Editor's Highlight: Mechanistic Toxicity Tests Based on an Adverse Outcome Pathway Network for Hepatic Steatosis

Disinfection Byproducts of Haloacetaldehydes Disrupt Hepatic Lipid Metabolism and Induce Lipotoxicity in High-Fat Culture Conditions

Unhealthy lifestyles, obesity, and environmental pollutants are strongly correlated with the development of nonalcoholic fatty liver disease (NAFLD). Haloacetaldehyde-associated disinfection byproducts (HAL-DBPs) at various multiples of concentrations found in finished drinking water together with high-fat (HF) were examined to gauge their mixed effects on hepatic lipid metabolism. Using new alternative methods (NAMs), studying effects in human cells in vitro for risk assessment, we investigated the combined effects of HF and HAL-DBPs on hepatic lipid metabolism and lipotoxicity in immortalized LO-2 human hepatocytes. Coexposure of HAL-DBPs at various multiples of environmental exposure levels with HF increased the levels of triglycerides, interfered with de novo lipogenesis, enhanced fatty acid oxidation, and inhibited the secretion of very low-density lipoproteins. Lipid accumulation caused by the coexposure of HAL-DBPs and HF also resulted in more severe lipotoxicity in these cells. Our results using an in vitro NAM-based method provide novel insights into metabolic reprogramming in hepatocytes due to coexposure of HF and HAL-DBPs and strongly suggest that the risk of NAFLD in sensitive populations due to HAL-DBPs and poor lifestyle deserves further investigation both with laboratory and epidemiological tools. We also discuss how results from our studies could be used in health risk assessments for HAL-DBPs.

Cyanotoxin cylindrospermopsin disrupts lipid homeostasis and metabolism in a 3D in vitro model of the human liver

Cylindrospermopsin, a potent hepatotoxin produced by harmful cyanobacterial blooms, poses environmental and human health concerns. We used a 3D human liver in vitro model based on spheroids of HepG2 cells, in combination with molecular and biochemical assays, automated imaging, targeted LC-MS-based proteomics, and lipidomics, to explore cylindrospermopsin effects on lipid metabolism and the processes implicated in hepatic steatosis. Cylindrospermopsin (1 μM, 48 h) did not significantly affect cell viability but partially reduced albumin secretion. However, it increased neutral lipid accumulation in HepG2 spheroids while decreasing phospholipid levels. Simultaneously, cylindrospermopsin upregulated genes for lipogenesis regulation (SREBF1) and triacylglycerol synthesis (DGAT1/2) and downregulated genes for fatty acid synthesis (ACLY, ACCA, FASN, SCD1). Fatty acid uptake, oxidation, and lipid efflux genes were not significantly affected. Targeted proteomics revealed increased levels of perilipin 2 (adipophilin), a major hepatocyte lipid droplet-associated protein. Lipid profiling quantified 246 lipid species in the spheroids, with 28 significantly enriched and 15 downregulated by cylindrospermopsin. Upregulated species included neutral lipids, sphingolipids (e.g., ceramides and dihexosylceramides), and some glycerophospholipids (phosphatidylethanolamines, phosphatidylserines), while phosphatidylcholines and phosphatidylinositols were mostly reduced. It suggests that cylindrospermopsin exposures might contribute to developing and progressing towards hepatic steatosis or metabolic dysfunction-associated steatotic liver disease (MASLD).

A Network Toxicology Approach for Mechanistic Modelling of Nanomaterial Hazard and Adverse Outcomes

Hazard assessment is the first step in evaluating the potential adverse effects of chemicals. Traditionally, toxicological assessment has focused on the exposure, overlooking the impact of the exposed system on the observed toxicity. However, systems toxicology emphasizes how system properties significantly contribute to the observed response. Hence, systems theory states that interactions store more information than individual elements, leading to the adoption of network based models to represent complex systems in many fields of life sciences. Here, they develop a network-based approach to characterize toxicological responses in the context of a biological system, inferring biological system specific networks. They directly link molecular alterations to the adverse outcome pathway (AOP) framework, establishing direct connections between omics data and toxicologically relevant phenotypic events. They apply this framework to a dataset including 31 engineered nanomaterials with different physicochemical properties in two different in vitro and one in vivo models and demonstrate how the biological system is the driving force of the observed response. This work highlights the potential of network-based methods to significantly improve their understanding of toxicological mechanisms from a systems biology perspective and provides relevant considerations and future data-driven approaches for the hazard assessment of nanomaterials and other advanced materials.

