TY - JOUR AU - Zoungas S. AU - Wong G. AU - Poulter N. AU - Kingwell B. AU - Sullivan D. AU - Woodward Mark AU - Nestel P. AU - Williams B. AU - Hillis G. AU - Marre M. AU - Simes J. AU - Tonkin A. AU - Rodgers A AU - Chalmers J. AU - Alshehry Z. AU - Mundra P. AU - Barlow C. AU - Mellett N. AU - McConville M. AU - Barnes E. AU - Meikle P. AU - Neal Bruce AB -

BACKGROUND: -Clinical lipid measurements do not show the full complexity of the altered lipid metabolism associated with diabetes 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 ionisation-tandem mass spectrometry on a case-cohort (n=3,779) subset from the ADVANCE (Action in Diabetes and Vascular disease: preterAx and diamicroN-MR Controlled Evaluation) trial. The-case cohort was 61% male with a mean age of 67. All participants had type 2 diabetes mellitus with one or more 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 (non-fatal myocardial infarction, non-fatal stroke and cardiovascular death) and cardiovascular death during a five year follow-up period. Multivariable models combining traditional risk factors with lipid species were optimized using the Akaike information criteria. C-statistics and net reclassification indices (NRI) were calculated within a five-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% CI, 0.678-0.682) to 0.700 (95% CI, 0.698-0.702, p<0.0001) with a corresponding continuous NRI of 0.227 (95% CI, 0.219-0.235). The prediction of cardiovascular death was improved with the incorporation of 4 lipid species to the base model, showing an increase in the C-statistic from 0.740 (95% CI, 0.738-0.742) to 0.760 (95% CI, 0.757-0.762, p<0.0001) and a continuous NRI of 0.328 (95%CI, 0.317-0.339). The results were validated in a subcohort with type 2 diabetes (n=511) from the LIPID (The Long-Term Intervention with Pravastatin in Ischaemic Disease) trial. CONCLUSIONS: -The improvement in the prediction of cardiovascular events, above traditional risk factors, demonstrates the potential of plasma lipid species as biomarkers for cardiovascular risk stratification in diabetes. Clinical Trial Registration-https://clinicaltrials.gov; Identifier: NCT00145925.

AD - Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia; King Fahad Medical City, Riyadh, Saudi Arabia; Department of Biochemistry and Molecular Biology, The University of Melbourne, VIC, Australia.
Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia.
Department of Biochemistry and Molecular Biology, The University of Melbourne, VIC, Australia.
The NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
The Royal Prince Alfred Hospital, Sydney, NSW, Australia.
Hopital Bichat-Claude Bernard and Universite Paris 7, Paris, France.
The George Institute for Global Health, Sydney, NSW, Australia.
University College London and the National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK.
School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia & The George Institute for Global Health, Sydney, NSW, Australia.
The George Institute for Global Health, Sydney, NSW, Australia & Department of Cardiology, Royal Perth Hospital, University of Western Australia, WA, Australia.
The George Institute for Global Health, Sydney, NSW, Australia; The George Institute for Global Health, University of Oxford, UK; Department of Epidemiology, Johns Hopkins University, Baltimore, MD.
Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia & Department of Biochemistry and Molecular Biology, The University of Melbourne, VIC, Australia peter.meikle@bakeridi.edu.au. AN - 27756783 BT - Circulation CN - [IF}]: 14.430 DP - NLM ET - 2016/10/21 J2 - Circulation LA - Eng LB - AUS
CDV
PROF
FP
FY17 N1 - Alshehry, Zahir H
Mundra, Piyushkumar A
Barlow, Christopher K
Mellett, Natalie A
Wong, Gerard
McConville, Malcolm J
Simes, John
Tonkin, Andrew M
Sullivan, David R
Barnes, Elizabeth H
Nestel, Paul J
Kingwell, Bronwyn A
Marre, Michel
Neal, Bruce
Poulter, Neil R
Rodgers, Anthony
Williams, Bryan
Zoungas, Sophia
Hillis, Graham S
Chalmers, John
Woodward, Mark
Meikle, Peter J
United States
Circulation. 2016 Oct 18. pii: CIRCULATIONAHA.116.023233. N2 -

BACKGROUND: -Clinical lipid measurements do not show the full complexity of the altered lipid metabolism associated with diabetes 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 ionisation-tandem mass spectrometry on a case-cohort (n=3,779) subset from the ADVANCE (Action in Diabetes and Vascular disease: preterAx and diamicroN-MR Controlled Evaluation) trial. The-case cohort was 61% male with a mean age of 67. All participants had type 2 diabetes mellitus with one or more 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 (non-fatal myocardial infarction, non-fatal stroke and cardiovascular death) and cardiovascular death during a five year follow-up period. Multivariable models combining traditional risk factors with lipid species were optimized using the Akaike information criteria. C-statistics and net reclassification indices (NRI) were calculated within a five-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% CI, 0.678-0.682) to 0.700 (95% CI, 0.698-0.702, p<0.0001) with a corresponding continuous NRI of 0.227 (95% CI, 0.219-0.235). The prediction of cardiovascular death was improved with the incorporation of 4 lipid species to the base model, showing an increase in the C-statistic from 0.740 (95% CI, 0.738-0.742) to 0.760 (95% CI, 0.757-0.762, p<0.0001) and a continuous NRI of 0.328 (95%CI, 0.317-0.339). The results were validated in a subcohort with type 2 diabetes (n=511) from the LIPID (The Long-Term Intervention with Pravastatin in Ischaemic Disease) trial. CONCLUSIONS: -The improvement in the prediction of cardiovascular events, above traditional risk factors, demonstrates the potential of plasma lipid species as biomarkers for cardiovascular risk stratification in diabetes. Clinical Trial Registration-https://clinicaltrials.gov; Identifier: NCT00145925.

PY - 2016 SN - 1524-4539 (Electronic)
0009-7322 (Linking) ST - CirculationCirculation T2 - Circulation TI - Plasma Lipidomic Profiles Improve Upon Traditional Risk Factors for the Prediction of Cardiovascular Events in Type 2 Diabetes Y2 - FY17 ER -