CONSISTENT AND CONFLICTING METABOLOMIC SIGNATURES OF RADIATION EXPOSURE: A REVIEW OF CROSS-SPECIES EVIDENCE
Publication Information
Volume:
1
Pages:
14
Submitted:
October 18, 2026
Status:
Pending
Abstract
Background: Biodosimetry categorizes the severity of radiation exposure and the urgency of clinical response, which is especially important in emergency settings where physical dosimetry is unavailable or unreliable. Metabolomics, the study of small molecule metabolites that reflect real time metabolic response, offers an unbiased, dose-dependent complement to existing clinical and hematological triage methods.
Objective: To consolidate cross-species metabolomic evidence of radiation exposure and identify consistent versus conflicting biomarker signals for biodosimetry applications
Methods: This review consolidated evidence across more than one hundred study arms drawn from preclinical and clinical literature, comparing findings generated using the two principal analytical platforms: mass spectrometry (MS), valued for its sensitivity and high throughput, and nuclear magnetic resonance (NMR) spectroscopy, valued for its reproducibility and minimal sample preparation.
Results: Several metabolites most notably citrulline, citric acid/citrate, uric acid, and creatine show consistent, dose-responsive trends across species and biofluids, making them leading candidates for a biomarker panel. Taurine and carnitine show a moderately consistent directional trend tempered by sex or species-specific exceptions, while xanthine, hypoxanthine, threonine, and creatinine show more variable, time-dependent responses, reflecting the influence of genetic background, sex, timepoint, and radiation quality on the metabolome. A further group of metabolites, each reported in only one or two studies, cannot yet be assessed for reliability.
Conclusion: This review consolidates the current evidence base, highlights where signals are consistent versus conflicting, and outlines the remaining barriers chiefly inter-individual variability, cross-species extrapolation, and lack of platform standardization to clinical translation of metabolomic biodosimetry.