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This Article Full Text Full Text (PDF) Supplemental Tables All Versions of this Article: 34/1/127    most recent 00025.2008v1 Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Google Scholar Articles by Cvijanovich, N. PubMed PubMed Citation Articles by Cvijanovich, N.

Validating the genomic signature of pediatric septic shock

¹ Cincinnati Children's Hospital Medical Center and Cincinnati Children's Hospital Research Foundation, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio
² Children's Hospital and Research Center Oakland, Oakland, California
³ C. S. Mott Children's Hospital at the University of Michigan, Ann Arbor, Michigan
⁴ The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
⁵ Children's Mercy Hospital, Kansas City, Missouri
⁶ Penn State Children's Hospital, Hershey, Pennsylvania
⁷ St. Louis Children's Hospital, Washington University School of Medicine, St. Louis, Missouri
⁸ Children's Hospital of Orange County, Orange, California
⁹ Children's National Medical Center, Washington, District of Columbia

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 95–100% 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 <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.

microarray; pediatrics; T cell function; zinc