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Mol Syst Biol DOI:10.1038/msb.2008.50

Metabolic profiling of the human response to a glucose challenge reveals distinct axes of insulin sensitivity.

Publication TypeJournal Article
Year of Publication2008
AuthorsShaham, O, Wei, R, Wang, TJ, Ricciardi, C, Lewis, GD, Vasan, RS, Carr, SA, Thadhani, R, Gerszten, RE, Mootha, VK
JournalMol Syst Biol
Volume4
Pages214
Date Published2008
ISSN1744-4292
KeywordsAdult, Biomarkers, Blood Glucose, Chromatography, Liquid, Fasting, Female, Glucose Intolerance, Glucose Tolerance Test, Glycolysis, Homeostasis, Humans, Insulin, Insulin Resistance, Ketones, Kinetics, Lipolysis, Male, Middle Aged, Peptide Hydrolases, Prediabetic State, Tandem Mass Spectrometry
Abstract

Glucose ingestion after an overnight fast triggers an insulin-dependent, homeostatic program that is altered in diabetes. The full spectrum of biochemical changes associated with this transition is currently unknown. We have developed a mass spectrometry-based strategy to simultaneously measure 191 metabolites following glucose ingestion. In two groups of healthy individuals (n=22 and 25), 18 plasma metabolites changed reproducibly, including bile acids, urea cycle intermediates, and purine degradation products, none of which were previously linked to glucose homeostasis. The metabolite dynamics also revealed insulin's known actions along four key axes--proteolysis, lipolysis, ketogenesis, and glycolysis--reflecting a switch from catabolism to anabolism. In pre-diabetics (n=25), we observed a blunted response in all four axes that correlated with insulin resistance. Multivariate analysis revealed that declines in glycerol and leucine/isoleucine (markers of lipolysis and proteolysis, respectively) jointly provide the strongest predictor of insulin sensitivity. This observation indicates that some humans are selectively resistant to insulin's suppression of proteolysis, whereas others, to insulin's suppression of lipolysis. Our findings lay the groundwork for using metabolic profiling to define an individual's 'insulin response profile', which could have value in predicting diabetes, its complications, and in guiding therapy.

URLhttp://dx.doi.org/10.1038/msb.2008.50
DOI10.1038/msb.2008.50
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/18682704?dopt=Abstract

Alternate JournalMol. Syst. Biol.
PubMed ID18682704
PubMed Central IDPMC2538910
Grant ListN01-HC-25195 / HC / NHLBI NIH HHS / United States
R01 HL083197 / HL / NHLBI NIH HHS / United States
R01 HL083141 / HL / NHLBI NIH HHS / United States
R01-HL-083197 / HL / NHLBI NIH HHS / United States
M01 RR001066 / RR / NCRR NIH HHS / United States
R01 HL086875 / HL / NHLBI NIH HHS / United States
MO1-RR01066 / RR / NCRR NIH HHS / United States
U01HL083141 / HL / NHLBI NIH HHS / United States
N01HC25195 / HL / NHLBI NIH HHS / United States
R01-HL-086875 / HL / NHLBI NIH HHS / United States