Abstract: Objective To investigate the diagnostic value of plasma growth and differentiation factor-15 (GDF-15) level, GDF-15mRNA expression in circulating mononuclear cells (MNCs), and plasma pro-B-type natriuretic peptide (NT-proBNP) level for heart failure in patients with different underlying cardiac diseases, namely dilated cardiomyopathy (DCM) and coronary artery heart disease (CAD), and assess their value in predicting the severity of heart failure and long-term cardiovascular disease (CVD) events. Methods Fasting venous blood samples were collected from 261 patients with DCM and 251 patients with CAD admitted in our hospital between January, 2018 and January, 2019, with 132 healthy individuals serving as the control group. The plasma level of GDF-15 was measured by enzyme-linked immunosorbent assay (ELISA), and the expression of GDF-15 mRNA in the MNCs was measured by real-time PCR. We also analyzed the expression of GDF-15 in patients with different NYHA classes, and the ROC curve was used to evaluate the predictive power of GDF-15 mRNA for CVD events. Results The plasma levels of GDF-15 and GDF-15 mRNA in the MNCs were significantly higher in patients with DCM and CAD than in the control group (P<0.01). Plasma GDF-15 levels were significantly higher in NYHA class IV patients than in class II and III patients, and GDF-15 mRNA expressions in the MNCs were much higher in class III and IV patients than class II patients (P<0.01). ROC curve analysis showed that for predicting CVD events, the area under the curve (AUC) was 0.73 (95% CI: 0.69-0.77, P<0.001) for NT-proBNP alone, as compared with 0.83 (95% CI: 0.79-0.86, P<0.001) for GDF-15 mRNA in the MNCs combined with NT-proBNP. Conclusion Plasma GDF-15 level and GDF-15 mRNA expression level in the MNSc can both be used as biomarkers for heart failure. Plasma level of GDF-15 is more sensitive for predicting NYHA class IV patients with heart failure, while GDF-15 mRNA level in the MNCs better predicts class II patients. The combination of NT-proBNP with GDF-15 mRNAlevel in the MNCs can more accurately predict the risk of long-term CVD events.