E-GEOD-9692
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: PRJNA103591PRJNA94397
DISEASE(S): Septic Shock,Normal
PROVIDER: E-GEOD-9692 | ExpressionAtlas | 2015-10-22
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-GEOD-9692-analysis-methods.tsv | Tabular | |||
| E-GEOD-9692-atlasExperimentSummary.Rdata | Rdata | |||
| E-GEOD-9692-configuration.xml | Xml | |||
| E-GEOD-9692-percentile-ranks.tsv | Tabular | |||
| E-GEOD-9692.condensed-sdrf.tsv | Tabular |
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Similar Datasets
Project description:In an ongoing translational research program involving microarray-based expression profiles in pediatric septic shock, we have now conducted longitudinal studies focused on the temporal expression profiles of canonical signaling pathways and gene networks. Genome-level expression profiles were generated from whole blood-derived RNA samples of children with septic shock (n = 30 individual patients) corresponding to days 1 and 3 of admission to the pediatric intensive care unit. Based on sequential statistical and expression filters, day 1 and day 3 of septic shock were characterized by differential regulation of 2,142 and 2,504 gene probes, respectively, relative to normal control patients. Venn analysis demonstrated 239 unique genes in the day 1 data set, 598 unique genes in the day 3 data set, and 1,906 genes common to both data sets. Analyses targeted toward derivation of biological function from these data sets demonstrated time-dependent, differential regulation of genes involved in multiple canonical signaling pathways and gene networks primarily related to immunity and inflammation. Notably, multiple and distinct gene networks involving T cell- and MHC antigen-related biological processes were persistently downregulated from day 1 to day 3. Further analyses demonstrated large scale and persistent downregulation of genes corresponding to functional annotations related to zinc homeostasis. These data represent the largest reported cohort of patients with septic shock, which has undergone longitudinal genome-level expression profiling. The data further advance our genome-level understanding of pediatric septic shock and support novel hypotheses that can be readily tested at both the experimental and translational levels. Experiment Overall Design: To define the longitudinal, genome-level expression profile of children with septic shock.
2008-06-16 | E-GEOD-8121 | biostudies-arrayexpress
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:Goal of the experiment: To identify correlated genes, pathways and groups of patients with systemic inflammatory response syndrome and septic shock that is indicative of biologically important processes active in these patients. Background: We measured gene expression levels and profiles of children with systemic inflammatory response syndrome (SIRS) and septic shock as a means for discovering patient sub-groups and gene signatures that are active in disease-affected individuals and potentially in patients with poor outcomes. Methods: Microarray and bioinformatics analyses of 123 microarray chips representing whole blood derived RNA from controls, children with SIRS, and children with septic shock. Results: A discovery-based filtering approach was undertaken to identify genes whose expression levels were altered in patients with SIRS or septic shock. Clustering of these genes identified 3 Major and several minor sub-groups of patients with SIRS or septic shock. The three groups differed with respect to incidence of septic shock and trended toward differences in mortality. Statistical analyses demonstrated that 6,435 gene probes were differentially regulated between the three patient sub-groups (false discovery rate < 0.001%). Of these gene probes, 623 gene probes within 7 major gene ontologies accounted for the majority of group differentiation. Network analyses of these 623 gene probes demonstrated 5 major gene networks that were differentially expressed between the 3 groups. Statistical comparison of septic shock survivors and non-survivors identified one major gene network that was under expressed in a high fraction of the non-survivors and identified potential biomarkers for poor outcome. Conclusions: This is the first genome-level demonstration of pediatric patient sub-groups with SIRS and septic shock. The sub-groups differ clinically and differentially express 5 major gene networks. We have identified gene signatures and potential biomarkers associated with poor outcome in children with septic shock. These data represent a major advancement in our genome-level understanding of pediatric SIRS and septic shock. Experiment Overall Design: Children < 10 years of age admitted to the pediatric intensive care unit and meeting the criteria for either SIRS or septic shock were eligible for the study. SIRS and septic shock were defined based on pediatric-specific criteria. We did not use separate categories of "sepsis" or "severe sepsis". Patients meeting criteria for "sepsis" or "severe sepsis" were placed in the categories of SIRS and septic shock, respectively, for study purposes. Control patients were recruited from the outpatient or inpatient departments of the participating institutions using the following exclusion criteria: a recent febrile illness (within 2 weeks), recent use of anti-inflammatory medications (within 2 weeks), or any history of chronic or acute disease associated with inflammation. Experiment Overall Design: After obtaining informed consent, blood samples were obtained on Day 1 of the study, and when possible on Day 3 of the study. Blood samples were divided for RNA extraction and isolation of serum. Severity of illness was calculated based on the PRISM III score. Organ failure was defined based on pediatric-specific criteria. Annotated clinical and laboratory data were collected daily while in the intensive care unit. Study patients were placed in the study categories of SIRS or Septic Shock on Day 1 of the study. On Day 3 of the study, patients were classified as SIRS, Septic Shock, or SIRS resolved (no longer meeting criteria for SIRS). All study patients were followed for 28 days to determine mortality or survival. Clinical, laboratory, and biological data were entered and stored using a web-based data base developed locally.
