appeared in 2017 and 2018 provided important advances in our understanding of DILI, paving the way for our improved ability to make a more definitive diagnosis and risk assessment.

Drug-Induced Liver Injury: Biomarkers, Requirements, Candidates, and Validation

The hepatotoxicity of drugs is the main cause of drug withdrawal from the pharmaceutical market and interruption of the development of new molecules. Biomarkers are useful in several situations. In case of suspected drug-induced liver injury (DILI), biomarkers can be used to confirm liver damage, its severity, prognosis, confirm drug causality, or define the type of DILI. In this review, we will first present the currently used biomarkers and candidate biomarkers for the future. The current biomarkers are certainly very helpful including with the assistance of diagnostic method such the Roussel Uclaf Causality Assessment Method, but provide a limited information for the early detection of liver injury, the role of specific drug and the prediction of DILI. Some biomarkers are promising but they are not yet available for routine use. Studies are still needed to confirm their interest, particularly in comparison to Roussel Uclaf Causality Assessment Method.

Old problem, new solutions: biomarker discovery for acetaminophen liver toxicity

Introduction: Although the hepatotoxicity of acetaminophen is a well-known problem, the search for reliable biomarker of toxicity is still a current issue as clinical tools are missing to assess patients intoxicated following chronic use, sequential ingestion, use of modified release formulations or in case of delayed arrival to hospital. The need for new specific and robust biomarkers for acetaminophen toxicity has prompted many studies exploring the use of blood levels of acetaminophen derivatives, mitochondrial damage markers, liver cell apoptosis and/or necrosis markers and circulating microRNAs. Areas covered: In this review, we present a concise overview of the most promising biomarkers currently under evaluation including descriptions of their properties with respect to exposure type, APAP specificity, and potential clinical application. In addition, we illustrate the power of new technologies for biomarker research and describe their current application to the field of acetaminophen-induced hepatotoxicity. Expert opinion: Recently the use of extracellular vesicles isolation in combination with omics techniques has opened a new perspective to the field of biomarker research. However, the potential of those new technologies for the prediction and monitoring of hepatic diseases and acetaminophen toxicity has not yet been fully taken into consideration.

Latest advances in diagnosing and predicting DILI: what was new in 2017?

Drug-induced liver injury (DILI) remains an increasingly recognized cause of hepatotoxicity and liver failure worldwide. In 2017, we continued to learn about predicting, diagnosing, and prognosticating drug hepatotoxicity. Areas covered: In this review, we selected from over 1200 articles from 2017 to synopsize updates in DILI. There were new HLA haplotypes associated with medications including HLA-C0401 and HLA-B*14. There has been continued work with quantitative systems pharmacology, particularly with the DILIsym® initiative, which employs mathematical representations of DILI mechanisms to predict hepatotoxicity in simulated populations. Additionally, knowledge regarding microRNAs (miRNAs) continues to expand. Some new miRNAs this past year include miRNA-223 and miRNA-605. Aside from miRNAs, other biomarkers for diagnosis, prognosis, and even prediction of DILI were explored. Studies on K18, OPN, and MCSFR have correlated DILI and liver-associated death within 6 months. Conversely, a new prognostic panel using apolipoportein-A1 and haptoglobin has been proposed to predict recovery. Further study of CDH5 has also provided researchers a possible new biomarker for prediction and susceptibility to DILI. Expert commentary: Although research on DILI remains quite promising, there is yet to be a reliable, simple method to predict, diagnose, and risk assess this form of hepatotoxicity.

GC-MS metabolomics reveals disturbed metabolic pathways in primary mouse hepatocytes exposed to subtoxic levels of 3,4-methylenedioxymethamphetamine (MDMA)

3,4-Methylenedioxymethamphetamine (MDMA, ecstasy) is a well-known hepatotoxic drug. Although its toxicity has been thoroughly studied at high concentrations, there is still insufficient knowledge on possible alterations of cell function at subtoxic concentrations, which are in fact more representative concentrations of intoxication scenarios. In this study, a gas chromatography-mass spectrometry (GC-MS) metabolomics approach was used to investigate the metabolic changes in primary mouse hepatocytes (PMH) exposed to two subtoxic concentrations of MDMA (LC₀₁ and LC₁₀) for 24 h. Metabolomic profiling of both intracellular metabolites and volatile metabolites in the extracellular medium of PMH was performed. Multivariate analysis showed that the metabolic pattern of cells exposed to MDMA discriminates from the controls in a concentration-dependent manner. Exposure to LC₁₀ MDMA induces a significant increase in some intracellular metabolites, including oleic acid and palmitic acid, and a decrease in glutamate, aspartate, 5-oxoproline, fumarate, malate, phosphoric acid, α-ketoglutarate and citrate. Extracellular metabolites such as acetophenone, formaldehyde, pivalic acid, glyoxal and 2-butanone were found significantly increased after exposure to MDMA, compared to controls, whereas 4-methylheptane, 2,4-dimethyl-1-heptene, nonanal, among others, were found significantly decreased. The panel of discriminatory metabolites is mainly involved in tricarboxylic acid (TCA) cycle, fatty acid metabolism, glutamate metabolism, antioxidant defenses and possibly changes in the liver enzyme machinery. Overall, these results highlight the potential of the intra- and extracellular metabolome to study alterations triggered by subtoxic concentrations of MDMA in hepatic cell functions, which represents a more realistic appraisal of early toxicity events posed by exposure to this drug. In addition, these results also revealed some metabolites that may be used as potential biomarkers indicative of early events in the hepatotoxicity induced by MDMA.

Fat burner-induced acute liver injury: Case series of four patients

Dietary supplements known as "fat burners" are typically marketed with claims of increasing energy expenditure through alterations in fat metabolism. They are marketed as natural products and their use is thus perceived as a safe body weight reduction strategy. We report on five episodes of liver injury in four patients. Liver injury was associated with consumption of different commercially available fat burners: Green tea extract (Camellia sinensis), Garcinia gummi-gutta, green coffee beans, and spirulina (blue-green algae). The patients were admitted to the Department of Gastroenterology and Hepatology at the University Medical Center Ljubljana, in Slovenia, from May 2010 to July 2015. The first patient developed acute liver failure and had to be treated by liver transplantation. Second patient developed acute hepatitis that resolved spontaneously. Another patient required multiple surgical procedures due to severe hemorrhage after liver biopsy. The last patient was treated for two separate episodes of fat burner-induced liver injury after ingesting two different products, in 2010 and 2015. Liver biopsy was performed in all patients and histopathologic examination revealed no other cause of liver injury. Viral, autoimmune, and metabolic liver diseases were excluded, making unsupervised consumption of fat burners the most likely causative agent.