Integration of multi-omics and benchmark dose modeling to support adverse outcome pathways

Area of Science:

• Radiation toxicology
• Systems biology
• Genomics and proteomics

Background:

• Omics technologies and benchmark dose (BMD) modeling advance the identification of doses causing specific biological changes.
• Adverse Outcome Pathways (AOPs) link toxicants to adverse effects via key events (KEs).
• Integrating omics data with AOPs quantitatively connects molecular events to phenotypic outcomes.

Purpose of the Study:

• To apply omics-based BMD analyses in an in vitro blood model exposed to radiation.
• To identify point of departure (POD) values for key events (KEs) leading to acute myeloid leukemia (AOP 432).

Main Methods:

• White blood cells were cultured and exposed to X-radiation.
• Transcriptomic and proteomic changes were analyzed 24 hours post-exposure.
• BMD modeling identified perturbed genes, proteins, and pathways relevant to AOP 432 KEs.

Main Results:

• BMD modeling identified 1294 genes and 167 proteins with median BMD lower confident limit (BMD) values of 1.35 and 0.32 Gy, respectively.
• Pathway analysis revealed processes including DNA damage/repair, oxidative stress, cell cycle regulation, immune responses, and cancer development, aligning with AOP 432 KEs.
• BMDL values for pathways linked to KEs were generally below 0.5 Gy, with some genes showing BMDLs <0.05 Gy.

Conclusions:

• This research offers insights into predictive mechanisms of radiation-induced effects.
• The findings inform risk analysis for low-dose radiation (< 0.1 Gy) by identifying associated doses of activity.