Host Immune Biosignatures Predict Septic Shock and Mortality in Solid Organ Transplant Recipients With Gram-Negative Bacteremia.

Authors

Emily M Eichenberger, Felicia Ruffin, Geeta M Karadkhele, Christian P Larsen, Vance G Fowler

Published in

The Journal of infectious diseases. Oct 05, 2026. Epub Oct 05, 2026.

Abstract

The aim of this study was to determine whether the addition of immunologic biosignatures to a predictive model based solely on clinical data could improve the model's ability to predict patient outcome among solid organ transplant (SOT) recipients with gram-negative bacteremia (GNB).
Plasma was prospectively collected from SOT recipients with GNB. Twenty-seven cytokines, chemokines, and immunoglobulin levels were quantified. Two logistic regression models were specified: a clinical model including age, transplanted organ, and time since transplant and a clinical-immunologic model that additionally incorporated the first two principal components. Model performance was evaluated using area under the curve (AUC). Internal validation was performed by repeated 10-fold cross-validation. AUCs were compared with a paired t test.
Of 169 SOT recipients with GNB, 45 (26.6%) experienced an adverse outcome (septic shock or death). When compared with the clinical model alone, the clinical-immunologic model demonstrated superior discrimination (AUC, 0.70 vs 0.84; P < .001). Principal component 1, characterized by broad immune dysregulation, was associated with increased risk for adverse outcome (odds ratio, 1.43; 95% CI, 1.24-1.69) and was characterized by strong contributions from innate proinflammatory mediators (TNF-α, IL-1β, IL-6, IL-8, MCP-1, MIP-1β, IL12p70, MIP-1α, and GMCSF), anti-inflammatory mediators (IL-10, IL-4, and IL-13), and IL-2. In contrast, principal component 2 was associated with a favorable outcome (odds ratio, 0.61; 95% CI, .43-.84) and reflected coordinated adaptive immunity, with dominant contributions from Th1, Th17, and humoral pathways (TNFβ, IFNg, IP-10, IL-17A, IgG, IgM).
Immune biosignatures significantly improved prediction of adverse outcomes beyond clinical factors in SOT recipients with GNB.

PMID:
42831489
Bibliographic data and abstract were imported from PubMed on 05 Oct 2026.

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