The diagnostic value of peroxisome proliferator-activated receptor-γ coactivator-1α in identifying different chronic heart failure phenotypes

Background Despite advances in diagnosing and treating chronic heart failure (HF), the underlying mechanisms in different HF phenotypes remain unclear. Mitochondrial energy metabolism is crucial in HF etiology. Our study aimed to explore the value of metabolic-associated biomarker peroxisome proliferator-activated receptor-γ coactivator-1α (PGC1α) in identifying different HF phenotypes. Methods A total of 172 participants were enrolled in the Affiliated Hospital of Xuzhou Medical University and were subsequently divided into four groups based on the European Society of Cardiology HF management guideline: the non-HF control (Control, N = 46), heart failure with reduced ejection fraction (HFrEF, N = 54), heart failure with mildly reduced ejection fraction (HFmrEF, N = 22), and heart failure with preserved ejection fraction (HFpEF, N = 50) groups. Each participant’s baseline data were recorded, blood samples were taken, and echocardiography was conducted. The level of PGC1α expression was determined using an enzyme-linked immunosorbent assay (ELISA) kit. The receiver operative characteristics (ROC) curve was further established in the four groups to assess the diagnostic value for overall HF and each HF phenotype with the calculation of the area under the curve (AUC) and 95% confidence interval (CI). Results PGC1α expression was significantly increased in HF patients (315.0 ± 69.58 nmol/L) compared to non-HF participants (233.3 ± 32.69 nmol/L). Considering different HF phenotypes, PGC1α expression was considerably higher in the HFmrEF group (401.6 ± 45.1 nmol/L)than in the other two phenotypes (299.5 ± 62.27 nmol/L for HFrEF and 293.5 ± 56.37 nmol/L for HFpEF, respectively).Furthermore, the AUCs of PGC1α in overall HF and each HF phenotype were all over 0.8, showing the ideal diagnostic value. Additionally, we provided the cut-off criteria for clinical use, which needs further validation. There was no significant correlation between PGC1α and N-terminal (NT)-prohormone B-type natriuretic peptide (BNP)/blood glucose, suggesting that PGC1α might exert a unique function in HF yet in a different pattern. Conclusion We discovered that PGC1α could be used as a potential biomarker for differentiating HF patients from those without HF and for distinguishing HFmrEF from HFrEF and HFpEF.