Association of a peripheral blood metabolic profile with coronary artery disease and risk of subsequent cardiovascular events.
BACKGROUND
Molecular tools may provide insight into cardiovascular risk. We assessed whether metabolites discriminate coronary artery disease (CAD) and predict risk of cardiovascular events.


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.
Shah
Svati H
SH
Department of Medicine, Duke University, Durham, NC, USA. svati.shah@duke.edu <svati.shah@duke.edu>
Bain
James R
JR
Muehlbauer
Michael J
MJ
Stevens
Robert D
RD
Crosslin
David R
DR
Haynes
Carol
C
Dungan
Jennifer
J
Newby
L Kristin
LK
Hauser
Elizabeth R
ER
Ginsburg
Geoffrey S
GS
Newgard
Christopher B
CB
Kraus
William E
WE
D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000097:blood; D003324:Coronary Artery Disease / Q000235:genetics* / Q000378:metabolism; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D013058:Mass Spectrometry; D055442:Metabolome; D008875:Middle Aged; D009203:Myocardial Infarction / Q000150:complications / Q000235:genetics; D016017:Odds Ratio; D025341:Principal Component Analysis; D016016:Proportional Hazards Models; D012372:ROC Curve; D012307:Risk Factors
D015415:Biomarkers