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Deriving an optimal transcriptomic metric to establish protective and relevant transcriptomic points of departure for risk assessment application (ICEM, Health Canada)
Citation:
Reardon, A., L. Everett, J. Harrill, AND I. Shah. Deriving an optimal transcriptomic metric to establish protective and relevant transcriptomic points of departure for risk assessment application (ICEM, Health Canada). Presented at 13th International Conference on Environmental Mutagens, Ottawa, Ontario, CANADA, August 27 - September 01, 2022. https://doi.org/10.23645/epacomptox.25048451
Impact/Purpose:
Anthony Reardon from Health Canada is planning on presenting work on a transcriptomics science approach document at the upcoming ICEM 2022 conference. Several EPA authors (Logan, Josh, Imran) provided comments on drafts of this document, which is still in development. Anthony Reardon requested to include these EPA scientists as authors on his abstract for ICEM, and Anthony will be the presenter.
Description:
The expanding number and complexity of substances used in products on the Canadian market presents a major challenge for risk assessment evaluating the health or ecological risks posed by these chemicals. The increasing demand and general paucity of data provides the opportunity to implement novel, more efficient strategies of assessment that use in vitro and in silico based methods. This investigation aims to increase confidence in the use of new approach methods (NAM)-based metrics in risk assessment and promote their implementation in a regulatory framework. A uniform workflow was applied across numerous datasets containing diverse chemicals to determine the most reliable and robust transcriptomic point of departure (tPOD) and compare these endpoints to those derived from traditional in vivo data. Transcriptomic data from chemicals (n = 110) across datasets were analysed using benchmark concentration (BMC) modeling and all samples were subject to identical parameters to create a uniform scenario to derive minimal bioactivity concentrations across numerous exposures and cell types. The 25th ranked gene was identified as the most consistent and reliable approach compared to other BMC distribution level metrics. High-throughput toxicokinetics was employed to translate tPODs (µM) to human relevant estimates (mg/kg-bw/day) that were found to be more conservative (i.e., protective) when compared to traditional endpoints. The derived tPODs presented across diverse chemicals and datasets provides evidence that in vitro data may be equal to or even more protective than traditional animal-derived data when used for chemical prioritization, building further confidence in using these approaches in risk assessment applications.
URLs/Downloads:
DOI: Deriving an optimal transcriptomic metric to establish protective and relevant transcriptomic points of departure for risk assessment application (ICEM, Health Canada)
AREARDON_TRANSCRIPTOMICS_P07_ICEM.PDF (PDF, NA pp, 2450.27 KB, about PDF)