Submitted on January 28, 2008
Accepted on April 30, 2008
VALIDATING THE GENOMIC SIGNATURE OF PEDIATRIC SEPTIC SHOCK
Natalie Cvijanovich1, Thomas P. Shanley2, Richard Lin3, Geoffrey L Allen4, Neal J. Thomas5, Paul Checchia6, Nick Anas7, Robert J Freishtat8, Marie Monaco9, Kelli Odoms9, Bhuvaneswari Sakthivel10, and Hector R. Wong9*
1 Pediatrics, Children's Hospital and Research Center Oakland, Oakland, California, United States
2 Pediatrics, C.S. Mott Children's Hospital at the University of Michigan, Ann Arbor, Michigan, United States
3 Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
4 Pediatrics, Children's Mercy Hospital, Kansas City, Missouri, United States
5 Pediatrics, Penn State Children's Hospital, Hershey, Pennsylvania, United States
6 Pediatrics, St. Louis Children's Hospital, St. Louis, Missouri, United States
7 Pediatrics, Children's Hospital of Orange County, Orange, California, United States
8 Pediatrics, Children's National Medical Center, Washington, District of Columbia, United States
9 Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States
10 Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States
* To whom correspondence should be addressed. E-mail: hector.wong{at}cchmc.org.
We previously generated genome-wide expression data (microarray) from children with septic shock having the potential to lead the field into novel areas of investigation. Herein we seek to validate our data through a bioinformatic approach centered on a validation patient cohort. Forty-two children with a clinical diagnosis of septic shock and 15 normal controls served as the training data set, while 30 separate children with septic shock and 14 separate normal controls served as the test data set. Class prediction modeling using the training data set and the previously reported genome-wide expression signature of pediatric septic shock correctly identified 95 to 100% of controls and septic shock patients in the test data set, depending on the class prediction algorithm and the gene selection method. Subjecting the test data set to an identical filtering strategy as that used for the training data set, demonstrated 75% concordance between the two gene lists. Subjecting the test data set to a purely statistical filtering strategy, with highly stringent correction for multiple comparisons, demonstrated less than 50% concordance with the previous gene filtering strategy. However, functional analysis of this statistics-based gene list demonstrated similar functional annotations and signaling pathways as that seen in the training data set. In particular, we validated that pediatric septic shock is characterized by large scale repression of genes related to zinc homeostasis and lymphocyte function. These data demonstrate that the previously reported genome-wide expression signature of pediatric septic shock is applicable to a validation cohort of patients.
