Cross-platform validation of a mouse blood gene signature for quantitative reconstruction of radiation dose

Abstract

In the search for biological markers after a large-scale exposure of the human population to radiation, gene expression is a sensitive endpoint easily translatable to in-field high throughput applications. Primarily, the ex-vivo irradiated healthy human blood model has been used to generate available gene expression datasets. This model has limitations i.e., lack of signaling from other irradiated tissues and deterioration of blood cells cultures over time. In vivo models are needed; therefore, we present our novel approach to define a gene signature in mouse blood cells that quantitatively correlates with radiation dose (at 1 Gy/min). Starting with available microarray datasets, we selected 30 radiation-responsive genes and performed cross-validation/training–testing data splits to downselect 16 radiation-responsive genes. We then tested these genes in an independent cohort of irradiated adult C57BL/6 mice (50:50 both sexes) and measured mRNA by quantitative RT-PCR in whole blood at 24 h. Dose reconstruction using net signal (difference between geometric means of top 3 positively correlated and top 4 negatively correlated genes with dose), was highly improved over the microarrays, with a root mean square error of ± 1.1 Gy in male and female mice combined. There were no significant sex-specific differences in mRNA or cell counts after irradiation.

Variable Dose Rates in Realistic Radiation Exposures: Effects on Small Molecule Markers of Ionizing Radiation in the Murine Model

“…For immunophenotyping, blood was collected after irradiation and an aliquot was added to EDTA and then processed for immunophenotyping using a CytoFLEX flow cytometer (Beckman Coulter Inc., Brea, CA) as described previously ( 20 ). Briefly, cell counts were quantified by flow cytometry, using mouse antibodies for WBC (Biolegend, catalog #103115, APC/Cy7 anti-mouse CD45), B cells (Biolegend catalog #115508, PE anti-mouse CD19), T cells (Biolegend catalog #100312 APC anti-mouse CD3ϵ) and neutrophils (Biolegend, catalog #127627, Brilliant Violet 421™ anti-mouse Ly-6G).…”

Circulating miRNA profiles in COVID-19 patients and meta-analysis: implications for disease progression and prognosis

“…While these individual studies offer valuable insights, we decided to perform a meta-analytical approach by aggregating and analyzing findings from different studies (including our own). Previously, meta-analysis have been utilized to improve diagnosis and prognosis of multiple injuries and diseases 13 – 15 . The goal of our work is to identify common COVID-19 molecular signatures by reconciling discrepancies or variations between individual studies.…”