Association of a Peripheral Blood Metabolic Profile With Coronary Artery Disease and Risk of Subsequent Cardiovascular Events

Abstract

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 ("eventreplication" group; nϭ63 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 Pϭ0.002, replication Pϭ0.01), and 1 comprising urea cycle metabolites (factor 9, initial Pϭ0.0004, replication Pϭ0.01). 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; Pϭ0.02; factor 9, OR, 0.67; 95% CI, 0.52 to 0.87; Pϭ0.003) and replication (factor 4, OR, 1.43; 95% CI, 1.07 to 1.91; Pϭ0.02; factor 9, OR, 0.66; 95% CI, 0.48 to 0.91; Pϭ0.01) groups. A factor composed of dicarboxylacylcarnitines predicted death/myocardial infarction (event group hazard ratio 2.17; 95% CI, 1.23 to 3.84; Pϭ0.007) and was associated with cardiovascular events in the event-replication group (OR, 1.52; 95% CI, 1.08 to 2.14; Pϭ0.01). Conclusions-Metabolite profiles are associated with CAD and subsequent cardiovascular events.(Circ Cardiovasc Genet. 2010;3:207-214.)Key Words: metabolism Ⅲ risk factors Ⅲ coronary artery disease C oronary artery disease (CAD) is the leading cause of death in industrialized countries. Many accepted risk factors for CAD are metabolic. However, there remains an incomplete mechanistic understanding of CAD risk and equally important, a need to refine our ability to identify individuals at highest risk of cardiovascular events. Given the complex nature of CAD, evaluation with more comprehensive tools may improve risk stratification and enhance our understanding of the disease process. Metabolomics, the study of small-molecule metabolites, may be particularly useful for the diagnosis of human disease. Studies have demonstrated heritability of metabolites in mice, 1 and we have shown that metabolite profiles are heritable in human families with early-onset CAD, 2 suggesting that the known heritability of CAD may be mediated at least in part through metabolic components measurable in peripheral blood. Clinical Perspective on p 214In this study, we performed quantitative profiling of 69 metabolites, including acylcarnitine species (byproducts of mitochondrial fatty aci...

Metabolomic Profiling Identifies Novel Circulating Biomarkers of Mitochondrial Dysfunction Differentially Elevated in Heart Failure With Preserved Versus Reduced Ejection Fraction: Evidence for Shared Metabolic Impairments in Clinical Heart Failure

“…Fourteen PCA‐derived metabolite factors were identified, clustering in biologically related groupings similar to our previous studies (detailed PCA results in Data S5; Table S3) 30, 46. In the basic model, omnibus ANCOVA identified 2 metabolite factors significant at the Bonferroni‐corrected significance threshold ( P< 0.0036); both were composed of acylcarnitines of varying chain length (Table 2).…”

“…In addition, we studied 3 major groups along the HF spectrum; used large cohort sizes compared with previous HF metabolomic analyses; used a targeted metabolomic approach permitting metabolite quantitation; and used state‐of‐the‐art assessment and analytic techniques 18, 30, 31, 32…”

“…Absolute quantification of the metabolites was performed using stable isotope dilution as we have done previously 30, 31. Three conventional metabolites (ketones, nonesterified fatty acids, and 3‐hydroxybutyrate) were assayed using a Beckman‐Coulter DXC600 analyzer and reagents from Wako Chemicals (Richmond, VA).…”

“…This reduced the full set of 63 metabolites into 14 uncorrelated factors, which altogether explained 44.6% of the data variance. Individual metabolites with absolute value of factor load ≥0.4 are reported as composing a given factor, as is commonly done based on convention 30, 41, 42, 43. To facilitate factor comparisons across groups, general linear models were constructed: “basic” models (adjusted for age, race, and sex) and “fully adjusted” models (adjusted for age, race, sex, body mass index [BMI], diabetes mellitus, hypertension, dyslipidemia, smoking, glomerular filtration rate [GFR], batch, and number of diseased coronary arteries [number of epicardial vessels with ≥75% stenosis graded by 2 observers at the time of catheterization]).…”

Regulation of PP2Cm expression by miRNA-204/211 and miRNA-22 in mouse and human cells

“…Ppm1k-deficient mice develop impaired BCAA npg catabolism and elevated plasma concentrations of BCAA and BCKA [7] . Recently, disrupted BCAA homeostasis has been linked to metabolic, neurological, and cardiovascular diseases [8][9][10] , although the role of PP2Cm in the pathogenesis of these diseases remains to be established.…”