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      Mining Public Toxicogenomic Data Reveals Insights and Challenges in Delineating Liver Steatosis Adverse Outcome Pathways

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          Abstract

          Exposure to chemicals contributes to the development and progression of fatty liver, or steatosis, a process characterized by abnormal accumulation of lipids within liver cells. However, lack of knowledge on how chemicals cause steatosis has prevented any large-scale assessment of the 80,000+ chemicals in current use. To address this gap, we mined a large, publicly available toxicogenomic dataset associated with 18 known steatogenic chemicals to assess responses across assays ( in vitro and in vivo) and species (i.e., rats and humans). We identified genes that were differentially expressed (DEGs) in rat in vivo, rat in vitro, and human in vitro studies in which rats or in vitro primary cell lines were exposed to the chemicals at different doses and durations. Using these DEGs, we performed pathway enrichment analysis, analyzed the molecular initiating events (MIEs) of the steatosis adverse outcome pathway (AOP), and predicted metabolite changes using metabolic network analysis. Genes indicative of oxidative stress were among the DEGs most frequently observed in the rat in vivo studies. Nox4, a pro-fibrotic gene, was down-regulated across these chemical exposure conditions. We identified eight genes ( Cyp1a1, Egr1, Ccnb1, Gdf15, Cdk1, Pdk4, Ccna2, and Ns5atp9) and one pathway (retinol metabolism), associated with steatogenic chemicals and whose response was conserved across the three in vitro and in vivo systems. Similarly, we found the predicted metabolite changes, such as increases of saturated and unsaturated fatty acids, conserved across the three systems. Analysis of the target genes associated with the MIEs of the current steatosis AOP did not provide a clear association between these 18 chemicals and the MIEs, underlining the multi-factorial nature of this disease. Notably, our overall analysis implicated mitochondrial toxicity as an important and overlooked MIE for chemical-induced steatosis. The integrated toxicogenomics approach to identify genes, pathways, and metabolites based on known steatogenic chemicals, provide an important mean to assess development of AOPs and gauging the relevance of new testing strategies.

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          Most cited references49

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          Adverse outcome pathways: a conceptual framework to support ecotoxicology research and risk assessment.

          Ecological risk assessors face increasing demands to assess more chemicals, with greater speed and accuracy, and to do so using fewer resources and experimental animals. New approaches in biological and computational sciences may be able to generate mechanistic information that could help in meeting these challenges. However, to use mechanistic data to support chemical assessments, there is a need for effective translation of this information into endpoints meaningful to ecological risk-effects on survival, development, and reproduction in individual organisms and, by extension, impacts on populations. Here we discuss a framework designed for this purpose, the adverse outcome pathway (AOP). An AOP is a conceptual construct that portrays existing knowledge concerning the linkage between a direct molecular initiating event and an adverse outcome at a biological level of organization relevant to risk assessment. The practical utility of AOPs for ecological risk assessment of chemicals is illustrated using five case examples. The examples demonstrate how the AOP concept can focus toxicity testing in terms of species and endpoint selection, enhance across-chemical extrapolation, and support prediction of mixture effects. The examples also show how AOPs facilitate use of molecular or biochemical endpoints (sometimes referred to as biomarkers) for forecasting chemical impacts on individuals and populations. In the concluding sections of the paper, we discuss how AOPs can help to guide research that supports chemical risk assessments and advocate for the incorporation of this approach into a broader systems biology framework.
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            Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments.

            One of the main objectives in the analysis of microarray experiments is the identification of genes that are differentially expressed under two experimental conditions. This task is complicated by the noisiness of the data and the large number of genes that are examined simultaneously. Here, we present a novel technique for identifying differentially expressed genes that does not originate from a sophisticated statistical model but rather from an analysis of biological reasoning. The new technique, which is based on calculating rank products (RP) from replicate experiments, is fast and simple. At the same time, it provides a straightforward and statistically stringent way to determine the significance level for each gene and allows for the flexible control of the false-detection rate and familywise error rate in the multiple testing situation of a microarray experiment. We use the RP technique on three biological data sets and show that in each case it performs more reliably and consistently than the non-parametric t-test variant implemented in Tusher et al.'s significance analysis of microarrays (SAM). We also show that the RP results are reliable in highly noisy data. An analysis of the physiological function of the identified genes indicates that the RP approach is powerful for identifying biologically relevant expression changes. In addition, using RP can lead to a sharp reduction in the number of replicate experiments needed to obtain reproducible results.
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              Nonalcoholic fatty liver disease: pathology and pathogenesis.

              Nonalcoholic fatty liver disease (NAFLD) is recognized as the leading cause of chronic liver disease in adults and children. NAFLD encompasses a spectrum of liver injuries ranging from steatosis to steatohepatitis with or without fibrosis. Fibrosis may progress to cirrhosis and complications including hepatocellular carcinoma. Histologic findings represent the complexity of pathophysiology. NAFLD is closely associated with obesity and is most closely linked with insulin resistance; the current Western diet, high in saturated fats and fructose, plays a significant role. There are several mechanisms by which excess triglycerides are acquired and accumulate in hepatocytes. Formation of steatotic droplets may be disordered in NAFLD. Visceral adipose tissue dysfunction in obesity and insulin resistance results in aberrant cytokine expression; many cytokines have a role in liver injury in NAFLD. Cellular stress and immune reactions, as well as the endocannabinoid system, have been implicated in animal models and in some human studies.
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/206406
                URI : https://loop.frontiersin.org/people/284761
                URI : https://loop.frontiersin.org/people/187800
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                18 October 2019
                2019
                : 10
                : 1007
                Affiliations
                [1] 1Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command , Fort Detrick, MD, United States
                [2] 2The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. , Bethesda, MD, United States
                Author notes

                Edited by: Chris Vulpe, University of Florida, United States

                Reviewed by: Xuefang Liang, Inner Mongolia University, China; Annamaria Colacci, Agenzia Regionale Prevenzione E Ambiente Della Regione Emilia-Romagna, Italy

                *Correspondence: Mohamed Diwan M. AbdulHameed, mabdulhameed@ 123456bhsai.org ; Anders Wallqvist, sven.a.wallqvist.civ@ 123456mail.mil

                This article was submitted to Toxicogenomics, a section of the journal Frontiers in Genetics

                Article
                10.3389/fgene.2019.01007
                6813744
                86ca90c3-161d-422b-a279-4d34c55b1d7c
                Copyright © 2019 AbdulHameed, Pannala and Wallqvist

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 06 June 2019
                : 23 September 2019
                Page count
                Figures: 6, Tables: 1, Equations: 4, References: 72, Pages: 14, Words: 7470
                Categories
                Genetics
                Original Research

                Genetics
                liver steatosis,adverse outcome pathway,mie,steatosis aop,data mining
                Genetics
                liver steatosis, adverse outcome pathway, mie, steatosis aop, data mining

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