Project description:This dataset is composed of the unique patients (276; at the Day 1 timepoint) that are present in the six other GEO datasets published by Hector Wong and the Genomics of Pediatric SIRS and Septic Shock Investigators. This dataset thus includes all unique patients from GSE4607, GSE8121, GSE9692, GSE13904, GSE26378, and GSE26440. These are only from the Day 1 timepoint. The original studies examined pediatric patients admitted to the ICU, who were later classified as either SIRS (non-infectious) or Sepsis or Septic Shock (infectious). There is also a group of healthy controls. Although the original studies examine patients at both ICU day 1 and ICU day 3, here we have only aggregated ICU day 1 patients. All samples here were downloaded as .CEL files and re-normalized together using gcRMA using R package 'affy'. The normalized data can be found on the series record and contains the gcRMA normalized expression values.
Project description:This dataset is composed of the unique patients (276; at the Day 1 timepoint) that are present in the six other GEO datasets published by Hector Wong and the Genomics of Pediatric SIRS and Septic Shock Investigators. This dataset thus includes all unique patients from GSE4607, GSE8121, GSE9692, GSE13904, GSE26378, and GSE26440. These are only from the Day 1 timepoint.
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.
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. Keywords: Septic shock, SIRS, pediatrics, outcome, infection, inflammation
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. Keywords: Normal vs diseased
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.
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.
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
Project description:Genome wide DNA methylation profiling of monocytes from healthy donors, systemic inflammatory response syndrome (SIRS) and septic patients. The Illumina Infinium MethylationEPIC Beadchip was used to obtain DNA methylation profiles across approximately 850,000 CpGs in CD14+CD66bneg monocytes isolated from PBMCs of 11 healthy donors, 4 SIRS and 14 septic patients.