Characterizing Variability and Uncertainty Associated with Transcriptomic Dose–Response Modeling

• Published in: Environmental science & technology 2022-11, Vol.56 (22), p.15960-15968
• Main Authors: Ewald, Jessica D., Basu, Niladri, Crump, Doug, Boulanger, Emily, Head, Jessica
• Format: Article
• Language: English
• Subjects: Animals; Chlorpyrifos; Coturnix; Datasets; Design of experiments; Dose-Response Relationship, Drug; Ecotoxicology and Public Health; Experimental design; Pesticides; Risk assessment; Risk Assessment - methods; Toxicogenetics - methods; Transcriptome; Transcriptomics; Uncertainty
• ISSN: 0013-936X; 1520-5851
• DOI: 10.1021/acs.est.2c04665

Transcriptomics dose–response analysis (TDRA) has emerged as a promising approach for integrating toxicogenomics data into a risk assessment context; however, variability and uncertainty associated with experimental design are not well understood. Here, we evaluated n = 55 RNA-seq profiles derived from Japanese quail liver tissue following exposure to chlorpyrifos (0, 0.04, 0.1, 0.2, 0.4, 1, 2, 4, 10, 20, and 40 μg/g; n = 5 replicates per group) via egg injection. The full dataset was subsampled 637 times to generate smaller datasets with different dose ranges and spacing (designs A–E) and number of replicates (n = 2–5). TDRA of the 637 datasets revealed substantial variability in the gene and pathway benchmark doses, but relative stability in overall transcriptomic point-of-departure (tPOD) values when tPODs were calculated with the “pathway” and “mode” methods. Further, we found that tPOD values were more dependent on the dose range and spacing than on the number of replicates, suggesting that optimal experimental designs should use fewer replicates (n = 2 or 3) and more dose groups to reduce uncertainty in the results. Finally, tPOD values ranged by over ten times for all surveyed experimental designs and tPOD types, suggesting that tPODs should be interpreted as order-of-magnitude estimates.