Toxicogenomics of Five Cytostatics in Fathead Minnow (Pimephales promelas) Larvae.

In this study, the toxicogenomic effects of five cytostatics (tamoxifen, methotrexate, capecitabine, cyclophosphamide, and ifosfamide) on fathead minnow (Pimephales promelas) larvae were evaluated. Post-fertilization eggs were exposed to increasing concentrations of the drugs for six days. The expression levels of two genetic biomarkers for toxicity and four thyroid hormone-related gene pathways were measured. Interestingly, the results showed that all concentrations of the five cytostatics affect the transcription levels of both toxicity biomarker genes. Additionally, the thyroid hormone-related genes had different expression levels than the control, with the most significant changes observed in those larvae exposed to cyclophosphamide and ifosfamide. While a previous study found no effects on fish morphology, this study suggests that the five cytostatics modify subtle molecular responses of P. promelas, highlighting the importance of assessing multibiological level endpoints throughout the lifecycle of animals to understand the full portrait of potential effects of cytostatics and other contaminants.

Toxicogenomics of the Freshwater Oligochaete, Tubifex tubifex (Annelida, Clitellata), in Acute Water-Only Exposure to Arsenic.

A toxicogenomic approach was used for toxicity evaluation of arsenic in the aquatic environment, and differential gene expression was investigated from 24 h and 96 h water-only acute toxicity tests with the aquatic oligochaete, Tubifex tubifex (Annelida, Clitellata). Several toxicological endpoints (survival and autotomy) of the oligochaete and tissue residues were measured, and dose-response modelling of gene expression data was studied. A reference transcriptome of the aquatic oligochaete, T. tubifex, was reconstructed for the first time, and genes related to cell stress response (Hsc70, Hsp10, Hsp60, and Hsp83), energy metabolism (COX1), oxidative stress (Cat, GSR, and MnSOD), and the genes involved in the homeostasis of organisms (CaM, RpS13, and UBE2) were identified and characterised. The potential use of the genes identified for risk assessment in freshwater ecosystems as early biomarkers of arsenic toxicity is discussed.

Short-term test for the toxicogenomic assessment of ecotoxic modes of action in Myriophyllum spicatum.

In environmental risk assessment of substances, the 14-day growth inhibition test following OECD test guideline 239 is employed to assess toxicity in the macrophyte Myriophyllum spicatum. Currently, this test evaluates physiological parameters and does not allow the identification of the mode of action (MoA) by which adverse effects are induced. However, for an improved ecotoxicity assessment of substances, knowledge about their ecotoxic MoA in non-target organisms is required. It has previously been suggested that the identification of gene expression changes can contribute to MoA identification. Therefore, we developed a shortened three-day assay for M. spicatum including the transcriptomic assessment of global gene expression changes and applied this assay to two model substances, the herbicide and photosynthesis inhibitor bentazone and the pharmaceutical and HMG-CoA reductase inhibitor atorvastatin. Due to the lack of a reference genome for M. spicatum we performed a de novo transcriptome assembly followed by a functional annotation to use the toxicogenomic results for MoA discrimination. The gene expression changes induced by low effect concentrations of these substances were used to identify differentially expressed genes (DEGs) and impaired biological functions for the respective MoA. We observed both concentration-dependent numbers and differentiated patterns of DEGs for both substances. While bentazone impaired genes involved in the response to reactive oxygen species as well as light response, and also genes involved in developmental processes, atorvastatin exposure led to a differential regulation of genes related to brassinosteroid response as well as potential metabolic shifts between the mevalonate and methyl erythritol 4-phosphate pathway. Based on these responses, we identified biomarker candidates for the assessment of MoA in M. spicatum. Utilizing the shortened assay developed in this study, the investigation of the identified biomarker candidates may contribute to the development of future MoA-specific screening approaches in the ecotoxicological hazard prediction using aquatic non-standard model organisms.

