Screening for drinking water contaminants of concern using an automated exposure-focused workflow.

BACKGROUND: The number of chemicals present in the environment exceeds the capacity of government bodies to characterize risk. Therefore, data-informed and reproducible processes are needed for identifying chemicals for further assessment. The Minnesota Department of Health (MDH), under its Contaminants of Emerging Concern (CEC) initiative, uses a standardized process to screen potential drinking water contaminants based on toxicity and exposure potential. OBJECTIVE: Recently, MDH partnered with the U.S. Environmental Protection Agency (EPA) Office of Research and Development (ORD) to accelerate the screening process via development of an automated workflow accessing relevant exposure data, including exposure new approach methodologies (NAMs) from ORD's ExpoCast project. METHODS: The workflow incorporated information from 27 data sources related to persistence and fate, release potential, water occurrence, and exposure potential, making use of ORD tools for harmonization of chemical names and identifiers. The workflow also incorporated data and criteria specific to Minnesota and MDH's regulatory authority. The collected data were used to score chemicals using quantitative algorithms developed by MDH. The workflow was applied to 1867 case study chemicals, including 82 chemicals that were previously manually evaluated by MDH. RESULTS: Evaluation of the automated and manual results for these 82 chemicals indicated reasonable agreement between the scores although agreement depended on data availability; automated scores were lower than manual scores for chemicals with fewer available data. Case study chemicals with high exposure scores included disinfection by-products, pharmaceuticals, consumer product chemicals, per- and polyfluoroalkyl substances, pesticides, and metals. Scores were integrated with in vitro bioactivity data to assess the feasibility of using NAMs for further risk prioritization. SIGNIFICANCE: This workflow will allow MDH to accelerate exposure screening and expand the number of chemicals examined, freeing resources for in-depth assessments. The workflow will be useful in screening large libraries of chemicals for candidates for the CEC program.

Advancing the science of a read-across framework for evaluation of data-poor chemicals incorporating systematic and new approach methods.

The assessment of human health hazards posed by chemicals traditionally relies on toxicity studies in experimental animals. However, most chemicals currently in commerce do not meet the minimum data requirements for hazard identification and dose-response analysis in human health risk assessment. Previously, we introduced a read-across framework designed to address data gaps for screening-level assessment of chemicals with insufficient in vivo toxicity information (Wang et al., 2012). It relies on inference by analogy from suitably tested source analogues to a target chemical, based on structural, toxicokinetic, and toxicodynamic similarity. This approach has been used for dose-response assessment of data-poor chemicals relevant to the U.S. EPA's Superfund program. We present herein, case studies of the application of this framework, highlighting specific examples of the use of biological similarity for chemical grouping and quantitative read-across. Based on practical knowledge and technological advances in the fields of read-across and predictive toxicology, we propose a revised framework. It includes important considerations for problem formulation, systematic review, target chemical analysis, analogue identification, analogue evaluation, and incorporation of new approach methods. This work emphasizes the integration of systematic methods and alternative toxicity testing data and tools in chemical risk assessment to inform regulatory decision-making.

Adverse Outcome Pathway 'Footprinting': A Novel Approach to the Integration of 21st Century Toxicology Information into Chemical Mixtures Risk Assessment.

For over a decade, New Approach Methodologies (NAMs) such as structure-activity/read-across, -omics technologies, and Adverse Outcome Pathway (AOP), have been considered within regulatory communities as alternative sources of chemical and biological information potentially relevant to human health risk assessment. Integration of NAMs into applications such as chemical mixtures risk assessment has been limited due to the lack of validation of qualitative and quantitative application to adverse health outcomes in vivo, and acceptance by risk assessors. However, leveraging existent hazard and dose-response information, including NAM-based data, for mixture component chemicals across one or more levels of biological organization using novel approaches such as AOP 'footprinting' proposed herein, may significantly advance mixtures risk assessment. AOP footprinting entails the systematic stepwise profiling and comparison of all known or suspected AOPs involved in a toxicological effect at the level of key event (KE). The goal is to identify key event(s) most proximal to an adverse outcome within each AOP suspected of contributing to a given health outcome at which similarity between mixture chemicals can be confidently determined. These key events are identified as the 'footprint' for a given AOP. This work presents the general concept, and a hypothetical example application, of AOP footprinting as a key methodology for the integration of NAM data into mixtures risk assessment.

