Genomic landscape of the individual host response and outcomes in severe sepsis revealed by transcriptomic profiling and quantitative trait mapping (validation cohort)
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Emma Davenport
PROVIDER: E-MTAB-4451 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:We assayed leukocyte global gene expression for a prospective discovery cohort of 106 adult patients admitted to UK intensive care units with sepsis due to community acquired pneumonia or faecal peritonitis. We assigned all samples to sepsis response signature groups after performing unsupervised analysis of the transcriptomic data.
2017-05-01 | E-MTAB-5274 | biostudies-arrayexpress
Project description:We assayed leukocyte global gene expression for a prospective validation cohort of 221 adult patients admitted to UK intensive care units with sepsis due to community acquired pneumonia or faecal peritonitis. 10 samples from patients scheduled for elective cardiac surgery were also assayed as non-septic controls. We assigned all samples to sepsis response signature groups after performing unsupervised analysis of the transcriptomic data.
2017-05-01 | E-MTAB-5273 | biostudies-arrayexpress
Project description:We assayed leukocyte global gene expression for a prospective discovery cohort of 265 adult patients admitted to UK intensive care units with severe sepsis due to community acquired pneumonia.
2016-02-25 | E-MTAB-4421 | biostudies-arrayexpress
Project description:To investigate immunologic alterations taking place in patients with nosocomial sepsis, we undertook genomic expression analysis of white blood cells (WBC) using DNA microarrays in a small sample of trauma patients who developed severe sepsis/septic shock during their ICU stay and compared with trauma patients with uncomplicated sepsis. RNA was extracted from blood obtained upon admission (a) and at the onset of the disease (b).
2012-08-01 | E-MEXP-3621 | biostudies-arrayexpress
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:The study was aimed to identify mechanisms linked to complicated courses after severe trauma by a systems biology approach. In severe trauma, overwhelming systemic inflammation can result in adverse events and the development of complications, including sepsis. In a prospective study, RNA samples from circulating leukocytes from patients with multiple injury (injury severity score ⥠17) were analyzed for dynamic changes in gene expression over a period of 21 days by whole genome screening. Based on their clinical presentation, patients were divided into two subgroups: patients with secondary sepsis after trauma (n=5) and patients with systemic inflammation without infection (n=5). Expression cluster were defined by correlating gene expression data with clinical outcome parameters. Using unsupervised clustering, patients with systemic inflammation only and patients with sepsis showed a distinct expression pattern and the discrimination of clinical presentation was reflected by clustering of the samples. Explorative gene set analysis revealed robust upregulation of genes related to âhemoglobin metabolism/oxygen transportâ and âpathogenic E.coli infectionâ. 10 patients with multi-system trauma (ISS ⥠17 points) admitted to the Division of Trauma Surgery at the University Hospital Zurich were included. Whole blood from trauma patients was collected within the first 6 h after trauma (day 0) and on days 1, 2, 3, 5, 7, 10, 14, and 21. Total cellular RNA from circulating leukocytes was isolated using PaxGene Blood RNA Kit (PreAnalytix) for transcriptome profiling. RNA from blood of trauma patients was extracted and subjected to microarray analysis for comparison of longitudinal transcriptomic responses of patients. RNA samples of circulating leukocytes covering time points directly after admission (D0) and on the consecutive days (D1-D21) were subject to multifactorial microarray data analysis: Differences in dynamics of transcripts were assessed by contrasting time- and individual-resolved changes for sepsis and systemic inflammation without infection.
2015-11-01 | E-GEOD-70311 | 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:Melioidosis is a neglected tropical disease caused by the Gram-negative bacterium Burkholderia pseudomallei. It is widespread in Southeast Asia and under-reported across tropical regions worldwide. Patients present with a range of clinical syndromes including sepsis, pneumonia and focal abscesses, with a mortality rate of 40% in hospitalized patients in Thailand. Up to two-thirds of patients with melioidosis have diabetes mellitus. In this experiment we sought to characterize pathways activated by whole killed B. pseudomallei bacteria and by three vaccine candidate proteins from B. pseudomallei, BPSL2520 (uncharacterized protein), BPSS1525 (BopE) and BPSL2096 (AhpC) in patients with diabetes and acute melioidosis.
