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BMC Medicine
Published in: BMC Medicine 1/2009

Open Access 01-12-2009 | Research article

Identification of pediatric septic shock subclasses based on genome-wide expression profiling

Authors: Hector R Wong, Natalie Cvijanovich, Richard Lin, Geoffrey L Allen, Neal J Thomas, Douglas F Willson, Robert J Freishtat, Nick Anas, Keith Meyer, Paul A Checchia, Marie Monaco, Kelli Odom, Thomas P Shanley

Published in: BMC Medicine | Issue 1/2009

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Abstract

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 three putative subclasses (analysis of variance, 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 three 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.

Conclusion

Genome-wide expression profiling can identify pediatric septic shock subclasses having clinically relevant phenotypes.
Appendix
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Metadata
Title
Identification of pediatric septic shock subclasses based on genome-wide expression profiling
Authors
Hector R Wong
Natalie Cvijanovich
Richard Lin
Geoffrey L Allen
Neal J Thomas
Douglas F Willson
Robert J Freishtat
Nick Anas
Keith Meyer
Paul A Checchia
Marie Monaco
Kelli Odom
Thomas P Shanley
Publication date
01-12-2009
Publisher
BioMed Central
Published in
BMC Medicine / Issue 1/2009
Electronic ISSN: 1741-7015
DOI
https://doi.org/10.1186/1741-7015-7-34

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