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J Clin Invest DOI:10.1172/JCI44442

Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humans.

Publication TypeJournal Article
Year of Publication2011
AuthorsRhee, EP, Cheng, S, Larson, MG, Walford, GA, Lewis, GD, McCabe, E, Yang, E, Farrell, L, Fox, CS, O'Donnell, CJ, Carr, SA, Vasan, RS, Florez, JC, Clish, CB, Wang, TJ, Gerszten, RE
JournalJ Clin Invest
Volume121
Issue4
Pages1402-11
Date Published2011 Apr
ISSN1558-8238
KeywordsAdult, Aged, Biomarkers, Case-Control Studies, Diabetes Mellitus, Type 2, Dyslipidemias, Exercise Test, Female, Glucose Tolerance Test, Humans, Insulin, Insulin Resistance, Lipids, Male, Middle Aged, Molecular Structure, Predictive Value of Tests, Risk Factors, Triglycerides
Abstract

Dyslipidemia is an independent risk factor for type 2 diabetes, although exactly which of the many plasma lipids contribute to this remains unclear. We therefore investigated whether lipid profiling can inform diabetes prediction by performing liquid chromatography/mass spectrometry-based lipid profiling in 189 individuals who developed type 2 diabetes and 189 matched disease-free individuals, with over 12 years of follow up in the Framingham Heart Study. We found that lipids of lower carbon number and double bond content were associated with an increased risk of diabetes, whereas lipids of higher carbon number and double bond content were associated with decreased risk. This pattern was strongest for triacylglycerols (TAGs) and persisted after multivariable adjustment for age, sex, BMI, fasting glucose, fasting insulin, total triglycerides, and HDL cholesterol. A combination of 2 TAGs further improved diabetes prediction. To explore potential mechanisms that modulate the distribution of plasma lipids, we performed lipid profiling during oral glucose tolerance testing, pharmacologic interventions, and acute exercise testing. Levels of TAGs associated with increased risk for diabetes decreased in response to insulin action and were elevated in the setting of insulin resistance. Conversely, levels of TAGs associated with decreased diabetes risk rose in response to insulin and were poorly correlated with insulin resistance. These studies identify a relationship between lipid acyl chain content and diabetes risk and demonstrate how lipid profiling could aid in clinical risk assessment.

URLhttp://dx.doi.org/10.1172/JCI44442
DOI10.1172/JCI44442
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/21403394?dopt=Abstract

Alternate JournalJ. Clin. Invest.
PubMed ID21403394
PubMed Central IDPMC3069773
Grant ListN01-HC-25195 / HC / NHLBI NIH HHS / United States
R01-DK-HL081572 / DK / NIDDK NIH HHS / United States
R01 DK081572 / DK / NIDDK NIH HHS / United States
R01 HL081572 / HL / NHLBI NIH HHS / United States
K23 HL091106 / HL / NHLBI NIH HHS / United States
R01 DK088214 / DK / NIDDK NIH HHS / United States
T32-DK-00754023 / DK / NIDDK NIH HHS / United States
N01HC25195 / HL / NHLBI NIH HHS / United States