High-quality harmonized and standardized PFAS toxicogenomics data collectionAOP-based Analysis of Curated Transcriptomic Data Reveals a Context-dependent Core Mechanism of PFAS-induced Liver Steatosis

Dataset

Description

This dataset provides a curated, harmonized, and standardized collection of toxicogenomic data for per- and polyfluoroalkyl substances (PFAS), developed to support mechanistic, context-aware hazard characterization within a precision toxicology framework.

The collection integrates publicly available transcriptomic datasets generated following PFAS exposure across multiple biological systems, species, exposure durations, and concentrations. All datasets were subjected to rigorous quality control, standardized preprocessing, and harmonization to ensure interoperability and comparability across studies. To address critical data gaps, particularly in immune-related contexts, the collection also includes newly generated transcriptomic profiles from PMA-differentiated THP-1 macrophages exposed to seven PFAS (legacy and emerging alternatives) at multiple subtoxic, equipotent concentrations and time points (24 h, 48 h, and 72 h).

The dataset is specifically structured to enable integration with the Adverse Outcome Pathway (AOP) framework and supports the reconstruction of context-dependent mechanistic pathways linking molecular initiating events to downstream key events and adverse outcomes. 

The repository includes:





Entry-level metadata


Normalized expression matrices



Raw count matrix


Filtered and unfiltered differentially expressed genes



Scripts and workflows used for data curation, standardization, preprocessing, and subsequent analysis


A detailed table of entry-level characteristics.


This resource addresses current limitations in chemical risk assessment by enabling multi-chemical, multi-endpoint, and biologically contextualized analyses. The dataset is fully interoperable and extensible, allowing future integration of additional toxicogenomic datasets processed using the same quality standards and workflows, and can be readily adapted to other chemical classes.
Date made available19 Dec 2025
PublisherZenodo

Funding

FundersFunder number
European Commission101037509, 101043848, 101137405, 101137742

    Field of science, Statistics Finland

    • 3111 Biomedicine

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