Presymptomatic microRNA-based biomarker signatures for the prognosis of localized radiation injury in mice

The threat of nuclear or radiological events requires early diagnostic tools for radiation induced health effects. Localized radiation injuries (LRI) are severe outcomes of such events, characterized by a latent presymptomatic phase followed by symptom onset ranging from erythema and edema to ulceration and tissue necrosis. Early diagnosis is crucial for effective triage and adapted treatment, potentially through minimally invasive biomarkers including circulating microRNAs (miRNAs), which have been correlated with tissue injuries and radiation exposure, suggesting their potential in diagnosing LRI. In this study, we sought to identify early miRNA signatures for LRI severity prognosis before clinical symptoms appear. Using a mouse model of hindlimb irradiation at 0, 20, 40, or 80 Gy previously shown to lead to localized injuries of different severities, we performed broad-spectrum plasma miRNA profiling at two latency stages (day 1 and 7 post-irradiation). The identified candidate miRNAs were then challenged using two independent mouse cohorts to refine miRNA signatures. Through sparse partial least square discriminant analysis (sPLS-DA), signatures of 14 and 16 plasma miRNAs segregated animals according to dose groups at day 1 and day 7, respectively. Interestingly, these signatures shared 9 miRNAs, including miR-19a-3p, miR-93-5p, miR-140-3p, previously associated with inflammation, radiation response and tissue damage. In addition, the Bayesian latent variable modeling confirmed significant correlations between these prognostic miRNA signatures and day 14 clinical and functional outcomes from unrelated mice. This study identified plasma miRNA signatures that might be used throughout the latency phase for the prognosis of LRI severity. These results suggest miRNA profiling could be a powerful tool for early LRI diagnosis, thereby improving patient management and treatment outcomes in radiological emergency situations.