A quantitative weight-of-evidence method for confidence assessment of adverse outcome pathway networks: A case study on chemical-induced liver steatosis

The field of chemical toxicity testing is undergoing a transition to overcome the limitations of in vivo experiments. This evolution involves implementing innovative non-animal approaches to improve predictability and provide a more precise understanding of toxicity mechanisms. Adverse outcome pathway (AOP) networks are pivotal in organizing existing mechanistic knowledge related to toxicological processes. However, these AOP networks are dynamic and require regular updates to incorporate the latest data. Regulatory challenges also persist due to concerns about the reliability of the information they offer. This study introduces a generic Weight-of-Evidence (WoE) scoring method, aligned with the tailored Bradford-Hill criteria, to quantitatively assess the confidence levels in key event relationships (KERs) within AOP networks. We use the previously published AOP network on chemical-induced liver steatosis, a prevalent form of human liver injury, as a case study. Initially, the existing AOP network is optimized with the latest scientific information extracted from PubMed using the free SysRev platform for artificial intelligence (AI)-based abstract inclusion and standardized data collection. The resulting optimized AOP network, constructed using Cytoscape, visually represents confidence levels through node size (key event, KE) and edge thickness (KERs). Additionally, a Shiny application is developed to facilitate user interaction with the dataset, promoting future updates. Our analysis of 173 research papers yielded 100 unique KEs and 221 KERs among which 72 KEs and 170 KERs, respectively, have not been previously documented in the prior AOP network or AOP-wiki. Notably, modifications in de novo lipogenesis, fatty acid uptake and mitochondrial beta-oxidation, leading to lipid accumulation and liver steatosis, garnered the highest KER confidence scores. In conclusion, our study delivers a generic methodology for developing and assessing AOP networks. The quantitative WoE scoring method facilitates in determining the level of support for KERs within the optimized AOP network, offering valuable insights into its utility in both scientific research and regulatory contexts. KERs supported by robust evidence represent promising candidates for inclusion in an in vitro test battery for reliably predicting chemical-induced liver steatosis within regulatory frameworks.

Spectral fingerprinting of cellular lipid droplets using stimulated Raman scattering microscopy and chemometric analysis

Hyperspectral stimulated Raman scattering (SRS) microscopy is a powerful method for direct visualisation and compositional analysis of cellular lipid droplets. Here we report the application of spectral phasor analysis as a convenient method for the segmentation of lipid droplets using the hyperspectral SRS spectrum in the high wavenumber and fingerprint region of the spectrum. Spectral phasor analysis was shown to discriminate six fatty acids based on vibrational spectroscopic features in solution. The methodology was then applied to studying fatty acid metabolism and storage in a mammalian cancer cell model and during drug-induced steatosis in a hepatocellular carcinoma cell model. The accumulation of fatty acids into cellular lipid droplets was shown to vary as a function of the degree of unsaturation, whilst in a model of drug-induced steatosis, the detection of increased saturated fatty acid esters was observed. Taking advantage of the fingerprint and high wavenumber regions of the SRS spectrum has yielded a greater insight into lipid droplet composition in a cellular context. This approach will find application in the label-free profiling of intracellular lipids in complex disease models.

How Does CBG Administration Affect Sphingolipid Deposition in the Liver of Insulin-Resistant Rats?

BACKGROUND

Cannabigerol (CBG), a non-psychotropic phytocannabinoid found in Cannabis sativa plants, has been the focus of recent studies due to its potential therapeutic properties. We proposed that by focusing on sphingolipid metabolism, which plays a critical role in insulin signaling and the development of insulin resistance, CBG may provide a novel therapeutic approach for metabolic disorders, particularly insulin resistance.

METHODS

In a rat model of insulin resistance induced by a high-fat, high-sucrose diet (HFHS), we aimed to elucidate the effect of intragastrically administered CBG on hepatic sphingolipid deposition and metabolism. Moreover, we also elucidated the expression of sphingolipid transporters and changes in the sphingolipid concentration in the plasma.

