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 HowardKelli Harmon, Eileen Beckman, Erin Frank, Christopher J. Lindsell

*Corresponding author for this work

Research output: Contribution to journalArticle

114 Citations (Scopus)

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

Fingerprint

Precision Medicine
Septic Shock
Pediatrics
Gene Expression
Adrenal Cortex Hormones
Odds Ratio
Genes
Computer-Assisted Image Processing
Mortality
Glucocorticoid Receptors
Adaptive Immunity
Critical Care
Area Under Curve
Confidence Intervals
Physicians
Messenger RNA
Therapeutics

Keywords

  • Adaptive immunity
  • Gene expression
  • Glucocorticoids
  • Sepsis
  • Subclassification

ASJC Scopus subject areas

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

Cite this

Wong, H. R., Cvijanovich, N. Z., Anas, N., Allen, G. L., Thomas, N. J., Bigham, M. T., ... Lindsell, C. J. (2015). Developing a clinically feasible personalized medicine approach to pediatric septic shock. American journal of respiratory and critical care medicine, 191(3), 309-315. https://doi.org/10.1164/rccm.201410-1864OC
Wong, Hector R. ; Cvijanovich, Natalie Z. ; Anas, Nick ; Allen, Geoffrey L. ; Thomas, Neal J. ; Bigham, Michael T. ; Weiss, Scott L. ; Fitzgerald, Julie ; Checchia, Paul A. ; Meyer, Keith ; Shanley, Thomas P. ; Quasney, Michael ; Hall, Mark ; Gedeit, Rainer ; Freishtat, Robert J. ; Nowak, Jeffrey ; Shekhar, Raj S. ; Gertz, Shira ; Dawson, Emily ; Howard, Kelli ; Harmon, Kelli ; Beckman, Eileen ; Frank, Erin ; Lindsell, Christopher J. / Developing a clinically feasible personalized medicine approach to pediatric septic shock. In: American journal of respiratory and critical care medicine. 2015 ; Vol. 191, No. 3. pp. 309-315.
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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 2015, 'Developing a clinically feasible personalized medicine approach to pediatric septic shock', American journal of respiratory and critical care medicine, vol. 191, no. 3, pp. 309-315. https://doi.org/10.1164/rccm.201410-1864OC

Developing a clinically feasible personalized medicine approach to pediatric septic shock. / Wong, Hector R.; Cvijanovich, Natalie Z.; Anas, Nick; Allen, Geoffrey L.; Thomas, Neal J.; Bigham, Michael T.; Weiss, Scott L.; Fitzgerald, Julie; Checchia, Paul A.; Meyer, Keith; Shanley, Thomas P.; Quasney, Michael; Hall, Mark; Gedeit, Rainer; Freishtat, Robert J.; Nowak, Jeffrey; Shekhar, Raj S.; Gertz, Shira; Dawson, Emily; Howard, Kelli; Harmon, Kelli; Beckman, Eileen; Frank, Erin; Lindsell, Christopher J.

In: American journal of respiratory and critical care medicine, Vol. 191, No. 3, 01.02.2015, p. 309-315.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Developing a clinically feasible personalized medicine approach to pediatric septic shock

AU - Wong, Hector R.

AU - Cvijanovich, Natalie Z.

AU - Anas, Nick

AU - Allen, Geoffrey L.

AU - Thomas, Neal J.

AU - Bigham, Michael T.

AU - Weiss, Scott L.

AU - Fitzgerald, Julie

AU - Checchia, Paul A.

AU - Meyer, Keith

AU - Shanley, Thomas P.

AU - Quasney, Michael

AU - Hall, Mark

AU - Gedeit, Rainer

AU - Freishtat, Robert J.

AU - Nowak, Jeffrey

AU - Shekhar, Raj S.

AU - Gertz, Shira

AU - Dawson, Emily

AU - Howard, Kelli

AU - Harmon, Kelli

AU - Beckman, Eileen

AU - Frank, Erin

AU - Lindsell, Christopher J.

PY - 2015/2/1

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N2 - 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.

AB - 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.

KW - Adaptive immunity

KW - Gene expression

KW - Glucocorticoids

KW - Sepsis

KW - Subclassification

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