A recent consensus conference concluded that there are no diagnostic criteria specific for differentiating between systemic inflammation and sepsis, and that a lack of sepsis molecular markers underscores the challenge still present in diagnosing sepsis. In preliminary studies, we systematically tested the hypothesis that circulating leukocyte gene expression profiles and plasma proteomic profiles can be used to diagnose sepsis and model the response to systemic inflammation. Having proved our hypothesis in preclinical models, we are now ready to move to the bedside. One of the very few data-rich environments where infection can be predicted on a population basis is the intensive care unit (ICU), typically manifested as ventilator-associated pneumonia (VAP). We hypothesize that circulating leukocyte RNA and plasma protein profiles over time in patients can be used to model the host response to sepsis secondary to VAP, and that the application of this model to clinical decision making will significantly improve our diagnostic and prognostic capabilities. To test this hypothesis, we established the University-wide infrastructure necessary, involving faculty from the departments of Surgery, Anesthesiology, Medicine, Pediatrics, Genetics, Pathology and Immunology, Radiation Oncology, Biostatistics, Systems Engineering, Computer Science, and Mathematics.
In Aim 1, we measure changes over time in the circulating leukocyte transcriptome and plasma proteome of patients at risk for VAP.
In Aim 2, we model the host response to VAP using generic and organism-specific markers that differentiate between patients who respond or do not respond to therapy. The optimized sample collection protocols are in use. Serial blood samples are drawn over 21 days from intubated patients at risk for VAP. Pilot data from the first two patients are presented herein, describing the clinical trajectory of Gram-negative pneumonia. Funds from this award are necessary to generate the preliminary data for a larger study, to untangle the septic response from the systemic inflammatory response.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21GM075023-01
Application #
6961282
Study Section
Special Emphasis Panel (ZRG1-SBIB-G (02))
Program Officer
Somers, Scott D
Project Start
2005-09-30
Project End
2007-08-31
Budget Start
2005-09-30
Budget End
2006-08-31
Support Year
1
Fiscal Year
2005
Total Cost
$229,375
Indirect Cost
Name
Washington University
Department
Surgery
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Werner, Jason A; Schierding, William; Dixon, David et al. (2012) Preliminary evidence for leukocyte transcriptional signatures for pediatric ventilator-associated pneumonia. J Intensive Care Med 27:362-9
Muenzer, Jared T; Jaffe, David M; Schwulst, Steve J et al. (2010) Evidence for a novel blood RNA diagnostic for pediatric appendicitis: the riboleukogram. Pediatr Emerg Care 26:333-8
Cobb, J Perren; Moore, Ernest E; Hayden, Doug L et al. (2009) Validation of the riboleukogram to detect ventilator-associated pneumonia after severe injury. Ann Surg 250:531-9
Polpitiya, Ashoka D; McDunn, Jonathan E; Burykin, Anton et al. (2009) Using systems biology to simplify complex disease: immune cartography. Crit Care Med 37:S16-21
McDunn, Jonathan E; Husain, Kareem D; Polpitiya, Ashoka D et al. (2008) Plasticity of the systemic inflammatory response to acute infection during critical illness: development of the riboleukogram. PLoS One 3:e1564
Checchia, Paul A; Schierding, William; Polpitiya, Ashoka et al. (2008) Myocardial transcriptional profiles in a murine model of sepsis: evidence for the importance of age. Pediatr Crit Care Med 9:530-5