Advances in Assessing Hazard and Risk to Emerging Threats and Emergency Response: Comparing and Contrasting Efforts of 3 Federal Agencies.

Federal statutes authorize several agencies to protect human populations from chemical emergencies and provide guidance to evacuate, clean, and reoccupy affected areas. Each of the authorized federal agencies has developed programs to provide managers, public health officials, and regulators, with a rapid assessment of potential hazards and risks associated with chemical emergencies. Emergency responses vary based on exposure scenarios, routes, temporal considerations, and the substance(s) present. Traditional chemical assessments and derivation of toxicity values are time-intensive, typically requiring large amounts of human epidemiological and experimental animal data. When a rapid assessment of health effects is needed, an integrated computational approach of augmenting extant toxicity data with in vitro (new alternative toxicity testing methods) data can provide a quick, evidence-based solution. In so doing, multiple streams of data can be used, including literature searches, hazard, dose-response, physicochemical, environmental fate, transport property data, in vitro cell bioactivity testing, and toxicogenomics. The field of toxicology is moving, towards increased use of this approach as it transforms from observational to predictive science. The challenge is to objectively and transparently derive toxicity values using this approach to protect human health and the environment. Presented here are examples and efforts toward rapid risk assessment that demonstrate unified, parallel, and complementary work to provide timely protection in times of chemical emergency.

Sourcing data on chemical properties and hazard data from the US-EPA CompTox Chemicals Dashboard: A practical guide for human risk assessment.

For the past six decades, human health risk assessment of chemicals has relied on in vivo data from human epidemiological and experimental animal toxicological studies to inform the derivation of non-cancer toxicity values. The ongoing evolution of this risk assessment paradigm in an environmental landscape of data-poor chemicals has highlighted the need to develop and implement non-testing methods, so-called New Approach Methodologies (NAMs). NAMs include a growing number of in silico and in vitro data streams designed to inform hazard properties of chemicals, including kinetics and dynamics at different levels of biological organization, environmental fate and transport, and exposure. NAMs provide a fit-for-purpose science-basis for human hazard and risk characterization of chemicals ranging from data-gap filling applications to broad evidence-based decision-making. Systematic assembly and delivery of empirical and predicted data for chemicals are paramount to advancing chemical evaluation, and software tools serve an essential role in delivering these data to the scientific community. The CompTox Chemicals Dashboard (from here on referred to as the "Dashboard") is one such tool and is a publicly available web-based application developed by the US Environmental Protection Agency to provide access to chemistry, toxicity and exposure information for ~900,000 chemicals. The Dashboard is increasingly becoming a valuable resource for assessors tasked with the evaluation of potential human health risks associated with chemical exposures. In this context, the significant amount of information present in the Dashboard facilitates: 1) assembly of information on physicochemical properties and environmental fate and transport and exposure parameters and metrics; 2) identification of cancer and non-cancer health effects from extant human and experimental animal studies in the public domain and/or information not available in the public domain (i.e., "grey literature"); 3) systematic literature searching and review for developing cancer and non-cancer hazard evidence bases; and 4) access to mechanistic information that can aid or augment the analysis of traditional toxicology evidence bases, or potentially, serve as the primary basis for informing hazard identification and dose-response when traditional bioassay data are lacking. Finally, in silico predictive tools developed to conduct structure-activity or read-across analyses are also available within the Dashboard. This practical tutorial is intended to address key questions from the human health risk assessment community dealing with chemicals in both food and in the environment. Perspectives for future development or refinement of the Dashboard highlight foreseen activities to further support the research and risk assessment community in cancer and non-cancer chemical evaluations.

The Next Generation Blueprint of Computational Toxicology at the U.S. Environmental Protection Agency.

