Characterization of Two Stable Biodosimeters for Absorbed Ionizing Radiation Dose Estimation in Multiple Combined Injury Models.

Abstract

Radiation damage and deposition caused by radiological or nuclear public health incidents (e.g., accidents or attacks) may lead to acute radiation syndrome and other complications. Accurate and effective radiation dose assessment is necessary for triaging irradiated patients and determining treatment plans. However, there is no systematic evaluation of whether radiation biodosimetry is affected by comorbidities. The weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEG) co-analysis of the RNA-sequencing data in human peripheral blood after irradiation from the Gene Expression Omnibus (GEO) database identified seven radiation-specific genes, including five upregulated genes and two downregulated genes. Five radiation-specific genes (CCNG1, CDKN1A, GADD45A, GZMB, PHLDA3) showed a strong linear correlation with the total-body X-ray radiation model. The above five genes were used to validate further several radiation combined injury models, including infection, trauma, and burns, while considering different sexes and ages in animal studies on the radiation response from 0 to 10 Gy. The receiving operator characteristic (ROC) curve analysis revealed that the CCNG1 and CDKN1A genes performed the best in radiation dose-response across both mice and humans. Moreover, the CCNG1 protein could accurately predict the absorbed doses for up to 28 days after exposure (>95%). Our findings suggested that the CCNG1 and CDKN1A mRNA performed optimally in radiation dose response, independent of trauma, burns, age, and sex. Additionally, the CCNG1 protein revealed a strong linear correlation between radiation dose and time postirradiation. Our study demonstrated the potential feasibility of using CCNG1 and CDKN1A as injury biomarkers in radiation accident management.