Plasma Lipidomic Profiles Improve on Traditional Risk Factors for the Prediction of Cardiovascular Events in Type 2 Diabetes Mellitus

Z.H. Alshehry, P.A. Mundra, C.K. Barlow, N.A. Mellett, G. Wong, M.J. Mcconville, J. Simes, A.M. Tonkin, D.R. Sullivan, E.H. Barnes, P.J. Nestel, B.A. Kingwell, M. Marre, B. Neal, N.R. Poulter, A. Rodgers, B. Williams, S. Zoungas, Graham S. Hillis, J. ChalmersM. Woodward, P.J. Meikle

    Research output: Contribution to journalArticle

    101 Citations (Scopus)


    © 2016 American Heart Association, Inc.
    Background: Clinical lipid measurements do not show the full complexity of the altered lipid metabolism associated with diabetes mellitus or cardiovascular disease. Lipidomics enables the assessment of hundreds of lipid species as potential markers for disease risk. Methods: Plasma lipid species (310) were measured by a targeted lipidomic analysis with liquid chromatography electrospray ionization-tandem mass spectrometry on a case-cohort (n=3779) subset from the ADVANCE trial (Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation). The case-cohort was 61% male with a mean age of 67 years. All participants had type 2 diabetes mellitus with ≥1 additional cardiovascular risk factors, and 35% had a history of macrovascular disease. Weighted Cox regression was used to identify lipid species associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, and cardiovascular death) and cardiovascular death during a 5-year follow-up period. Multivariable models combining traditional risk factors with lipid species were optimized with the Akaike information criteria. C statistics and NRIs were calculated within a 5-fold cross-validation framework. Results: Sphingolipids, phospholipids (including lyso- and ether- species), cholesteryl esters, and glycerolipids were associated with future cardiovascular events and cardiovascular death. The addition of 7 lipid species to a base model (14 traditional risk factors and medications) to predict cardiovascular events increased the C statistic from 0.680 (95% confidence interval [CI], 0.678-0.682) to 0.700 (95% CI, 0.698-0.702; P
    Original languageEnglish
    Pages (from-to)1637-1650
    Issue number21
    Early online date8 Oct 2016
    Publication statusPublished - 22 Nov 2016


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