The U.S. Environmental Protection Agency (EPA) is faced with the challenge of efficiently and credibly evaluating chemical safety often with limited or no available toxicity data. The expanding number of chemicals found in commerce and the environment, coupled with time and resource requirements for traditional toxicity testing and exposure characterization, continue to underscore the need for new approaches. In 2005, EPA charted a new course to address this challenge by embracing computational toxicology (CompTox) and investing in the technologies and capabilities to push the field forward. The return on this investment has been demonstrated through results and applications across a range of human and environmental health problems, as well as initial application to regulatory decision-making within programs such as the EPA's Endocrine Disruptor Screening Program. The CompTox initiative at EPA is more than a decade old. This manuscript presents a blueprint to guide the strategic and operational direction over the next 5 years. The primary goal is to obtain broader acceptance of the CompTox approaches for application to higher tier regulatory decisions, such as chemical assessments. To achieve this goal, the blueprint expands and refines the use of high-throughput and computational modeling approaches to transform the components in chemical risk assessment, while systematically addressing key challenges that have hindered progress. In addition, the blueprint outlines additional investments in cross-cutting efforts to characterize uncertainty and variability, develop software and information technology tools, provide outreach and training, and establish scientific confidence for application to different public health and environmental regulatory decisions.

A case study on the application of an expert-driven read-across approach in support of quantitative risk assessment of p,p'-dichlorodiphenyldichloroethane.

Deriving human health risk estimates for environmental chemicals has traditionally relied on in vivo toxicity databases to characterize potential adverse health effects and associated dose-response relationships. In the absence of in vivo toxicity information, new approach methods (NAMs) such as read-across have the potential to fill the required data gaps. This case study applied an expert-driven read-across approach to identify and evaluate analogues to fill non-cancer oral toxicity data gaps for p,p'-dichlorodiphenyldichloroethane (p,p'-DDD), an organochlorine contaminant known to occur at contaminated sites in the U.S. The source analogue p,p'-dichlorodiphenyltrichloroethane (DDT) and its no-observed-adverse-effect level of 0.05 mg/kg-day were proposed for the derivation of screening-level health reference values for the target chemical, p,p'-DDD. Among the primary similarity contexts (structure, toxicokinetics, and toxicodynamics), toxicokinetic considerations were instrumental in separating p,p'-DDT as the best source analogue from other potential candidates (p,p'-DDE and methoxychlor). In vitro high-throughput screening (HTS) assays from ToxCast were used to evaluate similarity in bioactivity profiles and make inferences toward plausible mechanisms of toxicity to build confidence in the read-across approach. This work demonstrated the value of NAMs such as read-across and in vitro HTS in human health risk assessment of environmental contaminants with the potential to inform regulatory decision-making.

Editor's Highlight: Application of Gene Set Enrichment Analysis for Identification of Chemically Induced, Biologically Relevant Transcriptomic Networks and Potential Utilization in Human Health Risk Assessment.

The rate of new chemical development in commerce combined with a paucity of toxicity data for legacy chemicals presents a unique challenge for human health risk assessment. There is a clear need to develop new technologies and incorporate novel data streams to more efficiently inform derivation of toxicity values. One avenue of exploitation lies in the field of transcriptomics and the application of gene expression analysis to characterize biological responses to chemical exposures. In this context, gene set enrichment analysis (GSEA) was employed to evaluate tissue-specific, dose-response gene expression data generated following exposure to multiple chemicals for various durations. Patterns of transcriptional enrichment were evident across time and with increasing dose, and coordinated enrichment plausibly linked to the etiology of the biological responses was observed. GSEA was able to capture both transient and sustained transcriptional enrichment events facilitating differentiation between adaptive versus longer term molecular responses. When combined with benchmark dose (BMD) modeling of gene expression data from key drivers of biological enrichment, GSEA facilitated characterization of dose ranges required for enrichment of biologically relevant molecular signaling pathways, and promoted comparison of the activation dose ranges required for individual pathways. Median transcriptional BMD values were calculated for the most sensitive enriched pathway as well as the overall median BMD value for key gene members of significantly enriched pathways, and both were observed to be good estimates of the most sensitive apical endpoint BMD value. Together, these efforts support the application of GSEA to qualitative and quantitative human health risk assessment.

Incorporating new technologies into toxicity testing and risk assessment: moving from 21st century vision to a data-driven framework.

