DTT Data Collections Guided Search

Biomarkers predictive of molecular and toxicological effects are needed to interpret emerging high-throughput transcriptomic data streams. The TGx-DDI biomarker was compared to microarray data in a compendium derived from human cells using the Running Fisher test, a nonparametric correlation test. In addition, the Tox21 p53 assay examined p53 responses at multiple doses at 16 h and in parallel identified doses that were cytotoxic. This dataset contains 19 biosets that were positive in the Tox21 Assay.

This data collection contains a subset of clinical chemistry individual animal data collected between 1987 and 2016 by the Division of Translational Toxicology (DTT). Additional data will be added to this dataset as it becomes available.

Assay names, tissue inputs, test compounds, species, strains, routes, units, and treatment roles have been standardized. The original values from the legacy data can be found on the right side of the dataset.

Original observed values (Adjusted Original Value) have been adjusted to numeric values and converted using the Conversion Factor field. The Conversion Factor is based on the Standard Unit assigned to a Standard Assay Name.

Simple dose-response studies can be identified by the Is Study Dose Response field.

The ICCVAM in vitro basal cytotoxicity assays proposed for setting starting doses for in vivo acute oral toxicity studies.

Summary body weight data with ratio of the treatment group body weight mean to the control group body weight mean.

The dataset provides data on the effects of chemicals on the Estrogen Receptor (ER) from uterotrophic assays.

We took as a case study the challenge to find work on flame retardants conducted by authors affiliated with the National Toxicology Program

Findings:
24 NTP-authored reports
26 publications in CEBS (many conducted on libraries of compounds, some FR
23 in Pubmed (and not in CEBS)  search: (affiliation = “National Toxicology Program”) and (flame)
7 in both CEBS and PubMed

We then reviewed the abstract to identify the species, cell system, duration of exposure and assays / endpoints measured. 

Result – a data set listing 70 publications, 68 distinct chemicals or chemical mixtures, and 295 chemical/publication combination (i.e. a chemical listed in a publication)

Historically DTT has Chemtrack Testing Status Pages (TSP), we integrated them with the CEBS Pages. Most of the Chemtrack TSPs are mapped to the CEBS Test Article Pages by aligning the Test Articles. A few of the TSPs are mapped to the CEBS Publication Pages or other CEBS pages.

The dataset provides a list of recommended reference substances for validation of In Vitro Murine Local Lymph Node Assay (LLNA) for skin sensitization.

Data of animal neurological and developmental/congenital outcomes from chemical exposure with relevance to human health effects.

Conclusions from Ames studies for each strain, activation condition, etc.

The dataset provides DTT conclusions from bioassay level of evidence, and genetic toxicology measures of bacterial mutagenicity, micronucleus, and comet assay; February 2022 version.

In TR544 and subsequent reports, for studies showing multiple chemical-related neoplastic effects that if considered individually would be assigned to different levels of evidence categories. In a study with clear evidence of carcinogenic activity at some tissue sites, other responses that alone might be deemed some evidence are indicated as “were also related” to chemical exposure. In studies with clear or some evidence of carcinogenic activity, other responses that alone might be termed equivocal evidence are indicated as “may have been” related to chemical exposure.  These levels of evidence are now included in this dataset.

Inhalation Threshold Limit Values (TLVs) for 112 chemicals listed in the 2015, American Conference of Governmental Industrial Hygienists (ACGIH) booklet entitled "TLVs and BEIs Based on the Documentation of the Threshold Limit Values for Chemical Substances and Physical Agents & Biological Exposure Indices".

Data of animal biological systems affected by chemical exposure with relevance to human health effects.

Annotation of Hallmark Gene Sets using NextBio platform to identify correlations between Hallmark Gene Sets and gene expression studies focusing on liver, heart and kidney tissue in rodents and humans. Additionally, correlations to gene expression studies in other tissues in rodents are described herein.

Biomarkers predictive of molecular and toxicological effects are needed to interpret emerging high-throughput transcriptomic data streams. The TGx-DDI biomarker was compared to microarray data in a compendium derived from human cells using the Running Fisher test, a nonparametric correlation test. This dataset contains 274 biosets with a significant TGx-DDI biomarker correlation.

This dataset contains individual animal lesions from the Division of Translational Toxicology (DTT) studies including legacy and recently reported data.  Tissue name, locator, morphology, and modifier terminologies have been harmonized for this dataset.  

We have a current DTT dictionary available at https://doi.org/10.22427/NTP-DATA-002-00092-0002-0000-5. The terms used to develop this collection is available here: https://doi.org/10.22427/NTP-DATA-002-00092-0001-0000-4.
 
