Analysis of the ToxCast Chemical-Assay Space Using the Comparative Toxicogenomics Database

Developmental neurotoxicity (DNT) QSAR combination prediction model establishment and structural characteristics interpretation

With the incidence of neurodevelopmental disorders on the rise, it is imperative to screen and evaluate developmental neurotoxicity (DNT) compounds from a large number of environmental chemicals and understand their mechanisms. In this study, DNT qualitative structure-activity relationship (QSAR) study was carried out for the first time based on DNT data of mammals and structural characterization of DNT compounds was preliminarily illustrated. Five different classification algorithms and two feature selection methods were used to construct prediction models. The best model had good predictive ability on the external test set, but a small application domain (AD). Through combining of three different models, both MCC and AD values were improved. Furthermore, electronical properties, van der Waals volume-related properties and S, Cl or P containing substructure were found to be associated with DNT through modeling descriptors analysis and structure alerts (SAs) identification. This study lays a foundation for further DNT prediction of environmental exposures in human and contributes to the understanding of DNT mechanism.

Toxicogenomics scoring system: TGSS, a novel integrated risk assessment model for chemical carcinogenicity prediction

BACKGROUND

Given the increasing exposure of humans to environmental chemicals and the limitations of conventional toxicity test, there is an urgent need to develop next-generation risk assessment methods.

OBJECTIVES

This study aims to establish a novel computational system named Toxicogenomics Scoring System (TGSS) to predict the carcinogenicity of chemicals coupling chemical-gene interactions with multiple cancer transcriptomic datasets.

METHODS

Chemical-related gene signatures were derived from chemical-gene interaction data from the Comparative Toxicogenomics Database (CTD). For each cancer type in TCGA, genes were ranked by their effects on tumorigenesis, which is based on the differential expression between tumor and normal samples. Next, we developed carcinogenicity scores (C-scores) using pre-ranked GSEA to quantify the correlation between chemical-related gene signatures and ranked gene lists. Then we established TGSS by systematically evaluating the C-scores in multiple chemical-tumor pairs. Furthermore, we examined the performance of our approach by ROC curves or prognostic analyses in TCGA and multiple independent cancer cohorts.

RESULTS

Forty-six environmental chemicals were finally included in the study. C-score was calculated for each chemical-tumor pair. The C-scores of IARC Group 3 chemicals were significantly lower than those of chemicals in Group 1 (P-value = 0.02) and Group 2 (P-values = 7.49 ×10^-5). ROC curves analysis indicated that C-score could distinguish "high-risk chemicals" from the other compounds (AUC = 0.67) with a specificity and sensitivity of 0.86 and 0.57. The results of survival analysis were also in line with the assessed carcinogenicity in TGSS for the chemicals in Group 1. Finally, consistent results were further validated in independent cancer cohorts.

CONCLUSION

TGSS highlighted the great potential of integrating chemical-gene interactions with gene-cancer relationships to predict the carcinogenic risk of chemicals, which would be valuable for systems toxicology.

Network pharmacology and molecular docking analysis on the mechanism of Baihe Zhimu decoction in the treatment of postpartum depression

Baihe Zhimu decoction (BZD) has significant antidepressant properties and is widely used to treat mental diseases. However, the multitarget mechanism of BZD in postpartum depression (PPD) remains to be elucidated. Therefore, the aim of this study was to explore the molecular mechanisms of BDZ in treating PPD using network pharmacology and molecular docking. Active components and their target proteins were screened from the traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The PPD-related targets were obtained from the OMIM, CTD, and GeneCards databases. After overlap, the targets of BZD against PPD were collected. Protein-protein interaction (PPI) network and core target analyses were conducted using the STRING network platform and Cytoscape software. Moreover, molecular docking methods were used to confirm the high affinity between BZD and targets. Finally, the DAVID online tool was used to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of overlapping targets. The TCMSP database showed that BZD contained 23 active ingredients in PPD. KEGG analysis showed that overlapping genes were mainly enriched in HIF-1, dopaminergic synapses, estrogen, and serotonergic synaptic signalling pathways. Combining the PPI network and KEGG enrichment analysis, we found that ESR1, MAOA, NR3C1, VEGFA, and mTOR were the key targets of PPD. In addition, molecular docking confirmed the high affinity between BZD and the PPD target. Verified by a network pharmacology approach based on data mining and molecular docking methods, the multi-target drug BZD may serve as a promising therapeutic candidate for PPD, but further in vivo/in vitro experiments are needed.

