Sayanti Bhattacharya1, Christopher B Granger2, Damian Craig3, Carol Haynes4, James Bain5, Robert D Stevens6, Elizabeth R Hauser7, Christopher B Newgard8, William E Kraus9, L Kristin Newby10, Svati H Shah11. 1. Duke Global Health Institute, Durham, NC, USA; Duke Institute of Molecular Physiology, Durham, NC, USA. Electronic address: sayanti.bhattacharya@duke.edu. 2. Division of Cardiovascular Medicine, Duke University School of Medicine, Durham, NC, USA; Duke Clinical Research Institute, Durham, NC, USA. Electronic address: christopher.granger@duke.edu. 3. Duke Institute of Molecular Physiology, Durham, NC, USA. Electronic address: damian.craig@duke.edu. 4. Duke Institute of Molecular Physiology, Durham, NC, USA. Electronic address: carol.haynes@duke.edu. 5. Duke Institute of Molecular Physiology, Durham, NC, USA. Electronic address: james.bain@duke.edu. 6. Duke Institute of Molecular Physiology, Durham, NC, USA. Electronic address: rdjestev@duke.edu. 7. Duke Institute of Molecular Physiology, Durham, NC, USA. Electronic address: elizabeth.hauser@duke.edu. 8. Duke Institute of Molecular Physiology, Durham, NC, USA. Electronic address: newga002@mc.duke.edu. 9. Duke Institute of Molecular Physiology, Durham, NC, USA. Electronic address: william.kraus@duke.edu. 10. Division of Cardiovascular Medicine, Duke University School of Medicine, Durham, NC, USA; Duke Clinical Research Institute, Durham, NC, USA. Electronic address: kristin.newby@duke.edu. 11. Duke Global Health Institute, Durham, NC, USA; Duke Institute of Molecular Physiology, Durham, NC, USA; Division of Cardiovascular Medicine, Duke University School of Medicine, Durham, NC, USA; Duke Clinical Research Institute, Durham, NC, USA. Electronic address: svati.shah@duke.edu.
Abstract
OBJECTIVE: To validate independent associations between branched-chain amino acids (BCAA) and other metabolites with coronary artery disease (CAD). METHODS: We conducted mass-spectrometry-based profiling of 63 metabolites in fasting plasma from 1983 sequential patients undergoing cardiac catheterization. Significant CAD was defined as CADindex ≥ 32 (at least one vessel with ≥ 95% stenosis; N = 995) and no CAD as CADindex ≤ 23 and no previous cardiac events (N = 610). Individuals (N = 378) with CAD severity between these extremes were excluded. Principal components analysis (PCA) reduced large numbers of correlated metabolites into uncorrelated factors. Association between metabolite factors and significant CAD vs. no CAD was tested using logistic regression; and between metabolite factors and severity of CAD was tested using linear regression. RESULTS: Of twelve PCA-derived metabolite factors, two were associated with CAD in multivariable models: factor 10, composed of BCAA (adjusted odds ratio, OR, 1.20; 95% CI 1.05-1.35, p = 0.005) and factor 7, composed of short-chain acylcarnitines, which include byproducts of BCAA metabolism (adjusted OR 1.30; 95% CI 1.14-1.48, p = 0.001). After adjustment for glycated albumin (marker of insulin resistance [IR]) both factors 7 (p = 0.0001) and 10 (p = 0.004) remained associated with CAD. Severity of CAD as a continuous variable (including patients with non-obstructive disease) was associated with metabolite factors 2, 3, 6, 7, 8 and 9; only factors 7 and 10 were associated in multivariable models. CONCLUSIONS: We validated the independent association of metabolites involved in BCAA metabolism with CAD extremes. These metabolites may be reporting on novel mechanisms of CAD pathogenesis that are independent of IR and diabetes.
OBJECTIVE: To validate independent associations between branched-chain amino acids (BCAA) and other metabolites with coronary artery disease (CAD). METHODS: We conducted mass-spectrometry-based profiling of 63 metabolites in fasting plasma from 1983 sequential patients undergoing cardiac catheterization. Significant CAD was defined as CADindex ≥ 32 (at least one vessel with ≥ 95% stenosis; N = 995) and no CAD as CADindex ≤ 23 and no previous cardiac events (N = 610). Individuals (N = 378) with CAD severity between these extremes were excluded. Principal components analysis (PCA) reduced large numbers of correlated metabolites into uncorrelated factors. Association between metabolite factors and significant CAD vs. no CAD was tested using logistic regression; and between metabolite factors and severity of CAD was tested using linear regression. RESULTS: Of twelve PCA-derived metabolite factors, two were associated with CAD in multivariable models: factor 10, composed of BCAA (adjusted odds ratio, OR, 1.20; 95% CI 1.05-1.35, p = 0.005) and factor 7, composed of short-chainacylcarnitines, which include byproducts of BCAA metabolism (adjusted OR 1.30; 95% CI 1.14-1.48, p = 0.001). After adjustment for glycated albumin (marker of insulin resistance [IR]) both factors 7 (p = 0.0001) and 10 (p = 0.004) remained associated with CAD. Severity of CAD as a continuous variable (including patients with non-obstructive disease) was associated with metabolite factors 2, 3, 6, 7, 8 and 9; only factors 7 and 10 were associated in multivariable models. CONCLUSIONS: We validated the independent association of metabolites involved in BCAA metabolism with CAD extremes. These metabolites may be reporting on novel mechanisms of CAD pathogenesis that are independent of IR and diabetes.
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