Exploring the molecular mechanisms by which per- and polyfluoroalkyl substances induce polycystic ovary syndrome through in silico toxicogenomic data mining.

The pathogeny of polycystic ovary syndrome (PCOS) is intricate, with endocrine disruptors (EDCs) being acknowledged as significant environmental factors. Research has shown a link between exposure to per- and polyfluoroalkyl substances (PFAS) and the development and progression of PCOS, although the precise mechanism is not fully understood. This study utilized toxicogenomics and comparative toxicogenomics databases to analyze data and investigate how PFAS mixtures may contribute to the development of PCOS. The results indicated that 74 genes are associated with both PFAS exposure and PCOS progression. Enrichment analysis suggested that cell cycle regulation and steroid hormone synthesis may be crucial pathways through which PFAS mixtures participate in the development of PCOS, involving important genes such as CCNB1 and SRD5A1. Furthermore, the study identified transcription factors (TFs) and miRNAs that may be involved in the onset and progression of PCOS, constructing regulatory networks encompassing TFs-mRNA interactions and miRNA-mRNA relationships to elucidate their regulatory roles in gene expression. By utilizing data mining techniques based on toxicogenomic databases, this study provides relatively comprehensive insights into the association between exposure factors and diseases compared to traditional toxicology studies. These findings offer new perspectives for further in vivo or in vitro investigations and contribute to understanding the pathogenesis of PCOS, thereby providing valuable references for identifying clinical treatment targets.

DTox: A deep neural network-based in visio lens for large scale toxicogenomics data.

With the advancement of large-scale omics technologies, particularly transcriptomics data sets on drug and treatment response repositories available in public domain, toxicogenomics has emerged as a key field in safety pharmacology and chemical risk assessment. Traditional statistics-based bioinformatics analysis poses challenges in its application across multidimensional toxicogenomic data, including administration time, dosage, and gene expression levels. Motivated by the visual inspection workflow of field experts to augment their efficiency of screening significant genes to derive meaningful insights, together with the ability of deep neural architectures to learn the image signals, we developed DTox, a deep neural network-based in visio approach. Using the Percellome toxicogenomics database, instead of utilizing the numerical gene expression values of the transcripts (gene probes of the microarray) for dose-time combinations, DTox learned the image representation of 3D surface plots of distinct time and dosage data points to train the classifier on the experts' labels of gene probe significance. DTox outperformed statistical threshold-based bioinformatics and machine learning approaches based on numerical expression values. This result shows the ability of image-driven neural networks to overcome the limitations of classical numeric value-based approaches. Further, by augmenting the model with explainability modules, our study showed the potential to reveal the visual analysis process of human experts in toxicogenomics through the model weights. While the current work demonstrates the application of the DTox model in toxicogenomic studies, it can be further generalized as an in visio approach for multi-dimensional numeric data with applications in various fields in medical data sciences.

Toxicogenomics of the C-C chemokine receptor type 5 (CCR5): Exploring the potential impacts of chemical-CCR5 interactions on inflammation and human health.

This article explores the impact of environmental chemicals on CCR5 expression and related inflammatory responses based on curated data from the Comparative Toxicogenomics Database (CTD). A total of 143 CCR5-interacting chemicals was found, with 229 chemical interactions. Of note, 67 (29.3%) out of 229 interactions resulted in "increased expression" of CCR5 mRNA or CCR5 protein, and 42 (18.3%) chemical interactions resulted in "decreased expression". The top-5 CCR5-interacting chemicals were "Tetrachlorodibenzodioxin", "Lipopolysaccharides", "Benzo(a)pyrene", "Drugs, Chinese Herbal", and "Ethinyl Estradiol". Based on the number of interactions and importance as environmental contaminant, we then focused our analysis on Tetrachlorodibenzodioxin and Benzo(a)pyrene. There is some consistency in the data supporting an increase in CCR5 expression triggered by Tetrachlorodibenzodioxin; although data concerning CCR5-Benzo(a)pyrene interactions is limited. Considering the high linkage disequilibrium between CCR5 and CCR2 genes, we also search for chemicals that interact with both genes, which resulted in 72 interacting chemicals, representing 50.3% of the 143 CCR5-interacting chemicals and 37.5% of the 192 CCR2-interacting chemicals. In conclusion, CTD data showed that environmental contaminants indeed affect CCR5 expression, with a tendency towards increased expression. The interaction of environmental contaminants with other chemokine receptor genes may potentialize their toxic effects on the chemokine system, favoring inflammation.

