Developing a clinically feasible personalized medicine approach to pediatric septic shock

  • Hector R. Wong
  • , Natalie Z. Cvijanovich
  • , Nick Anas
  • , Geoffrey L. Allen
  • , Neal J. Thomas
  • , Michael T. Bigham
  • , Scott L. Weiss
  • , Julie Fitzgerald
  • , Paul A. Checchia
  • , Keith Meyer
  • , Thomas P. Shanley
  • , Michael Quasney
  • , Mark Hall
  • , Rainer Gedeit
  • , Robert J. Freishtat
  • , Jeffrey Nowak
  • , Raj S. Shekhar
  • , Shira Gertz
  • , Emily Dawson
  • , Kelli Howard
  • Kelli Harmon, Eileen Beckman, Erin Frank, Christopher J. Lindsell

Research output: Contribution to journalArticlepeer-review

248 Scopus 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.

Original languageEnglish (US)
Pages (from-to)309-315
Number of pages7
JournalAmerican journal of respiratory and critical care medicine
Volume191
Issue number3
DOIs
StatePublished - Feb 1 2015

All Science Journal Classification (ASJC) codes

  • Pulmonary and Respiratory Medicine
  • Critical Care and Intensive Care Medicine

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