Early dose stratification 4 h after ionizing radiation exposure using a peripheral blood transcriptional gene panel
Abstract
Biodosimetry is essential for absorbed-dose estimation following occupational radiation accidents where early clinical decisions determine whether individuals require hospitalization or can be managed on an outpatient basis. Radioinduced transcriptomic alterations are a promising tool for rapid dose estimation. We established a gene expression panel for dose classification at 4 h post-exposure, reducing the time typically required for cytogenetic assays. Peripheral blood leukocytes from healthy individuals were X-ray irradiated and cultured for 4 h. RNA was sequenced and reads were mapped to the human hg38 genome (STAR software). Differentially expressed genes (DEGs) were identified using DESeq2 (false discovery rate, FDR, < 0.05). Radiation specificity was confirmed using eight independent microarray datasets from multiple disease conditions. DEGs were validated by RT-qPCR. A total of 215 DEGs were identified; hierarchical clustering separated samples by absorbed dose. AEN, CD70, CDKN1A, DDB2, FDXR, PCNA, and VPREB3 showed strong dose-dependent transcriptional changes across multiple disease conditions, demonstrating specificity to IR. A LASSO logistic regression model discriminated between low-dose (0–100 cGy) and high-dose (≥ 200 cGy) exposures, achieving AUC-ROC = 0.88 with CDKN1A and CD70, and AUC-ROC = 1.00 with CDKN1A, CD70, and DDB2. This gene panel offers a reliable tool for early classification of radiation exposure, supporting improved treatment of exposed individuals.
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BibTeX
@article{biolatti2026early,
title = {{Early dose stratification 4 h after ionizing radiation exposure using a peripheral blood transcriptional gene panel}},
author = {Luisa V. Biolatti and Maria S. Ausas and Jerónimo Leberle and Damián G. Hernández and Lara Negrin and Laura Mazzitelli-Fuentes and Adriana Cascon and Ananya Choudhury and Nicolas Bellora and Irene L. Ibañez},
journal = {Scientific Reports},
year = {2026},
month = oct,
doi = {10.1038/s41598-026-75083-1},
url = {https://www.nature.com/articles/s41598-026-75083-1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Early dose stratification 4 h after ionizing radiation exposure using a peripheral blood transcriptional gene panel
AU - Luisa V. Biolatti
AU - Maria S. Ausas
AU - Jerónimo Leberle
AU - Damián G. Hernández
AU - Lara Negrin
AU - Laura Mazzitelli-Fuentes
AU - Adriana Cascon
AU - Ananya Choudhury
AU - Nicolas Bellora
AU - Irene L. Ibañez
PY - 2026
DA - 2026/10/22
JO - Scientific Reports
DO - 10.1038/s41598-026-75083-1
UR - https://www.nature.com/articles/s41598-026-75083-1
AB - Biodosimetry is essential for absorbed-dose estimation following occupational radiation accidents where early clinical decisions determine whether individuals require hospitalization or can be managed on an outpatient basis. Radioinduced transcriptomic alterations are a promising tool for rapid dose estimation. We established a gene expression panel for dose classification at 4 h post-exposure, reducing the time typically required for cytogenetic assays. Peripheral blood leukocytes from healthy individuals were X-ray irradiated and cultured for 4 h. RNA was sequenced and reads were mapped to the human hg38 genome (STAR software). Differentially expressed genes (DEGs) were identified using DESeq2 (false discovery rate, FDR, < 0.05). Radiation specificity was confirmed using eight independent microarray datasets from multiple disease conditions. DEGs were validated by RT-qPCR. A total of 215 DEGs were identified; hierarchical clustering separated samples by absorbed dose. AEN, CD70, CDKN1A, DDB2, FDXR, PCNA, and VPREB3 showed strong dose-dependent transcriptional changes across multiple disease conditions, demonstrating specificity to IR. A LASSO logistic regression model discriminated between low-dose (0–100 cGy) and high-dose (≥ 200 cGy) exposures, achieving AUC-ROC = 0.88 with CDKN1A and CD70, and AUC-ROC = 1.00 with CDKN1A, CD70, and DDB2. This gene panel offers a reliable tool for early classification of radiation exposure, supporting improved treatment of exposed individuals.
SN - 2045-2322
ER -