Screening the critical protein subnetwork to delineate potential mechanisms and protective agents associated with arsenic-induced cutaneous squamous cell carcinoma: A toxicogenomic study.

Recent studies show that complex mechanisms are involved in arsenic-induced malignant transformation of cells. This study aimed to decipher molecular mechanisms associated with arsenic-induced cutaneous squamous cell carcinoma (cSCC) and suggest potential protective factors. RNA-seq-based differentially expressed genes between arsenic-exposed human keratinocytes (HaCaT) and controls were used to construct a protein-protein interaction (PPI) network and discover critical subnetwork-based mechanisms. Protective compounds against arsenic toxicity were determined and their target interactions in the core sub-network were identified by the comparative toxicogenomic database (CTD). The binding affinity between the effective factor and target was calculated by molecular docking. A total of 15 key proteins were screened out as critical arsenic-responsive subnetwork (FN1, IL-1A, CCN2, PECAM1, FGF5, EDN1, FGF1, PXDN, DNAJB9, XBP1, ERN1, PDIA4, DNAJB11, FOS, PDIA6) and 7 effective protective agents were identified (folic acid, quercetin, zinc, acetylcysteine, methionine, catechin, selenium). The GeneMANIA predicted detailed interactions of the subnetwork and revealed terms related to unfolded protein response as the main processes. FN1, IL1A and CCN2, as top significant genes, had good docking affinity with folic acid and quercetin, as selected key compounds. Integration of gene expression and protein-protein interaction related to arsenic exposure in cSCC explored the potential mechanisms and protective agents.

The alternation of halobenzoquinone disinfection byproduct on toxicogenomics of DNA damage and repair in uroepithelial cells.

Halobenzoquinones (HBQs) were recently discovered as an emerging class of drinking water disinfection byproducts with carcinogenic concern. However, the molecular mechanism underlying HBQs-induced DNA damage is not clear. In this study, we integrated in vitro genotoxicity, computational toxicology, and the quantitative toxicogenomic analysis of HBQs on DNA damage/repair pathways in human bladder epithelial cells SV-HUC-1. The results showed that HBQs could induce cytotoxicity with the descending order as 2,6-DIBQ > 2,6-DCBQ ≈ 2,6-DBBQ. Also, HBQs can increase DNA damage in SV-HUC-1 cells and thus generate genotoxicity. However, there is no significant difference in genotoxicity among the three HBQs. The results of molecular docking and molecular dynamics simulation further confirmed that HBQs had high binding fractions and stability to DNA. Toxicogenomic analysis indicated that HBQs interfered with DNA repair pathways, mainly affecting base excision repair, nucleotide excision repair and homologous recombination repair. These results have provided new insights into the underlying molecular mechanisms of HBQs-induced DNA damage, and contributed to the understanding of the relationship between exposure to DBPs and risks of developing bladder cancer.

Toxicogenetic, biochemical, and anatomical effects of the herbicide Clethodim on Allium cepa L.