The data contained herein were collected in 2021 from a source now known to contain omissions.  We plan to replace with an up to date dataset in 2023.

Conclusions from Drosophila germ cell mutagenicity studies.

Conclusions from mammalian cell cytogenetics studies for CHO-W-B1 hamsters.

Conclusions from mammalian cell mutagenics studies for each activation condition.

Conclusions from rodent cytogenetics studies for B6C3F1 mice.

Study and trial conclusions from in vivo micronucleus assays for each strain and tissue, etc.

This dataset provides an overview of public studies accessioned into the DTT Collection, including test compounds and standardized study factors like sex, species, strain, route, role, and vehicle. Standard terms are derived from the Data Dictionary.

Inhalation Threshold Limit Values (TLVs) for 103 chemicals originally listed in Schaper, M. (1993), Development of a database for sensory irritants and its use in establishing occupational exposure limits, Am. Ind. Hyg. Assoc. J. 54: 488-544; doi: 10.1080/15298669391355017, were updated in 2015. Data resulting from this update are included in this data table.

Catalog of studies of Environmental Health (EH) interest with expression data performed by members of DTT, NIEHS and other collaborators.  Work can be filtered using common metadata using the CEBS data collections interface.
 
Other metadata useful to interpret a toxicology or EH study are being collected; this project is expected to evolve.  For the present time, links to external files with metadata and other data for the subjects are provided where they are available from the author.
 
Each study is linked to a public repository or other source to permit the data themselves to be retrieved.  If the study is deposited in the Gene Expression Omnibus (GEO) then the link to the tools provided by GEO to analyze the data is 
also provided.
 
This catalog is from voluntary submissions.  To submit data for consideration please contact CEBS-Support@mail.nih.gov 

Keywords: microarray, microarrays, next-generation, sequence, sequencing, transcriptomics

This dataset provides a mapping of individual subjects that have data occurring in multiple legacy databases. GDB is a legacy database that contains data relating to hematology, organ weights, andrology, and other clinical chemistry recorded observations (Single Point Data). TDMSE is a legacy database that contains data relating to histopathology and clinical pathology findings (Observation Data). When a subject underwent assays from both categories (Single Point Data and Observation Data), then the subjects are represented in both databases, by different unique identifiers. This dataset provides the mapping necessary to identify a single subject across single point and observation data findings.

The dataset provides a list of recommended reference substances for evaluation or validation of In Vitro Androgen Receptor (AR) agonism assays.

This dataset contains lists of DTT chemicals sent to various collaborators for public and/or private DTT studies.
A copy of the form used to submit chemistry lists is available here: Chemical List Submission Form.

This dataset contains lists of modern terms, along with DevTox and ontology metadata, used by DTT for developmental morphologies.

This dataset contains a list of analytes used in DTT studies along with their ontology metadata and definitions.

This dataset contains a collection of assays that are routinely used by DTT investigators.  Metadata included are DDD ID, standard unit, definition, display name, and ontology metadata.

Phase I and II C. elegans and zebrafish toxicity estimates. Developmental Effects of the ToxCast™ Phase I and Phase II Chemicals in Caenorhabditis elegans and Corresponding Responses in Zebrafish, Rats, and Rabbits. Windy A. Boyd , Marjolein V. Smith , Caroll A. Co , Jason R. Pirone , Julie R. Rice , Keith R. Shockley , and Jonathan H. Freedman. Published:01May2016. https://doi.org/10.1289/ehp.1409645.

This data collection contains a subset of hematology individual animal data collected between 1987 and 2016 by the Division of Translational Toxicology (DTT). Additional data will be added to this dataset as it becomes available.

Assay names, tissue inputs, test compounds, species, strains, routes, units, and treatment roles have been standardized. The original values from the legacy data can be found on the right side of the dataset. Original observed values (Adjusted Original Value) have been adjusted to numeric values and converted using the Conversion Factor field. The Conversion Factor is based on the Standard Unit assigned to a Standard Assay Name.

Simple dose-response studies can be identified by the Is Study Dose Response field.

Evaluation of androgen assay results using a curated Hershberger database. Kleinstreuer NC, Browne P, Chang X, Judson R, Casey W, Ceger P, Deisenroth C, Baker N, Markey K, Thomas RS. Published: 25 May 2018. https://doi.org/10.1016/j.reprotox.2018.08.017. Performance data from applying the ToxCast/Tox 21 androgen receptor model, based on 11 high throughput assays, to 39 reference chemicals.