2008-06-13 | E-GEOD-4607 | biostudies-arrayexpress
Project description:Background: Septic shock is a heterogeneous syndrome within which probably exist several biological subclasses. Discovery and identification of septic shock subclasses could provide the foundation for the design of more specifically targeted therapies. Herein we tested the hypothesis that pediatric septic shock subclasses can be discovered through genome-wide expression profiling. Methods: Genome-wide expression profiling was conducted using whole blood-derived RNA from 98 children with septic shock, followed by a series of bioinformatic approaches targeted at subclass discovery and characterization. Results: Three putative subclasses (subclasses A, B, and C) were initially identified based on an empiric, discovery-oriented expression filter and unsupervised hierarchical clustering. Statistical comparison of the 3 putative subclasses (ANOVA, Bonferonni correction, p < 0.05) identified 6,934 differentially regulated genes. K means clustering of these 6,934 genes generated 10 coordinately regulated gene clusters corresponding to multiple signaling and metabolic pathways, all of which were differentially regulated across the 3 subclasses. Leave one out cross validation procedures indentified 100 genes having the strongest predictive values for subclass identification. Forty-four of these 100 genes corresponded to signaling pathways relevant to the adaptive immune system and glucocorticoid receptor signaling, the majority of which were repressed in subclass A patients. Subclass A patients were also characterized by repression of genes corresponding to zinc-related biology. Phenotypic analyses revealed that subclass A patients were younger, had a higher illness severity, and a higher mortality rate than patients in subclasses B and C. Conclusions: Genome-wide expression profiling can identify pediatric septic shock subclasses having clinically relevant phenotypes. Expression data from 98 children with septic shock and 32 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 to derive expression-based subclasses of patients using discovery oriented expression and statistical filters, followed by unsupervised hierarchical clustering.
