References
- Ahmad, T., et al., 2016. Prognostic implications of long-chain acylcarnitines in heart failure and reversibility with mechanical circulatory support. Journal of the American college of cardiology, 67 (3), 291–299.
- Alshehry, Z.H., et al., 2016. Plasma lipidomic profiles improve on traditional risk factors for the prediction of cardiovascular events in type 2 diabetes mellitus. Circulation, 134 (21), 1637–1650.
- Amur, S., et al., 2008. Integration and use of biomarkers in drug development, regulation and clinical practice: a US regulatory perspective. Biomarkers in medicine, 2(3), 305–311.
- Anand, I.S., et al., 2010. Serial measurement of growth-differentiation factor-15 in heart failure: relation to disease severity and prognosis in the Valsartan Heart Failure Trial. Circulation, 122 (14), 1387–1395.
- Benjamin, E.J., et al., 2017. Heart disease and stroke statistics-2017 update: a report from the American Heart Association. Circulation, 135 (10), e146–e603.
- Chapman, M.J., et al., 2011. Triglyceride-rich lipoproteins and high-density lipoprotein cholesterol in patients at high risk of cardiovascular disease: evidence and guidance for management. European heart journal, 32 (11), 1345–1361.
- Cheng, M.L., et al., 2015. Metabolic disturbances identified in plasma are associated with outcomes in patients with heart failure: diagnostic and prognostic value of metabolomics. Journal of the American college of cardiology, 65 (15), 1509–1520.
- Collins, G.S., et al., 2015. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMC medicine, 13 (1), 1.
- Daniels, L.B. and Maisel, A.S., 2007. Natriuretic peptides. Journal of the American college of cardiology, 50 (25), 2357–2368.
- de Boer, R.A., et al., 2011. Predictive value of plasma galectin-3 levels in heart failure with reduced and preserved ejection fraction. Annals of medicine, 43 (1), 60–68.
- Delles, C., et al., 2018. Nuclear magnetic resonance-based metabolomics identifies phenylalanine as a novel predictor of incident heart failure hospitalisation: results from PROSPER and FINRISK 1997. European Journal of Heart Failure, 20 (4), 663–673.
- Di Angelantonio, E., et al., 2009. Major lipids, apolipoproteins, and risk of vascular disease. JAMA, 302 (18), 1993–2000.
- Egstrup, M., et al., 2012. Prediction of outcome by highly sensitive troponin T in outpatients with chronic systolic left ventricular heart failure. The American journal of cardiology, 110 (4), 552–557.
- Floegel, A., et al., 2018. Serum metabolites and risk of myocardial infarction and ischemic stroke: a targeted metabolomic approach in two German prospective cohorts. European journal of epidemiology, 33 (1), 55–66.
- Ganna, A., et al., 2014. Large-scale metabolomic profiling identifies novel biomarkers for incident coronary heart disease. PLoS genetics, 10 (12), e1004801.
- Goldberg, I.J., Trent, C.M., and Schulze, P.C., 2012. Lipid metabolism and toxicity in the heart. Cell metabolism, 15 (6), 805–812.
- Havulinna, A. S., et al., 2016. Circulating ceramides predict cardiovascular outcomes in the population-based FINRISK 2002 cohort. Arteriosclerosis, Thrombosis, and Vascular Biology, 36 (12), 2424–2430.
- Hokanson, J.E. and Austin, M.A., 1996. Plasma triglyceride level is a risk factor for cardiovascular disease independent of high-density lipoprotein cholesterol level: a metaanalysis of population-based prospective studies. European journal of cardiovascular prevention & rehabilitation, 3 (2), 213–219.
- Kalim, S., et al., 2013. A plasma long‐chain acylcarnitine predicts cardiovascular mortality in incident dialysis patients. Journal of the American heart association, 2 (6), e000542.
- Kempf, T., et al., 2007. Prognostic utility of growth differentiation factor-15 in patients with chronic heart failure. Journal of the American college of cardiology, 50 (11), 1054–1060.
- Kume, S., et al., 2014. Predictive properties of plasma amino acid profile for cardiovascular disease in patients with type 2 diabetes. PLoS One, 9 (6), e101219.
- Ky, B., et al., 2012. Multiple biomarkers for risk prediction in chronic heart failure. Circulation: heart failure, 5 (2), 183–190.
- Laaksonen, R., et al., 2016. Plasma ceramides predict cardiovascular death in patients with stable coronary artery disease and acute coronary syndromes beyond LDL-cholesterol. European heart journal, 37 (25), 1967–1976.
- Liberati, A., et al., 2009. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS medicine, 6 (7), e1000100.
