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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Vydané v:	The American heart journal Ročník 163; číslo 5; s. 844 - 850.e1
Hlavní autori:	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
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York, NY Elsevier Inc 01.05.2012 Mosby Elsevier Limited
Predmet:	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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Popis
Shrnutí:	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.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23
ISSN:	0002-8703 1097-6744 1097-6744
DOI:	10.1016/j.ahj.2012.02.005