The Program seeks to improve our systems-level understanding of the key regulatory elements that direct the host response to serious injury. A greater understanding of the innate inflammatory response to serious injury will lead to the development of novel genomic and proteomic markers that can predict outcome, and will identify potential new avenues for further basic and clinical research, as well as targets for immunomodulatory interventions. The Program is organized to employ multiple high-throughput analytical tools including microarray and comparative, quantitative proteomics coupled with novel macroscale and microfluidics cell separation methodologies and bioinformatics approaches (including knowledge-based pathway analysis).
The specific aims i n Years 6-10 are as follows. (1) Determine genome-wide expression and the cellular proteome from well-defined cellular subpopulations of circulating leukocytes from hospitalized patients following severe trauma and burn injuries. (2) In these cell populations, identify patterns of gene expression and proteomic responses to the innate inflammatory response associated with different clinical trajectories and outcomes. (3) Using a systems biology approach, discover new biological knowledge based upon total cellular proteomics and genomics obtained from the cellular subpopulations. New knowledge will be obtained by fostering and supporting groups of investigators in vastly disparate disciplines, including clinicians, biochemists, immunologists, statisticians, and computational and systems biologists. These interactions will lead to the development of new paradigms for our biological understanding of the injury response. The project tasks and activities include the following: (1) enrollment of 580 severely traumatized or burned patients with stringent entry criteria and standardized guidelines for patient care; (2) high-throughput quantitative, comparative proteomic and functional proteomic analyses of enriched blood leukocyte populations; (3) genome-wide expression analysis of these same leukocyte populations using state-of-the-art high throughput formats; (4) implementation of a web-enabled trauma-related database containing clinical, physiologic, proteomic, and genomic expression data; (5) computational analysis of the complex data by data interpretation groups, comprised of biostatisticians, critical care physicians and basic scientists with the ultimate goal being an integrated systems view of the injury response. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54GM062119-07
Application #
7287427
Study Section
Special Emphasis Panel (ZGM1-PPBC-5 (GL))
Program Officer
Somers, Scott D
Project Start
2000-09-01
Project End
2011-08-31
Budget Start
2007-09-01
Budget End
2008-08-31
Support Year
7
Fiscal Year
2007
Total Cost
$7,963,235
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199
Gale, Stephen C; Kocik, Jurek F; Creath, Robert et al. (2016) A comparison of initial lactate and initial base deficit as predictors of mortality after severe blunt trauma. J Surg Res 205:446-455
Agarwal, Shailesh; Loder, Shawn; Brownley, Cameron et al. (2016) Inhibition of Hif1? prevents both trauma-induced and genetic heterotopic ossification. Proc Natl Acad Sci U S A 113:E338-47
Lopez, Maria-Cecilia; Efron, Philip A; Ozrazgat-Baslanti, Tezcan et al. (2016) Sex-based differences in the genomic response, innate immunity, organ dysfunction, and clinical outcomes after severe blunt traumatic injury and hemorrhagic shock. J Trauma Acute Care Surg 81:478-85
Sood, Ravi F; Gibran, Nicole S; Arnoldo, Brett D et al. (2016) Early leukocyte gene expression associated with age, burn size, and inhalation injury in severely burned adults. J Trauma Acute Care Surg 80:250-7
Mathias, Brittany; Lipori, Gigi; Moldawer, Lyle L et al. (2016) Integrating ""big data"" into surgical practice. Surgery 159:371-4
Mason, Stephanie A; Nathens, Avery B; Finnerty, Celeste C et al. (2016) Hold the Pendulum: Rates of Acute Kidney Injury are Increased in Patients Who Receive Resuscitation Volumes Less than Predicted by the Parkland Equation. Ann Surg 264:1142-1147
Hsu, Jessie J; Finkelstein, Dianne M; Schoenfeld, David A (2015) Outcome-Driven Cluster Analysis with Application to Microarray Data. PLoS One 10:e0141874
Hou, Jiayi; Archer, Kellie J (2015) Regularization method for predicting an ordinal response using longitudinal high-dimensional genomic data. Stat Appl Genet Mol Biol 14:93-111
Yan, Shuangchun; Tsurumi, Amy; Que, Yok-Ai et al. (2015) Prediction of multiple infections after severe burn trauma: a prospective cohort study. Ann Surg 261:781-92
Kutcher, Matthew E; Howard, Benjamin M; Sperry, Jason L et al. (2015) Evolving beyond the vicious triad: Differential mediation of traumatic coagulopathy by injury, shock, and resuscitation. J Trauma Acute Care Surg 78:516-23

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