- Lok, D.J., et al., 2010. Prognostic value of galectin-3, a novel marker of fibrosis, in patients with chronic heart failure: data from the DEAL-HF study. Clinical research in cardiology, 99 (5), 323–328.
- Lopaschuk, G.D., et al., 2010. Myocardial fatty acid metabolism in health and disease. Physiological reviews, 90 (1), 207–258.
- Masson, S., et al., 2012. Serial measurement of cardiac troponin T using a highly sensitive assay in patients with chronic heart failure: data from 2 large randomized clinical trials. Circulation, 125 (2), 280–288.
- Miller, M., et al., 2011. Triglycerides and cardiovascular disease: a scientific statement from the American Heart Association. Circulation, 123 (20), 2292–2333.
- Moons, K.G., et al., 2014. Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist. PLoS medicine, 11 (10), e1001744.
- Mundra, P.A., et al., 2018. Large-scale plasma lipidomic profiling identifies lipids that predict cardiovascular events in secondary prevention. JCI insight, 3 (17).
- Niizeki, T., et al., 2009. Combination of conventional biomarkers for risk stratification in chronic heart failure. Journal of cardiology, 53 (2), 179–187.
- Paynter, N. P., et al., 2018. Metabolic predictors of incident coronary heart disease in women. Circulation, 137 (8), 841–853.
- Pepe, M.S., et al., 2008. Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design. JNCI: journal of the national cancer institute, 100 (20), 1432–1438.
- Prescott, S.M., et al., 2000. Platelet-activating factor and related lipid mediators. Annual review of biochemistry, 69 (1), 419–445.
- Rizza, S., et al., 2014. Metabolomics signature improves the prediction of cardiovascular events in elderly subjects. Atherosclerosis, 232 (2), 260–264.
- Sambola, A., et al., 2003. Role of risk factors in the modulation of tissue factor activity and blood thrombogenicity. Circulation, 107 (7), 973–977.
- Sarwar, N., et al., 2007. Clinical perspective. Circulation, 115 (4), 450–458.
- Sevastou, I., et al., 2013. Lysoglycerophospholipids in chronic inflammatory disorders: the PLA2/LPC and ATX/LPA axes. Biochimica et biophysica acta (BBA) – molecular and cell biology of lipids, 1831 (1), 42–60.
- Shah, S.H., et al., 2010. Association of a peripheral blood metabolic profile with coronary artery disease and risk of subsequent cardiovascular events. Circulation: Cardiovascular Genetics, 3 (2), 207–214.
- Shah, S.H., et al., 2012. Baseline metabolomic profiles predict cardiovascular events in patients at risk for coronary artery disease. American heart journal, 163 (5), 844–850.
- StataCorp. 2015. Stata statistical software: release 14. College Station (TX): StataCorp LP.
- Stegemann, C., et al., 2014. Lipidomics profiling and risk of cardiovascular disease in the prospective population-based Bruneck study. Circulation, 129 (18), 1821–1831.
- Tang, W. W., et al., 2013. Intestinal microbial metabolism of phosphatidylcholine and cardiovascular risk. New England Journal of Medicine, 368 (17), 1575–1584.
- Tang, W. W., et al., 2014. Prognostic value of elevated levels of intestinal microbe-generated metabolite trimethylamine-n-oxide in patients with heart failure. Journal of the American College of Cardiology, 64 (18), 1908–1914.
- Vaarhorst, A.A., et al., 2014. A metabolomic profile is associated with the risk of incident coronary heart disease. American heart journal, 168 (1), 45–52.
- Wang, C.H., et al., 2017. Metabolic profile provides prognostic value better than galectin-3 in patients with heart failure. Journal of cardiology, 70 (1), 92–98.
- Wang, Z., et al., 2011. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature, 472 (7341), 57–63.
- Wang, T. J., et al., 2011. Metabolite profiles and the risk of developing diabetes. Nature Medicine, 17 (4), 448–453.
- Wang, D. D., et al., 2017. Plasma ceramides, mediterranean diet, and incident cardiovascular disease in the PREDIMED trial (Prevencion con Dieta Mediterranea). Circulation, 135 (21), 2028–2040.
- Wang, T.J., et al., 2006. Multiple biomarkers for the prediction of first major cardiovascular events and death. New England journal of medicine, 355 (25), 2631–2639.
- Wende, A.R. and Abel, E.D., 2010. Lipotoxicity in the heart. Biochimica et biophysica acta (BBA) – molecular and cell biology of lipids, 1801 (3), 311–319.
- Wishart, D.S., et al., 2018. HMDB 4.0: the human metabolome database for 2018. Nucleic acids research, 46 (D1), D608–D617.
- Wurtz, P., et al., 2015. Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts. Circulation, 131 (9), 774–785.