Gene Expression Profiles in Children with Suspected Sepsis in the Emergency Department
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ABSTRACT:
PROVIDER: PRJNA488482 | ENA |
REPOSITORIES: ENA
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Project description:Around 42,000 children suffer from severe sepsis each year in the US alone, resulting in significant morbidity, mortality and billion dollar expenditures in the US healthcare system. Sepsis recognition is a clinical challenge in children. Biomarkers are needed to tailor appropriate antimicrobial therapies and improve risk stratification. The goal of this study was to determine if gene expression profiles from peripheral blood were associated with pathogen type and sepsis severity in children treated for suspected sepsis.
2020-01-01 | GSE119217 | GEO
Project description:1364 plasma proteome samples taken at time-of-admission to the emergency department from patients suspected of sepsis.
Used initially with the following abstract:
Sepsis is one of the leading causes of mortality in the world. Currently, the heterogeneity of sepsis makes it challenging to determine the molecular mechanisms that define the syndrome. Here, we leverage population scale proteomics to analyze a well-defined cohort of 1364 blood samples taken at time-of-admission to the emergency department from patients suspected of sepsis. We identified panels of proteins using explainable artificial intelligence that predict clinical outcomes and applied these panels to reduce high-dimensional proteomics data to a low-dimensional interpretable latent space (ILS). Using the ILS, we constructed an adaptive digital twin model that accurately predicted organ dysfunction, mortality, and early-mortality-risk patients using only data available at time-of-admission. In addition to being highly effective for investigating sepsis, this approach supports the flexible incorporation of new data and can generalize to other diseases to aid in translational research and the development of precision medicine.
2024-04-08 | MSV000094486 | MassIVE
Project description:Sepsis is a syndromic response to infection and is frequently a final common pathway to death from many infectious diseases worldwide. The global burden of sepsis is difficult to ascertain, although a recent scientific publication estimated that there were 48.9 million cases and 11 million sepsis-related deaths worldwide, which accounted for almost 20% of all global deaths. Here we analyzed the whole blood transcriptome of 5 healthy controls and 5 patients with confirmed sepsis from the Department of Emergency, Division of Surgical critical care, Tongji Trauma Center, Tongji Hospital, Tongji Medical College. This research aims to understand the expression of immune cells in sepsis patients and to construct an immune cell landscape of sepsis.
2023-02-05 | GSE224095 | GEO
Project description:Nasal swab specimens were collected from children who presented to the emergency department with an acute exacerbation of asthma or wheeze. Samples were also collected from control subjects. Convalescent/quiescent samples were collected from children who were followed-up at least 6 weeks after an acute exacerbation of asthma or wheeze. Gene expression was profiled on microarrays.
2019-02-17 | GSE103166 | GEO
Project description:Both sepsis and acute respiratory distress syndrome (ARDS) rely on imprecise clinical definitions leading to heterogeneity, which has contributed to negative trials. Because circulating protein/DNA complexes have been implicated in sepsis and ARDS, we aimed to develop a proteomic signature of DNA-bound proteins to discriminate between children with sepsis with and without ARDS. We performed a prospective case-control study in 12 children with sepsis with ARDS matched to 12 children with sepsis without ARDS on age, severity of illness score, and source of infection. We performed co-immunoprecipitation and downstream proteomics in plasma collected ≤ 24 h of intensive care unit admission. Expression profiles were generated, and a random forest classifier was used on differentially expressed proteins to develop a signature which discriminated ARDS. The classifier was tested in six independent blinded samples. Neutrophil and nucleosome proteins were over-represented in ARDS, including two S100A proteins, superoxide dismutase (SOD), and three histones. Random forest produced a 10-protein signature that accurately discriminated between children with sepsis with and without ARDS. This classifier perfectly assigned six independent blinded samples as having ARDS or not. We validated higher expression of the most informative discriminating protein, galectin-3-binding protein, in children with ARDS. Our methodology has applicability to isolation of DNA-bound proteins from plasma. Our results support the premise of a molecular definition of ARDS, and give preliminary insight into why some children with sepsis, but not others, develop ARDS.