Based on existing data and previous work, a series of studies is proposed as a basis toward a pragmatic early step in transforming toxicity testing. These studies were assembled into a data-driven framework that invokes successive tiers of testing with margin of exposure (MOE) as the primary metric. The first tier of the framework integrates data from high-throughput in vitro assays, in vitro-to-in vivo extrapolation (IVIVE) pharmacokinetic modeling, and exposure modeling. The in vitro assays are used to separate chemicals based on their relative selectivity in interacting with biological targets and identify the concentration at which these interactions occur. The IVIVE modeling converts in vitro concentrations into external dose for calculation of the point of departure (POD) and comparisons to human exposure estimates to yield a MOE. The second tier involves short-term in vivo studies, expanded pharmacokinetic evaluations, and refined human exposure estimates. The results from the second tier studies provide more accurate estimates of the POD and the MOE. The third tier contains the traditional animal studies currently used to assess chemical safety. In each tier, the POD for selective chemicals is based primarily on endpoints associated with a proposed mode of action, whereas the POD for nonselective chemicals is based on potential biological perturbation. Based on the MOE, a significant percentage of chemicals evaluated in the first 2 tiers could be eliminated from further testing. The framework provides a risk-based and animal-sparing approach to evaluate chemical safety, drawing broadly from previous experience but incorporating technological advances to increase efficiency.

Temporal concordance between apical and transcriptional points of departure for chemical risk assessment.

The number of legacy chemicals without toxicity reference values combined with the rate of new chemical development is overwhelming the capacity of the traditional risk assessment paradigm. More efficient approaches are needed to quantitatively estimate chemical risks. In this study, rats were dosed orally with multiple doses of six chemicals for 5 days and 2, 4, and 13 weeks. Target organs were analyzed for traditional histological and organ weight changes and transcriptional changes using microarrays. Histological and organ weight changes in this study and the tumor incidences in the original cancer bioassays were analyzed using benchmark dose (BMD) methods to identify noncancer and cancer points of departure. The dose-response changes in gene expression were also analyzed using BMD methods and the responses grouped based on signaling pathways. A comparison of transcriptional BMD values for the most sensitive pathway with BMD values for the noncancer and cancer apical endpoints showed a high degree of correlation at all time points. When the analysis included data from an earlier study with eight additional chemicals, transcriptional BMD values for the most sensitive pathway were significantly correlated with noncancer (r = 0.827, p = 0.0031) and cancer-related (r = 0.940, p = 0.0002) BMD values at 13 weeks. The average ratio of apical-to-transcriptional BMD values was less than two, suggesting that for the current chemicals, transcriptional perturbation did not occur at significantly lower doses than apical responses. Based on our results, we propose a practical framework for application of transcriptomic data to chemical risk assessment.

Application of computational toxicological approaches in human health risk assessment. I. A tiered surrogate approach.

Hazard identification and dose-response assessment for chemicals of concern found in various environmental media are typically based on epidemiological and/or animal toxicity data. However, human health risk assessments are often requested for many compounds found at contaminated sites throughout the US that have limited or no available toxicity information from either humans or animals. To address this issue, recent efforts have focused on expanding the use of structure-activity relationships (SAR) approaches to identify appropriate surrogates and/or predict toxicological phenotype(s) and associated adverse effect levels. A tiered surrogate approach (i.e., decision tree) based on three main types of surrogates (structural, metabolic, and toxicity-like) has been developed. To select the final surrogate chemical and its surrogate toxicity value(s), a weight-of-evidence approach based on the proposed decision tree is applied. In addition, a case study with actual toxicity data serves as the evaluation to support our tiered surrogate approach. Future work will include case studies demonstrating the utility of the surrogate approach under different scenarios for data-poor chemicals. In conclusion, our surrogate approach provides a reasonable starting point for identifying potential toxic effects, target organs, and/or modes-of-action, and for selecting surrogate chemicals from which to derive either reference or risk values.

Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment.

The traditional approach for estimating noncancer and cancer reference values in quantitative chemical risk assessment is time and resource intensive. The extent and nature of the studies required under the traditional approach has limited the number of chemicals with published risk assessments. In this study, female mice were exposed for 13 weeks to multiple concentrations of five chemicals that were positive in a 2-year cancer bioassay. Traditional histological and organ weight changes were evaluated, and gene expression microarray analysis was performed on the target tissues. The histological, organ weight changes, and the original tumor incidences in the original cancer bioassay were analyzed using standard benchmark dose (BMD) methods to identify noncancer and cancer points of departure, respectively. The dose-related changes in gene expression were also analyzed using a BMD approach and the responses grouped based on cellular biological processes. A comparison of the transcriptional BMD values with those for the traditional noncancer and cancer apical endpoints showed a high degree of correlation for specific cellular biological processes. For chemicals with human exposure data, the transcriptional BMD values were also used to calculate a margin of exposure. The margins of exposure ranged from 1900 to 54,000. Both the correlation between the BMD values for the transcriptional and apical endpoints and the margin of exposure analysis suggest that transcriptional BMD values may be used as potential points of departure for noncancer and cancer risk assessment.

