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We have reported and validated that serum interleukin-8 levels, measured within the first 24 hours of admission to the pediatric intensive care unit, can predict a 95 percent probability of survival in children with septic shock. Accordingly, we have proposed that interleukin-8 can be used as a stratification biomarker to exclude children from interventional clinical trials that carry more than minimal risk, as a means to improve the risk-to-benefit ratio of the intervention.
Wong, H.R., Cvijanovich N., Wheeler, D.S., Bigham, M.T., Monaco, M., Odoms, K., Macias, W.L., and Williams, M.D. Interleukin-8 as a stratification tool for interventional trials involving pediatric septic shock. Am J Respir Crit Care Med. 178:276-282, 2008.
PERSEVERE is a multi-biomarker-based risk model to predict outcome and illness severity for individual children with septic shock. The candidate stratification biomarkers have been selected in a systematic and unbiased manner using our gene expression database. The model was recently derived, validated, and published in collaboration with Christopher Lindsell, PhD, and Shelia Salisbury, PhD, from the Center for Clinical and Translational Science and Training at the University of Cincinnati. The serum candidate biomarkers are measured using a multiplex platform developed in collaboration with the Millipore Corp. PERSEVERE was funded by an American Recovery and Reinvestment Act Challenge Grant sponsored by the National Heart, Lung and Blood Institute.
Recently we received an Innovation Fund Award from the Cincinnati Children's Center for Technology Commercialization.
List of candidate stratification biomarkers for PERSEVERE.
In collaboration with the Center for Acute Care Nephrology at Cincinnati Children’s, we have recently derived a list of 21 candidate genes to predict persistent, severe, septic shock-associated kidney injury within 24 hours of admission to the pediatric intensive care unit. These 21 genes are being further explored to identify serum-based biomarkers for septic shock associated kidney injury via a recently awarded grant from the National Institutes of Health.
Twenty-one candidate stratification genes for predicting septic shock-associated kidney injury.
Using unsupervised hierarchical clustering, we have identified three subclasses of children with septic shock based exclusively on differential patterns of gene expression. We then interrogated the clinical database and found that one of the three subclasses had a substantially higher level of illness severity, degree of organ failure and mortality, compared to the other two subclasses. Subsequently, the subclass-defining gene signature was distilled to a 100-gene expression signature and depicted using gene expression mosaics that give microarray data a “face” that allows for intuitive pattern recognition (The Gene Expression Dynamics Inspector (GEDI)). Clinicians without formal bioinformatics training were able to reliably allocate patients to the correct subclasses. In a subsequent study, we validated the existence of these clinically relevant subclasses in a formal, separate validation cohort of children with septic shock. We are currently exploring the feasibility of bringing this classification to the bedside in the form of a rapid, clinician-friendly readout.
The one-hundred subclass-defining genes.
GEDI mosaics demonstrating the three gene expression-based septic shock subclasses
We recently identified interleukin-27 (IL-27) as a novel biomarker to predict bacterial infection in critically ill children. IL-27 was discovered using our extensive gene expression database, and in our initial derivation cohort it outperformed procalcitonin, which is currently one of the most widely used clinical biomarkers for infection. We are now designing studies to further test the diagnostic capabilities of IL-27 in other patient populations, including adults.
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