2024-02-14 | PXD049377 | Pride
Project description:Background: Sepsis involves aberrant immune responses to infection, but the exact nature of this immune dysfunction remains poorly defined. Bacterial endotoxins like lipopolysaccharide (LPS) are potent inducers of inflammation, which has been associated with the pathophysiology of sepsis, but repeated exposure can also induce a suppressive effect known as endotoxin tolerance or cellular reprogramming. It has been proposed that endotoxin tolerance might be associated with the immunosuppressive state that was primarily observed during late-stage sepsis. However, this relationship remains poorly characterised. Here we clarify the underlying mechanisms and timing of immune dysfunction in sepsis. Methods: We defined a gene expression signature characteristic of endotoxin tolerance. Gene-set test approaches were used to correlate this signature with early sepsis, both newly and retrospectively analysing microarrays from 593 patients in 11 cohorts. Then we recruited a unique cohort of possible sepsis patients at first clinical presentation in an independent blinded controlled observational study to determine whether this signature was associated with the development of confirmed sepsis and organ dysfunction. Findings: All sepsis patients presented an expression profile strongly associated with the endotoxin tolerance signature (p < 0.01; AUC 96.1%). Importantly, this signature further differentiated between suspected sepsis patients who did, or did not, go on to develop confirmed sepsis, and predicted the development of organ dysfunction. Interpretation: Our data support an updated model of sepsis pathogenesis in which endotoxin tolerance-mediated immune dysfunction (cellular reprogramming) is present throughout the clinical course of disease and related to disease severity. Thus endotoxin tolerance might offer new insights guiding the development of new therapies and diagnostics for early sepsis. For the RNA-Seq study reported here, 73 patients were recruited with deferred consent at the time of first examination in an emergency ward based on the opinion of physicians that there was a potential for the patient's condition to develop into sepsis. These were retrospectively divided into groups based on clinical features and compared to 11 non-urgent surgical controls.
2014-11-14 | E-GEOD-63311 | biostudies-arrayexpress
Project description:The temporal evolution of sepsis was monitored by transcriptional profiling of five critically ill children with meningococcal sepsis and sepsis-induced multiple organ failure. Blood was sampled at 6 time points during the first 48 hours of their admission to pediatric intensive care, where the children received standard clinical treatment including organ support and antimicrobial therapy. Striking transcript instability was observed over the 48 hours, with increasing numbers of regulated genes over time. Most notably, proposed biomarkers for sepsis risk stratification also showed expression instability, with varied expression levels over 48 hours. This study demonstrates the extent of the complexity of temporal changes in gene expression that occur during the evolution of sepsis-induced multiple organ failure. Importantly, stratification tools that propose expression of biomarkers must take into account the temporal changes, over the use of single snapshots that may be less informative.
2013-04-03 | E-MEXP-3850 | biostudies-arrayexpress
Project description:Blood RNA sequencing was performed on a cohort of adults attending the Emergency Department with suspected infection who had subsequently-confirmed viral, bacterial, or no infection diagnoses
| PRJEB45290 | ENA
Project description:Normal children, children with SIRS, children with sepsis, and children with septic shock. Objectives: To advance our biological understanding of pediatric septic shock, we measured the genome-level expression profiles of critically ill children representing the systemic inflammatory response syndrome (SIRS), sepsis, and septic shock spectrum. Experiment Overall Design: Prospective observational study involving microarray-based bioinformatics.
2009-01-05 | E-GEOD-13904 | biostudies-arrayexpress
Project description:<p>Sepsis, defined as life-threatening organ dysfunction caused by infection is difficult to distinguish clinically from infection or post-operative inflammation. We hypothesized that in a heterogeneous group of critically ill children, there would be different metabolic profiles between post-operative inflammation, bacterial and viral infection and infection with or without organ dysfunction. 1D 1H nuclear magnetic resonance spectra were acquired in plasma samples from critically ill children. We included children with bacterial (n = 25) and viral infection (n = 30) and controls (n = 58) (elective cardiac surgery without infection). Principal component analysis was used for data exploration and partial least squares discriminant analysis models for the differences between groups. Area under receiver operating characteristic curve (AUC) values were used to evaluate the models. Univariate analysis demonstrated differences between controls and bacterial and viral infection. There was excellent discrimination between bacterial and control (AUC = 0.94), and viral and control (AUC = 0.83), with slightly more modest discrimination between bacterial and viral (AUC = 0.78). There was modest discrimination (AUC = 0.73) between sepsis with organ dysfunction and infection with no organ dysfunction. In critically ill children, NMR metabolomics differentiates well between those with a post-operative inflammation but no infection, and those with infection (bacterial and viral), and between sepsis and infection.</p>
2020-11-19 | MTBLS563 | MetaboLights