Document Name and Accession

Document Name: Metabolomics - Risk Factor Study: Gas Chromatography/Mass Spec - BMI/Lipids/Glucose Factorial Design, Offspring Cohort Exam 8, Generation 3 Cohort Exam 1: Description
Document Accession: phd004306.1

Document

View pdf copy of original document

Link to associated tableMetabolomics - Risk Factor Study: Gas Chromatography/Mass Spec - BMI/Lipids/Glucose Factorial Design, Offspring Cohort Exam 8, Generation 3 Cohort Exam 1: Description

Title/nature of data: Metabolomic Signatures of Metabolic Risk Factors


Study description

Objective: We characterized metabolomic derangements of three metabolic risk factors: obesity, dyslipidemia, and dysglycemia.

Methods: 650 participants from the Framingham Study were sampled from high vs. low strata of body mass index, lipids, and glucose. We conducted targeted gas chromatography-mass spectrometry (GC/MS) on fasting plasma samples. With generalized linear mixed models, we identified biomarkers that differed in their effects on obesity, dyslipidemia, or dysglycemia at p< 4.2 X10-4 (0.05/120). External replication was conducted in an independent sample of 670 participants from the BioImage Study.

Results: Highly significant main effects were noted for obesity (glutamic acid, sitosterol, uric acid), dyslipidemia (sphingomyelins, glutamic acid, lactic acid), and dysglycemia (fructose, 2-hydroxybutanoic acid, aminomalonic acid). Three metabolites (glutamic acid, lactic acid, and sphingomyelin [d18:1/17:0]) were associated with all three metabolic risk factors (p<0.001). We then carried forward 37 metabolites, of which nine for obesity, 13 for dyslipidemia, and seven for dysglycemia had p<0.001 in the replication sample. Of these 37 metabolites, glutamic acid and sitosterol were significant at p<0.001 across all three traits.

Conclusions: We identified multiple biomarkers of metabolic risk factors and identified a glutamate-related metabotype that included dysregulated transaminase reactions. Understanding the pathways represented by our results may help unravel molecular derangements contributing to metabolic syndrome and its risk factors.

Relevant Publications: (please add lines as necessary)

Reference (include Title, Author, etc)Pubmed ID (if available)
Cheng, S., Rhee, E.P., Larson, M.G., Lewis, G.D., McCabe, E.L., Shen, D., Palma, M.J., Roberts, L.D., Dejam, A., Souza, A.L., et al. Metabolite profiling identifies pathways associated with metabolic risk in humans. Circulation 125:2222-2231
Wang, T.J., Larson, M.G., Vasan, R.S., Cheng, S., Rhee, E.P., McCabe, E., Lewis, G.D., Fox, C.S., Jacques, P.F., Fernandez, C., et al. Metabolite profiles and the risk of developing diabetes. Nat Med 17:448-453
Muntendam, P., McCall, C., Sanz, J., Falk, E., and Fuster, V. The BioImage Study: novel approaches to risk assessment in the primary prevention of atherosclerotic cardiovascular disease--study design and objectives. Am Heart J 160:49-57 e41.

Study attribution: (please add lines as necessary)

HeaderNameAffiliation
Principal InvestigatorDaniel LevyNIH/NHLBI
Principal InvestigatorMartin LarsonBoston University, School of Mathematics and Statistics
Funding Source*FHS contract supplement, NHLBI Intramural FundingNational Heart, Lung and Blood Institute
*A necessary field

Acknowledgements:

The Framingham Heart Study is funded by NIH contract N01-HC-25195. This study was made possible by a CRADA between BG Medicine, Inc., Boston University (M. Larson, PI), and the National Heart Lung, and Blood Institute (D. Levy, PI). This project also was supported by the Intramural Research Program of the National Heart, Lung, and Blood Institute, National Institutes of Health.