Faculty Collaboration Database

Developing a clinically feasible personalized medicine approach to pediatric septic shock. Am J Respir Crit Care Med 2015 Feb 01;191(3):309-15

Date

12/10/2014

Pubmed ID

25489881

Pubmed Central ID

PMC4351580

DOI

10.1164/rccm.201410-1864OC

Scopus ID

2-s2.0-84922311029 (requires institutional sign-in at Scopus site)   214 Citations

Abstract

RATIONALE: Using microarray data, we previously identified gene expression-based subclasses of septic shock with important phenotypic differences. The subclass-defining genes correspond to adaptive immunity and glucocorticoid receptor signaling. Identifying the subclasses in real time has theranostic implications, given the potential for immune-enhancing therapies and controversies surrounding adjunctive corticosteroids for septic shock.

OBJECTIVES: To develop and validate a real-time subclassification method for septic shock.

METHODS: Gene expression data for the 100 subclass-defining genes were generated using a multiplex messenger RNA quantification platform (NanoString nCounter) and visualized using gene expression mosaics. Study subjects (n = 168) were allocated to the subclasses using computer-assisted image analysis and microarray-based reference mosaics. A gene expression score was calculated to reduce the gene expression patterns to a single metric. The method was tested prospectively in a separate cohort (n = 132).

MEASUREMENTS AND MAIN RESULTS: The NanoString-based data reproduced two septic shock subclasses. As previously, one subclass had decreased expression of the subclass-defining genes. The gene expression score identified this subclass with an area under the curve of 0.98 (95% confidence interval [CI95] = 0.96-0.99). Prospective testing of the subclassification method corroborated these findings. Allocation to this subclass was independently associated with mortality (odds ratio = 2.7; CI95 = 1.2-6.0; P = 0.016), and adjunctive corticosteroids prescribed at physician discretion were independently associated with mortality in this subclass (odds ratio = 4.1; CI95 = 1.4-12.0; P = 0.011).

CONCLUSIONS: We developed and tested a gene expression-based classification method for pediatric septic shock that meets the time constraints of the critical care environment, and can potentially inform therapeutic decisions.

Author List

Wong HR, Cvijanovich NZ, Anas N, Allen GL, Thomas NJ, Bigham MT, Weiss SL, Fitzgerald J, Checchia PA, Meyer K, Shanley TP, Quasney M, Hall M, Gedeit R, Freishtat RJ, Nowak J, Shekhar RS, Gertz S, Dawson E, Howard K, Harmon K, Beckman E, Frank E, Lindsell CJ

Author

Rainer G. Gedeit MD Associate Chief Medical Officer in the Children's Administration department at Children's Wisconsin

MESH terms used to index this publication - Major topics in bold

Child
Child, Preschool
Feasibility Studies
Female
Gene Expression Regulation
Glucocorticoids
Humans
Infant
Intensive Care Units, Pediatric
Male
Mathematical Computing
Odds Ratio
Phenotype
Precision Medicine
Prospective Studies
Reproducibility of Results
Severity of Illness Index
Shock, Septic
Signal Transduction