Mode of action as a determining factor in additivity models for chemical mixture risk assessment.

It is inevitable that in a lifetime humans will be exposed to a diverse array of chemical mixtures through occupational, recreational, and/or domestic activities. These mixtures may be simple, consisting of two or more definable compounds, or may be more complex containing several hundred related congeners and/or unrelated compounds. Due to a paucity of mixtures toxicity data, the estimation of risk of adverse health effects associated with mixtures typically comes from empirical observations of single chemical exposures. Under existing policy, characterizing the relative contribution of each compound depends on identification of the target organ or tissue dose, mode of action, and duration of effect. Currently, there is no consensus on what constitutes a toxic mode or mechanism of action, nor is there a universally accepted framework to determine similarity or independence of mode of action for mixtures risk assessment. This lack of a comprehensive classification paradigm for mode or mechanism of toxic action continues to be a major rate-limiting step in the advancement of mixtures risk assessment. A potential unifying approach to characterizing mode of action involves critical evaluation of data at all levels of biological organization for identification of 'key events'. Development of a biologically plausible weight of evidence description of the key obligatory steps in mechanistic pathways may facilitate selection of the most appropriate component-based mixtures risk assessment approach. Hypothetical case studies are presented to demonstrate the quantitative impact of the choice of dose addition or response addition to estimate risk.

Metformin prevents alcohol-induced liver injury in the mouse: Critical role of plasminogen activator inhibitor-1.

BACKGROUND & AIMS: The biguanide drug metformin has recently been found to improve steatosis and liver damage in animal models and in humans with nonalcoholic steatohepatitis. METHODS: The aim of the present study was to determine whether metformin also prevents steatosis and liver damage in mouse models of acute and chronic alcohol exposure. RESULTS: Acute ethanol exposure caused a >20-fold increase in hepatic lipids, peaking 12 hours after administration. Metformin treatment significantly blunted the ethanol effect by >60%. Although metformin is a known inducer of AMP kinase (AMPK) activity, the hepatoprotective property of metformin did not correlate with activation of AMPK or of AMPK-dependent pathways. Instead, the protective effects of metformin correlated with complete prevention of the upregulation of plasminogen activator inhibitor (PAI)-1 caused by ethanol. Indeed, a similar protective effect against acute alcohol-induced lipid accumulation was observed in PAI-1-/- mice. Hepatic fat accumulation caused by chronic enteral ethanol feeding was also prevented by metformin or by knocking out PAI-1. Under these conditions, necroinflammatory changes caused by ethanol were also significantly attenuated. CONCLUSIONS: Taken together, these findings suggest a novel mechanism of action for metformin and identify a new role of PAI-1 in hepatic injury caused by ethanol.

4,4'-methylenedianiline-induced hepatotoxicity is modified by N-acetyltransferase 2 (NAT2) acetylator polymorphism in the rat.

4,4'-Methylenedianiline (MDA) is widely used in the manufacturing of polyurethane foam, epoxy resins, and polymers. Exposure to MDA induces liver damage in humans and rats. MDA undergoes N-acetylation catalyzed by N-acetyltransferase 1 (NAT1) and 2 (NAT2) in the liver. Both human and rat NAT2 are polymorphic, and human NAT2 genetic polymorphism modifies the frequency and/or severity of drug and xenobiotic toxicity in human populations. Recombinant expression of rat Nats in Escherichia coli showed that MDA was acetylated by both recombinant rat Nat1 and Nat2 and was catalyzed at substantially higher rates by rapid acetylator Nat2 compared with slow acetylator Nat2. Rapid acetylator F344 rat liver cytosols catalyzed the N-acetylation of MDA at significantly higher rates than those from slow acetylator Wistar-Kyoto (WKY) inbred rats. To test the effect of NAT2 genetic polymorphism on hepatotoxicity from acute MDA exposure, we compared hepatotoxicity in rapid (F344) and slow (WKY) Nat2 acetylator inbred rats that were administered MDA. Based on the results of dose-response studies ranging up to 150 mg/kg MDA administered by intragastric gavage, the effect of a moderately hepatotoxic dose (37.5 mg/kg) was compared in rapid versus slow acetylator rats. Plasma alanine transaminase enzyme activities were approximately 5-fold higher (p < 0.05) in rapid versus slow acetylator rats after MDA treatment, and necrotizing hepatitis with portal damage consisting of bile ductular necrosis, portal expansion, and inflammation was clearly more prominent. These results suggest that acetylator phenotype is an important factor for susceptibility toward MDA hepatotoxicity.

