Gene-expression profiling of peripheral blood mononuclear cells in sepsis
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE9960 | GEO | 2009/04/01
SECONDARY ACCESSION(S): PRJNA103971
REPOSITORIES: GEO
Similar Datasets
Project description:To identify signature genes that help distinguish (1) sepsis from non-infectious causes of systemic inflammatory response syndrome, (2) between Gram-positive and Gram-negative sepsis. Experiment Overall Design: A total of 70 critically ill patients (46 sepsis and 24 control) were enrolled in a single-centre observational study. Gene-expression profiling was performed using Affymetrix microarray (U133plus2) with 54,675 transcript. Data was divided into a training set (n=35) and a validation set (n=35). A molecular signature was developed in the training set and was then validated in the validation set.
2009-04-12 | E-GEOD-9960 | biostudies-arrayexpress
Project description:Objective: It is unclear whether the host response of gram-positive sepsis differs from gram-negative sepsis at a transcriptome level. Using microarray technology, we compared the gene-expression profiles of gram-positive sepsis and gram-negative sepsis in critically ill patients. Design: A prospective cross-sectional study. Setting: A 20-bed general intensive care unit of a tertiary referral hospital. Patients: Seventy-two patients admitted to the intensive care unit. Interventions: Intravenous blood was collected for leukocyte separation and RNA extraction. Microarray experiements were then performed examing the expression level of 19,232 genes in each sample. Measurements and Main Results: There was no difference in the expression profile between gram-positive and gram-negative sepsis. The finding remained unchanged even when genes with lower expression level were included or after statistical stringency was lowered. There were, however, ninety-four genes differentially expressed between sepsis and control patients. These genes included those involved in immune regulation, inflammation and mitochondrial function. Hierarchical cluster analysis confirmed that the difference in gene expression profile existed between sepsis and control patients, but not between gram-positive and gram-negative patients. Conclusion: Gram-positive and gram-negative sepsis share a common host response at a transcriptome level. These findings support the hypothesis that the septic response is non-specific and is designed to provide a more general response that can be elicited by a wide range of different micro-organisms. Keywords: disease state analysis, gram-positive sepsis, gram-negative sepsis
2007-12-01 | GSE6535 | GEO
Project description:Systemic immune cells dysregulation, especially the inflammatory factors over-production plays the pivotal role in sepsis induced abnormalities. We further analyzed how HDCA affects the systemic immune cells during sepsis by employing scRNA-seq for PBMCs.
2022-02-10 | GSE195965 | GEO
Project description:Objective: It is unclear whether the host response of gram-positive sepsis differs from gram-negative sepsis at a transcriptome level. Using microarray technology, we compared the gene-expression profiles of gram-positive sepsis and gram-negative sepsis in critically ill patients. Design: A prospective cross-sectional study. Setting: A 20-bed general intensive care unit of a tertiary referral hospital. Patients: Seventy-two patients admitted to the intensive care unit. Interventions: Intravenous blood was collected for leukocyte separation and RNA extraction. Microarray experiements were then performed examing the expression level of 19,232 genes in each sample. Measurements and Main Results: There was no difference in the expression profile between gram-positive and gram-negative sepsis. The finding remained unchanged even when genes with lower expression level were included or after statistical stringency was lowered. There were, however, ninety-four genes differentially expressed between sepsis and control patients. These genes included those involved in immune regulation, inflammation and mitochondrial function. Hierarchical cluster analysis confirmed that the difference in gene expression profile existed between sepsis and control patients, but not between gram-positive and gram-negative patients. Conclusion: Gram-positive and gram-negative sepsis share a common host response at a transcriptome level. These findings support the hypothesis that the septic response is non-specific and is designed to provide a more general response that can be elicited by a wide range of different micro-organisms. The study included seventy-two critically ill patients admitted to the intensive care unit (ICU) of Nepean Hospital, Sydney, Australia. Of these, fifty-five patients were diagnosed to have sepsis, as confirmed by microbiological culture. The remaining seventeen patients did not have sepsis and were therefore used as controls. The study was approved by the hospital ethics committee and informed consent was obtained from all patients or their relatives. Patient Samples. Whole blood was taken from each patient on admission to ICU. Neutrophils were separated from whole blood using density-gradient separation with Ficoll-PaqueP P(Amersham). Subsequent neutrophil RNA extraction was performed using guanidinium thiocyanate (Ambion). Microarray Experiment. The neutrophil RNA was converted to cDNA, fluorescently labeled and hybridized to its complimentary sequences on the microarray (Invitrogen). The fluorescent signals on each micrroarray were captured using the GenePix 4000B laser scanner (Axon Instruments). Expression level of each gene was represented by the intensity of its fluorescent signal. Data Extraction. All signal intensity values were processed using background-subtraction method. Prior to analysis, all values were log-transformed and normalized by fitting a print-tip group Lowess curve. Normalization minimizes bias due to dye chemistry, signal intensity or location of a gene on the array. It ensures the detection of genes that are truly differentially expressed, instead of those caused by experimental artifacts or variation in the hybridization process. After normalization, genes that had more than 50% of data missing were removed. We then selected genes that had at least 80% of the data showing two-fold changes from the geneâs median values. After filtering, 1617 genes were available for further analysis.