Evaluation of androgen assay results using a curated Hershberger database. Kleinstreuer NC, Browne P, Chang X, Judson R, Casey W, Ceger P, Deisenroth C, Baker N, Markey K, Thomas RS. Published: 25 May 2018. https://doi.org/10.1016/j.reprotox.2018.08.017. Performance data from applying the ToxCast/Tox 21 androgen receptor model, based on 11 high throughput assays, to 39 reference chemicals.

Evaluation of androgen assay results using a curated Hershberger database. Kleinstreuer NC, Browne P, Chang X, Judson R, Casey W, Ceger P, Deisenroth C, Baker N, Markey K, Thomas RS. Published: 25 May 2018. https://doi.org/10.1016/j.reprotox.2018.08.017. Performance data from applying the ToxCast/Tox 21 androgen receptor model, based on 11 high throughput assays, to 39 reference chemicals.

Conclusions from comet assays for each strain, organ, etc.

Collection of DTT research products and other works of interest to environmental health scientists

Study and trial conclusions from micronucleus assays for each cell type and activation condition, etc.

This data collection contains a subset of organ weight individual animal data collected between 1987 and 2016 by the Division of Translational Toxicology (DTT). Additional data will be added to this dataset as it becomes available.

Assay names, tissue inputs, test compounds, species, strains, routes, units, and treatment roles have been standardized. The original values from the legacy data can be found on the right side of the dataset. Original observed values (Adjusted Original Value) have been adjusted to numeric values and converted using the Conversion Factor field. The Conversion Factor is based on the Standard Unit assigned to a Standard Assay Name.

Simple dose-response studies can be identified by the Is Study Dose Response field.

The purity data is for the DTT Tox21 Phase 2 chemicals provided to NCATS for the Tox21 Phase 2 program. These data results from the analysis of neat chemicals, prior to the preparation of the DMSO solutions sent to NCATS and should not be equated with NCATS QC Day 0 or QC Day 4 data.

Key for the purity flags in the MRI 1-page reports

This dataset contains a list of modern tissue terms used by DTT for histopathology and gross pathology.  Metadata include scope of term, body system, sex specificity, paired flag and ontology.

This dataset contains lesions found in studies where each dose group had two or more of the lesion.  Lesions with a statistically significant difference (p<0.05) in incidence between the exposed and control animals are flagged.

The data contained herein were collected in 2020 from a source now known to contain omissions.  We plan to replace with an up to date dataset in 2023.

This dataset contains a list of modern locator terms used by DTT for histopathology and gross pathology.  Metadata include scope of term and ontology.

This dataset contains a list of modern modifier terms used by DTT for histopathology and gross pathology.  Metadata include scope of term and ontology.

This dataset contains a list of modern morphology terms used by DTT for histopathology and gross pathology.  Metadata include scope of term, malignant/benign, neoplastic/non-neoplastic, systemic, severity, qualifier flags and ontology.

Full dataset, method, and other related data are available at https://doi.org/10.22427/NTP-DATA-500-010-002-000-8 

This project was centered around curating in vivo transcriptional biomarkers of toxicity for use in interpreting DTT transcriptomic dose-response studies, and secondarily for the construct validity assessment of in vitro biological systems. The curation encompassed extensive data compilation for each gene, including aliases, associations with toxicity and disease at the transcriptional level, and summaries of related protein families and structures. Additionally, we collected information on proteins known to interact with gene products, linked to relevant gene databases, and annotated with Gene Ontology (GO) terms, MSigDB signatures, and pathway descriptions. This curation also extended to the cellular locations of gene products, mechanistic insights into gene roles in pathogenesis, upstream regulators such as transcription factors, and expression profiles in specific tissues and cell types under normal and disease conditions. We also explored the chemical inducers of the transcriptional response and documented biomarker associations with specific diseases in relevant organs. This effort entailed extensive curation, data crawling, machine learning, and the use of artificial intelligence, specifically an LLM-based agentic workflow. The resultant product of this effort includes 125 reports covering transcriptional biomarkers across 12 tissues: liver, kidney, heart, skeletal muscle, lung, intestine, skin, thyroid, bone marrow, colon, and brain. This foundational work is pivotal to our initial documentation of how transcriptional biomarkers function within biological systems and respond to toxicological challenges, thereby facilitating more accurate assessments of potential hazards and therapeutic interventions. It is intended that this curated resource will act as a living repository of information and be updated as additional knowledge becomes available.