Pesticides are compounds with several chemical or biological agents developed to potentiate the biocide action. Their use is associated with increased economic and agricultural productivity worldwide but can harm health and the environment, damaging existing biota. Clethodim is a systemic post-emergent herbicide for grasses, highly selective for cotton, coffee, onions, carrots, soybeans, etc. Therefore, this work aimed to evaluate the harmful effect of the herbicide Clethodim with the model plant Allium cepa. A series of tests were conducted to evaluate the effects of the herbicide under study. Germination tests, root growth, cell, and nucleolar cycle analysis, as well as oxidative stress assessment and histological analysis of the roots, were performed. The results indicated that the herbicide demonstrated phytotoxicity, inhibiting germination at C1 (1.92 g/L) and C3 (0.84 g/L), and root growth at all concentrations, presenting mutagenicity at C1 (1.92 g/L) and C4 (0.24 g/L), evidenced by the increased frequency of micronuclei. In addition, changes were observed in the enzymatic activity of the enzymes catalase at concentrations C1 (1.92 g/L) and C2 (0.96 g/L) and ascorbate peroxidase at concentrations C1 (1.92 g/L), C2 (0. 96 g/L), and C3 (0.48 g/L) and in cell elongation at concentrations C1 (1.92 g/L) and C3 (0.48 g/L), demonstrated in histological analyses of the root apex.

Toxicogenomic Effects of Dissolved Saxitoxin on the Early Life Stages of the Longfin Yellowtail (Seriola rivoliana).

Harmful algal blooms (HABs) can produce a variety of noxious effects and, in some cases, the massive mortality of wild and farmed marine organisms. Some HAB species produce toxins that are released into seawater or transferred via food webs (particulate toxin fraction). The objective of the present study was to identify the toxicological effects of subacute exposure to saxitoxin (STX) during embryonic and early larval stages in Seriola rivoliana. Eggs were exposed to dissolved 19 STX (100 µg L-1). The toxic effects of STX were evaluated via the hatching percentage, the activity of three enzymes (protein and alkaline phosphatases and peroxidase), and the expression of four genes (HSF2, Nav1.4b, PPRC1, and DUSP8). A low hatching percentage (less than 5%) was observed in 44 hpf (hours post fertilization) embryos exposed to STX compared to 71% in the unexposed control. At this STX concentration, no oxidative stress in the embryos was evident. However, STX induced the expression of the NaV1.4 channel α-subunit (NaV1.4b), which is the primary target of this toxin. Our results revealed the overexpression of all four candidate genes in STX-intoxicated lecithotrophic larvae, reflecting the activation of diverse cellular processes involved in stress responses (HSF2), lipid metabolism (PPRC1), and MAP kinase signaling pathways associated with cell proliferation and differentiation (DUSP8). The effects of STX were more pronounced in young larvae than in embryos, indicating a stage-specific sensitivity to the toxin.

Transgenerational effects of BDE-47 to zebrafish based on histomorphometry and toxicogenomic analyses.

Exposure to 2, 2', 4, 4'-tetrabromodiphenyl ether (BDE-47) has been found to have an impact on reproductive output and endocrine function in female zebrafish (Danio rerio). However, the transgenerational effects of BDE-47 have not been fully explored in previous reports. In this study, female zebrafish were exposed to BDE-47 for three consecutive weeks. The oogenesis, sex hormones, reproductive histology, and transcriptional profiles of genes along the hypothalamus-pituitary-gonad (HPG) axis were assessed in the exposed-F0 generation. After mating with unexposed males, the transgenerational effects of BDE-47 were evaluated on the basis of histopathology, morphometry and toxicogenome of the unexposed F1 generations at the larval stage. Results indicated that exposure to BDE-47 impaired reproductive capacity, disrupted endocrine system in F0 zebrafish, and compromised craniofacial skeletons and vertebrae development in F1 generations. In addition, through the use of toxicogenomics approach, immune-responsive pathways were found to be significantly enriched, and the transcript expression profiling of immune-related DEGs (IRDs) were dramatically inhibited in F1 generations following maternal BDE-47 exposure, indicating its immunotoxicity to offspring larvae. These findings advance our understanding of the transgenerational toxicity of BDE-47 and advocate for a more comprehensive assessment of other PBDE congeners through histomorphometry and toxicogenomic approaches.

