High-dimensional proteomics identifies organ injury patterns associated with outcomes in human trauma

Abstract

Introduction: Severe traumatic injury with shock can lead to direct and indirect organ injury; however, tissue-specific biomarkers are limited in clinical panels. We used proteomic and metabolomic databases to identify organ injury patterns after severe injury in humans.

Methods: Plasma samples (times 0, 24, and 72 hours after arrival to trauma center) from injured patients enrolled in two randomized prehospital trials were subjected to multiplexed proteomics (SomaLogic Inc., Boulder, CO). Patients were categorized by outcome: nonresolvers (died >72 hours or required ≥7 days of critical care), resolvers (survived to 30 days and required <7 days of critical care), and low Injury Severity Score (ISS) controls. Established tissue-specific biomarkers were identified through a literature review and cross-referenced with tissue specificity from the Human Protein Atlas. Untargeted plasma metabolomics (Metabolon Inc., Durham, NC), inflammatory mediators, and endothelial damage markers were correlated with injury biomarkers. Kruskal-Wallis/Mann-Whitney U tests with false discovery rate correction assessed differences in biomarker expression across outcome groups (significance; p < 0.1).

Results: Of 142 patients, 78 were nonresolvers (median ISS, 30), 34 were resolvers (median ISS, 22), and 30 were low ISS controls (median ISS, 1). A broad release of tissue-specific damage markers was observed at admission; this was greater in nonresolvers. By 72 hours, nine cardiac, three liver, eight neurologic, and three pulmonary proteins remained significantly elevated in nonresolvers compared with resolvers. Cardiac damage biomarkers showed the greatest elevations at 72 hours in nonresolvers and had significant positive correlations with proinflammatory mediators and endothelial damage markers. Nonresolvers had lower concentrations of fatty acid metabolites compared with resolvers, particularly acyl carnitines and cholines.

Conclusion: We identified an immediate release of tissue-specific biomarkers with sustained elevation in the liver, pulmonary, neurologic, and especially cardiac injury biomarkers in patients with complex clinical courses after severe injury. The persistent myocardial injury in nonresolvers may be due to a combination of factors including metabolic stress, inflammation, and endotheliopathy.

Figure 1.

Heatmap of Tissue-Specific Biomarkers Stratified by Timepoint and Outcome in PAMPer Cohort Number of subjects in each group: 30 Low injury severity score (ISS) controls, 34 (Resolving 0h), 78 (Non-resolving 0h), 32 (Resolving 24h), 72 (Non-resolving 24h), 32 (Resolving 72h), 71 (Non-resolving 72h). * Represents significant elevation with adjusted p-value <0.1 across outcome groups

Figure 2.

Time-dependent Relative Concentrations of Analyzed Cardiac Damage Biomarkers Stratified by Patient Outcome Dot and error bars represent mean and standard deviation of respective outcome groups. Black line and gray bars represent mean and standard deviation of relative protein concentration in low injury severity control group at timepoint 0-hours. * Signifies significant difference in relative concentration between resolving and non-resolving after false discovery rate correction. Number of subjects the same as Figure 1.

Figure 3.

Heatmap of Plasma Acyl Carnitine and Acyl Choline Fatty Acid Metabolites Stratified by Timepoint and Patient Outcome Number of subjects in each group: 17 Healthy Controls, 43 Resolving 0h, 102 Non-resolving 0h, 42 Resolving 24h, 100 Non-resolving 24h, 43 Resolving 72h, 99 Non-resolving 72h.

Figure 4.

Representative Time-dependent Trajectories of Acyl Carnitines, Acyl Cholines, Medium Chain Fatty Acids, and Lactate Across Outcome Groups. Depicted trajectories are representative of metabolites in acyl carnitine (Panel A), acyl choline (Panel B), medium chain fatty acids (Panel C), and pyruvate (Panel D). Number of subjects the same as Figure 3.

Figure 5.

Network of highly correlated (Spearman’s coefficient >0.5) cardiac metabolites (SomaLogic), fatty acid metabolites (Metabolon) and markers of endothelipathy (ELISA) in PAMPer patients at 0h