Harnessing the Plasma Proteome to Mirror Current and Predict Future Cardiac Remodeling After Myocardial Infarction

Comprehensive Quality Analysis of Conventional and Novel Biomarkers in Diagnosing and Predicting Prognosis of Coronary Artery Disease, Acute Coronary Syndrome, and Heart Failure, a Comprehensive Literature Review

Coronary artery disease (CAD), acute coronary syndrome (ACS), and heart failure (HF) are major global health issues with high morbidity and mortality rates. Biomarkers like cardiac troponins (cTn) and natriuretic peptides (NPs) are crucial tools in cardiology, but numerous new biomarkers have emerged, proving increasingly valuable in CAD/ACS. These biomarkers are classified based on their mechanisms, such as fibrosis, metabolism, inflammation, and congestion. The integration of established and emerging biomarkers into clinical practice is an ongoing process, and recognizing their strengths and limitations is crucial for their accurate interpretation, incorporation into clinical settings, and improved management of CVD patients. We explored established biomarkers like cTn, NPs, and CRP, alongside newer biomarkers such as Apo-A1, IL-17E, IgA, Gal-3, sST2, GDF-15, MPO, H-FABP, Lp-PLA2, and ncRNAs; provided evidence of their utility in CAD/ACS diagnosis and prognosis; and empowered clinicians to confidently integrate these biomarkers into clinical practice based on solid evidence.

From multi-omics approaches to personalized medicine in myocardial infarction

Myocardial infarction (MI) is a prevalent cardiovascular disease characterized by myocardial necrosis resulting from coronary artery ischemia and hypoxia, which can lead to severe complications such as arrhythmia, cardiac rupture, heart failure, and sudden death. Despite being a research hotspot, the etiological mechanism of MI remains unclear. The emergence and widespread use of omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and other omics, have provided new opportunities for exploring the molecular mechanism of MI and identifying a large number of disease biomarkers. However, a single-omics approach has limitations in understanding the complex biological pathways of diseases. The multi-omics approach can reveal the interaction network among molecules at various levels and overcome the limitations of the single-omics approaches. This review focuses on the omics studies of MI, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and other omics. The exploration extended into the domain of multi-omics integrative analysis, accompanied by a compilation of diverse online resources, databases, and tools conducive to these investigations. Additionally, we discussed the role and prospects of multi-omics approaches in personalized medicine, highlighting the potential for improving diagnosis, treatment, and prognosis of MI.