Genotoxicity Assessment of Haloacetaldehyde Disinfection Byproducts via a Simplified Yeast-Based Toxicogenomics Assay.

Haloacetaldehydes (HALs) represent the third-largest category of disinfection byproducts (DBPs) in drinking water in terms of weight. As a subset of unregulated DBPs, only a few HALs have undergone assessment, yielding limited information regarding their genotoxicity mechanisms. Herein, we developed a simplified yeast-based toxicogenomics assay to evaluate the genotoxicity of five specific HALs. This assay recorded the protein expression profiles of eight Saccharomyces cerevisiae strains fused with green fluorescent protein, including all known DNA damage and repair pathways. High-resolution real-time pathway activation data and protein expression profiles in conjunction with clustering analysis revealed that the five HALs induced various DNA damage and repair pathways. Among these, chloroacetaldehyde and trichloroacetaldehyde were found to be positively associated with genotoxicity, while dichloroacetaldehyde, bromoacetaldehyde, and tribromoacetaldehyde displayed negative associations. The protein effect level index, which are molecular end points derived from a toxicogenomics assay, exhibited a statistically significant positive correlation with the results of traditional genotoxicity assays, such as the comet assay (rp = 0.830 and p < 0.001) and SOS/umu assay (rp = 0.786 and p = 0.004). This yeast-based toxicogenomics assay, which employs a minimal set of gene biomarkers, can be used for mechanistic genotoxicity screening and assessment of HALs and other chemical compounds. These results contribute to bridging the knowledge gap regarding the molecular mechanisms underlying the genotoxicity of HALs and enable the categorization of HALs based on their distinct DNA damage and repair mechanisms.

Involvement of toxic metals and PCBs mixture in the thyroid and male reproductive toxicity: In silico toxicogenomic data mining.

Toxicological research is mostly limited to considering the effects of a single substance, even though the real exposure of people is reflected in their daily exposure to many different chemical substances in low-doses. This in silico toxicogenomic study aims to provide evidence for the selected environmental (organo)metals (lead, cadmium, methyl mercury) + polychlorinated biphenyls mixture involvement in the possible alteration of thyroid, and male reproductive system function, and furthermore to predict the possible toxic mechanisms of the environmental cocktail. The Comparative Toxicogenomic Database, GeneMANIA online software, and ToppGene Suite portal were used as the main tools for toxicogenomic data mining and gene ontology analysis. The results show that 35 annotated common genes between selected chemicals and endocrine system diseases can interact on the co-expression level. Our study highlighted the disruption of the cytokines, the cell's response to oxidative stress, and the influence of the transcription factors as the potential core of toxicological mechanisms of the discussed mixture's effects. The connected toxicological effects of the tested mixture were abnormal sperm cells, a disrupted level of testosterone, and thyroid hormones. The core mechanisms of these effects were inflammation, oxidative stress, disruption of androgen receptor signaling, and the alteration of the FOXO3-Keap-1/NRF2-HMOX1-NQO1 pathway signaling most likely controlled by the co-expression of overlapped genes among used chemicals. This in silico research can be used as a potential core for the determination of biomarkers that can be monitored in future further in vitro and in vivo experiments.

Effects of mixed heavy metals on obstructive lung function: findings from epidemiological and toxicogenomic data.

