Application of combined omics platforms to accelerate biomedical discovery in diabesity

Irwin J. Kurland; Domenico Accili; Charles Burant; Steven M. Fischer; Barbara B. Kahn; Christopher B. Newgard; Suma Ramagiri; Gabriele V. Ronnett; John A. Ryals; Mark Sanders; Joe Shambaugh; John Shockcor; Steven S. Gross

doi:10.1111/nyas.12116

Application of combined omics platforms to accelerate biomedical discovery in diabesity

Irwin J. Kurland, Domenico Accili, Charles Burant, Steven M. Fischer, Barbara B. Kahn, Christopher B. Newgard, Suma Ramagiri, Gabriele V. Ronnett, John A. Ryals, Mark Sanders, Joe Shambaugh, John Shockcor, Steven S. Gross

School of Medicine

Research output: Contribution to journal › Article › peer-review

26 Scopus citations

Abstract

Diabesity has become a popular term to describe the specific form of diabetes that develops late in life and is associated with obesity. While there is a correlation between diabetes and obesity, the association is not universally predictive. Defining the metabolic characteristics of obesity that lead to diabetes, and how obese individuals who develop diabetes different from those who do not, are important goals. The use of large-scale omics analyses (e.g., metabolomic, proteomic, transcriptomic, and lipidomic) of diabetes and obesity may help to identify new targets to treat these conditions. This report discusses how various types of omics data can be integrated to shed light on the changes in metabolism that occur in obesity and diabetes.

Original language	English (US)
Pages (from-to)	1-16
Number of pages	16
Journal	Annals of the New York Academy of Sciences
Volume	1287
Issue number	1
DOIs	https://doi.org/10.1111/nyas.12116
State	Published - May 2013

Keywords

Diabesity
Diabetes
Lipidomics
Metabolism, metabolic profiling
Metabolomics
Obesity
Omics
Proteomics

ASJC Scopus subject areas

General Biochemistry, Genetics and Molecular Biology
History and Philosophy of Science

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10.1111/nyas.12116

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Kurland, I. J., Accili, D., Burant, C., Fischer, S. M., Kahn, B. B., Newgard, C. B., Ramagiri, S., Ronnett, G. V., Ryals, J. A., Sanders, M., Shambaugh, J., Shockcor, J., & Gross, S. S. (2013). Application of combined omics platforms to accelerate biomedical discovery in diabesity. Annals of the New York Academy of Sciences, 1287(1), 1-16. https://doi.org/10.1111/nyas.12116

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abstract = "Diabesity has become a popular term to describe the specific form of diabetes that develops late in life and is associated with obesity. While there is a correlation between diabetes and obesity, the association is not universally predictive. Defining the metabolic characteristics of obesity that lead to diabetes, and how obese individuals who develop diabetes different from those who do not, are important goals. The use of large-scale omics analyses (e.g., metabolomic, proteomic, transcriptomic, and lipidomic) of diabetes and obesity may help to identify new targets to treat these conditions. This report discusses how various types of omics data can be integrated to shed light on the changes in metabolism that occur in obesity and diabetes.",

keywords = "Diabesity, Diabetes, Lipidomics, Metabolism, metabolic profiling, Metabolomics, Obesity, Omics, Proteomics",

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AU - Kahn, Barbara B.

AU - Newgard, Christopher B.

AU - Ramagiri, Suma

AU - Ronnett, Gabriele V.

AU - Ryals, John A.

AU - Sanders, Mark

AU - Shambaugh, Joe

AU - Shockcor, John

AU - Gross, Steven S.

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Application of combined omics platforms to accelerate biomedical discovery in diabesity

Abstract

Keywords

ASJC Scopus subject areas

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