For nearly a decade, our research group has had the privilege of developing and mining a multicenter, microarray-based, genome-wide expression database of critically ill children (≤10 y of age) with septic shock.

validating the genomic signature of pediatric septic shock-54

Comparator groups include age-matched normal controls, critically ill children meeting criteria for sepsis, and critically ill children meeting criteria for the systemic inflammatory response syndrome (SIRS), based on pediatric-specific definitions (1).

Septic shock is a heterogeneous syndrome within which probably exist several biological subclasses.

The studies have progressed from an initial discovery-oriented and exploratory phase to a new phase in which the data are being translated and applied to address several areas of clinical need.

The expression data are based on whole blood–derived RNA and are focused on the initial, acute presentation to the pediatric intensive care unit (PICU) with a clinical diagnosis of septic shock.

Using computer-based image analysis, patients were classified into one of three subclasses ("A," "B," or "C") based on color and pattern similarity relative to reference mosaics generated from the original derivation cohort. The consensus classification of the clinicians had modest agreement with the computer algorithm.

After subclassification, the clinical database was mined for phenotyping. Septic shock is a heterogeneous syndrome with variable physiological and biological manifestations across patient groups [1, 2].Prospective observational study involving microarray-based bioinformatics. Multiple pediatric intensive care units in the United States. Patients in subclass A were characterized by repression of genes corresponding to adaptive immunity and glucocorticoid receptor signaling.Separate derivation (n = 98) and validation (n = 82) cohorts of children with septic shock. Gene expression mosaics of the 100 class-defining genes were generated for 82 individual patients in the validation cohort. Separate subclass assignments were conducted by 21 individual clinicians, using visual inspection.Genome-wide expression profiling was conducted using whole blood-derived RNA from 98 children with septic shock, followed by a series of bioinformatic approaches targeted at subclass discovery and characterization.Three putative subclasses (subclasses A, B, and C) were initially identified based on an empiric, discovery-oriented expression filter and unsupervised hierarchical clustering.The concept of septic shock subclasses is clinically relevant in that potentially it could have major implications for the design of more specifically targeted therapies [].