Preservation of intestinal structural integrity by zinc is independent of metallothionein in alcohol-intoxicated mice.

Intestinal-derived endotoxins are importantly involved in alcohol-induced liver injury. Disruption of intestinal barrier function and endotoxemia are common features associated with liver inflammation and injury due to acute ethanol exposure. Zinc has been shown to inhibit acute alcohol-induced liver injury. This study was designed to determine the inhibitory effect of zinc on alcohol-induced endotoxemia and whether the inhibition is mediated by metallothionein (MT) or is independent of MT. MT knockout (MT-KO) mice were administered three oral doses of zinc sulfate (2.5 mg zinc ion/kg body weight) every 12 hours before being administered a single dose of ethanol (6 g/kg body weight) by gavage. Ethanol administration caused liver injury as determined by increased serum transaminases, parenchymal fat accumulation, necrotic foci, and an elevation of tumor necrosis factor (TNF-alpha). Increased plasma endotoxin levels were detected in ethanol-treated animals whose small intestinal structural integrity was compromised as determined by microscopic examination. Zinc supplementation significantly inhibited acute ethanol-induced liver injury and suppressed hepatic TNF-alpha production in association with decreased circulating endotoxin levels and a significant protection of small intestine structure. As expected, MT levels remained undetectable in the MT-KO mice under the zinc treatment. These results thus demonstrate that zinc preservation of intestinal structural integrity is associated with suppression of endotoxemia and liver injury induced by acute exposure to ethanol and the zinc protection is independent of MT.

A critical involvement of oxidative stress in acute alcohol-induced hepatic TNF-alpha production.

Tumor necrosis factor-alpha (TNF-alpha) production is a critical factor in the pathogenesis of alcoholic liver injury. Both oxidative stress and endotoxin have been implicated in the process of alcohol-induced TNF-alpha production. However, a cause-and-effect relationship between these factors has not been fully defined. The present study was undertaken to determine the mediators of acute alcohol-induced TNF-alpha production using a mouse model of acute alcohol hepatotoxicity. Alcohol administration via gavage at a dose of 6 g/kg to 129/Sv mice induced hepatic TNF-alpha production in Kupffer cells as demonstrated by measuring protein levels, immunohistochemical localization, and mRNA expression. Alcohol intoxication caused liver injury in association with increases in plasma endotoxin and hepatic lipid peroxidation. Treatment with an endotoxin neutralizing protein significantly suppressed alcohol-induced elevation of plasma endotoxin, hepatic lipid peroxidation, and inhibited TNF-alpha production. Treatment with antioxidants, N-ACETYL-L-CYSTEINE, or dimethylsulfoxide, failed to attenuate plasma endotoxin elevation, but significantly inhibited alcohol-induced hepatic lipid peroxidation, TNF-alpha production and steatosis. All treatments prevented alcohol-induced necrotic cell death in the liver. This study thus systemically dissected the relationship among plasma endotoxin elevation, hepatic oxidative stress, and TNF-alpha production following acute alcohol administration, and the results demonstrate that oxidative stress mediates endotoxin-induced hepatic TNF-alpha production in acute alcohol intoxication.

Suppression of Fas-mediated signaling pathway is involved in zinc inhibition of ethanol-induced liver apoptosis.