The molecular mechanisms and associations of mixed heavy metals (lead, mercury, and cadmium) on obstructive lung function (OLF) in males and females remain unknown. Here, we evaluated the interaction between the forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) ratio and three common heavy metals in males and females (n = 6221). Molecular processes involved in OLF development caused by mixed heavy metals were also identified to corroborate the earlier findings. In both males and females, as well as across the entire population, we found that serum cadmium levels were inversely related to the FEV1/FVC ratio. Interactions between serum cadmium and lead, as well as cadmium and mercury, were observed in relation to the FEV1/FVC ratio. Additionally, we observed negative correlations between the FEV1/FVC ratio and mixed serum cadmium, lead, and mercury in both men and women as well as in the overall population. Seven genes were identified as contributing to the etiology of OLF and targeted by combined heavy metals in silico analysis (CYP1A1, CRP, CXCL8, HMOX1, IL6, NOS2, and TNF). The primary relationships between these genes were co-expression interactions. The significant transcription factors and miRNAs associated with OLF and a combination of the examined heavy metals were identified as NFKB2, hsa-miR-155-5p, and hsa-miR-203a-3p. The main biological processes involved in the emergence of OLF induced by mixed heavy metals were listed as inflammatory and oxidative stress pathways, lung fibrosis, chronic obstructive pulmonary disease, as well as cytokine activity, monooxygenase activity, oxidoreductase activity, and interleukin-8 production. Threshold estimations and miRNA sponge patterns for heavy metal exposure levels associated with OLF were evaluated for both males and females. This study found that cadmium plays the most important role in the mixture of cadmium, lead, and mercury in the pathogenesis of OLF. Future studies are required to verify our findings and uncover the molecular mechanisms of long-term exposure to a variety of heavy metals, especially cadmium, in other populations, including children, adolescents, and the elderly.

Abnormality of mussel in the early developmental stages induced by graphene and triphenyl phosphate: In silico toxicogenomic data-mining, in vivo, and toxicity pathway-oriented approach.

Increasing number of complex mixtures of organic pollutants in coastal area (especially for nanomaterials and micro/nanoplastics associated chemicals) threaten aquatic ecosystems and their joint hazards are complex and demanding tasks. Mussels are the most sensitive marine faunal groups in the world, and their early developmental stages (embryo and larvae) are particularly susceptible to environmental contaminants, which can distinguish the probable mechanisms of mixture-induced growth toxicity. In this study, the potential critical target and biological processes affected by graphene and triphenyl phosphate (TPP) were developed by mining public toxicogenomic data. And their combined toxic effects were verified by toxicological assay at early developmental stages in filter-feeding mussels (embryo and larvae). It showed that interactions among graphene/TPP with 111 genes (ABCB1, TP53, SOD, CAT, HSP, etc.) affected phenotypes along conceptual framework linking these chemicals to developmental abnormality endpoints. The PPAR signaling pathway, monocarboxylic acid metabolic process, regulation of lipid metabolic process, response to oxidative stress, and gonad development were noted as the key molecular pathways that contributed to the developmental abnormality. Enriched phenotype analysis revealed biological processes (cell proliferation, cell apoptosis, inflammatory response, response to oxidative stress, and lipid metabolism) affected by the investigated mixture. Combined, our results supported that adverse effects induced by contaminants/ mixture could not only be mediated by single receptor signaling or be predicted by the simple additive effect of contaminants. The results offer a framework for better comprehending the developmental toxicity of environmental contaminants in mussels and other invertebrate species, which have considerable potential for hazard assessment of coastal mixture.

Exposure to mixed chemicals elevated triiodothyronine (T3) and follicle-stimulating hormone (FSH) levels: epidemiology and in silico toxicogenomic involvement.

