Diversified Shifts in the Cross Talk between Members of the Gut Microbiota and Development of Coronary Artery Diseases

Impact of the gut microbiome on atherosclerosis

Atherosclerosis is a chronic inflammatory metabolic disease with a complex pathogenesis. However, the exact details of its pathogenesis are still unclear, which limits effective clinical treatment of atherosclerosis. Recently, multiple studies have demonstrated that the gut microbiota plays a pivotal role in the onset and progression of atherosclerosis. This review discusses possible treatments for atherosclerosis using the gut microbiome as an intervention target and summarizes the role of the gut microbiome and its metabolites in the development of atherosclerosis. New strategies for the treatment of atherosclerosis are needed. This review provides clues for further research on the mechanisms of the relationship between the gut microbiota and atherosclerosis.

Faecalibacterium prausnitzii as a potential Antiatherosclerotic microbe

BACKGROUND

The gut microbiota plays a crucial role in coronary artery disease (CAD) development, but limited attention has been given to the role of the microbiota in preventing this disease. This study aimed to identify key biomarkers using metagenomics and untargeted metabolomics and verify their associations with atherosclerosis.

METHODS

A total of 371 participants, including individuals with various CAD types and CAD-free controls, were enrolled. Subsequently, significant markers were identified in the stool samples through gut metagenomic sequencing and untargeted metabolomics. In vivo and in vitro experiments were performed to investigate the mechanisms underlying the association between these markers and atherosclerosis.

RESULTS

Faecal omics sequencing revealed that individuals with a substantial presence of Faecalibacterium prausnitzii had the lowest incidence of CAD across diverse CAD groups and control subjects. A random forest model confirmed the significant relationship between F. prausnitzii and CAD incidence. Notably, F. prausnitzii emerged as a robust, independent CAD predictor. Furthermore, our findings indicated the potential of the gut microbiota and gut metabolites to predict CAD occurrence and progression, potentially impacting amino acid and vitamin metabolism. F. prausnitzii mitigated inflammation and exhibited an antiatherosclerotic effect on ApoE-/- mice after gavage. This effect was attributed to reduced intestinal LPS synthesis and reinforced mechanical and mucosal barriers, leading to decreased plasma LPS levels and an antiatherosclerotic outcome.

CONCLUSIONS

Sequencing of the samples revealed a previously unknown link between specific gut microbiota and atherosclerosis. Treatment with F. prausnitzii may help prevent CAD by inhibiting atherosclerosis.

Gut microbiome-based noninvasive diagnostic model to predict acute coronary syndromes

Background

Previous studies have shown that alterations in the gut microbiota are closely associated with Acute Coronary Syndrome (ACS) development. However, the value of gut microbiota for early diagnosis of ACS remains understudied.

Methods

We recruited 66 volunteers, including 29 patients with a first diagnosis of ACS and 37 healthy volunteers during the same period, collected their fecal samples, and sequenced the V4 region of the 16S rRNA gene. Functional prediction of the microbiota was performed using PICRUSt2. Subsequently, we constructed a nomogram and corresponding webpage based on microbial markers to assist in the diagnosis of ACS. The diagnostic performance and usefulness of the model were analyzed using boostrap internal validation, calibration curves, and decision curve analysis (DCA).

Results

Compared to that of healthy controls, the diversity and composition of microbial community of patients with ACS was markedly abnormal. Potentially pathogenic genera such as Streptococcus and Acinetobacter were significantly increased in the ACS group, whereas certain SCFA-producing genera such as Blautia and Agathobacter were depleted. In addition, in the correlation analysis with clinical indicators, the microbiota was observed to be associated with the level of inflammation and severity of coronary atherosclerosis. Finally, a diagnostic model for ACS based on gut microbiota and clinical variables was developed with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.963 (95% CI: 0.925-1) and an AUC value of 0.948 (95% CI: 0.549-0.641) for bootstrap internal validation. The calibration curves of the model show good consistency between the actual and predicted probabilities. The DCA showed that the model had a high net clinical benefit for clinical applications.

Conclusion

Our study is the first to characterize the composition and function of the gut microbiota in patients with ACS and healthy populations in Southwest China and demonstrates the potential effect of the microbiota as a non-invasive marker for the early diagnosis of ACS.

Association of the gut microbiota with coronary artery disease and myocardial infarction: A Mendelian randomization study

Background: Previous studies have indicated that the gut microbiota (GM) is associated with coronary artery disease (CAD), but the causality of these associations remains unestablished due to confounding factors and reverse causality. We conducted Mendelian randomization study (MR) to determine the causal effect of the specific bacterial taxa on CAD/myocardial infarction (MI) and identify the mediating factors involved. Methods: Two-sample MR, multivariable MR (MVMR) and mediation analysis were performed. Inverse-variance weighting (IVW) was the main method used to analyze causality, and sensitivity analysis was used to verify the reliability of the study. Causal estimates from CARDIoGRAMplusC4D and FinnGen databases were combined using the meta-analysis method, and repeated validation was conducted based on the UK Biobank (UKB) database. Confounders that may affect the causal estimates were corrected by MVMP and the potential mediation effects were investigated by using mediation analysis. Results: The study suggested that increased abundance of the RuminococcusUCG010 genus leads to a lower risk of CAD (OR, 0.88; 95% CI, 0.78, 1.00; p = 2.88 × 10^-2) and MI (OR, 0.88; 95% CI, 0.79, 0.97; p = 1.08 × 10^-2), with consistent results in both meta-analysis (CAD: OR, 0.86; 95% CI, 0.78, 0.96; p = 4.71 × 10^-3; MI: OR, 0.82; 95% CI, 0.73, 0.92; p = 8.25 × 10^-4) and repeated analysis of the UKB dataset (CAD: OR, 0.99; 95% CI, 0.99, 1.00, p = 2.53 × 10^-4; MI: OR, 0.99; 95% CI, 0.99, 1.00, p = 1.85 × 10-11). Based on multiple databases, T2DM was proved as a mediating factor in the causal effect of RuminococcusUCG010 and CAD/MI, with an average mediation effect proportion of 20% on CAD and 17% on MI, respectively. Conclusion: This MR study provided suggestive genetic evidence that the higher the RuminococcusUCG010 abundance is, the lower the risk of CAD and MI, with T2DM playing a mediating effect. This genus may become a novel target in strategies for treating and preventing CAD and MI.