4.5 Article

DDB2 and MDM2 genes are promising markers for radiation diagnosis and estimation of radiation dose independent of trauma and burns

期刊

FUNCTIONAL & INTEGRATIVE GENOMICS
卷 23, 期 4, 页码 -

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s10142-023-01222-w

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Biodosimetry; Radiation biomarkers; Radiation diagnosis; Trauma; Burn; Mass casualty radiation exposure

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Through analyzing microarray datasets of human blood samples exposed to different types of radiation, 33 multi-type ray co-induced genes were identified, mainly enriched in DNA damage, cellular apoptosis, and p53 signaling pathway. 12 radiation-specific genes independent of trauma and burns were further screened. DDB2 gene performed the best in the diagnosis of all types of ray radiation, while MDM2 gene was the best indicator for assessing radiation dose.
In the field of biodosimetry, the current accepted method for evaluating radiation dose fails to meet the need of rapid, large-scale screening, and most RNA marker-related studies of biodosimetry are concentrating on a single type of ray, while some other potential factors, such as trauma and burns, have not been covered. Microarray datasets that contain the data of human peripheral blood samples exposed to X-ray, neutron, and & gamma;-ray radiation were obtained from the GEO database. Totally, 33 multi-type ray co-induced genes were obtained at first from the differentially expressed genes (DEGs) and key genes identified by weighted gene co-expression network analysis (WGCNA), and these genes were mainly enriched in DNA damage, cellular apoptosis, and p53 signaling pathway. Following transcriptome sequencing of blood samples from 11 healthy volunteers, 13 patients with severe burns, and 37 patients with severe trauma, 6635 trauma-related DEGs and 7703 burn-related DEGs were obtained. Through the exclusion method, a total of 12 radiation-specific genes independent of trauma and burns were identified. ROC curve analysis revealed that the DDB2 gene performed the best in diagnosis of all three types of ray radiation, while correlation analysis showed that the MDM2 gene was the best in assessment of radiation dose. The results of multiple-linear regression analysis indicated that such analysis could improve the accuracy in assessment of radiation dose. Moreover, the DDB2 and MDM2 genes remained effective in radiation diagnosis and assessment of radiation dose in an external dataset. In general, the study brings new insights into radiation biodosimetry.

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