Apoptosis is critically involved in hepatic pathogenesis induced by acute alcohol exposure. This study was undertaken to test the hypothesis that zinc interferes with an important Fas ligand-mediated pathway in the liver, leading to the inhibition of ethanol-induced apoptosis. Male 129/Sv(PC)J mice were injected subcutaneously with ZnSO4 (5 mg of Zn ion/kg) in 12-hr intervals for 24 hr before intragastric administration of ethanol (5 g/kg) in 12-hr intervals for 36 hr. Ethanol-induced apoptosis in the liver was detected by a terminal deoxynucleotidyl transferase nick-end labeling assay and was further confirmed by electron microscopy. The number of apoptotic cells in the livers pretreated with zinc was significantly decreased, being only 15% of that found in the animals treated with ethanol only. Characteristic apoptotic morphological changes observed by electron microscopy were also inhibited by zinc. Importantly, zinc inhibited ethanol-induced activation of caspase-3, the primary executioner protease responsible for alcohol-induced liver apoptosis, and caspase-8 as determined by enzymatic assay. Immunohistochemical analysis revealed that zinc inhibited ethanol-induced endogenous Fas ligand activation, which is a key component in signaling pathways leading to hepatic caspase-8 and subsequent caspase-3 activation and apoptosis. These results demonstrate that zinc is a potent inhibitor of acute ethanol-induced liver apoptosis, and this effect occurs primarily through zinc interference with Fas ligand pathway and the suppression of caspase-3.

Prevention of alterations in intestinal permeability is involved in zinc inhibition of acute ethanol-induced liver damage in mice.

Acute ethanol exposure causes liver injury in experimental animals, and accumulating evidence suggests that a major responsible factor for the pathogenesis is endotoxemia, which results from bacterial endotoxin leakage from the small intestine due to increased intestinal permeability under alcohol challenge. The purpose of this study was to examine whether zinc pretreatment would inhibit acute ethanol-induced liver injury through prevention of intestinal permeability changes. Male 129 SvPCJ mice were treated with three intragastric doses of ZnSO4 at 5 mg of zinc ion per kg each dosing prior to acute ethanol challenge with a single oral dose of 6 g/kg ethanol. The zinc treatment did not alter the elevation of serum concentrations of alcohol. The acute ethanol exposure caused an elevation in serum alanine aminotransferase levels as well as fatty liver and hepatic degenerative necrotic foci as determined by biochemical assay and histochemical analysis, respectively. A significant increase in liver tumor necrosis factor-alpha (TNF-alpha) levels was detected by enzyme-linked immunosorbent assay. These pathological effects correlated well with increases in serum endotoxin levels. Importantly, acute ethanol treatment caused significant damage to the small intestine as determined by morphological analysis of intestinal sections and permeability assay. These alcohol-induced hepatic pathological changes and TNF-alpha elevation were significantly inhibited in the zinc-pretreated animals. The inhibitory action of zinc on alcohol-induced liver damage and activation of inflammation was associated with zinc suppression of alcohol-induced intestinal permeability changes. These results thus demonstrate that zinc prevention of increased intestinal permeability is importantly involved in the inhibition of acute ethanol-induced liver damage in mice.

Inducible nitric oxide synthase is required in alcohol-induced liver injury: studies with knockout mice.

BACKGROUND & AIMS: Oxidative stress contributes to early alcohol-induced liver injury, and superoxide (O(2)*-) production from NADPH oxidase plays a key role. However, the production of the free radical nitric oxide (NO*) by inducible nitric oxide synthase (iNOS) could also be involved. METHODS: To test this hypothesis, iNOS knockout (B6.129P2-Nos2 (tm1 Lau)) and wild-type mice were fed high-fat control or ethanol-containing diets for 4 weeks. RESULTS: Mean body weight gains were not significantly different between treatment groups, and average urine ethanol concentrations were similar in wild-type and iNOS knockout mice. After 4 weeks, serum alanine aminotransferase (ALT) levels were increased significantly about 4-fold over control values (29 +/- IU/L) by enteral ethanol (113 +/- 20) in wild-type mice; this effect of ethanol was significantly blunted in iNOS knockout mice (50 +/- 9). Similar protective effects against liver damage were observed if wild-type mice were treated with the iNOS inhibitor N -(3-aminomethyl)benzyl-acetamindine (1400W). Enteral ethanol also caused severe fatty accumulation, mild inflammation, and necrosis in the liver in wild-type mice but had no effect in iNOS knockout mice. The accumulation of 4-hydroxynonenal (lipid peroxidation) and 3-nitrotyrosine (reactive nitrogen species formation) protein adducts caused by alcohol was completely blocked in iNOS knockout mice. CONCLUSIONS: These data strongly support the hypothesis that iNOS is required for the pathogenesis of early alcohol-induced hepatitis by production of nitric oxide-derived pro-oxidants (e.g., peroxynitrite).