Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology

Abstract

Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.

Keywords: MRF; Metabolomics; Metabolomics reporting framework; OECD; QA/QC; Regulatory; TRF; Toxicology; Transcriptomics; Transcriptomics reporting framework.

Figure 1.. Modular structure of the omics reporting framework for transcriptomics and metabolomics.

Four principal types of modules are included: Study Summary Reporting Module (SSRM) describing a subset of reporting elements to provide a high level overview of the whole study; Toxicology Experiment Reporting Module (TERM) describing the in vivo or in vitro toxicology study; Data Acquisition and Processing Reporting Modules (DAPRM) describing the omics assays, data acquisition and processing; and Data Analysis Reporting Modules (DARM) describing the statistical analysis of the omics data. Orange modules are harmonized across transcriptomics and metabolomics, blue modules are specific to transcriptomics, and green modules are specific to metabolomics.

Figure 2.. Approach to trialling the reporting framework.

The modules within the framework are currently being reviewed for clarity, completeness, utility and ease of use through six trials. Each trial comprises five phases, involving a data provider (initial analysis –red box), end user (re-analysis – blue box), a trialling coordinator (green boxes) and the TRF or MRF expert groups (purple box). For a module to be approved, it must enable an end user to reproduce the analysis of an omics dataset, relative to the initial analysis by the data provider.