Study on the action mechanism of Wuling Powder on treating osteoporosis based on network pharmacology

Osteoporosis is a health problem to cause global concern. A lot of methods have been used to prevent and treat osteoporosis, but there is still a lack of effective treatment for osteoporosis owing to limited understanding of its mechanism. Therefore, the aim of this present study is to explore the underlying mechanism of Wuling Powder, a traditional Chinese medicine on treating osteoporosis. In this study, we firstly screened and identified the common targets between Wuling Powder and osteoporosis through the related databases, and then explored the relationships among these targets, Wuling Powder and osteoporosis by using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and network analyses. Subsequently, the molecular docking was performed by using systemsDock to evaluate the potential binding relationships between the active components of Wuling Powder and their related targets. The results showed that in total of 14 common targets including CREBBP, ADAM17, GOT1, GAPDH, USP8, ERBB2, EEF1A1, MTOR, RAC1, ETS1, DDX58, GCK, EGF and S100A8 were screened. EGF, ERBB2, MTOR and HIF-1 were the potential therapeutic targets for osteoporosis, and they were also the related targets for predicting active components in Wuling Powder. Taken together, we concluded that Wuling Powder might be used to treat osteoporosis through above these targets.

New Associations between Drug-Induced Adverse Events in Animal Models and Humans Reveal Novel Candidate Safety Targets

To improve our ability to extrapolate preclinical toxicity to humans, there is a need to understand and quantify the concordance of adverse events (AEs) between animal models and clinical studies. In the present work, we discovered 3011 statistically significant associations between preclinical and clinical AEs caused by drugs reported in the PharmaPendium database of which 2952 were new associations between toxicities encoded by different Medical Dictionary for Regulatory Activities terms across species. To find plausible and testable candidate off-target drug activities for the derived associations, we investigated the genetic overlap between the genes linked to both a preclinical and a clinical AE and the protein targets found to interact with one or more drugs causing both AEs. We discuss three associations from the analysis in more detail for which novel candidate off-target drug activities could be identified, namely, the association of preclinical mutagenicity readouts with clinical teratospermia and ovarian failure, the association of preclinical reflexes abnormal with clinical poor-quality sleep, and the association of preclinical psychomotor hyperactivity with clinical drug withdrawal syndrome. Our analysis successfully identified a total of 77% of known safety targets currently tested in in vitro screening panels plus an additional 431 genes which were proposed for investigation as future safety targets for different clinical toxicities. This work provides new translational toxicity relationships beyond AE term-matching, the results of which can be used for risk profiling of future new chemical entities for clinical studies and for the development of future in vitro safety panels.

Cytotoxicity Burst? Differentiating Specific from Nonspecific Effects in Tox21 in Vitro Reporter Gene Assays

BACKGROUND

High-throughput screening of chemicals with in vitro reporter gene assays in Tox21 has produced a large database on cytotoxicity and specific modes of action. However, the validity of some of the reported activities is questionable due to the "cytotoxicity burst," which refers to the supposition that many stress responses are activated in a nonspecific way at concentrations close to cell death.

OBJECTIVES

We propose a pragmatic method to identify whether reporter gene activation is specific or cytotoxicity-triggered by comparing the measured effects with baseline toxicity.

METHODS

Baseline toxicity, also termed narcosis, is the minimal toxicity any chemical causes. Quantitative structure-activity relationships (QSARs) developed for baseline toxicity in mammalian reporter gene cell lines served as anchors to define the chemical-specific threshold for the cytotoxicity burst and to evaluate the degree of specificity of the reporter gene activation. Measured 10% effect concentrations were related to measured or QSAR-predicted 10% cytotoxicity concentrations yielding specificity ratios (SR). We applied this approach to our own experimental data and to ∼ 8,000 chemicals that were tested in six of the high-throughput Tox21 reporter gene assays.