There is a dearth of evidence on the effects of a mixture of numerous different types of chemicals on hormone functions. We hypothesized that exposure to mixed chemicals may alter hormone levels. Thus, this study was to identify an association between the mixed chemicals (25 chemicals) and hormone levels (thyroxine (T4) and triiodothyronine (T3), thyroid-stimulating hormone (TSH), and follicle-stimulating hormone (FSH)) among 5687 Korean adults using four different statistical approaches. Furthermore, we elucidate the effects of the key chemicals on thyroid disease and infertility based on the findings from epidemiology data. The positive associations between mixed chemicals and T3 and between mixed chemicals and FSH were observed across different methods after adjusting for all possible confounders. In the weighted quantile sum regression models, there were positive associations between mixed chemicals and T3 (ß = 4.43, 95%CI: 2.81-5.88) and ln-transformed FSH (lnFSH) (ß = 0.15, 95%CI: 0.10-0.20). In the quantile g-computation models, positive associations were found between mixed chemicals and T3 (ß=2.15, 95%CI: 0.17-4.14) and lnFSH (ß=0.15, 95%CI: 0.07-0.22). In the Bayesian kernel machine regression models, culminative effects of mixed chemicals showed positive associations with T3 and lnFSH; mercury (group posterior inclusion probabilities (PIPs) = 0.557 and conditional PPI = 0.556) and lead (group PIP group = 0.815 and conditional PPI = 0.951) were the most important chemicals for T3 and FSH, respectively. The results obtained were partially robust when subjected to in silico toxicogenomic data. We identified several molecular mechanisms that were implicated in Hg-induced thyroid disease, including the selenium micronutrient network, oxidative stress response, IL-17 signaling pathway, poorly differentiated thyroid carcinoma, and primary hyperthyroidism. The molecular processes implicated in Pb-induced infertility were "response to nutrient levels," "gonad development," "male infertility," "female infertility," and "intrinsic pathway for apoptosis," with a particular focus on FSH. The present study investigated the threshold levels of the studied chemicals and their potential impact on the disruption of T3 and FSH hormones. Future research is warranted to determine the effects of mixed chemicals on various hormones because there have been few studies on the disruption of hormones caused by such mixed chemicals.

The Effect of Historical Data-Based Informative Prior on Benchmark Dose Estimation of Toxicogenomics.

High-throughput toxicogenomics as an advanced toolbox of Tox21 plays an increasingly important role in facilitating the toxicity assessment of environmental chemicals. However, toxicogenomic dose-response analyses are typically challenged by limited data, which may result in significant uncertainties in parameter and benchmark dose (BMD) estimation. Integrating historical data via prior distribution using a Bayesian method is a useful but not-well-studied strategy. The objective of this study is to evaluate the effectiveness of informative priors in genomic dose-response modeling and BMD estimation. Specifically, we aim to identify plausible informative priors and evaluate their effects on BMD estimates at both gene and pathway levels. A general informative prior and eight time-specific (from 3 h to 29 d) informative priors for seven commonly used continuous dose-response models were derived. Results suggest that the derived informative priors are sensitive to the specific data sets used for elicitation. Real data-based simulations indicate that BMD estimation with the time-specific informative priors can achieve increased or equivalent accuracy, significantly decreased uncertainty, and a slightly enhanced correlation with the points of departure estimated from apical end points than the counterparts with noninformative priors. Overall, our study systematically examined the effects of historical data-based informative priors on BMD estimates, highlighting the benefits of plausible information priors in advancing the practice of toxicogenomics.

CTD tetramers: a new online tool that computationally links curated chemicals, genes, phenotypes, and diseases to inform molecular mechanisms for environmental health.

The molecular mechanisms connecting environmental exposures to adverse endpoints are often unknown, reflecting knowledge gaps. At the Comparative Toxicogenomics Database (CTD), we developed a bioinformatics approach that integrates manually curated, literature-based interactions from CTD to generate a "CGPD-tetramer": a 4-unit block of information organized as a step-wise molecular mechanism linking an initiating Chemical, an interacting Gene, a Phenotype, and a Disease outcome. Here, we describe a novel, user-friendly tool called CTD Tetramers that generates these evidence-based CGPD-tetramers for any curated chemical, gene, phenotype, or disease of interest. Tetramers offer potential solutions for the unknown underlying mechanisms and intermediary phenotypes connecting a chemical exposure to a disease. Additionally, multiple tetramers can be assembled to construct detailed modes-of-action for chemical-induced disease pathways. As well, tetramers can help inform environmental influences on adverse outcome pathways (AOPs). We demonstrate the tool's utility with relevant use cases for a variety of environmental chemicals (eg, perfluoroalkyl substances, bisphenol A), phenotypes (eg, apoptosis, spermatogenesis, inflammatory response), and diseases (eg, asthma, obesity, male infertility). Finally, we map AOP adverse outcome terms to corresponding CTD terms, allowing users to query for tetramers that can help augment AOP pathways with additional stressors, genes, and phenotypes, as well as formulate potential AOP disease networks (eg, liver cirrhosis and prostate cancer). This novel tool, as part of the complete suite of tools offered at CTD, provides users with computational datasets and their supporting evidence to potentially fill exposure knowledge gaps and develop testable hypotheses about environmental health.