2010-05-25 | E-GEOD-6535 | biostudies-arrayexpress
Project description:Blood monocytes serve as the first line of host defense and are equipped to recognize and respond to infection by triggering an immune-inflammatory response. While most information on these cells comes from in vitro studies in humans or in vivo studies in mice, little is known about monocytes under human disease conditions. We investigated the role of monocytes during sepsis and its resolution in humans. A transcriptomal and functional analysis of blood monocytes from patients during gram negative sepsis and at recovery was performed. Monocytes from sepsis patients showed upregulation of a large number of pro-inflammatory genes and cytokines/chemokines, consistent with an ongoing systemic inflammation. However, these cells showed impairment to ex vivo endotoxin (LPS) challenge, displaying a quantitative decrease in the number of LPS-inducible genes. Moreover, they downregulated the expression of several pro-inflammatory cytokine/chemokine genes, activation marker genes and transcription factors associated with monocyte/macrophage activation, upon ex vivo LPS stimulation. Functionally, they downregulated expression of inflammatory cytokines/chemokines and antigen presentation-related molecules and functions. In contrast, genes and functions related to phagocytosis, anti-microbial activity and tissue remodeling where remained unaffected or even enhanced . Collectively, our observations suggest a genetic and functional re-programming of these cells during human sepsis progression. Understanding the molecular mechanisms which regulate this re-programming will allow to devise strategies which could modulate the response of these cells and hence, disease progression. Blood monocytes from gram-negative sepsis patients during sepsis (Sepsis) and following their recovery (Recovery/Basal) as well as healthy donor (control) were isolated. Thereafter, these cells were treated ex vivo with or without LPS for 3h and analysed for transcriptomic study.
2014-05-14 | E-GEOD-46955 | biostudies-arrayexpress
Project description:We investigated the individual phenotypic predisposition to developing uncomplicated infection or sepsis in a large cohort of non-infected patients undergoing major elective surgery. Whole blood RNA sequencing analysis was performed on preoperative samples taken from 267 patients. These comprised patients who developed postoperative infection with (n=77) or without (n=49) sepsis, non-infectious systemic inflammatory response (n=31), or an uncomplicated postoperative course (n=110). Machine learning classification models built on preoperative transcriptomic signatures predicted postoperative outcomes including sepsis.
2024-08-30 | GSE208581 | GEO
Project description:We here sought to better understand the transcriptomic alterations in sorted monocytes (CD14+), CD4+, CD8+ T cells and B cells (CD19+) of sepsis patients (n=6) relative to healthy subjects (n=4).
