Large-scale plasma lipidomic profiling identifies lipids that predict cardiovascular events in secondary prevention

LIPID Study Investigators

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

BACKGROUND: Plasma lipidomic measures may enable improved prediction of cardiovascular outcomes in secondary prevention. The aim of this study is to determine the association of plasma lipidomic measurements with cardiovascular events and assess their potential to predict such events.

METHODS: Plasma lipids (n = 342) were measured in a retrospective subcohort (n = 5,991) of the LIPID study. Proportional hazards regression was used to identify lipids associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death) and cardiovascular death. Multivariable models adding lipid species to traditional risk factors were created using lipid ranking established from the Akaike information criterion within a 5-fold cross-validation framework. The results were tested on a diabetic case cohort from the ADVANCE study (n = 3,779).

RESULTS: Specific ceramide species, sphingolipids, phospholipids, and neutral lipids containing omega-6 fatty acids or odd-chain fatty acids were associated with future cardiovascular events (106 species) and cardiovascular death (139 species). The addition of 7 lipid species to a base model (11 conventional risk factors) resulted in an increase in the C-statistics from 0.629 (95% CI, 0.628-0.630) to 0.654 (95% CI, 0.653-0.656) for prediction of cardiovascular events and from 0.673 (95% CI, 0.671-0.675) to 0.727 (95% CI, 0.725-0.728) for prediction of cardiovascular death. Categorical net reclassification improvements for cardiovascular events and cardiovascular death were 0.083 (95% CI, 0.081-0.086) and 0.166 (95% CI, 0.162-0.170), respectively. Evaluation on the ADVANCE case cohort demonstrated significant improvement on the base models.

CONCLUSIONS: The improvement in the prediction of cardiovascular outcomes, above conventional risk factors, demonstrates the potential of plasma lipidomic profiles as biomarkers for cardiovascular risk stratification in secondary prevention.

FUNDING: Bristol-Myers Squibb, the National Health and Medical Research Council of Australia (grants 211086, 358395, and 1029754), and the Operational Infrastructure Support Program of the Victorian government of Australia.

Original languageEnglish
Article numbere121326
JournalJCI Insight
Volume3
Issue number17
DOIs
Publication statusPublished - 6 Sep 2018
Externally publishedYes

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Secondary Prevention
Lipids
Omega-6 Fatty Acids
Myocardial Infarction
Government Programs
Sphingolipids
Organized Financing
Ceramides
Biomedical Research
Phospholipids
Cohort Studies
Fatty Acids
Biomarkers
Health

Cite this

@article{c0b1c1b70f1648b79a87c75376a73ab6,
title = "Large-scale plasma lipidomic profiling identifies lipids that predict cardiovascular events in secondary prevention",
abstract = "BACKGROUND: Plasma lipidomic measures may enable improved prediction of cardiovascular outcomes in secondary prevention. The aim of this study is to determine the association of plasma lipidomic measurements with cardiovascular events and assess their potential to predict such events.METHODS: Plasma lipids (n = 342) were measured in a retrospective subcohort (n = 5,991) of the LIPID study. Proportional hazards regression was used to identify lipids associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death) and cardiovascular death. Multivariable models adding lipid species to traditional risk factors were created using lipid ranking established from the Akaike information criterion within a 5-fold cross-validation framework. The results were tested on a diabetic case cohort from the ADVANCE study (n = 3,779).RESULTS: Specific ceramide species, sphingolipids, phospholipids, and neutral lipids containing omega-6 fatty acids or odd-chain fatty acids were associated with future cardiovascular events (106 species) and cardiovascular death (139 species). The addition of 7 lipid species to a base model (11 conventional risk factors) resulted in an increase in the C-statistics from 0.629 (95{\%} CI, 0.628-0.630) to 0.654 (95{\%} CI, 0.653-0.656) for prediction of cardiovascular events and from 0.673 (95{\%} CI, 0.671-0.675) to 0.727 (95{\%} CI, 0.725-0.728) for prediction of cardiovascular death. Categorical net reclassification improvements for cardiovascular events and cardiovascular death were 0.083 (95{\%} CI, 0.081-0.086) and 0.166 (95{\%} CI, 0.162-0.170), respectively. Evaluation on the ADVANCE case cohort demonstrated significant improvement on the base models.CONCLUSIONS: The improvement in the prediction of cardiovascular outcomes, above conventional risk factors, demonstrates the potential of plasma lipidomic profiles as biomarkers for cardiovascular risk stratification in secondary prevention.FUNDING: Bristol-Myers Squibb, the National Health and Medical Research Council of Australia (grants 211086, 358395, and 1029754), and the Operational Infrastructure Support Program of the Victorian government of Australia.",
author = "{LIPID Study Investigators} and Mundra, {Piyushkumar A} and Barlow, {Christopher K} and Nestel, {Paul J} and Barnes, {Elizabeth H} and Adrienne Kirby and Peter Thompson and Sullivan, {David R} and Alshehry, {Zahir H} and Mellett, {Natalie A} and Kevin Huynh and Jayawardana, {Kaushala S} and Corey Giles and McConville, {Malcolm J} and Sophia Zoungas and Hillis, {Graham S} and John Chalmers and Mark Woodward and Gerard Wong and Kingwell, {Bronwyn A} and John Simes and Tonkin, {Andrew M} and Meikle, {Peter J}",
year = "2018",
month = "9",
day = "6",
doi = "10.1172/jci.insight.121326",
language = "English",
volume = "3",
journal = "JCI Insight",
issn = "2379-3708",
publisher = "AMER SOC CLINICAL INVESTIGATION INC",
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Large-scale plasma lipidomic profiling identifies lipids that predict cardiovascular events in secondary prevention. / LIPID Study Investigators.