RESULTS

The results, surprisingly, showed a lack of changes in de novo ceramide synthesis pathway enzymes and significant enhancement in the expression of enzymes involved in ceramide catabolism, which was confirmed by changes in hepatic sphingomyelin, sphinganine, sphingosine-1-phosphate, and sphinganine-1-phosphate concentrations.

CONCLUSIONS

The results suggest that CBG treatment may modulate sphingolipid metabolism in the liver and plasma, potentially protecting the liver against the development of metabolic disorders such as insulin resistance.

In vitro to in vivo extrapolation and high-content imaging for simultaneous characterization of chemically induced liver steatosis and markers of hepatotoxicity

Chemically induced steatosis is characterized by lipid accumulation associated with mitochondrial dysfunction, oxidative stress and nucleus distortion. New approach methods integrating in vitro and in silico models are needed to identify chemicals that may induce these cellular events as potential risk factors for steatosis and associated hepatotoxicity. In this study we used high-content imaging for the simultaneous quantification of four cellular markers as sentinels for hepatotoxicity and steatosis in chemically exposed human liver cells in vitro. Furthermore, we evaluated the results with a computational model for the extrapolation of human oral equivalent doses (OED). First, we tested 16 reference chemicals with known capacities to induce cellular alterations in nuclear morphology, lipid accumulation, mitochondrial membrane potential and oxidative stress. Then, using physiologically based pharmacokinetic modeling and reverse dosimetry, OEDs were extrapolated from data of any stimulated individual sentinel response. The extrapolated OEDs were confirmed to be within biologically relevant exposure ranges for the reference chemicals. Next, we tested 14 chemicals found in food, selected from thousands of putative chemicals on the basis of structure-based prediction for nuclear receptor activation. Amongst these, orotic acid had an extrapolated OED overlapping with realistic exposure ranges. Thus, we were able to characterize known steatosis-inducing chemicals as well as data-scarce food-related chemicals, amongst which we confirmed orotic acid to induce hepatotoxicity. This strategy addresses needs of next generation risk assessment and can be used as a first chemical prioritization hazard screening step in a tiered approach to identify chemical risk factors for steatosis and hepatotoxicity-associated events.

Platycodin D ameliorates hyperglycaemia and liver metabolic disturbance in HFD/STZ-induced type 2 diabetic mice

In this work, we investigated the ameliorative effects of platycodin D (PD), a major active chemical ingredient isolated from the roots of Platycodon grandiflorum (PG), on high-fat diet (HFD)/streptozotocin (STZ)-induced type 2 diabetes (T2D) mice. PD treatment (2.5 and 5.0 mg kg^-1) improved HFD-induced body weight gain. PD administration also decreased the fasting blood glucose (FBG) level and improved glucose and insulin tolerance levels. These data collectively showed that PD could maintain glucose homeostasis. In addition, the diabetic mice with PD treatment also showed fewer pathological changes in liver tissues and improved hepatic functional indexes with respect to the levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), and recovery of abnormal liver function caused by T2D. Except for these, PD decreased the decomposition of hepatic glycogen. The results from western blot analysis showed that PD treatment might regulate the hepatic gluconeogenesis pathway with the increased phosphorylation/expression of AMPK and decreased expressions of PCK1 and G6Pase. In the aspect of lipid metabolism, PD decreased the whole-body lipid levels, including total cholesterol (TC), triglycerides (TG), and high-density lipoprotein (HDL), and reduced the hepatic fat accumulation induced by T2D through the AMPK/ACC/CPT-1 fatty acid anabolism pathway. In addition, the results of molecular docking showed that PD may have a potential direct effect on AMPK and other key glycolipid metabolism proteins. To summarize, PD modulation of hepatic glycolipid metabolism abnormalities is promising for T2D therapy in the future.

