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• Izamis, M
• Uygun, K
• Sharma, N
• Uygun, B
• Yarmush, M
• Berthiaume, F
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• Izamis, M
• Uygun, K
• Sharma, N
• Uygun, B
• Yarmush, M
• Berthiaume, F
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• Izamis, M
• Uygun, K
• Sharma, N
• Uygun, B
• Yarmush, M
• Berthiaume, F

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Metabolites 2012, 2(3), 458-478; doi:10.3390/metabo2030458

Article

Development of Metabolic Indicators of Burn Injury: Very Low Density Lipoprotein (VLDL) and Acetoacetate Are Highly Correlated to Severity of Burn Injury in Rats

Maria-Louisa Izamis ¹ , Korkut Uygun ¹ , Nripen S. Sharma ¹ , Basak Uygun ¹ , Martin L. Yarmush ^1,2  and Francois Berthiaume ^2,*

¹ Center for Engineering in Medicine, Massachusetts General Hospital, Harvard Medical School and the Shriners Hospitals for Children, Boston, MA 02114, USA ² Department of Biomedical Engineering, Rutgers University, Piscataway, NJ 08854, USA

* Author to whom correspondence should be addressed.

Received: 9 June 2012; in revised form: 3 July 2012 / Accepted: 4 July 2012 / Published: 16 July 2012

Download PDF Full-Text [328 KB, uploaded 16 July 2012 13:50 CEST]

Abstract: Hypermetabolism is a significant sequela to severe trauma such as burns, as well as critical illnesses such as cancer. It persists in parallel to, or beyond, the original pathology for many months as an often-fatal comorbidity. Currently, diagnosis is based solely on clinical observations of increased energy expenditure, severe muscle wasting and progressive organ dysfunction. In order to identify the minimum number of necessary variables, and to develop a rat model of burn injury-induced hypermetabolism, we utilized data mining approaches to identify the metabolic variables that strongly correlate to the severity of injury. A clustering-based algorithm was introduced into a regression model of the extent of burn injury. As a result, a neural network model which employs VLDL and acetoacetate levels was demonstrated to predict the extent of burn injury with 88% accuracy in the rat model. The physiological importance of the identified variables in the context of hypermetabolism, and necessary steps in extension of this preliminary model to a clinically utilizable index of severity of burn injury are outlined.

Keywords: hypermetabolism; metabonomics; flux analysis; cluster analysis; regression; variable selection; burn injury

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