Discovery of pharmaceutically-targetable pathways and prediction of survivorship for pneumonia and sepsis patients from the view point of ensemble gene noise

Tristan de Jong; Victor Guryev; Yury M. Moshkin

To circumvent this, we reasoned that 1) genes do not function in isolation, but rather act as ensembles representing biological pathways and/or subunits of protein complexes. From the whole blood expression profiles of patients under intensive care treatment we estimated how ensemble gene noise corresponds to a pathological state, such as sepsis, community/hospital acquired pneumonia (CAP) or viral H1N1 pneumonia (H1N1). From this analysis we identified a number of pathways for which ensemble gene noise associated positively with an individual health/disease state treated as an ordinal variable (healthy < early H1N1 phase < late H1N1 phase and healthy < sepsis/CAP survived < sepsis/CAP deceased patients). Finally, we identified pathways and complexes where deregulation is associated with a poor prognosis and predicted the clinical outcome (survival/mortality) for CAP/sepsis patients based on ensemble gene noise with high accuracy. We concluded that the ensemble gene noise provides a powerful tool for the discovery of systemic disease biomarkers, pharmaceutically targetable pathways and the prediction of a disease clinical outcome.