Heart failure (HF) remains a major cause of morbidity and mortality worldwide and represents a major challenge for diagnosis, prognosis and treatment due to its heterogeneity. Traditional biomarkers such as BNP and NT-proBNP are valuable but insufficient to capture the complexity of HF, especially phenotypes such as HF with preserved ejection fraction (HFpEF). Recent advances in multi-omics technology and novel biomarkers such as cell-free DNA (cfDNA), microRNAs (miRNAs), ST2 and galectin-3 offer transformative potential for HF management. This review explores the integration of these innovative biomarkers into clinical practice and highlights their benefits, such as improved diagnostic accuracy, enhanced risk stratification and non-invasive monitoring capabilities. By leveraging multi-omics approaches, including lipidomics and metabolomics, clinicians can uncover new pathways, refine the classification of HF phenotypes, and develop personalized therapeutic strategies tailored to individual patient profiles. Remarkable advances in proteomics and metabolomics have identified biomarkers associated with key HF mechanisms such as mitochondrial dysfunction, inflammation and fibrosis, paving the way for targeted therapies and early interventions. Despite the promising results, significant challenges remain in translating these findings into routine care, including high costs, technical limitations and the need for large-scale validation studies. This report argues for an integrative, multi-omics-based model to overcome these obstacles and emphasizes the importance of collaboration between researchers, clinicians and policy makers. By linking innovative science with practical applications, multi-omics approaches have the potential to redefine HF management and lead to better patient outcomes and more sustainable healthcare systems.
Keywords: Advanced bioinformatics; Biomarkers; Data complexity; Diagnostic tools; Lipidomics; Metabolomics; Multi-omics; Personalized medicine; Proteomics.
© 2025 The Authors.