In: JCI Insight, Vol. 3, No. 17, e121326, 06.09.2018.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Large-scale plasma lipidomic profiling identifies lipids that predict cardiovascular events in secondary prevention

AU - LIPID Study Investigators

AU - Mundra, Piyushkumar A

AU - Barlow, Christopher K

AU - Nestel, Paul J

AU - Barnes, Elizabeth H

AU - Kirby, Adrienne

AU - Thompson, Peter

AU - Sullivan, David R

AU - Alshehry, Zahir H

AU - Mellett, Natalie A

AU - Huynh, Kevin

AU - Jayawardana, Kaushala S

AU - Giles, Corey

AU - McConville, Malcolm J

AU - Zoungas, Sophia

AU - Hillis, Graham S

AU - Chalmers, John

AU - Woodward, Mark

AU - Wong, Gerard

AU - Kingwell, Bronwyn A

AU - Simes, John

AU - Tonkin, Andrew M

AU - Meikle, Peter J

PY - 2018/9/6

Y1 - 2018/9/6

N2 - BACKGROUND: Plasma lipidomic measures may enable improved prediction of cardiovascular outcomes in secondary prevention. The aim of this study is to determine the association of plasma lipidomic measurements with cardiovascular events and assess their potential to predict such events.METHODS: Plasma lipids (n = 342) were measured in a retrospective subcohort (n = 5,991) of the LIPID study. Proportional hazards regression was used to identify lipids associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death) and cardiovascular death. Multivariable models adding lipid species to traditional risk factors were created using lipid ranking established from the Akaike information criterion within a 5-fold cross-validation framework. The results were tested on a diabetic case cohort from the ADVANCE study (n = 3,779).RESULTS: Specific ceramide species, sphingolipids, phospholipids, and neutral lipids containing omega-6 fatty acids or odd-chain fatty acids were associated with future cardiovascular events (106 species) and cardiovascular death (139 species). The addition of 7 lipid species to a base model (11 conventional risk factors) resulted in an increase in the C-statistics from 0.629 (95% CI, 0.628-0.630) to 0.654 (95% CI, 0.653-0.656) for prediction of cardiovascular events and from 0.673 (95% CI, 0.671-0.675) to 0.727 (95% CI, 0.725-0.728) for prediction of cardiovascular death. Categorical net reclassification improvements for cardiovascular events and cardiovascular death were 0.083 (95% CI, 0.081-0.086) and 0.166 (95% CI, 0.162-0.170), respectively. Evaluation on the ADVANCE case cohort demonstrated significant improvement on the base models.CONCLUSIONS: The improvement in the prediction of cardiovascular outcomes, above conventional risk factors, demonstrates the potential of plasma lipidomic profiles as biomarkers for cardiovascular risk stratification in secondary prevention.FUNDING: Bristol-Myers Squibb, the National Health and Medical Research Council of Australia (grants 211086, 358395, and 1029754), and the Operational Infrastructure Support Program of the Victorian government of Australia.

AB - BACKGROUND: Plasma lipidomic measures may enable improved prediction of cardiovascular outcomes in secondary prevention. The aim of this study is to determine the association of plasma lipidomic measurements with cardiovascular events and assess their potential to predict such events.METHODS: Plasma lipids (n = 342) were measured in a retrospective subcohort (n = 5,991) of the LIPID study. Proportional hazards regression was used to identify lipids associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death) and cardiovascular death. Multivariable models adding lipid species to traditional risk factors were created using lipid ranking established from the Akaike information criterion within a 5-fold cross-validation framework. The results were tested on a diabetic case cohort from the ADVANCE study (n = 3,779).RESULTS: Specific ceramide species, sphingolipids, phospholipids, and neutral lipids containing omega-6 fatty acids or odd-chain fatty acids were associated with future cardiovascular events (106 species) and cardiovascular death (139 species). The addition of 7 lipid species to a base model (11 conventional risk factors) resulted in an increase in the C-statistics from 0.629 (95% CI, 0.628-0.630) to 0.654 (95% CI, 0.653-0.656) for prediction of cardiovascular events and from 0.673 (95% CI, 0.671-0.675) to 0.727 (95% CI, 0.725-0.728) for prediction of cardiovascular death. Categorical net reclassification improvements for cardiovascular events and cardiovascular death were 0.083 (95% CI, 0.081-0.086) and 0.166 (95% CI, 0.162-0.170), respectively. Evaluation on the ADVANCE case cohort demonstrated significant improvement on the base models.CONCLUSIONS: The improvement in the prediction of cardiovascular outcomes, above conventional risk factors, demonstrates the potential of plasma lipidomic profiles as biomarkers for cardiovascular risk stratification in secondary prevention.FUNDING: Bristol-Myers Squibb, the National Health and Medical Research Council of Australia (grants 211086, 358395, and 1029754), and the Operational Infrastructure Support Program of the Victorian government of Australia.

U2 - 10.1172/jci.insight.121326

DO - 10.1172/jci.insight.121326

M3 - Article

VL - 3

JO - JCI Insight

JF - JCI Insight

SN - 2379-3708

IS - 17

M1 - e121326

ER -