Derivation of metabolic point of departure using high-throughput in vitro metabolomics: investigating the importance of sampling time points on benchmark concentration values in the HepaRG cell line

Amongst omics technologies, metabolomics should have particular value in regulatory toxicology as the measurement of the molecular phenotype is the closest to traditional apical endpoints, whilst offering mechanistic insights into the biological perturbations. Despite this, the application of untargeted metabolomics for point-of-departure (POD) derivation via benchmark concentration (BMC) modelling is still a relatively unexplored area. In this study, a high-throughput workflow was applied to derive PODs associated with a chemical exposure by measuring the intracellular metabolome of the HepaRG cell line following treatment with one of four chemicals (aflatoxin B₁, benzo[a]pyrene, cyclosporin A, or rotenone), each at seven concentrations (aflatoxin B₁, benzo[a]pyrene, cyclosporin A: from 0.2048 μM to 50 μM; rotenone: from 0.04096 to 10 μM) and five sampling time points (2, 6, 12, 24 and 48 h). The study explored three approaches to derive PODs using benchmark concentration modelling applied to single features in the metabolomics datasets or annotated metabolites or lipids: (1) the 1st rank-ordered unannotated feature, (2) the 1st rank-ordered putatively annotated feature (using a recently developed HepaRG-specific library of polar metabolites and lipids), and (3) 25th rank-ordered feature, demonstrating that for three out of four chemical datasets all of these approaches led to relatively consistent BMC values, varying less than tenfold across the methods. In addition, using the 1st rank-ordered unannotated feature it was possible to investigate temporal trends in the datasets, which were shown to be chemical specific. Furthermore, a possible integration of metabolomics-driven POD derivation with the liver steatosis adverse outcome pathway (AOP) was demonstrated. The study highlights that advances in technologies enable application of in vitro metabolomics at scale; however, greater confidence in metabolite identification is required to ensure PODs are mechanistically anchored.

Obesogens in Foods

Obesogens, as environmental endocrine-disrupting chemicals, are supposed to have had an impact on the prevalence of rising obesity around the world over the last forty years. These chemicals are probably able to contribute not only to the development of obesity and metabolic disturbances in individuals, but also in their progeny, having the capability to epigenetically reprogram genetically inherited set-up points for body weight and body composition control during critical periods of development, such as fetal, early life, and puberty. In individuals, they may act on myriads of neuro-endocrine–immune metabolic regulatory pathways, leading to pathophysiological consequences in adipogenesis, lipogenesis, lipolysis, immunity, the influencing of central appetite and energy expenditure regulations, changes in gut microbiota–intestine functioning, and many other processes. Evidence-based medical data have recently brought much more convincing data about associations of particular chemicals and the probability of the raised risk of developing obesity. Foods are the main source of obesogens. Some obesogens occur naturally in food, but most are environmental chemicals, entering food as a foreign substance, whether in the form of contaminants or additives, and they are used in a large amount in highly processed food. This review article contributes to a better overview of obesogens, their occurrence in foods, and their impact on the human organism.

A biologically based model to quantitatively assess the role of the nuclear receptors liver X (LXR), and pregnane X (PXR) on chemically induced hepatic steatosis

Hepatic steatosis is characterized by the intracellular increase of free fatty acids (FFAs) in the form of triglycerides in hepatocytes. This hepatic adverse outcome can be caused by many factors, including exposure to drugs or environmental toxicants. Mechanistically, accumulation of lipids in the liver can take place via several mechanisms such as de novo synthesis and/or uptake of FFAs from serum via high fat content diets. De novo synthesis of FFAs within the liver is mediated by the liver X receptor (LXR), and their uptake into the liver is mediated through the pregnane X receptor (PXR). We investigated the impact of chemical exposure on FFAs hepatic content via activation of LXR and PXR by integrating chemical-specific physiologically based pharmacokinetic (PBPK) models with a quantitative toxicology systems (QTS) model of hepatic lipid homeostasis. Three known agonists of LXR and/or PXR were modeled: T0901317 (antagonist for both receptors), GW3965 (LXR only), and Rifampicin (PXR only). Model predictions showed that T0901317 caused the most FFAs build-up in the liver, followed by Rifampicin and then GW3965. These modeling results highlight the importance of PXR activation for serum FFAs uptake into the liver while suggesting that increased hepatic FAAs de novo synthesis alone may not be enough to cause appreciable accumulation of lipids in the liver under normal environmental exposure levels. Moreover, the overall PBPK-hepatic lipids quantitative model can be used to screen chemicals for their potential to cause in vivo hepatic lipid content buildup in view of their in vitro potential to activate the nuclear receptors and their exposure levels.

