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ToxStrategies scientists publish on the dose-response modeling of multi-omic responses to inorganic arsenic

ToxStrategies - Toxicology Consulting_Dose Response Modeling and Inorganic Arsenic

ToxStrategies scientists recently contributed to the publication of an article entitled ‘Benchmark Dose Modeling Estimates of the Concentrations of Inorganic Arsenic That Induce Changes to the Neonatal Transcriptome, Proteome, and Epigenome in a Pregnancy Cohort’ in Chemical Research in Toxicology. This study was a collaboration between Dr. Rebecca C. Fry (University of North Carolina), Dr. Scott Auerbach at the National Toxicology Program (NTP), and ToxStrategies scientists, Drs. Julia E. Rager, Grace Chappell, and Chad Thompson. The aim of this project was to evaluate the doses at which genomic and epigenomic changes occur in response to prenatal inorganic arsenic (iAs) exposure. Benchmark dose (BMD) modeling was carried out on multi-omic signatures in human cord blood using the updated version of BMDExpress (v2.0), recently released through the NIEHS.

Overall, DNA methylation changes were estimated to occur at lower exposure concentrations in comparison to other molecular endpoints. Multi-omic module eigengenes were derived through weighted gene co-expression network analysis, representing co-modulated signatures across transcriptomic, proteomic, and epigenomic profiles. One module eigengene was associated with decreased gestational age occurring alongside increased iAs exposure. Genes/proteins within this module eigengene showed enrichment for organismal development, including potassium voltage-gated channel subfamily Q member 1 (KCNQ1), an imprinted gene showing differential methylation and expression in response to iAs. Modeling of this prioritized multi-omic module eigengene resulted in a BMD(BMDL) of 58(45) μg/L U-tAs, which was estimated to correspond to drinking water arsenic concentrations of 51(40) μg/L. Results are in line with epidemiological evidence and present a variety of BMD measures to estimate doses at which prenatal iAs exposure influences neonatal outcome-relevant transcriptomic, proteomic, and epigenomic profiles.

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