Understanding the complexity of trauma-induced thromboinflammation necessitates data-driven approaches. We hypothesized that longitudinal plasma profiling could reveal underlying differences in patients with injury who present with similar clinical characteristics but ultimately have different outcomes. Here, we performed multiomic analyses of longitudinal plasma samples from a clinical trial of patients with traumatic injury to identify molecular endotypes and trajectories that were associated with patient outcomes. The pathophysiologic states of patients with trauma were defined by the longitudinal proteomic and metabolomic plasma profiles from a diverse cohort. Then, patients were endotyped according to their longitudinal trajectories through trauma omic states, and injury patterns and outcomes were compared. We identified endotypes associated with divergent clinical outcomes despite similar injury patterns at presentation. Organ failure and time spent in the intensive care unit (ICU) were predicted with high accuracy using omic markers. Patients who presented with evidence of elevated proteasome activation, catabolism, and superoxide formation were vulnerable to heart failure, lung failure, and acute lung injury, respectively. In addition, omic markers of increased hypoxia, RBC lysis, and hydrolase activity better fit mortality and ICU time compared with injury covariates, while providing biological insight. Injury and outcome patterns persisted in a validation trauma cohort after endotype assignment at a single, early time point. These data align with the understanding that patients with trauma may experience markedly different biological responses and outcomes despite similar clinical presentations. We suggest that mapping patient trajectories through biological injury states could provide a framework for personalized patient treatment after trauma.
Cohen et al. (2026) studied this question.