2017-09-22 | E-MTAB-6093 | biostudies-arrayexpress
Project description:Abstract<br>BACKGROUND: Gene expression profiling (GEP) in cells obtained from peripheral blood has demonstrated to be a very useful approach for biomarker discovery and for studying molecular pathogenesis of prevalent diseases. While there is limited literature availble on gene expression markers associated to Chronic Obstructive Pulmonary Disease (COPD), the transcriptomic picture associated to critical respiratory illness in this disease is not known to the present moment. <br>RESULTS: By using Agilent microarray chips, we have profiled gene expression signatures in whole blood of 28 COPD patients hospitalized with distinct degree of respiratory compromise.12 of them needed of admission to the ICU, while 16 were admitted to the Respiratory Medicine Service. GeneSpring GX 11.0 software was used for performing statistical comparison of transcript levels between ICU and non ICU patients. Ingenuity pathway analysis 8.5 (IPA) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were employed to select, annotate and visualize genes by function and pathway (gene ontology). T-test evidenced 1501 genes differentially expressed between ICU and non ICU patients. IPA and KEGG analysis of the most representative biological functions revealed that ICU patients showed increased levels of neutrohil gene transcripts, being [cathepsin G (CTSG)], [elastase, neutrophil expressed (ELANE)], [proteinase 3 (PRTN3)], [myeloperoxidase (MPO)], [cathepsin D (CTSD)], [defensin, alpha 3, neutrophil-specific (DEFA3)], azurocidin 1 (AZU1)], [bactericidal/permeability-increasing protein (BPI)] the most representative ones. Proteins codified by these genes form part of the azurophilic granules of neutrophils and are involved in both antimicrobial defence and tissue damage. This ?neutrophil signature? was paralleled by necessity of advanced respiratory and vital support, and presence of bacterial infection.<br>CONCLUSION: study of transcriptomic signatures in blood suggests a central role of neutrophil proteases in COPD patients with critical respiratory illness. Measurement / modulation of the expression of these genes could represent an option for clinical monitoring and treatment of severe COPD exacerbations. <br><br>Keywords: COPD, critical, expression, gene, microarray, neutrophil, proteases.<br><br>
2013-03-12 | E-MEXP-3589 | biostudies-arrayexpress
Project description:Background: Septic shock heterogeneity has important implications for the conduct of clinical trials and individual patient management. We previously addressed this heterogeneity by indentifying 3 putative subclasses of children with septic shock based on a 100-gene expression signature corresponding to adaptive immunity and glucocorticoid receptor signaling. Herein we attempted to prospectively validate the existence of these gene expression-based subclasses in a validation cohort. Methods: Gene expression mosaics were generated from the 100 class-defining genes for 82 individual patients in the validation cohort. Patients were classified into 1 of 3 subclasses (“A”, “B”, or “C”) based on color and pattern similarity relative to reference mosaics generated from the original derivation cohort. Separate classifications were conducted by 21 individual clinicians and a computer-based algorithm. After subclassification the clinical database was mined for clinical phenotyping. Results: In the final consensus subclassification generated by clinicians, subclass A patients had a higher illness severity, as measured by illness severity scores and maximal organ failure, relative to subclasses B and C. The k coefficient across all possible inter-evaluator comparisons was 0.633. Similar observations were made based on the computer-generated subclassification. Patients in subclass A were also characterized by repression of a large number of genes having functional annotations related to zinc biology. Conclusions: We have validated the existence of subclasses of children with septic shock based on a biologically relevant, 100-gene expression signature. The subclasses can be indentified by clinicians without formal bioinformatics training, at a clinically relevant time point, and have clinically relevant phenotypic differences. Expression data from 82 children with septic shock and 21 normal controls were generated using whole blood-derived RNA samples representing the first 24 hours of admission to the pediatric intensive care unit. The controls were used for normalization. Subsequently, we used the expression data from 100 class defining genes to validate the existence of pediatric septic shock subclasses having phenotypic differences.
2011-01-13 | E-GEOD-26378 | biostudies-arrayexpress