2011-01-13 | E-GEOD-26440 | biostudies-arrayexpress
Project description:Rationale: We previously generated genome-wide expression data in children with septic shock, based on whole blood-derive RNA, having the potential to lead the field into novel areas of investigation. Objective: Herein we seek to validate our data through a bioinformatic approach centered on a validation patient cohort. Methods: Microarray- and bioinformatics-centered analyses involving our previous data as a training data set (n = 42) and a new, validation cohort (n = 30) as the test data set. Measurements and Main Results: Class prediction modeling using the training data set and the previously reported genome-wide expression signature of pediatric septic shock correctly identified 93 to 100% of septic shock patients in the test data set, depending on the class prediction algorithm and the gene selection method. Subjecting the test data set to an identical filtering strategy as that used for the training data set, demonstrated 72% concordance between the two gene lists. Subjecting the test data set to a purely statistical filtering strategy, with highly stringent correction for multiple comparisons, demonstrated less than 50% concordance with the previous gene filtering strategy. However, functional analysis of this statistics-based gene list demonstrated similar functional annotations and signaling pathways as that seen in the learning data set. In particular, we validated that pediatric septic shock is characterized by large scale repression of genes related to zinc homeostasis and lymphocyte function. Conclusions: These data demonstrate that the previously reported genome-wide expression signature of pediatric septic shock is applicable to a validation cohort of patients. Experiment Overall Design: Table 1: Clinical and demographic data for all subjects in test data set. Experiment Overall Design: Controls Septic Shock Experiment Overall Design: No. of individual subjects 15 30 Experiment Overall Design: Mean age (years) ± S.D. 3.1 ± 3.5 3.2 ± 2.9 Experiment Overall Design: Mean PRISM Score ± S.D. n/a 18.9 ± 12.3 Experiment Overall Design: Gender (Male/Female) 8/7 16/14 Experiment Overall Design: Race (no.) A.A./Black (6) A.A./Black (2) Experiment Overall Design: Asian (4) White (26) White (5) Unreported (2)
2008-06-20 | E-GEOD-9692 | biostudies-arrayexpress
Project description:In an ongoing translational research program involving microarray-based expression profiles in pediatric septic shock, we have now conducted longitudinal studies focused on the temporal expression profiles of canonical signaling pathways and gene networks. Genome-level expression profiles were generated from whole blood-derived RNA samples of children with septic shock (n = 30 individual patients) corresponding to days 1 and 3 of admission to the pediatric intensive care unit. Based on sequential statistical and expression filters, day 1 and day 3 of septic shock were characterized by differential regulation of 2,142 and 2,504 gene probes, respectively, relative to normal control patients. Venn analysis demonstrated 239 unique genes in the day 1 data set, 598 unique genes in the day 3 data set, and 1,906 genes common to both data sets. Analyses targeted toward derivation of biological function from these data sets demonstrated time-dependent, differential regulation of genes involved in multiple canonical signaling pathways and gene networks primarily related to immunity and inflammation. Notably, multiple and distinct gene networks involving T cell- and MHC antigen-related biological processes were persistently downregulated from day 1 to day 3. Further analyses demonstrated large scale and persistent downregulation of genes corresponding to functional annotations related to zinc homeostasis. These data represent the largest reported cohort of patients with septic shock, which has undergone longitudinal genome-level expression profiling. The data further advance our genome-level understanding of pediatric septic shock and support novel hypotheses that can be readily tested at both the experimental and translational levels. Keywords: Inflammation; sepsis; innate immunity; T cells; MHC antigen Keywords: to be updated
2007-06-14 | GSE8121 | GEO
Project description:Genome wide DNA methylation profiling of 26 pediatric KMT2Ar rearranged ALLs in comparison to 22 previously profiled samples of different non-neoplastic human B-cell precursor populations (GSE45459). The Illumina Infinium 450k Human DNA methylation Beadchip was used.
2016-11-04 | GSE76585 | GEO
Project description:The aim of the project was to quantify protein aggregation and disaggregation in human cells after transient non-lethal heat shock and during recovery. In addition, the non-aggregating proteins were analyzed by two-dimensional proteome profiling to detect changes in thermal stability upon heat shock. For aggregation/disaggregation study, K562 cells were grown in light SILAC medium which was changed to heavy medium 90 minutes before heat treatment (10 minutes at 44C). After heat shock, cells were let to recover at 37C. Samples were collected before and after the heat shock as well as on multiple time points during recovery (one, two, three and five hours). Protein intensities from soluble fraction (extracted with mild detergent - NP40) was compared to a control samples that on parallel were treated with mock shock (10 minutes at +37C). Samples were labelled with TMT labels and pooled. The medium switch prior to heat shock also allowed to monitor changes in protein synthesis caused by the heat shock. For control, an analysis of total protein amount (extracted with strong detergent - SDS) was conducted. For two-dimensional proteome profiling, aliquots of heat shocked and mock shocked samples were exposed to a temperature gradient (from 37.0C to 66.3C). Samples from two adjacent temperatures were labelled with TMT and pooled. Proteins from soluble fractions were quantified and heat shock-induced changes in thermal stability were analyzed.
2020-09-22 | PXD017291 | Pride