Circulating Matrix Metalloproteinase-28 Levels Are Related to GRACE Scores and Short-Term Outcomes in Patients with Acute Myocardial Infarction

Unraveling the Cardiac Matrix: From Diabetes to Heart Failure, Exploring Pathways and Potential Medications

Myocardial infarction (MI) often leads to heart failure (HF) through acute or chronic maladaptive remodeling processes. This establishes coronary artery disease (CAD) and HF as significant contributors to cardiovascular illness and death. Therefore, treatment strategies for patients with CAD primarily focus on preventing MI and lessening the impact of HF after an MI event. Myocardial fibrosis, characterized by abnormal extracellular matrix (ECM) deposition, is central to cardiac remodeling. Understanding these processes is key to identifying new treatment targets. Recent studies highlight SGLT2 inhibitors (SGLT2i) and GLP-1 receptor agonists (GLP1-RAs) as favorable options in managing type 2 diabetes due to their low hypoglycemic risk and cardiovascular benefits. This review explores inflammation's role in cardiac fibrosis and evaluates emerging anti-diabetic medications' effectiveness, such as SGLT2i, GLP1-RAs, and dipeptidyl peptidase-4 inhibitors (DPP4i), in preventing fibrosis in patients with diabetes post-acute MI. Recent studies were analyzed to identify effective medications in reducing fibrosis risk in these patients. By addressing these areas, we can advance our understanding of the potential benefits of anti-diabetic medications in reducing cardiac fibrosis post-MI and improve patient outcomes in individuals with diabetes at risk of HF.

Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein–protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. The top hub genes such as MYC, EGFR, LNX1, YBX1, HSP90AA1, ESR1, FN1, TK1, ANLN and SMAD9 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Receiver operating characteristic curve (ROC) analysis confirmed that these genes were significantly associated with T1DM. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the advancement and progression of T1DM, and certain genes might be used as candidate target molecules to diagnose, monitor and treat T1DM.

Past, Present, and Future of Blood Biomarkers for the Diagnosis of Acute Myocardial Infarction-Promises and Challenges

Despite important advancements in acute myocardial infarction (AMI) management, it continues to represent a leading cause of mortality worldwide. Fast and reliable AMI diagnosis can significantly reduce mortality in this high-risk population. Diagnosis of AMI has relied on biomarker evaluation for more than 50 years. The upturn of high-sensitivity cardiac troponin testing provided extremely sensitive means to detect cardiac myocyte necrosis, but this increased sensitivity came at the cost of a decrease in diagnostic specificity. In addition, although cardiac troponins increase relatively early after the onset of AMI, they still leave a time gap between the onset of myocardial ischemia and our ability to detect it, thus precluding very early management of AMI. Newer biomarkers detected in processes such as inflammation, neurohormonal activation, or myocardial stress occur much earlier than myocyte necrosis and the diagnostic rise of cardiac troponins, allowing us to expand biomarker research in these areas. Increased understanding of the complex AMI pathophysiology has spurred the search of new biomarkers that could overcome these shortcomings, whereas multi-omic and multi-biomarker approaches promise to be game changers in AMI biomarker assessment. In this review, we discuss the evolution, current application, and emerging blood biomarkers for the diagnosis of AMI; we address their advantages and promises to improve patient care, as well as their challenges, limitations, and technical and diagnostic pitfalls. Questions that remain to be answered and hotspots for future research are also emphasized.

Diagnostic and Prognostic Biomarkers for Myocardial Infarction

The incidence of myocardial infarction (MI) increases every year worldwide. Better diagnostic and prognostic biomarkers for clinical applications are the consistent pursuit of MI research. In addition to electrocardiogram, echocardiography, coronary angiography, etc., circulating biomarkers are essential for the diagnosis, prognosis, and treatment effect monitoring of MI patients. In this review, we assessed both strength and weakness of MI circulating biomarkers including: (1) originated from damaged myocardial tissues including current golden standard cardiac troponin, (2) released from non-myocardial tissues due to MI-induced systems reactions, and (3) preexisted in blood circulation before the occurrence of MI event. We also summarized newly reported MI biomarkers. We proposed that the biomarkers preexisting in blood circulation before MI incidents should be emphasized in research and development for MI prevention in near future.