RESULTS

Confirmed baseline toxicants activated reporter gene activity around cytotoxic concentrations triggered by the cytotoxicity burst. In six Tox21 assays, 37%-87% of the active hits were presumably caused by the cytotoxicity burst (SR < 1 ) and only 2%-14% were specific with SR ≥ 10 against experimental cytotoxicity but 75%-97% were specific against baseline toxicity. This difference was caused by a large fraction of chemicals showing excess cytotoxicity.

CONCLUSIONS

The specificity analysis for measured in vitro effects identified whether a cytotoxicity burst had likely occurred. The SR-analysis not only prevented false positives, but it may also serve as measure for relative effect potency and can be used for quantitative in vitro-in vivo extrapolation and risk assessment of chemicals. https://doi.org/10.1289/EHP6664.

T1000: a reduced gene set prioritized for toxicogenomic studies

There is growing interest within regulatory agencies and toxicological research communities to develop, test, and apply new approaches, such as toxicogenomics, to more efficiently evaluate chemical hazards. Given the complexity of analyzing thousands of genes simultaneously, there is a need to identify reduced gene sets. Though several gene sets have been defined for toxicological applications, few of these were purposefully derived using toxicogenomics data. Here, we developed and applied a systematic approach to identify 1,000 genes (called Toxicogenomics-1000 or T1000) highly responsive to chemical exposures. First, a co-expression network of 11,210 genes was built by leveraging microarray data from the Open TG-GATEs program. This network was then re-weighted based on prior knowledge of their biological (KEGG, MSigDB) and toxicological (CTD) relevance. Finally, weighted correlation network analysis was applied to identify 258 gene clusters. T1000 was defined by selecting genes from each cluster that were most associated with outcome measures. For model evaluation, we compared the performance of T1000 to that of other gene sets (L1000, S1500, Genes selected by Limma, and random set) using two external datasets based on the rat model. Additionally, a smaller (T384) and a larger version (T1500) of T1000 were used for dose-response modeling to test the effect of gene set size. Our findings demonstrated that the T1000 gene set is predictive of apical outcomes across a range of conditions (e.g., in vitro and in vivo, dose-response, multiple species, tissues, and chemicals), and generally performs as well, or better than other gene sets available.

Research on the Potential Mechanism of Gypenosides on Treating Thyroid-Associated Ophthalmopathy Based on Network Pharmacology

Thyroid-associated ophthalmopathy is the commonest orbital disease in adults. However, shortcomings still exist in treatments. The aim of this study was to identify the efficacy and potential mechanism of gypenosides in the treatment of thyroid-associated ophthalmopathy. The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was screened for active compounds of gypenosides, and targets were predicted using Swiss Target Prediction. The targets of thyroid-associated ophthalmopathy were obtained from Online Mendelian Inheritance in Man, Comparative Toxicogenomic Database and GeneCards Human gene database. Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome Pathways were determined based on the common targets. Protein-protein interaction (PPI) network was constructed to further understand of relationship among target genes, compounds and proteins. Molecular docking was performed to investigate the binding ability between gypenosides and hub genes. A total of 70 targets for gypenosides and 804 targets for thyroid-associated ophthalmopathy were obtained with 8 common targets identified. GO analysis and KEGG pathway analysis revealed that the hub genes were enriched in JAK-STAT, while Reactome pathways analysis indicated genes enriched in interleukin pathways. PPI network showed STAT1, STAT3, and STAT4 were at the center. Additionally, molecular docking indicated that STAT1 and STAT3 display good binding forces with gypenosides. This study indicates that target genes mainly enriched in JAK-STAT signaling pathway, particularly in STATs, which can be combined with gypenosides. This may suggest that gypenosides have curative effect on thyroid-associated ophthalmopathy via the JAK-STAT pathway.

