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E-GEOD-59075 - Integrative ‘omic analysis of experimental bacteremia identifies a metabolic signature that distinguishes human sepsis from SIRS

Status
Released on 3 July 2015, last updated on 19 August 2015
Organism
Macaca fascicularis
Samples (18)
Protocols (2)
Description
Rationale: Sepsis is a leading cause of morbidity and mortality; early diagnosis and prediction of progression is difficult to determine. The integration of metabolomic and transcriptomic data in an experimental model of sepsis may be a novel method to identify molecular signatures of clinical sepsis. Objectives: Develop a biomarker panel for earlier diagnosis and prognostic characterization of sepsis patients to inform personalized clinical management and improve understanding of the pathophysiology of sepsis progression. Methods: Mild to severe sepsis, lung injury and death was recapitulated in Macaca fascicularis by intravenous inoculation of Escherichia coli. Plasma samples were obtained at time of challenge and at one, three, and five days later or time of euthanasia. Necropsy was performed and blood, lung, kidney and spleen samples were obtained. An integrative analysis of comprehensive metabolomic and transcriptomic datasets was performed to identify and parameterize a biomarker panel. Measurements and Main Results: Pathogen invasion, respiratory distress, lethargy and mortality was dose dependent. Severe infection and death were associated with metabolomic and transcriptomic changes indicative of mitochondrial, peroxisomal and liver dysfunction. Analysis of reciprocal pulmonary transcriptome and plasma metabolome data revealed an integrated host response that suggested dysregulated fatty acid catabolism resulting from peroxisome-proliferator activated receptor signaling. A representative 4-metabolite model effectively diagnosed sepsis in primates (AUC 0.966) and in two human sepsis cohorts (AUC=0.78 and 0.82). Conclusion: A model to guide early management of patients with sepsis was developed by analysis of reciprocal metabolomic and transcriptomic data in primates that diagnosed sepsis in humans. Transcriptomic analysis of lungs from Cynomolgus macaques challenged with E. coli
Experiment type
RNA-seq of coding RNA 
Contacts
MINSEQE
Exp. designProtocolsVariablesProcessedSeq. reads
Files
Investigation descriptionE-GEOD-59075.idf.txt
Sample and data relationshipE-GEOD-59075.sdrf.txt
Additional data (1)E-GEOD-59075.additional.1.zip
Links