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Evaluation of 5-Day In Vivo Rat Liver and Kidney with High-Throughput Transcriptomics for Estimating Benchmark Doses of Apical Outcomes

ABSTRACT: Evaluation of 5-Day In Vivo Rat Liver and Kidney with High-Throughput Transcriptomics for Estimating Benchmark Doses of Apical Outcomes

PROVIDER: PRJNA612884 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR11316100.fastq.gz	Fastqsanger.gz
	SRR11316200.fastq.gz	Fastqsanger.gz
	SRR11316300.fastq.gz	Fastqsanger.gz
	SRR11316400.fastq.gz	Fastqsanger.gz
	SRR11316500.fastq.gz	Fastqsanger.gz

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Evaluation of 5-Day In Vivo Rat Liver and Kidney with High-Throughput Transcriptomics for Estimating Benchmark Doses of Apical Outcomes

Project description:The Division of the National Toxicology Program (DNTP) is currently evaluating high-throughput transcriptomics (HTT) as an approach to provide estimates of chemical exposure that may pose minimal risk. HTT was evaluated in a 5-day in vivo rat model (with repeated dosing) with the objective to determine if benchmark doses (BMD) values for transcriptional pathway changes in the liver and kidney could estimate BMD values for traditional toxicological (apical) endpoints. Eighteen chemicals, most having been tested by the NTP in 2-year bioassays, were chosen for this study. Some of these chemicals are known to be potent hepatotoxicants (e.g. DE71, PFOA, furan, and methyl eugenol) in rodents, some exhibit toxicity but have minimal effects on the liver (e.g. acrylamide and α,β-thujone), and some exhibit little overt toxicity (e.g. ginseng and milk thistle extract) based on traditional toxicological evaluations. Male Sprague Dawley rats were exposed daily for 5 consecutive days by oral gavage to 8 to 10 dose levels of each chemical. Liver and kidney were collected 24 hours after the final exposure and assayed using HTT with the rat S1500+ platform. HTT dose-response data were analyzed using BMD Express 2.2 to determine transcriptional BMD values for liver and kidney. BMDS Wizard was used to determine apical BMD values for histopathological effects from historical chronic or sub-chronic toxicity studies. For many of the chemicals, the lowest transcriptional BMDs from the 5-day assays were within a factor of 5 of the lowest histopathological BMDs estimated from the traditional toxicity studies. These data suggest that using HTT in a 5-day in vivo model provides reasonable estimates of BMD values for traditional apical endpoints. This approach may be useful to prioritize chemicals for further testing while providing actionable data in a timely and cost-effective manner.

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Project description:A 5-day in vivo rat model was evaluated as an approach to estimate chemical exposures that may pose minimal risk by comparing benchmark dose (BMD) values for transcriptional changes in the liver and kidney to BMD values for toxicological endpoints from traditional toxicity studies. Eighteen chemicals, most having been tested by the National Toxicology Program in 2-year bioassays, were evaluated. Some of these chemicals are potent hepatotoxicants (eg, DE71, PFOA, and furan) in rodents, some exhibit toxicity but have minimal hepatic effects (eg, acrylamide and α,β-thujone), and some exhibit little overt toxicity (eg, ginseng and milk thistle extract) based on traditional toxicological evaluations. Male Sprague Dawley rats were exposed once daily for 5 consecutive days by oral gavage to 8-10 dose levels for each chemical. Liver and kidney were collected 24 h after the final exposure and total RNA was assayed using high-throughput transcriptomics (HTT) with the rat S1500+ platform. HTT data were analyzed using BMD Express 2 to determine transcriptional gene set BMD values. BMDS was used to determine BMD values for histopathological effects from chronic or subchronic toxicity studies. For many of the chemicals, the lowest transcriptional BMDs from the 5-day assays were within a factor of 5 of the lowest histopathological BMDs from the toxicity studies. These data suggest that using HTT in a 5-day in vivo rat model provides reasonable estimates of BMD values for traditional apical endpoints. This approach may be useful to prioritize chemicals for further testing while providing actionable data in a timely and cost-effective manner.

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