Distinct Urinary Metabolite Signatures Mirror In Vivo Oxidative Stress-Related Radiation Responses in Mice

Area of Science:

• Biochemistry
• Toxicology
• Metabolomics

Background:

• Ionizing radiation disrupts cellular metabolism and induces oxidative stress, potentially leading to organ damage.
• Understanding radiation's metabolic impact is crucial for developing countermeasures and diagnostic tools.

Purpose of the Study:

• To investigate the metabolic consequences of different types of radiation exposure.
• To identify urinary biomarkers indicative of radiation damage and oxidative stress.

Main Methods:

• Analysis of urinary metabolites in mice using targeted and untargeted metabolomics.
• Application of machine learning models to identify predictive biomarkers.

Main Results:

• Significant metabolic alterations, especially in oxidative stress pathways, were observed by Day 2 post-irradiation.
• High-dose whole-body irradiation (WBI HDR) caused persistent metabolic dysregulation by Day 30.
• Low-dose whole-body irradiation (WBI LDR) and partial-body irradiation (PBI BM2.5) groups showed metabolic profiles similar to controls by Day 30.
• Machine learning models accurately predicted radiation exposure type based on identified metabolites.

Conclusions:

• Urinary metabolomics can detect early signs of radiation-induced metabolic disruption.
• Specific metabolites serve as reliable biomarkers for classifying radiation exposure types and assessing damage.
• These findings support the development of diagnostic tools for radiation exposure.