The Need for, and the Role of the Toxicological Chemist in the Design of Safer Chemicals

During the past several decades, there has been an ever increasing emphasis for designers of new commercial (nonpharmaceutical) chemicals to include considerations of the potential impacts a planned chemical may have on human health and the environment as part of the design of the chemical, and to design chemicals such that they possess the desired use efficacy while minimizing threats to human health and the environment. Achievement of this goal would be facilitated by the availability of individuals specifically and formally trained to design such chemicals. Medicinal chemists are specifically trained to design and develop safe and clinically efficacious pharmaceutical substances. No such formally trained science hybrid exists for the design of safer commercial (nonpharmaceutical) chemicals. This article describes the need for and role of the "toxicological chemist," an individual who is formally trained in synthetic organic chemistry, biochemistry, physiology, toxicology, environmental science, and in the relationships between structure and commercial use efficacy, structure and toxicity, structure and environmental fate and effects, and global hazard, and trained to integrate this knowledge to design safer commercially efficacious chemicals. Using examples, this article illustrates the role of the toxicological chemist in designing commercially efficacious, safer chemical candidates.

Advancing Exposure Science through Chemical Data Curation and Integration in the Comparative Toxicogenomics Database

BACKGROUND

Exposure science studies the interactions and outcomes between environmental stressors and human or ecological receptors. To augment its role in understanding human health and the exposome, we aimed to centralize and integrate exposure science data into the broader biological framework of the Comparative Toxicogenomics Database (CTD), a public resource that promotes understanding of environmental chemicals and their effects on human health.

OBJECTIVES

We integrated exposure data within the CTD to provide a centralized, freely available resource that facilitates identification of connections between real-world exposures, chemicals, genes/proteins, diseases, biological processes, and molecular pathways.

METHODS

We developed a manual curation paradigm that captures exposure data from the scientific literature using controlled vocabularies and free text within the context of four primary exposure concepts: stressor, receptor, exposure event, and exposure outcome. Using data from the Agricultural Health Study, we have illustrated the benefits of both centralization and integration of exposure information with CTD core data.

RESULTS

We have described our curation process, demonstrated how exposure data can be accessed and analyzed in the CTD, and shown how this integration provides a broad biological context for exposure data to promote mechanistic understanding of environmental influences on human health.

CONCLUSIONS

Curation and integration of exposure data within the CTD provides researchers with new opportunities to correlate exposures with human health outcomes, to identify underlying potential molecular mechanisms, and to improve understanding about the exposome.

CITATION

Grondin CJ, Davis AP, Wiegers TC, King BL, Wiegers JA, Reif DM, Hoppin JA, Mattingly CJ. 2016. Advancing exposure science through chemical data curation and integration in the Comparative Toxicogenomics Database. Environ Health Perspect 124:1592-1599; http://dx.doi.org/10.1289/EHP174.

A test strategy for the assessment of additive attributed toxicity of tobacco products

The new EU Tobacco Product Directive (TPD) prohibits tobacco products containing additives that are toxic in unburnt form or that increase overall toxicity of the product. This paper proposes a strategy to assess additive attributed toxicity in the context of the TPD. Literature was searched on toxicity testing strategies for regulatory purposes from tobacco industry and governmental institutes. Although mainly traditional in vivo testing strategies have been applied to assess toxicity of unburnt additives and increases in overall toxicity of tobacco products due to additives, in vitro tests combined with toxicogenomics and validated using biomarkers of exposure and disease are most promising in this respect. As such, tests are needed that are sensitive enough to assess additive attributed toxicity above the overall toxicity of tobacco products, which can associate assay outcomes to human risk and exposure. In conclusion, new, sensitive in vitro assays are needed to conclude whether comparable testing allows for assessment of small changes in overall toxicity attributed to additives. A more pragmatic approach for implementation on a short-term is mandated lowering of toxic emission components. Combined with risk assessment, this approach allows assessment of effectiveness of harm reduction strategies, including banning or reducing of additives.