AKIRIN1 is a suitable reference gene in natural killer cells and granulocytes from patients with SIRS and septic shock
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PROVIDER: PRJNA509655 | ENA |
REPOSITORIES: ENA
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Project description:Timely and reliable distinction of non-infectious systemic inflammatory response syndrome (SIRS), common in critically ill patients, from sepsis to support adequate antimicrobial therapy safes lives but is clinically challenging. Expeditious sepsis biomarkers are thus urgently sought. Blood transcriptional profiling provides insights into sepsis pathophysiology, but variability in leukocyte subtype composition complicates profile interpretation, and reliable reference genes to normalize gene expression in sepsis are lacking. Here, we identified AKIRIN1 as a reference gene, specifically, in peripheral NK cells and granulocytes for differential gene expression analysis between patients with SIRS and septic shock on intensive care unit admission. Discovery by a two-step probabilistic selection from microarray data followed by validation through branched DNA assays in independent patients revealed several candidate reference genes in NK cells, namely, AKIRIN1, PPP6R3, TAX1BP1, and ADRBK1. For in vitro priming of NK cells, GUSB however was confirmed as reference gene of choice. Initially, no candidate genes could be validated in granulocytes, an additional rescreen of known reference genes by RT-PCR included. By serendipity, we could determine equal AKIRIN1 expression levels also in SIRS and septic shock granulocytes and no change by in vitro challenge of granulocytes with LPS. Inspection of four external neutrophil transcriptome datasets further support unchanged AKIRIN1 expression in human systemic inflammation. Invariable AKIRIN1 expression in peripheral NK cells and granulocytes needs further validation in sepsis and other infectious and inflammatory diseases. As a reference gene in these cells and conditions, AKIRIN1 may further our understanding of innate immunity and lead to new biomarkers.
2019-06-10 | GSE123729 | GEO
Project description:Timely and reliable distinction of non-infectious systemic inflammatory response syndrome (SIRS), common in critically ill patients, from sepsis to support adequate antimicrobial therapy safes lives but is clinically challenging. Expeditious sepsis biomarkers are thus urgently sought. Blood transcriptional profiling provides insights into sepsis pathophysiology, but variability in leukocyte subtype composition complicates profile interpretation, and reliable reference genes to normalize gene expression in sepsis are lacking. Here, we identified AKIRIN1 as a reference gene, specifically, in peripheral NK cells and granulocytes for differential gene expression analysis between patients with SIRS and septic shock on intensive care unit admission. Discovery by a two-step probabilistic selection from microarray data followed by validation through branched DNA assays in independent patients revealed several candidate reference genes in NK cells, namely, AKIRIN1, PPP6R3, TAX1BP1, and ADRBK1. For in vitro priming of NK cells, GUSB however was confirmed as reference gene of choice. Initially, no candidate genes could be validated in granulocytes, an additional rescreen of known reference genes by RT-PCR included. By serendipity, we could determine equal AKIRIN1 expression levels also in SIRS and septic shock granulocytes and no change by in vitro challenge of granulocytes with LPS. Inspection of four external neutrophil transcriptome datasets further support unchanged AKIRIN1 expression in human systemic inflammation. Invariable AKIRIN1 expression in peripheral NK cells and granulocytes needs further validation in sepsis and other infectious and inflammatory diseases. As a reference gene in these cells and conditions, AKIRIN1 may further our understanding of innate immunity and lead to new biomarkers.
2019-06-10 | GSE123730 | GEO
Project description:AKIRIN1 is a suitable reference gene in natural killer cells and granulocytes from patients with SIRS and septic shock [granulocytes]
| PRJNA509658 | ENA
Project description:AKIRIN1 is a suitable reference gene in natural killer cells and granulocytes from patients with SIRS and septic shock [NK cells]
| PRJNA509659 | ENA
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: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.
2015-05-12 | GSE66099 | GEO
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
2006-04-30 | GSE4607 | GEO
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.
2015-05-12 | E-GEOD-66099 | 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. Keywords: Normal vs diseased
2008-12-12 | GSE13904 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2019-06-10 | GSE123731 | GEO