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Series GSE26440 Query DataSets for GSE26440
Status Public on Jan 13, 2011
Title Expression data for derivation of septic shock subgroups
Organism Homo sapiens
Experiment type Expression profiling by array
Summary 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.
 
Overall design 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.
 
Contributor(s) Wong HR
Citation(s) 19624809, 21738952, 26376786, 24650276
Submission date Jan 04, 2011
Last update date Aug 16, 2019
Contact name Hector R Wong
E-mail(s) hector.wong@cchmc.org
Phone 513-636-4259
Fax 513-636-4267
Organization name Cincinnati Children's Hospital Medical Center
Department Pediatrics
Street address 3333 Burnet Avenue
City Cincinnati
State/province OH
ZIP/Postal code 45229
Country USA
 
Platforms (1)
GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array
Samples (130)
GSM648590 Septic Shock_biological rep1 01-0013
GSM648591 Septic Shock_biological rep2 01-0014
GSM648592 Septic Shock_biological rep3 01-0019
Relations
BioProject PRJNA136823

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE26440_RAW.tar 604.3 Mb (http)(custom) TAR (of CEL)
Processed data included within Sample table
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