Sepsis triggers a complex and heterogeneous host response, yet decades of biomarker studies have yielded few targeted therapeutics that improve patient outcomes. Single analyte approaches fail to capture the coordinated biological programs that drive organ dysfunction. Focusing on single or limited panels of biomarkers to endotype disease fundamentally misrepresents sepsis biology, which reflects simultaneous disruption of multiple cellular networks. However, pathway-level bioinformatic analyses interpret proteins as components of larger biological systems, enabling detection of coordinated molecular disturbances that individual biomarkers cannot capture. We conducted an exploratory cohort study profiling 1,196 plasma proteins in 15 critically-ill adults with sepsis on ICU Day 1 and Day 3 using proximity extension assays. Differential expression, Reactome and Gene Ontology (GO) enrichment analyses, protein-protein interaction networks, and immune cell deconvolution were combined to assess pathway-level perturbations and their clinical correlates. Early sepsis was defined by widespread inflammatory pathway dysregulation, with marked enrichment of immune system activation, neutrophil degranulation, cytokine signaling, and defense-response pathways. Despite significant clinical improvement of patients between ICU Day 1 and Day 3, only five proteins (ALDH3A1, CR2, CD200R1, IL1RL2, SAA4) demonstrated temporal change. Moreover, transcriptional pathways demonstrated negative enrichment by Day 3. Network analyses revealed highly interconnected inflammatory hubs centered on IL-6, IL-10, and CXCL8. In this exploratory cohort, early sepsis was characterized by enrichment of immune and transcriptional pathways. These pathway signals were consistently detected across multiple analytic approaches, including differential expression analysis, pathway enrichment, and protein-protein interaction network analyses. These findings highlight the value of high-dimensional, pathway-focused proteomic analyses for uncovering the biological programs underlying critical illness beyond what can be captured by individual biomarkers.
Nynatten et al. (Thu,) studied this question.