Intestinal Flora Metabolite Trimethylamine Oxide Is Inextricably Linked to Coronary Heart Disease

The identification of metabolites from gut microbiota in coronary heart disease via network pharmacology

Although the gut microbial metabolites exhibit potential effects on coronary heart disease (CHD), the underlying mechanism remains unclear. In this study, the active gut microbial metabolites acting on CHD and their potential mechanisms of action were explored through a network pharmacological approach. We collected a total of 208 metabolites from the gutMgene database and 726 overlapping targets from the similarity ensemble approach (SEA) and SwissTargetPrediction (STP) database, and ultimately identified 610 targets relevant to CHD. In conjunction with the gutMGene database, we identified 12 key targets. The targets of exogenous substances were removed, and 10 core targets involved in CHD were eventually retained. The microbiota-metabolites-targets-signalling pathways network analysis revealed that C-type lectin receptor signalling pathway, Lachnospiraceae, Escherichia, mitogen-activated protein kinase 1, prostaglandin-endoperoxidase synthase 2, phenylacetylglutamine and alcoholic acid are notable components of CHD and play important roles in the development of CHD. The results of molecular docking experiments demonstrated that AKT1-glycocholic acid and PTGS2-phenylacetylglutamine complexes may act on C-type lectin receptor signalling pathways. In this study, the key substances and potential mechanisms of gut microbial metabolites were analysed via network pharmacological methods, and a scientific basis and comprehensive idea were provided for the effects of gut microbial metabolites on CHD.

Beyond the Basics: Unraveling the Complexity of Coronary Artery Calcification

Coronary artery calcification (CAC) is mainly associated with coronary atherosclerosis, which is an indicator of coronary artery disease (CAD). CAC refers to the accumulation of calcium phosphate deposits, classified as micro- or macrocalcifications, that lead to the hardening and narrowing of the coronary arteries. CAC is a strong predictor of future cardiovascular events, such as myocardial infarction and sudden death. Our narrative review focuses on the pathophysiology of CAC, exploring its link to plaque vulnerability, genetic factors, and how race and sex can affect the condition. We also examined the connection between the gut microbiome and CAC, and the impact of genetic variants on the cellular processes involved in vascular calcification and atherogenesis. We aimed to thoroughly analyze the existing literature to improve our understanding of CAC and its potential clinical and therapeutic implications.

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.