Integrative bioinformatic analysis of prognostic biomarkers in heart failure: Insights from clinical trials

Abstract Background Heart failure (HF) remains a major cause of morbidity and mortality worldwide. Therefore, there is a need to identify robust biomarkers to improve early diagnosis, stratify disease severity and predict outcomes. Biomarkers such as galectin‐3 (Gal‐3), TIMP‐1, BNP, NT‐proBNP, CysC, CA125, ST2 and MMP9 have shown the potential to reflect the pathophysiology of HF. Despite their clinical potential, their integration into routine practice is still limited. The use of bioinformatics may help uncover critical associations between these biomarkers and the progression of HF, providing opportunities for personalized disease management. Methods Following PRISMA guidelines, a systematic review of clinical studies was performed using databases with time constraints. The major proteins associated with HF were identified and their diagnostic and prognostic roles were analysed. Results The study emphasizes that galectin‐3 (Gal‐3) and TIMP‐1 serve as key indicators of fibrosis and inflammation, while BNP and NT‐proBNP are reliable markers of cardiac stress. Cystatin C (CysC) reflects renal dysfunction, and CA125 correlates strongly with venous congestion. In addition, ST2 and MMP9 provide valuable insights into inflammation and tissue remodelling processes. These biomarkers are consistently elevated in patients with HF, emphasizing their critical role in detecting the systemic and cardiac manifestations of the disease. Conclusion Our results emphasize the importance of including biomarkers such as Gal‐3, TIMP‐1, BNP, NT‐proBNP, CysC, CA125, ST2 and MMP9 in the diagnosis and treatment of HF. Their upregulation reflects the complex pathophysiological processes of HF and supports their use in the clinical setting to improve diagnostic accuracy, prognostic precision and personalized therapeutic strategies.