Recent advances in the gut microbiome and microbial metabolites alterations of coronary artery disease

Identification of diagnostic biomarkers and immune cell infiltration in coronary artery disease by machine learning, nomogram, and molecular docking

Background

Coronary artery disease (CAD) is still a lethal disease worldwide. This study aims to identify clinically relevant diagnostic biomarker in CAD and explore the potential medications on CAD.

Methods

GSE42148, GSE180081, and GSE12288 were downloaded as the training and validation cohorts to identify the candidate genes by constructing the weighted gene co-expression network analysis. Functional enrichment analysis was utilized to determine the functional roles of these genes. Machine learning algorithms determined the candidate biomarkers. Hub genes were then selected and validated by nomogram and the receiver operating curve. Using CIBERSORTx, the hub genes were further discovered in relation to immune cell infiltrability, and molecules associated with immune active families were analyzed by correlation analysis. Drug screening and molecular docking were used to determine medications that target the four genes.

Results

There were 191 and 230 key genes respectively identified by the weighted gene co-expression network analysis in two modules. A total of 421 key genes found enriched pathways by functional enrichment analysis. Candidate immune-related genes were then screened and identified by the random forest model and the eXtreme Gradient Boosting algorithm. Finally, four hub genes, namely, CSF3R, EED, HSPA1B, and IL17RA, were obtained and used to establish the nomogram model. The receiver operating curve, the area under curve, and the calibration curve were all used to validate the accuracy and usefulness of the diagnostic model. Immune cell infiltrating was examined, and CAD patients were then divided into high- and low-expression groups for further gene set enrichment analysis. Through targeting the hub genes, we also found potential drugs for anti-CAD treatment by using the molecular docking method.

Conclusions

CSF3R, EED, HSPA1B, and IL17RA are potential diagnostic biomarkers for CAD. CAD pathogenesis is greatly influenced by patterns of immune cell infiltration. Promising drugs offers new prospects for the development of CAD therapy.

Chinese Herbal Medicines for Coronary Heart Disease: Clinical Evidence, Pharmacological Mechanisms, and the Interaction with Gut Microbiota

Coronary heart disease (CHD) is a common type of cardiovascular disease (CVD) that has been on the rise in terms of both incidence and mortality worldwide, presenting a significant threat to human health. An increasing body of studies has shown that traditional Chinese medicine (TCM), particularly Chinese herbal medicines (CHMs), can serve as an effective adjunctive therapy to enhance the efficacy of Western drugs in treating CHD due to their multiple targets and multiple pathways. In this article, we critically review data available on the potential therapeutic strategies of CHMs in the intervention of CHD from three perspectives: clinical evidence, pharmacological mechanisms, and the interaction with gut microbiota. We identified 20 CHMs used in clinical practice and it has been found that the total clinical effective rate of CHD patients improved on average by 17.78% with the intervention of these CHMs. Subsequently, six signaling pathways commonly used in treating CHD have been identified through an overview of potential pharmacological mechanisms of these 20 CHMs and the eight representative individual herbs selected from them. CHMs could also act on gut microbiota to intervene in CHD by modulating the composition of gut microbiota, reducing trimethylamine-N-oxide (TMAO) levels, increasing short-chain fatty acids (SCFAs), and maintaining appropriate bile acids (BAs). Thus, the therapeutic potential of CHMs for CHD is worthy of further study in view of the outcomes found in existing studies.