Converging global crises are forcing the rapid adoption of disruptive changes in drug discovery

Spiralling research costs combined with urgent pressures from the Coronavirus 2019 (COVID-19) pandemic and the consequences of climate disruption are forcing changes in drug discovery. Increasing the predictive power of in vitro human assays and using them earlier in discovery would refocus resources on more successful research strategies and reduce animal studies. Increasing laboratory automation enables effective social distancing for researchers, while allowing integrated data capture from remote laboratory networks. Such disruptive changes would not only enable more cost-effective drug discovery, but could also reduce the overall carbon footprint of discovering new drugs.

In Vitro Liver Toxicity Testing of Chemicals: A Pragmatic Approach

The liver is among the most frequently targeted organs by noxious chemicals of diverse nature. Liver toxicity testing using laboratory animals not only raises serious ethical questions, but is also rather poorly predictive of human safety towards chemicals. Increasing attention is, therefore, being paid to the development of non-animal and human-based testing schemes, which rely to a great extent on in vitro methodology. The present paper proposes a rationalized tiered in vitro testing strategy to detect liver toxicity triggered by chemicals, in which the first tier is focused on assessing general cytotoxicity, while the second tier is aimed at identifying liver-specific toxicity as such. A state-of-the-art overview is provided of the most commonly used in vitro assays that can be used in both tiers. Advantages and disadvantages of each assay as well as overall practical considerations are discussed.

A novel bile acid analog, A17, ameliorated non-alcoholic steatohepatitis in high-fat diet-fed hamsters

Being endocrine signaling molecules that regulate lipid metabolism and affect energy balance, bile acids are potential drug candidates for non-alcoholic steatohepatitis (NASH). Obeticholic acid (OCA) could improve NASH accompanied by significant side effects. Therefore, it is worthwhile to develop safer and more effective bile acid analogs. In this study, a new bile acid analog A17 was synthesized and its potential anti-NASH effects were assessed in vitro and in vivo. The impact of A17 on steatosis was investigated in the rat primary hepatocytes challenged with oleic acid. It was found that A17 alleviated lipid accumulation by reducing fatty acid (FA) uptake and promoting FA oxidation. The reduction of FA uptake came from inhibiting fatty acid translocase (Cd36) expression. The promotion of FA oxidation came from stimulating the phosphorylation of adenosine monophosphate (AMP)-activated protein kinase alpha (AMPKα). In addition, A17 reduced lipopolysaccharide-induced inflammation in Raw264.7 cells by activating Takeda G protein-coupled receptor 5 (TGR5). In in vivo study, male Golden Syrian hamsters were fed with high fat (HF) diet and then treated with 50 mg/kg/d A17 for 6 weeks. A17 lowered the lipid profiles and liver enzyme levels in serum and improved liver pathological conditions with less side effects compared with OCA. Further studies confirmed that the molecular mechanisms of A17 in vivo were similar to those in vitro. In conclusion, a novel bile acid analog A17 was identified to ameliorate NASH in HF-fed hamsters. The potential mechanisms could be contributed to reducing FA uptake, stimulating FA oxidation and relieving inflammation.

Human-Induced Pluripotent Stem Cell-Derived Hepatocytes and their Culturing Methods to Maintain Liver Functions for Pharmacokinetics and Safety Evaluation of Pharmaceuticals

Human hepatocytes are essential cell types for pharmacokinetics and the safety evaluation of pharmaceuticals. However, widely used primary hepatocytes with individual variations in liver function lose those functions rapidly in culture. Hepatic cell lines are convenient to use but have low liver functions. Human-Induced Pluripotent Stem (hiPS) cells can be expanded and potentially differentiated into any cell or tissue, including the liver. HiPS cell-derived Hepatocyte-Like Cells (hiPSHeps) are expected to be extensively used as consistent functional human hepatocytes. Many laboratories are investigating methods of using hiPS cells to differentiate hepatocytes, but the derived cells still have immature liver functions. In this paper, we describe the current uses and limitations of conventional hepatic cells, evaluating the suitability of hiPS-Heps to pharmacokinetics and the safety evaluation of pharmaceuticals, and discuss the potential future use of non-conventional non-monolayer culture methods to derive fully functional hiPS-Heps.

