Open AccessMetabolic profiling of the human response to a glucose challenge reveals distinct axes of insulin sensitivity
Author(s) -
Shaham Oded,
Wei Ru,
Wang Thomas J,
Ricciardi Catherine,
Lewis Gregory D,
Vasan Ramachandran S,
Carr Steven A,
Thadhani Ravi,
Gerszten Robert E,
Mootha Vamsi K
Publication year - 2008
Publication title -
molecular systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.523
H-Index - 148
ISSN - 1744-4292
DOI - 10.1038/msb.2008.50
Subject(s) - lipolysis , insulin , biology , medicine , endocrinology , anabolism , insulin resistance , glucose homeostasis , catabolism , metabolomics , carbohydrate metabolism , metabolite , glycolysis , metabolism , bioinformatics , adipose tissue
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.