Association of a peripheral blood metabolic profile with coronary artery disease and risk of subsequent cardiovascular events.
Journal Article (Journal Article)
BACKGROUND: Molecular tools may provide insight into cardiovascular risk. We assessed whether metabolites discriminate coronary artery disease (CAD) and predict risk of cardiovascular events. METHODS AND RESULTS: We performed mass-spectrometry-based profiling of 69 metabolites in subjects from the CATHGEN biorepository. To evaluate discriminative capabilities of metabolites for CAD, 2 groups were profiled: 174 CAD cases and 174 sex/race-matched controls ("initial"), and 140 CAD cases and 140 controls ("replication"). To evaluate the capability of metabolites to predict cardiovascular events, cases were combined ("event" group); of these, 74 experienced death/myocardial infarction during follow-up. A third independent group was profiled ("event-replication" group; n=63 cases with cardiovascular events, 66 controls). Analysis included principal-components analysis, linear regression, and Cox proportional hazards. Two principal components analysis-derived factors were associated with CAD: 1 comprising branched-chain amino acid metabolites (factor 4, initial P=0.002, replication P=0.01), and 1 comprising urea cycle metabolites (factor 9, initial P=0.0004, replication P=0.01). In multivariable regression, these factors were independently associated with CAD in initial (factor 4, odds ratio [OR], 1.36; 95% CI, 1.06 to 1.74; P=0.02; factor 9, OR, 0.67; 95% CI, 0.52 to 0.87; P=0.003) and replication (factor 4, OR, 1.43; 95% CI, 1.07 to 1.91; P=0.02; factor 9, OR, 0.66; 95% CI, 0.48 to 0.91; P=0.01) groups. A factor composed of dicarboxylacylcarnitines predicted death/myocardial infarction (event group hazard ratio 2.17; 95% CI, 1.23 to 3.84; P=0.007) and was associated with cardiovascular events in the event-replication group (OR, 1.52; 95% CI, 1.08 to 2.14; P=0.01). CONCLUSIONS: Metabolite profiles are associated with CAD and subsequent cardiovascular events.
Full Text
Duke Authors
- Bain, James R.
- Ginsburg, Geoffrey Steven
- Hauser, Elizabeth Rebecca
- Kraus, William Erle
- Newby, Laura Kristin
- Newgard, Christopher Bang
- Shah, Svati Hasmukh
- Stevens, Robert David
Cited Authors
- Shah, SH; Bain, JR; Muehlbauer, MJ; Stevens, RD; Crosslin, DR; Haynes, C; Dungan, J; Newby, LK; Hauser, ER; Ginsburg, GS; Newgard, CB; Kraus, WE
Published Date
- April 2010
Published In
Volume / Issue
- 3 / 2
Start / End Page
- 207 - 214
PubMed ID
- 20173117
Electronic International Standard Serial Number (EISSN)
- 1942-3268
Digital Object Identifier (DOI)
- 10.1161/CIRCGENETICS.109.852814
Language
- eng
Conference Location
- United States