Quizalofop-p-Ethyl Induces Adipogenesis in 3T3-L1 Adipocytes

Exposure to endocrine disrupting chemicals is an established risk factor for obesity. The most commonly used pesticide active ingredients have never been tested in an adipogenesis assay. We tested for the first time the potential of glyphosate, 2, 4-dichlorophenoxyacetic acid, dicamba, mesotrione, isoxaflutole, and quizalofop-p-ethyl (QpE) to induce lipid accumulation in murine 3T3-L1 adipocytes. Only QpE caused a dose-dependent statistically significant triglyceride accumulation from a concentration of 5 up to 100 µM. The QpE commercial formulation Targa Super was 100 times more cytotoxic than QpE alone. Neither the estrogen receptor antagonist ICI 182, 780 nor the glucocorticoid receptor antagonist RU486 was able to block the QpE-induced lipid accumulation. RNAseq analysis of 3T3-L1 adipocytes exposed to QpE suggests that this compound exerts its lipid accumulation effects via a peroxisome proliferator-activated receptor gamma (PPARγ)-mediated pathway, a nuclear receptor whose modulation influences lipid metabolism. QpE was further shown to be active in a PPARγ reporter gene assay at 100 µM, reaching 4% of the maximal response produced by rosiglitazone, which acts as a positive control. This indicates that lipid accumulation induced by QpE is only in part caused by PPARγ activation. The lipid accumulation capability of QpE we observe suggest that this pesticide, whose use is likely to increase in coming years may have a hitherto unsuspected obesogenic property.

Quantitative adverse outcome pathway (qAOP) models for toxicity prediction

The quantitative adverse outcome pathway (qAOP) concept is gaining interest due to its potential regulatory applications in chemical risk assessment. Even though an increasing number of qAOP models are being proposed as computational predictive tools, there is no framework to guide their development and assessment. As such, the objectives of this review were to: (i) analyse the definitions of qAOPs published in the scientific literature, (ii) define a set of common features of existing qAOP models derived from the published definitions, and (iii) identify and assess the existing published qAOP models and associated software tools. As a result, five probabilistic qAOPs and ten mechanistic qAOPs were evaluated against the common features. The review offers an overview of how the qAOP concept has advanced and how it can aid toxicity assessment in the future. Further efforts are required to achieve validation, harmonisation and regulatory acceptance of qAOP models.

Metabolomic-based assessment reveals dysregulation of lipid profiles in human liver cells exposed to environmental obesogens

Significant attention has been given to the potential of environmental chemicals to disrupt lipid homeostasis at the cellular level. These chemicals, classified as obesogens, are abundantly used in a wide variety of consumer products. However, there is a significant lack of information regarding the mechanisms by which environmental exposure can contribute to the onset of obesity and non-alcoholic fatty liver disease (NAFLD). Several studies have described the interaction of potential obesogens with lipid-related peroxisome proliferator-activated receptors (PPAR). However, no studies have quantified the degree of modification to lipidomic profiles in relevant human models, making it difficult to directly link PPAR agonists to the onset of lipid-related diseases. A quantitative metabolomic approach was used to examine the dysregulation of lipid metabolism in human liver cells upon exposure to potential obesogenic compounds. The chemicals rosiglitazone, perfluorooctanoic acid, di-2-ethylexylphthalate, and tributyltin significantly increased total lipids in liver cells, being diglycerides, triglycerides and phosphatidylcholines the most prominent. Contrarily, perfluorooctane sulfonic acid and the pharmaceutical fenofibrate appeared to lower total lipid concentrations, especially those belonging to the acylcarnitine, ceramide, triglyceride, and phosphatidylcholine groups. Fluorescence microscopy analysis for cellular neutral lipids revealed significant lipid bioaccumulation upon exposure to obesogens at environmentally relevant concentrations. This integrated omics analysis provides unique mechanistic insight into the potential of these environmental pollutants to promote diseases like obesity and NAFLD. Furthermore, this study provides a significant contribution to advance the understanding of molecular signatures related to obesogenic chemicals and to the development of alternatives to in vivo experimentation.