2020-07-20 | GSE136200 | GEO
Project description:Sepsis remains a leading cause of death and currently has no pathogenesis-specific therapy. Hampered progress is partly due to the lack of insight into deep mechanistic processes. Deciphering the functions of microRNAs in sepsis pathogeny became a dynamic research topic in the last decade. To screen for new microRNA targets for sepsis therapeutics, we used human samples: microRNA array data from peripheral blood mononuclear cells (PBMCs) from sepsis patients and controls, whole blood samples from sepsis survivors; and multiple animal models: mouse cecum ligation-puncture (CLP)-induced sepsis, mouse viral microRNA challenge, and baboon Gram-positive and Gram-negative sepsis models. miR-93-5p met the criteria for a therapeutic target, being overexpressed in baboons which died early after induction of sepsis and downregulated in humans who survived after sepsis. Therapeutically, inhibiting miR-93-5p prolonged the overall survival of mice with CLP-induced sepsis, with a stronger effect in old mice. Mechanistically, anti-miR-93-5p therapy reduced inflammatory monocytes and increased circulating effector memory T cells, especially CD4+ subset. Ago2-immunoprecipitation in miR-93-knockout T cells identified important regulatory receptors, CD28 and CD160, as direct miR-93-5p target genes. In conclusion, miR-93-5p is a potential therapeutic target in sepsis in the elderly through its regulation of both innate and adaptive immunity. We applied the Ago2-RIP Chip (Ribonucleoprotein ImmunoPrecipitation followed by microarray analysis) to identify miR-93-5p target mRNAs. This methodology uses beads coupled to either anti-Ago2 antibody (or an IgG control) to pull down the RISC complex together with any miRNA-interacting mRNAs. To define target genes of miR-93-5p, we assessed mRNA transcripts enriched in the Ago2-IP fraction of JURKAT parental cells or control cells (where miR-93-5p is present) but not in the two KO clones (where miR-93-5p is absent) by microarray
2023-06-13 | GSE223458 | GEO
Project description:Introduction: Sepsis is a complex immunological response to infection characterized by early hyperinflammation followed by severe and protracted immunosuppression, suggesting that a multi-marker approach has the greatest clinical utility for early detection, within a clinical environment focused on SIRS differentiation. Pre-clinical research using an equine sepsis model identified a panel of gene expression biomarkers that define the early aberrant immune activation. Thus, the primary objective was to apply these gene expression biomarkers to distinguish patients with sepsis from those who had undergone major open surgery and had clinical outcomes consistent with systemic inflammation due to physical trauma and wound healing. Methods: This was a multi-centre, prospective clinical trial conducted across 4 tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n=27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n=38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n=20). Each participant had minimally 5ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. Affymetrix array and multiplex tandem (MT)-PCR studies were conducted to evaluate transcriptional profiles in circulating white blood cells applying a set of 42 molecular markers that had been identified a priori. A LogitBoost algorithm was used to create a machine learning diagnostic rule to predict sepsis outcomes. Results: Based on preliminary microarray analyses comparing HC and sepsis groups. A panel of 42-gene expression markers were identified that represented key innate and adaptive immune function, cell cycling, WBC differentiation, extracellular remodelling and immune modulation pathways. Comparisons against GEO data confirmed the definitive separation of the sepsis cohort. Quantitative PCR results suggest the capacity for this test to differentiate severe systemic inflammation from HC is 92%. AUC ROC curve findings demonstrated sepsis prediction within a mixed inflammatory population, was between 86 - 92%. Conclusions: This novel molecular biomarker test has a clinically relevant sensitivity and specificity profile, and has the capacity for early detection of sepsis via the monitoring of critical care patients. GEO Note: Data made available represents the preliminary microarray investigation performed on Human U133 Plus 2.0 GeneChips (Affymetrix), assaying 41 patient samples (Sepsis n=10, Post-Surgical n=11, Control n=20). This was a multi-centre, prospective clinical trial conducted across 4 tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n=27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n=38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n=20). Each participant had minimally 5ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. The GEO data represents the preliminary microarray investigation performed on Human U133 Plus 2.0 GeneChips (Affymetrix), assaying 41 patient samples (Sepsis n=10, Post-Surgical n=11, Control n=20).
2011-11-01 | E-GEOD-28750 | biostudies-arrayexpress
Project description:To examine whether gene-expression profiling of circulating leukocytes is different between patients with sepsis as compared to controls. The signature genes identified will then be used to develop a prediction model to assist the diagnosis of sepsis. Keywords: Prediction study
2007-07-01 | GSE5772 | GEO