Baseline metabolomic profiles predict cardiovascular events in patients at risk for coronary artery disease

Cardiovascular risk models remain incomplete. Small-molecule metabolites may reflect underlying disease and, as such, serve as novel biomarkers of cardiovascular risk. We studied 2,023 consecutive patients undergoing cardiac catheterization. Mass spectrometry profiling of 69 metabolites and lipid as...

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Bibliographic Details
Published in:The American heart journal Vol. 163; no. 5; pp. 844 - 850.e1
Main Authors: Shah, Svati H., Sun, Jie-Lena, Stevens, Robert D., Bain, James R., Muehlbauer, Michael J., Pieper, Karen S., Haynes, Carol, Hauser, Elizabeth R., Kraus, William E., Granger, Christopher B., Newgard, Christopher B., Califf, Robert M., Newby, L. Kristin
Format: Journal Article
Language:English
Published: New York, NY Elsevier Inc 01.05.2012
Mosby
Elsevier Limited
Subjects:
Adult
Age Distribution
Analysis of Variance
Atherosclerosis (general aspects, experimental research)
Biological and medical sciences
Biomarkers - blood
Blood and lymphatic vessels
Blood Chemical Analysis
Cardiac Catheterization - methods
Cardiac Catheterization - statistics & numerical data
Cardiology
Cardiology. Vascular system
Cardiovascular
Cardiovascular disease
Cardiovascular Diseases - diagnosis
Cardiovascular Diseases - epidemiology
Cardiovascular Diseases - metabolism
Cohort Studies
Confidence Intervals
Coronary Artery Disease - diagnosis
Coronary Artery Disease - epidemiology
Coronary Artery Disease - metabolism
Coronary heart disease
Female
Heart
Heart attacks
Humans
Lipids - blood
Male
Medical sciences
Metabolites
Metabolomics - methods
Middle Aged
Mortality
Multivariate Analysis
Predictive Value of Tests
Prevalence
Prognosis
Retrospective Studies
Risk Assessment
Severity of Illness Index
Sex Distribution
Stroke Volume
Survival Analysis
NRI
CI
GRACE
HR
IQR
MI
IDI
MURDOCK CV
PCA
Global Registry of Acute Coronary Events
myocardial infarction
net reclassification improvement
interquartile range
Measurement to Understand the Reclassification of Disease of Cabarrus and Kannapolis Cardiovascular Study
integrated discrimination index
hazard ratio
confidence interval
principal component analysis
Vascular disease
Human
Atherosclerosis
Risk factor
Patient
Cardiovascular disease
Circulatory system
Cardiology
Predictive factor
Coronary heart disease
Profile
ISSN:0002-8703, 1097-6744, 1097-6744
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Summary:Cardiovascular risk models remain incomplete. Small-molecule metabolites may reflect underlying disease and, as such, serve as novel biomarkers of cardiovascular risk. We studied 2,023 consecutive patients undergoing cardiac catheterization. Mass spectrometry profiling of 69 metabolites and lipid assessments were performed in fasting plasma. Principal component analysis reduced metabolites to a smaller number of uncorrelated factors. Independent relationships between factors and time-to-clinical events were assessed using Cox modeling. Clinical and metabolomic models were compared using log-likelihood and reclassification analyses. At median follow-up of 3.1 years, there were 232 deaths and 294 death/myocardial infarction (MI) events. Five of 13 metabolite factors were independently associated with mortality: factor 1 (medium-chain acylcarnitines: hazard ratio [HR] 1.12 [95% CI, 1.04-1.21], P = .005), factor 2 (short-chain dicarboxylacylcarnitines: HR 1.17 [1.05-1.31], P = .005), factor 3 (long-chain dicarboxylacylcarnitines: HR 1.14 [1.05-1.25], P = .002); factor 6 (branched-chain amino acids: HR 0.86 [0.75-0.99], P = .03), and factor 12 (fatty acids: HR 1.19 [1.06-1.35], P = .004). Three factors independently predicted death/MI: factor 2 (HR 1.11 [1.01-1.23], P = .04), factor 3 (HR 1.13 [1.04-1.22], P = .005), and factor 12 (HR 1.18 [1.05-1.32], P = .004). For mortality, 27% of intermediate-risk patients were correctly reclassified (net reclassification improvement 8.8%, integrated discrimination index 0.017); for death/MI model, 11% were correctly reclassified (net reclassification improvement 3.9%, integrated discrimination index 0.012). Metabolic profiles predict cardiovascular events independently of standard predictors.
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ISSN:0002-8703
1097-6744
1097-6744
DOI:10.1016/j.ahj.2012.02.005