A metabolomic approach to understanding the metabolic link between obesity and diabetes

Seokjae Park, Krishna Chaitanya Sadanala, Eun Kyoung Kim

Research output: Contribution to journalArticlepeer-review

Abstract

Obesity and diabetes arise from an intricate interplay between both genetic and environmental factors. It is well recognized that obesity plays an important role in the development of insulin resistance and diabetes. Yet, the exact mechanism of the connection between obesity and diabetes is still not completely understood. Metabolomics is an analytical approach that aims to detect and quantify small metabolites. Recently, there has been an increased interest in the application of metabolomics to the identification of disease biomarkers, with a number of well-known biomarkers identified. Metabolomics is a potent approach to unravel the intricate relationships between metabolism, obesity and progression to diabetes and, at the same time, has potential as a clinical tool for risk evaluation and monitoring of disease. Moreover, metabolomics applications have revealed alterations in the levels of metabolites related to obesity-associated diabetes. This review focuses on the part that metabolomics has played in elucidating the roles of metabolites in the regulation of systemic metabolism relevant to obesity and diabetes. It also explains the possible metabolic relation and association between the two diseases. The metabolites with altered profiles in individual disorders and those that are specifically and similarly altered in both disorders are classified, categorized and summarized.

Original languageEnglish (US)
Pages (from-to)587-596
Number of pages10
JournalMolecules and Cells
Volume38
Issue number7
DOIs
StatePublished - 2014
Externally publishedYes

Keywords

  • Biomarkers
  • Diabetes
  • Metabolites
  • Metabolomics
  • Obesity

ASJC Scopus subject areas

  • Molecular Biology
  • Cell Biology

Fingerprint

Dive into the research topics of 'A metabolomic approach to understanding the metabolic link between obesity and diabetes'. Together they form a unique fingerprint.

Cite this