Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of mouse and human spleen to determine a molecular signature for sepsis

ABSTRACT: Accuracy of sepsis prediction was obtained using cross-validation of gene expression data from 12 human spleen samples and from 16 mouse spleen samples. For blood studies, classifiers were constructed using data from a training data set of 26 microarrays. The error rate of the classifiers was estimated on seven de-identified microarrays, and then on a subsequent cross-validation for all 33 blood microarrays. Estimates of classification accuracy of sepsis in human spleen were 67.1%; in mouse spleen, 96%; and in mouse blood, 94.4% (all estimates were based on nested cross-validation). Lists of genes with substantial changes in expression between study and control groups were used to identify nine mouse common inflammatory response genes, six of which were mapped into a single pathway using contemporary pathway analysis tools. Experiment Overall Design: Exploratory studies were conducted using spleens from septic patients and from mice with abdominal sepsis. Seven patients with sepsis after injury were identified retrospectively and compared with six injured patients. C57BL/6 male mice were subjected to cecal ligation and puncture, or to IP lipopolysaccharide. Control mice had sham laparotomy or injection of IP saline, respectively. A sepsis classification model was created and tested on blood samples from septic mice.

ORGANISM(S): Mus musculus

SUBMITTER: J Perren Cobb

PROVIDER: E-GEOD-5663 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Molecular diagnostics in sepsis: from bedside to bench.

Chung T Philip TP Laramie Jason M JM Meyer Donald J DJ Downey Thomas T Tam Laurence H Y LH Ding Huashi H Buchman Timothy G TG Karl Irene I Stormo Gary D GD Hotchkiss Richard S RS Cobb J Perren JP

Journal of the American College of Surgeons 20060911 5

<h4>Background</h4>Based on recent in vitro data, we tested the hypothesis that microarray expression profiles can be used to diagnose sepsis, distinguishing in vivo between sterile and infectious causes of systemic inflammation.<h4>Study design</h4>Exploratory studies were conducted using spleens from septic patients and from mice with abdominal sepsis. Seven patients with sepsis after injury were identified retrospectively and compared with six injured patients. C57BL/6 male mice were subjecte ...[more]

PMID: 17084318

Similar Datasets

Project description:Sepsis is defined as a systemic inflammatory response secondary to a proven or suspected infection. Mechanisms governing this inflammatory response have been shown to be complex and dynamic, involving cross-talking among diverse signaling pathways. However, current knowledge on mechanisms underlying sepsis is far from providing a complete picture of the syndrome, justifying additional efforts that might add to this scenario. Microarray-based expression profiling is a powerful approach for the investigation of complex clinical conditions such as sepsis: the analysis of gene transcription at the genome level potentially avoids results derived from biased assumptions. In this study we investigate whole-genome gene expression profiles of mononuclear cells from survivor and non-survivor septic patients. Blood samples were collected at the time of sepsis diagnosis and seven days later, allowing us to evaluate the role of biological processes or genes possibly involved in patient recovery. Aiming to circumvent, at least partially, the heterogeneity of septic patients we included only patients admitted with sepsis caused by community-acquired pneumonia. Global gene expression profiling allowed us to characterize early sepsis, as compared to healthy individuals. Our results corroborate literature reports on inflammation response in the early stages of sepsis but highlight great heterogeneity in gene expression during sepsis progress. Additionally, global gene expression in the early stage was also able to distinguish sepsis from septic shock and correlated with patient outcome. Differences in oxidative stress seem to be associated with clinical outcome, since significant differences in the expression profile of related genes were observed between survivors and non-survivors at the time of patient enrollment (early sepsis). However, our results substantiate current knowledge supporting that sepsis syndrome development is indeed multifaceted. Although the initial infection of enrolled patients was pneumonia, seven days later gene expression profiles seemed to be characteristic of each patient, common gene expression changes distinguishing survivors from non-survivors. This result could be associated with the underlying health status of each one of them, with complications due to sepsis itself as well as with distinct timing for response to treatment. In this study we investigate whole-genome gene expression profiles of mononuclear cells from survivor (n=5) and non-survivor (n=5) septic patients, as well as from 3 healthy controls. Blood samples were collected at the time of sepsis diagnosis and seven days later, allowing us to evaluate the role of biological processes or genes possibly involved in patient recovery. Aiming to circumvent, at least partially, the heterogeneity of septic patients we included only patients admitted with sepsis caused by community-acquired pneumonia.

Dataset Information

Transcription profiling of mouse and human spleen to determine a molecular signature for sepsis

Publications

Molecular diagnostics in sepsis: from bedside to bench.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets