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A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set.

ABSTRACT: Although several dozen studies of gene expression in sepsis have been published, distinguishing sepsis from a sterile systemic inflammatory response syndrome (SIRS) is still largely up to clinical suspicion. We hypothesized that a multicohort analysis of the publicly available sepsis gene expression data sets would yield a robust set of genes for distinguishing patients with sepsis from patients with sterile inflammation. A comprehensive search for gene expression data sets in sepsis identified 27 data sets matching our inclusion criteria. Five data sets (n = 663 samples) compared patients with sterile inflammation (SIRS/trauma) to time-matched patients with infections. We applied our multicohort analysis framework that uses both effect sizes and P values in a leave-one-data set-out fashion to these data sets. We identified 11 genes that were differentially expressed (false discovery rate ?1%, inter-data set heterogeneity P > 0.01, summary effect size >1.5-fold) across all discovery cohorts with excellent diagnostic power [mean area under the receiver operating characteristic curve (AUC), 0.87; range, 0.7 to 0.98]. We then validated these 11 genes in 15 independent cohorts comparing (i) time-matched infected versus noninfected trauma patients (4 cohorts), (ii) ICU/trauma patients with infections over the clinical time course (3 cohorts), and (iii) healthy subjects versus sepsis patients (8 cohorts). In the discovery Glue Grant cohort, SIRS plus the 11-gene set improved prediction of infection (compared to SIRS alone) with a continuous net reclassification index of 0.90. Overall, multicohort analysis of time-matched cohorts yielded 11 genes that robustly distinguish sterile inflammation from infectious inflammation.

SUBMITTER: Sweeney TE

PROVIDER: S-EPMC4734362 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set.

Sweeney Timothy E TE Shidham Aaditya A Wong Hector R HR Khatri Purvesh P

Science translational medicine 20150501 287

Although several dozen studies of gene expression in sepsis have been published, distinguishing sepsis from a sterile systemic inflammatory response syndrome (SIRS) is still largely up to clinical suspicion. We hypothesized that a multicohort analysis of the publicly available sepsis gene expression data sets would yield a robust set of genes for distinguishing patients with sepsis from patients with sterile inflammation. A comprehensive search for gene expression data sets in sepsis identified ...[more]

PMID: 25972003

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Project description:BackgroundThe adipokine leptin regulates energy expenditure, vascular function, bone and cartilage growth as well as the immune system and systemic inflammatory response. Several activating effects towards T cells, monocytes, endothelium cells and cytokine production have been reported suggesting a protective role of leptin in the setting of an acute systemic inflammation. However, the pathophysiological role of leptin during severe sepsis is currently not elucidated in detail. This study aims to investigate leptin expression in cultured human adipocytes within an inflammatory model and in patients suffering from severe sepsis and evaluates treatment effects of drotrecogin alpha (activated) (DAA), the recombinant form of human activated protein C.MethodsIn an in-vitro inflammatory model of adipocyte cell-culture the effect of DAA on leptin mRNA expression was evaluated. Synthesis of mRNA was measured by quantitative polymerase chain reaction (qPCR). Additionally, supernatants of these adipocytes as well as serum levels of adiponectin were measured in blood of 104 severe septic patients by ELISA-method. 26 patients were treated with DAA (DAA+), 78 patients were not treated with DAA (DAA-).ResultsStimulation of human adipocytes with TNF alpha over 6 and 24 hours resulted in a significant decrease by 46% and 59% of leptin mRNA transcripts compared to un-stimulated controls (p < 0.05). Leptin levels of supernatants of adipocyte culture decreased by 25% and 23% (p < 0.05) after incubation with TNF alpha after 6 and 24 hours. Incubation with DAA at 50 ng/ml DAA and 5 μg/ml doubled mRNA expression significantly at 24 hours (p < 0.05) but not at 6 hours. From day 1 to day 3 of sepsis, leptin levels increased in DAA+ compared to DAA- patients (p<0.10).ConclusionsLeptin appears to be involved in the pathogenesis of a systemic inflammatory response during sepsis. Administration of DAA significantly increased leptin expression. The specific mechanism or even benefit of DAA towards leptin needs further ongoing research.

Project description:Diagnosis of sepsis in burn patients remains difficult for various reasons. One major problem is the definition of sepsis itself. Therefore, previous and current sepsis definitions are a matter of ongoing validation, but a well-defined consensus on which clinical and laboratory parameters to incorporate in such a definition is lacking. The aim of the present study was to compare the incidence and time-related occurrence of septic events according to different definitions as well as their accompanying time course of pro-inflammatory biomarkers. Across the first 14 days after admission, the incidence and time point of sepsis according to three different definitions (Sepsis-3, Sepsis American Burns Association [ABA] 2007, Sepsis Zurich Burn Center) were assessed on a daily basis in adult burn patients with total body surface area (TBSA) ≥15% admitted to the Zurich Burn Center between May 2015 and October 2018. In order to investigate how well daily drawn proinflammatory biomarkers (white blood cells (WBCs), C-reactive protein (CRP), procalcitonin (PCT), and novel pancreatic stone protein (PSP)) reflect the progression of sepsis depending on its type of definition, a longitudinal mixed model analysis was performed across the first 14 days for septic and non-septic patients. Additionally, the relative increase of biomarker levels 24, 48, and 72 h prior to a septic event was analyzed for each definition used. In our cohort of 90 severely burned patients, Sepsis-3 identified 46 patients (51.1%) as septic, while ABA 2007 and the Zurich Burn Center definition counted 33 patients (36.7%) and 24 patients (26.6%), respectively. Sepsis-3 detected sepsis about 1 day earlier than Sepsis ABA 2007 (p < 0.001) and about 0.5 days earlier than Sepsis Zurich Burn Center (p = 0.04). The course of pro-inflammatory biomarkers was largely unaffected by the type of sepsis definition. Irrespective of the sepsis definition, PSP was the only marker to demonstrate a highly significant interaction between time and group (sepsis versus no sepsis) (p < 0.001) with a 3.3-5.5-fold increase within 72 h before the event of sepsis, whereas CRP, PCT, and WBC showed only mild undulations. Despite the ongoing dilemma of how to define sepsis in burn patients, a continually calculated SOFA score as used in Sepsis-3 is advantageous to early identify a patient's detrimental progression to sepsis. Inclusion of biomarkers, such as PSP, may help support the burn specialist's diagnosis of sepsis and could improve the diagnostic performance of current and future definitions in burn patients.

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A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set.

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A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set.

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