Applying genomics in regulatory toxicology: a report of the ECETOC workshop on omics threshold on non-adversity.

In a joint effort involving scientists from academia, industry and regulatory agencies, ECETOC's activities in Omics have led to conceptual proposals for: (1) A framework that assures data quality for reporting and inclusion of Omics data in regulatory assessments; and (2) an approach to robustly quantify these data, prior to interpretation for regulatory use. In continuation of these activities this workshop explored and identified areas of need to facilitate robust interpretation of such data in the context of deriving points of departure (POD) for risk assessment and determining an adverse change from normal variation. ECETOC was amongst the first to systematically explore the application of Omics methods, now incorporated into the group of methods known as New Approach Methodologies (NAMs), to regulatory toxicology. This support has been in the form of both projects (primarily with CEFIC/LRI) and workshops. Outputs have led to projects included in the workplan of the Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) group of the Organisation for Economic Co-operation and Development (OECD) and to the drafting of OECD Guidance Documents for Omics data reporting, with potentially more to follow on data transformation and interpretation. The current workshop was the last in a series of technical methods development workshops, with a sub-focus on the derivation of a POD from Omics data. Workshop presentations demonstrated that Omics data developed within robust frameworks for both scientific data generation and analysis can be used to derive a POD. The issue of noise in the data was discussed as an important consideration for identifying robust Omics changes and deriving a POD. Such variability or "noise" can comprise technical or biological variation within a dataset and should clearly be distinguished from homeostatic responses. Adverse outcome pathways (AOPs) were considered a useful framework on which to assemble Omics methods, and a number of case examples were presented in illustration of this point. What is apparent is that high dimension data will always be subject to varying processing pipelines and hence interpretation, depending on the context they are used in. Yet, they can provide valuable input for regulatory toxicology, with the pre-condition being robust methods for the collection and processing of data together with a comprehensive description how the data were interpreted, and conclusions reached.

An evaluation of the effects of mixed heavy metals on prediabetes and type 2 diabetes: epidemiological and toxicogenomic analysis.

The link between mixed heavy metals (mercury, lead, and cadmium), prediabetes, and type 2 diabetes mellitus (T2DM), especially molecular mechanisms, is poorly understood. Thus, we aimed to identify the association between mixed heavy metals and T2DM and its components using a data set from the Korean National Health and Nutrition Examination Survey. We further analyzed the main molecular mechanisms implicated in T2DM development induced by mixed heavy metals using in-silico analysis. Our findings observed that serum mercury was associated with prediabetes, elevated glucose, and ln2-transformed glucose when using different statistical methods. "AGE-RAGE signaling pathway in diabetic complications", "non-alcoholic fatty liver disease", "metabolic Syndrome X", and three miRNAs (hsa-miR-98-5p, hsa-let-7a-5p, and hsa-miR-34a-5p) were listed as the most important molecular mechanisms related to T2DM development caused by mixed heavy metals. These miRNA sponge structures were created and examined, and they may be beneficial in the treatment of T2DM. The predicted cutoff values for three heavy metal levels linked to T2DM and its components were specifically identified. Our results imply that chronic exposure to heavy metals, particularly mercury, may contribute to the development of T2DM. To understand the changes in the pathophysiology of T2DM brought on by a combination of heavy metals, more research is required.