Transcriptomic Biomarkers of Toxicological Effect

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.