Prospective Validation of a Transcriptomic Metric in Severe Trauma

Supplemental Digital Content is available in the text Objective: To prospectively validate a previously discovered transcriptomic biomarker consisting of 63 blood leukocyte gene expression (S63) values to discriminate between trauma patients who rapidly recover and those with prolonged hospital stays who would benefit from early biological interventions. Background: Many severe trauma patients are successfully resuscitated but have complicated clinical trajectories leading to long-term functional, physical, and cognitive deficiencies. Identifying those trauma patients early would improve treatment plans and resource allocation. Unfortunately, current clinical scores and biomarkers used in trauma clinical trials have typically lacked adequate predictive ability. Methods: An independent, prospective, observational cohort study was performed involving 127 trauma subjects. The prospective cohort included patients admitted between October 2013 and August 2016 at 2 United States Level-1 trauma centers. An additional secondary analysis was performed using the Activation of Coagulation and Inflammation in Trauma (ACIT2) database of 26 trauma patients. Results: The S63 transcriptomic metric (AUC 0.80) outperformed clinical markers and plasma interleukin-6 for prospectively predicting trauma patients who require intensive care unit stays longer than 5 days with ongoing organ dysfunction. The same metric applied to an existing dataset (ACIT2) was similarly effective (AUC 0.85) at predicting multiorgan failure. Conclusions: A single transcriptomic metric of blood leukocyte gene expression can be used in blunt trauma cohorts at 24 hours to distinguish patients who rapidly recover from those with complicated clinical trajectories. The transcriptomic metric has been operationalized on an Food and Drug Administration 510(k)-cleared platform otherwise used for cancer diagnostics. This metric is only modestly improved when combined with clinical markers.