Predicting the Probability that a Chemical Causes Steatosis Using Adverse Outcome Pathway Bayesian Networks (AOPBNs)

Adverse outcome pathway Bayesian networks (AOPBNs) are a promising avenue for developing predictive toxicology and risk assessment tools based on adverse outcome pathways (AOPs). Here, we describe a process for developing AOPBNs. AOPBNs use causal networks and Bayesian statistics to integrate evidence across key events. In this article, we use our AOPBN to predict the occurrence of steatosis under different chemical exposures. Since it is an expert-driven model, we use external data (i.e., data not used for modeling) from the literature to validate predictions of the AOPBN model. The AOPBN accurately predicts steatosis for the chemicals from our external data. In addition, we demonstrate how end users can utilize the model to simulate the confidence (based on posterior probability) associated with predicting steatosis. We demonstrate how the network topology impacts predictions across the AOPBN, and how the AOPBN helps us identify the most informative key events that should be monitored for predicting steatosis. We close with a discussion of how the model can be used to predict potential effects of mixtures and how to model susceptible populations (e.g., where a mutation or stressor may change the conditional probability tables in the AOPBN). Using this approach for developing expert AOPBNs will facilitate the prediction of chemical toxicity, facilitate the identification of assay batteries, and greatly improve chemical hazard screening strategies.

Transcriptome analysis in normal human liver cells exposed to 2, 3, 3', 4, 4', 5 - Hexachlorobiphenyl (PCB 156)

BACKGROUNDS

Polychlorinated biphenyls are persistent environmental pollutants associated with the onset of non-alcoholic fatty liver disease in humans, but there is limited information on the underlying mechanism. In the present study, we investigated the alterations in gene expression profiles in normal human liver cells L-02 following exposure to 2, 3, 3', 4, 4', 5 - hexachlorobiphenyl (PCB 156), a potent compound that may induce non-alcoholic fatty liver disease.

METHODS

The L-02 cells were exposed to PCB 156 for 72 h and the contents of intracellular triacylglyceride and total cholesterol were subsequently measured. Microarray analysis of mRNAs and long non-coding RNAs (lncRNAs) in the cells was also performed after 3.4 μM PCB 156 treatment.

RESULTS

Exposure to PCB 156 (3.4 μM, 72 h) resulted in significant increases of triacylglyceride and total cholesterol concentrations in L-02 cells. Microarray analysis identified 222 differentially expressed mRNAs and 628 differentially expressed lncRNAs. Gene Ontology and pathway analyses associated the differentially expressed mRNAs with metabolic and inflammatory processes. Moreover, lncRNA-mRNA co-expression network revealed 36 network pairs comprising 10 differentially expressed mRNAs and 34 dysregulated lncRNAs. The results of bioinformatics analysis further indicated that dysregulated lncRNA NONHSAT174696, lncRNA NONHSAT179219, and lncRNA NONHSAT161887, as the regulators of EDAR, CYP1B1, and ALDH3A1 respectively, played an important role in the PCB 156-induced lipid metabolism disorder.

CONCLUSION

Our findings provide an overview of differentially expressed mRNAs and lncRNAs in L-02 cells exposed to PCB 156, and contribute to the field of polychlorinated biphenyl-induced non-alcoholic fatty liver disease.

Mechanisms of Environmental Contributions to Fatty Liver Disease

PURPOSE

Fatty liver disease (FLD) affects over 25% of the global population and may lead to liver-related mortality due to cirrhosis and liver cancer. FLD caused by occupational and environmental chemical exposures is termed "toxicant-associated steatohepatitis" (TASH). The current review addresses the scientific progress made in the mechanistic understanding of TASH since its initial description in 2010.

RECENT FINDINGS

Recently discovered modes of actions for volatile organic compounds and persistent organic pollutants include the following: (i) the endocrine-, metabolism-, and signaling-disrupting chemical hypotheses; (ii) chemical-nutrient interactions and the "two-hit" hypothesis. These key hypotheses were then reviewed in the context of the steatosis adverse outcome pathway (AOP) proposed by the US Environmental Protection Agency. The conceptual understanding of the contribution of environmental exposures to FLD has progressed significantly. However, because this is a new research area, more studies including mechanistic human data are required to address current knowledge gaps.

