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Nucleotide motif-guided selection of plasma microRNA biomarkers in trauma
Boyang Ren1, Ruoxing Li2, Chien-Yu Lin1
1Center for Shock, Trauma and Anesthesiology Research, University of Maryland School of Medicine, Baltimore, MD, USA.
Abstract:
Trauma remains a leading cause of morbidity and mortality in part due to complex pathophysiological responses. Yet our abilities to predict these changes are limited. Plasma miRNAs have been proposed as DAMPs that drive immune response and organ injury. Here, we test a panel of plasma miRNAs-selected based on next-generation sequencing and nucleotide motifs identified via a machine-learning algorithm-for their abilities to predict subclinical pathophysiological injuries. We find marked and severity-dependent increases in the miRNA biomarkers following trauma, which are closely associated with various injury markers. AUROC indicates that these biomarkers possess strong diagnostic and predictive abilities in overall trauma severity, organ injury, coagulation, endothelial activation, and inflammation. In a combined cohort of trauma and sepsis, miR-224-5p and miR-145-5p emerge as particularly effective in differentiating the two critical illnesses. These observations offer insights into potential values of the plasma miRNAs in the prediction of critical pathophysiological injury in trauma.
Insights
Plasma microRNAs (miRNAs) show promise in predicting trauma severity and organ injury. These biomarkers, identified using machine learning, offer insights into critical illness prediction and differentiation between trauma and sepsis.
Area of Science:
- Biochemistry
- Immunology
- Genomics
Background:
- Trauma is a major cause of death, with complex responses hindering prediction.
- Plasma microRNAs (miRNAs) are implicated as damage-associated molecular patterns (DAMPs) influencing immune responses and organ damage.
- Current methods for predicting trauma-induced pathophysiological changes are limited.
Purpose of the Study:
- To evaluate a panel of plasma miRNAs for predicting subclinical injuries after trauma.
- To assess the diagnostic and predictive capabilities of these miRNA biomarkers.
- To identify specific miRNAs that can differentiate between trauma and sepsis.
Main Methods:
- Plasma miRNAs were selected using next-generation sequencing and a machine-learning algorithm identifying nucleotide motifs.
- A panel of selected plasma miRNAs was tested for predictive abilities in trauma patients.
- Area Under the Receiver Operating Characteristic curve (AUROC) analysis was used to assess diagnostic performance.
Main Results:
- Trauma induced marked, severity-dependent increases in plasma miRNA levels.
- miRNA biomarker levels correlated closely with various injury markers.
- The biomarkers demonstrated strong predictive abilities for overall trauma severity, organ injury, coagulation, endothelial activation, and inflammation.
- In a combined trauma and sepsis cohort, miR-224-5p and miR-145-5p effectively differentiated the conditions.
Conclusions:
- Plasma miRNAs can serve as valuable biomarkers for predicting critical pathophysiological injuries in trauma.
- Specific miRNAs, such as miR-224-5p and miR-145-5p, show potential for distinguishing between trauma and sepsis.
- These findings highlight the potential of miRNAs in early detection and management of critical illnesses post-trauma.
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