Metabolite Profiling Identifies Pathways Associated With Metabolic Risk in Humans

Susan Cheng(Broad Institute), Eugene P. Rhee(Broad Institute), Martin G. Larson(Broad Institute), Gregory D. Lewis(Broad Institute), Elizabeth L. McCabe(Broad Institute), Dongxiao Shen(Broad Institute), Melinda J. Palma(Broad Institute), Lee D. Roberts(Broad Institute), André Dejam(Broad Institute), Amanda L. Souza(Broad Institute), Amy Deik(Broad Institute), Martin Magnusson(Broad Institute), Caroline S. Fox(Broad Institute), Christopher J. O’Donnell(Broad Institute), Ramachandran S. Vasan(Broad Institute), Olle Melander(Broad Institute), Clary B. Clish(Broad Institute), Robert E. Gerszten(Broad Institute), Thomas J. Wang(Broad Institute)
Circulation
April 12, 2012
Cited by 593Open Access
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Abstract

BACKGROUND: Although metabolic risk factors are known to cluster in individuals who are prone to developing diabetes mellitus and cardiovascular disease, the underlying biological mechanisms remain poorly understood. METHODS AND RESULTS: To identify pathways associated with cardiometabolic risk, we used liquid chromatography/mass spectrometry to determine the plasma concentrations of 45 distinct metabolites and to examine their relation to cardiometabolic risk in the Framingham Heart Study (FHS; n=1015) and the Malmö Diet and Cancer Study (MDC; n=746). We then interrogated significant findings in experimental models of cardiovascular and metabolic disease. We observed that metabolic risk factors (obesity, insulin resistance, high blood pressure, and dyslipidemia) were associated with multiple metabolites, including branched-chain amino acids, other hydrophobic amino acids, tryptophan breakdown products, and nucleotide metabolites. We observed strong associations of insulin resistance traits with glutamine (standardized regression coefficients, -0.04 to -0.22 per 1-SD change in log-glutamine; P<0.001), glutamate (0.05 to 0.14; P<0.001), and the glutamine-to-glutamate ratio (-0.05 to -0.20; P<0.001) in the discovery sample (FHS); similar associations were observed in the replication sample (MDC). High glutamine-to-glutamate ratio was associated with lower risk of incident diabetes mellitus in FHS (odds ratio, 0.79; adjusted P=0.03) but not in MDC. In experimental models, administration of glutamine in mice led to both increased glucose tolerance (P=0.01) and decreased blood pressure (P<0.05). CONCLUSIONS: Biochemical profiling identified circulating metabolites not previously associated with metabolic traits. Experimentally interrogating one of these pathways demonstrated that excess glutamine relative to glutamate, resulting from exogenous administration, is associated with reduced metabolic risk in mice.


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