Data Driven Analysis Reveals Shared Transcriptome Response, Immune Cell Composition, and Distinct Mortality Rates...

Sepsis and trauma are common health problems and provide great challenges in critical care. Diverse patient responses to these conditions further complicate patient management and outcome prediction. Whole blood transcriptomics provides a unique opportunity to follow the molecular response in the critically ill. Prior results show robust and diverse genomic signal in the acute phase and others have found shared biological mechanisms across divergent disease etiologies. We hypothesize that selected transcriptomics responses, particularly immune mechanisms are shared across disease etiologies. We further hypothesize that these processes may identify homogenous patient subgroups with shared clinical course in critical illness deciphering disease heterogeneity. These processes may serve as universal markers for predicting a complicated clinical course and/or risk of a poor outcome.

We present a system level, data driven, genome-wide analysis of whole blood gene expression for a total of 382 patients suffering from either abdominal sepsis (49), pulmonary sepsis (107) or trauma (158) and compare these to gene expression in healthy controls (68).

We relied on available open genetic data from gene expression omnibus for patients diagnosed with abdominal sepsis, community-acquired pneumonia, or trauma which also included healthy control patients.

Our results confirm that immune processes are shared across disease etiologies in critical illnesses. We identify two consistent and distinct patient subgroups through deconvolution of serum transcriptomics: 1) increased neutrophils and naïve CD4 cell fractions and 2) suppressed neutrophil fraction. Furthermore, we found immune and inflammatory processes were downregulated in subgroup 2, a configuration previously shown to be more susceptible to multiple organ failure. Correspondingly, this subgroup had significantly higher mortality rates in all three etiologies of illness (0% vs 6.1%, p = 3.1 × 10 for trauma; 15.0% vs 25.4%, p = 4.4 × 10 for community-acquired pneumonia, and 7.1% vs 20.0%, p = 3.4 × 10 for abdominal sepsis).

We identify two consistent subgroups of critical illness based on serum transcriptomics and derived immune cell fractions, with significantly different survival rates. This may serve as a universal predictor of complicated clinical course or treatment response and, importantly, may identify opportunities for subgroup-specific immunomodulatory intervention.