Extracting and Benchmarking Emerging Adverse Outcome Pathway Knowledge

As the community of toxicological researchers, risk assessors, and risk managers adopt the adverse outcome pathway (AOP) framework for organizing toxicological knowledge, the number and diversity of AOPs in the online AOP knowledgebase (KB) continues to grow. To track and investigate this growth, AOPs in the AOP-KB were assembled into a single network. Summary measures on the current state of the AOP-KB and the overall connectivity and structural features of the resulting network were calculated. Our results show that networking the 187 user-defined AOPs currently described in the AOP-KB resulted in the emergence of 9405 unique, previously undescribed, linear AOPs (LAOPs). To investigate patterns in this emerging knowledge, we assembled the AOP-KB network retrospectively by sequentially adding each of the 187 user-defined AOPs and found that the creation of new AOPs that borrowed components from previously existing AOPs in the KB most described emergence of new LAOPs. However, the introduction of nonadjacent key event relationships and cycles among KEs also play key roles in emergent LAOPs. We provide examples of how to identify application-specific critical paths from this large number of LAOPs. Our research shows that the global AOP network may have considerable value as a source of emergent toxicological knowledge. These findings are not only helpful for understanding the nature of this emergent information but can also be used to manage and guide future development of the AOP-KB, and how to tailor this wealth of information to specific applications.

Integrated transcriptomics and metabolomics reveal signatures of lipid metabolism dysregulation in HepaRG liver cells exposed to PCB 126

Chemical pollutant exposure is a risk factor contributing to the growing epidemic of non-alcoholic fatty liver disease (NAFLD) affecting human populations that consume a western diet. Although it is recognized that intoxication by chemical pollutants can lead to NAFLD, there is limited information available regarding the mechanism by which typical environmental levels of exposure can contribute to the onset of this disease. Here, we describe the alterations in gene expression profiles and metabolite levels in the human HepaRG liver cell line, a validated model for cellular steatosis, exposed to the polychlorinated biphenyl (PCB) 126, one of the most potent chemical pollutants that can induce NAFLD. Sparse partial least squares classification of the molecular profiles revealed that exposure to PCB 126 provoked a decrease in polyunsaturated fatty acids as well as an increase in sphingolipid levels, concomitant with a decrease in the activity of genes involved in lipid metabolism. This was associated with an increased oxidative stress reflected by marked disturbances in taurine metabolism. A gene ontology analysis showed hallmarks of an activation of the AhR receptor by dioxin-like compounds. These changes in metabolome and transcriptome profiles were observed even at the lowest concentration (100 pM) of PCB 126 tested. A decrease in docosatrienoate levels was the most sensitive biomarker. Overall, our integrated multi-omics analysis provides mechanistic insight into how this class of chemical pollutant can cause NAFLD. Our study lays the foundation for the development of molecular signatures of toxic effects of chemicals causing fatty liver diseases to move away from a chemical risk assessment based on in vivo animal experiments.

Adverse outcome pathway networks I: Development and applications

Based on the results of a Horizon Scanning exercise sponsored by the Society of Environmental Toxicology and Chemistry that focused on advancing the adverse outcome pathway (AOP) framework, the development of guidance related to AOP network development was identified as a critical need. This not only included questions focusing directly on AOP networks, but also on related topics such as mixture toxicity assessment and the implementation of feedback loops within the AOP framework. A set of two articles has been developed to begin exploring these concepts. In the present article (part I), we consider the derivation of AOP networks in the context of how it differs from the development of individual AOPs. We then propose the use of filters and layers to tailor AOP networks to suit the needs of a given research question or application. We briefly introduce a number of analytical approaches that may be used to characterize the structure of AOP networks. These analytical concepts are further described in a dedicated, complementary article (part II). Finally, we present a number of case studies that illustrate concepts underlying the development, analysis, and application of AOP networks. The concepts described in the present article and in its companion article (which focuses on AOP network analytics) are intended to serve as a starting point for further development of the AOP network concept, and also to catalyze AOP network development and application by the different stakeholder communities. Environ Toxicol Chem 2018;37:1723-1733. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

An Update on Adverse Outcome Pathways Leading to Liver Injury

Chemical-induced liver injury can be manifested in a number of ways, such as cholestasis, steatosis, fibrosis, and cancer. The mechanisms driving these toxicological processes have been well characterized and have been embedded in adverse outcome pathway frameworks in recent years. This article provides a concise overview of these constructs.