Calibration curve for radiation dose estimation using FDXR gene expression biodosimetry - premises and pitfalls

Area of Science:

• Radiation Biology
• Molecular Biology
• Biotechnology

Background:

• Gene expression alterations after radiation exposure are key for dose reconstruction and health effect prediction.
• FDXR is a promising biomarker due to its upregulation in white blood cells post-irradiation.
• Standardized protocols are lacking for gene expression-based biodosimetry, impacting accuracy and reliability.

Purpose of the Study:

• To evaluate the sensitivity of transcriptional biodosimetry to protocol variations across laboratories.
• To establish guidelines for calculating calibration curves using FDXR expression data.
• To enhance the accuracy, reproducibility, and reliability of radiation dose assessment.

Main Methods:

• Utilized two sets of irradiated blood samples from a RENEB exercise.
• Analyzed FDXR expression via qPCR in participating laboratories using distinct primers/probes and reference genes.
• Generated calibration curves using linear and non-linear regression for dose estimation.

Main Results:

• Dose estimates for sham and 0.4 Gy samples showed high consistency across laboratories.
• Estimates for the 1.8 Gy sample were less precise but acceptable for high-dose triage.
• Variations in primers/probes and reference genes did not significantly impact dose estimates.

Conclusions:

• Methodological differences in FDXR analysis do not significantly affect dose estimates if protocols are sound.
• Linear regression is preferred for calibration curves relating log absorbed dose to FDXR ΔCt values.
• A calibration curve using this method provides reliable dose estimations from 50 mGy to 4 Gy.