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

Zahir H. Alshehry, Piyushkumar A Mundra, Christopher K. Barlow, Natalie A Mellett, Gerard Wong, Malcolm J McConville, R John Simes, Andrew M. Tonkin, David R Sullivan, Elizabeth Helen Barnes, Paul John Nestel, Bronwyn A. Kingwell, Michel Marre, Bruce Neal, Neil R Poulter, Anthony Rodgers, Bryan Williams, Sophia Zoungas, Graham S. Hillis, John Chalmers & 2 others Mark Woodward, Peter J. Meikle

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Abstract

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<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 into 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 net reclassification index of 0.328 (95% CI, 0.317-0.339). The results were validated in a subcohort with type 2 diabetes mellitus (n=511) from the LIPID trial (Long-Term Intervention With Pravastatin in Ischemic Disease). 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 mellitus. Clinical Trial Registration: URL: https://clinicaltrials.gov. Unique identifier: NCT00145925.

Original languageEnglish
Pages (from-to)1637-1650
Number of pages14
JournalCirculation
Volume134
Issue number21
DOIs
Publication statusPublished - 22 Nov 2016

Keywords

  • biomarker
  • cardiovascular outcomes
  • diabetes mellitus
  • lipids
  • mass spectrometry

Cite this

Alshehry, Zahir H. ; Mundra, Piyushkumar A ; Barlow, Christopher K. ; Mellett, Natalie A ; Wong, Gerard ; McConville, Malcolm J ; Simes, R John ; Tonkin, Andrew M. ; Sullivan, David R ; Barnes, Elizabeth Helen ; Nestel, Paul John ; 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. / Plasma Lipidomic Profiles Improve on Traditional Risk Factors for the Prediction of Cardiovascular Events in Type 2 Diabetes Mellitus. In: Circulation. 2016 ; Vol. 134, No. 21. pp. 1637-1650.
@article{d6f2863012974b03bc43d52d9d9abeb2,
title = "Plasma Lipidomic Profiles Improve on Traditional Risk Factors for the Prediction of Cardiovascular Events in Type 2 Diabetes Mellitus",
abstract = "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<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 into 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 net reclassification index of 0.328 (95{\%} CI, 0.317-0.339). The results were validated in a subcohort with type 2 diabetes mellitus (n=511) from the LIPID trial (Long-Term Intervention With Pravastatin in Ischemic Disease). 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 mellitus. Clinical Trial Registration: URL: https://clinicaltrials.gov. Unique identifier: NCT00145925.",
keywords = "biomarker, cardiovascular outcomes, diabetes mellitus, lipids, mass spectrometry",
author = "Alshehry, {Zahir H.} and Mundra, {Piyushkumar A} and Barlow, {Christopher K.} and Mellett, {Natalie A} and Gerard Wong and McConville, {Malcolm J} and Simes, {R John} and Tonkin, {Andrew M.} and Sullivan, {David R} and Barnes, {Elizabeth Helen} and Nestel, {Paul John} and Kingwell, {Bronwyn A.} and Michel Marre and Bruce Neal and Poulter, {Neil R} and Anthony Rodgers and Bryan Williams and Sophia Zoungas and Hillis, {Graham S.} and John Chalmers and Mark Woodward and Meikle, {Peter J.}",
year = "2016",
month = "11",
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doi = "10.1161/CIRCULATIONAHA.116.023233",
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journal = "Circulation",
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publisher = "Am Heart Assoc",
number = "21",

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Alshehry, ZH, Mundra, PA, Barlow, CK, Mellett, NA, Wong, G, McConville, MJ, Simes, RJ, Tonkin, AM, Sullivan, DR, Barnes, EH, Nestel, PJ, Kingwell, BA, Marre, M, Neal, B, Poulter, NR, Rodgers, A, Williams, B, Zoungas, S, Hillis, GS, Chalmers, J, Woodward, M & Meikle, PJ 2016, 'Plasma Lipidomic Profiles Improve on Traditional Risk Factors for the Prediction of Cardiovascular Events in Type 2 Diabetes Mellitus', Circulation, vol. 134, no. 21, pp. 1637-1650. https://doi.org/10.1161/CIRCULATIONAHA.116.023233

Plasma Lipidomic Profiles Improve on Traditional Risk Factors for the Prediction of Cardiovascular Events in Type 2 Diabetes Mellitus. / Alshehry, Zahir H.; Mundra, Piyushkumar A; Barlow, Christopher K.; Mellett, Natalie A; Wong, Gerard; McConville, Malcolm J; Simes, R John; Tonkin, Andrew M.; Sullivan, David R; Barnes, Elizabeth Helen; Nestel, Paul John; 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.

In: Circulation, Vol. 134, No. 21, 22.11.2016, p. 1637-1650.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Plasma Lipidomic Profiles Improve on Traditional Risk Factors for the Prediction of Cardiovascular Events in Type 2 Diabetes Mellitus

AU - Alshehry, Zahir H.

AU - Mundra, Piyushkumar A

AU - Barlow, Christopher K.

AU - Mellett, Natalie A

AU - Wong, Gerard

AU - McConville, Malcolm J

AU - Simes, R John

AU - Tonkin, Andrew M.

AU - Sullivan, David R

AU - Barnes, Elizabeth Helen

AU - Nestel, Paul John

AU - Kingwell, Bronwyn A.

AU - Marre, Michel

AU - Neal, Bruce

AU - Poulter, Neil R

AU - Rodgers, Anthony

AU - Williams, Bryan

AU - Zoungas, Sophia

AU - Hillis, Graham S.

AU - Chalmers, John

AU - Woodward, Mark

AU - Meikle, Peter J.

PY - 2016/11/22

Y1 - 2016/11/22

N2 - 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<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 into 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 net reclassification index of 0.328 (95% CI, 0.317-0.339). The results were validated in a subcohort with type 2 diabetes mellitus (n=511) from the LIPID trial (Long-Term Intervention With Pravastatin in Ischemic Disease). 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 mellitus. Clinical Trial Registration: URL: https://clinicaltrials.gov. Unique identifier: NCT00145925.

AB - 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<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 into 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 net reclassification index of 0.328 (95% CI, 0.317-0.339). The results were validated in a subcohort with type 2 diabetes mellitus (n=511) from the LIPID trial (Long-Term Intervention With Pravastatin in Ischemic Disease). 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 mellitus. Clinical Trial Registration: URL: https://clinicaltrials.gov. Unique identifier: NCT00145925.

KW - biomarker

KW - cardiovascular outcomes

KW - diabetes mellitus

KW - lipids

KW - mass spectrometry

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