Predictive Approaches and Technology Development for Identification of Susceptibility to Multiple Independent Infections in Trauma Patients

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Despite significant advances in trauma care, infections remain the primary cause of morbidity and mortality in severe trauma patients primarily due to their increased risk for multiple independent infection episodes (MIIE), secondary to dysregulated immunity, compromised skin barrier, and prolonged hospitalization. Current methods to combat infections mainly focus on early diagnosis and treatment after they establish. Analyzing retrospectively, a unique, comprehensive multi-center transcriptome and clinical database of adult blunt trauma patients from the “Inflammation and the Host Response to Injury Study” (Glue Grant), we developed a first-in-class multi-biomarker panel that predicts the risk of increased susceptibility to MIIE days before infections occur. The predictive pipeline we developed is a method that is fundamentally different from existing approaches/technologies that focus on rapid pathogen or sepsis detection after establishment. Our predictive model using blood RNA gene signatures of patients with severe trauma provides a more accurate prediction of MIIE outcome compared to using only clinical assessment. This proposal's overall objectives are to test the clinical utility of our method prospectively and develop a simplified, sensitive assay that will be clinically expedient for the assessment of the infection susceptibility risk prognostic biomarkers (ISRPB) expression levels. This will meet our long-term goal of a translational precision medicine strategy aspiring to be FDA qualified. Our success in modeling retrospectively the risk of increased susceptibility to MIIE in an adult severe trauma cohort let us hypothesize that the identified gene panel of multiple ISRPB can be validated in a blunt and penetrating severe adult trauma patient population and that a model combining ISRPB genomic measures with clinical data will be an effective and easy-to-use tool for clinicians to predict which trauma patients are at increased risk for MIIE. Thus, Aim 1 is designed to conduct a prospective study to externally validate the identified ISRPB multi-gene panel in predicting increased risk for MIIE in a new adult trauma patient population; Aim 2 will identify clinical variables and differences in pathogen prevalence associated with MIIE and construct combined models for MIIE outcome prediction that include transcriptomic and clinical measures; and Aim 3 will employ cutting edge technology to develop a clinically expedient and sensitive assay to predict MIIE. The proposed strategy is expected to lead to a paradigm shift in infection control, which currently heavily depends on the routine monitoring of vital signs and clinical symptoms of overt infection. Our approach will collectively create an innovative combinatorial strategy for early MIIE prediction and provide means for infection prophylaxis that will reduce patient morbidity and mortality, shorten hospital stays, reduce care costs, improve antibiotic stewardship and limit adverse side effects in patients associated with antibiotic use. Our approach could also be applied to other conditions that render patients vulnerable to infections.