The Types and Proportions of Commensal Microbiota Have a Predictive Value in Coronary Heart Disease

Exploring the Gut Microbiota-Retina Axis: Implications for Health and Disease

The gut microbiota represents a rich and adaptive microbial network inhabiting the gastrointestinal tract, performing key functions in nutrient processing, immune response modulation, intestinal wall protection, and microbial defense. Its composition remains highly personalized and responsive to external influences, including lifestyle patterns, physical activity, body composition, and nutritional intake. The interactions of the gut microbiota with bodily systems are conventionally interpreted as broad systemic impacts on organ balance. Yet, emerging research-exemplified by the gut microbiota-brain axis-suggests the potential existence of more targeted and direct communication mechanisms. Dysbiosis, characterized by microbial ecosystem disturbance, generates multiple metabolic compounds capable of entering systemic circulation and reaching distant tissues, notably including ocular structures. This microbial imbalance has been associated with both systemic and localized conditions linked to eye disorders. Accumulating scientific evidence now supports the concept of a gut-retina axis, underscoring the significant role of microbiota disruption in generating various retinal pathologies. This review comprehensively investigates gut microbiota composition, functional dynamics, and dysbiosis-induced alterations, with specific focus on retinal interactions in age-related macular degeneration, diabetic retinopathy, glaucoma, and retinal artery occlusion. Moreover, the review explores microbiota-targeted therapeutic strategies, including precision nutritional interventions and microbial transplantation, as potential modulators of retinal disease progression.

Multi-omics analysis identifies Sphingomonas and specific metabolites as key biomarkers in elderly Chinese patients with coronary heart disease

Background

Abnormal component changes of gut microbiota are related to the pathogenesis and progression of coronary heart disease (CHD), and gut microbiota-derived metabolites are key factors in host-microbiome interactions. This study aimed to explore the key gut microbiota and metabolites, as well as their relationships in CHD.

Methods

Feces samples and blood samples were collected from CHD patients and healthy controls. Then, the obtained feces samples were sent for 16s rRNA gene sequencing, and the blood samples were submitted for metabolomics analysis. Finally, conjoint analysis of 16s rRNA gene sequencing and metabolomics data was performed.

Results

After sequencing, there were no significant differences in Chao 1, observed species, Simpson, Shannon, Pielou's evenness and Faith's PD between the CHD patients and controls. At phylum level, the dominant phyla were Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. At genus level, the abundance of Sphingomonas, Prevotella, Streptococcus, Desulfovibrio, and Shigella was relatively higher in CHD patients; whereas Roseburia, Corprococcus, and Bifidobacterium was relatively lower. Randomforest analysis showed that Sphingomonas was more important for CHD. Through metabolomic analysis, a total of 155 differential metabolites were identified, and were enriched in many signaling pathways. Additionally, the AUC of the conjoint analysis (0.908) was higher than that of gut microbiota species (0.742).

Conclusion

In CHD patients, the intestinal flora was disordered, as well as Sphingomonas and the identified differential metabolites may serve as was candidate biomarkers for CHD occurrence and progression.

The Mediterranean Diet, Its Microbiome Connections, and Cardiovascular Health: A Narrative Review

The Mediterranean diet (MD), rich in minimally processed plant foods and in monounsaturated fats but low in saturated fats, meat, and dairy products, represents one of the most studied diets for cardiovascular health. It has been shown, from both observational and randomized controlled trials, that MD reduces body weight, improves cardiovascular disease surrogates such as waist-to-hip ratios, lipids, and inflammation markers, and even prevents the development of fatal and nonfatal cardiovascular disease, diabetes, obesity, and other diseases. However, it is unclear whether it offers cardiovascular benefits from its individual components or as a whole. Furthermore, limitations in the methodology of studies and meta-analyses have raised some concerns over its potential cardiovascular benefits. MD is also associated with characteristic changes in the intestinal microbiota, mediated through its constituents. These include increased growth of species producing short-chain fatty acids, such as Clostridium leptum and Eubacterium rectale, increased growth of Bifidobacteria, Bacteroides, and Faecalibacterium prausnitzii species, and reduced growth of Firmicutes and Blautia species. Such changes are known to be favorably associated with inflammation, oxidative status, and overall metabolic health. This review will focus on the effects of MD on cardiovascular health through its action on gut microbiota.

Intestinal microbiota and metabolome perturbations in ischemic and idiopathic dilated cardiomyopathy

BACKGROUND

Various clinical similarities are present in ischemic (ICM) and idiopathic dilated cardiomyopathy (IDCM), leading to ambiguity on some occasions. Previous studies have reported that intestinal microbiota appeared dysbiosis in ICM, whether implicating in the IDCM remains unclear. The aim of this study was to assess the alterations in intestinal microbiota and fecal metabolites in ICM and IDCM.

METHODS

ICM (n = 20), IDCM (n = 22), and healthy controls (HC, n = 20) were enrolled in this study. Stool samples were collected for 16S rRNA gene sequencing and gas chromatography-mass spectrometry (GC-MS) analysis.

RESULTS

Both ICM and IDCM exhibited reduced alpha diversity and altered microbial community structure compared to HC. At the genus level, nine taxa including Blautia, [Ruminococcus]_torques_group, Christensenellaceae_R-7_group, UCG-002, Corynebacterium, Oceanobacillus, Gracilibacillus, Klebsiella and Citrobacter was specific to ICM, whereas one taxa Alistipes uniquely altered in IDCM. Likewise, these changes were accompanied by significant metabolic differences. Further differential analysis displayed that 18 and 14 specific metabolites uniquely changed in ICM and IDCM, respectively. The heatmap was generated to display the association between genera and metabolites. Receiver operating characteristic curve (ROC) analysis confirmed the predictive value of the distinct microbial-metabolite features in disease status. The results showed that microbial (area under curve, AUC = 0.95) and metabolic signatures (AUC = 0.84) were effective in discriminating ICM from HC. Based on the specific microbial and metabolic features, the patients with IDCM could be separated from HC with an AUC of 0.80 and 0.87, respectively. Furthermore, the gut microbial genus (AUC = 0.88) and metabolite model (AUC = 0.89) were comparable in predicting IDCM from ICM. Especially, the combination of fecal microbial-metabolic features improved the ability to differentiate IDCM from ICM with an AUC of 0.96.

CONCLUSION

Our findings highlighted the alterations of gut microbiota and metabolites in different types of cardiomyopathies, providing insights into the pathophysiological mechanisms of myocardial diseases. Moreover, multi-omics analysis of fecal samples holds promise as a non-invasive tool for distinguishing disease status.

Characterization of gut microbiota in adults with coronary atherosclerosis

Background

Cardiovascular disease, which is mainly caused by coronary atherosclerosis, is one of the leading causes of death and disability worldwide. Gut microbiota likely play an important role in coronary atherosclerosis. This study aims to investigate the microbiota profile of adults with coronary atherosclerosis to provide a theoretical basis for future research.

Methods

Fecal samples were collected from 35 adult patients diagnosed with coronary atherosclerosis and 32 healthy adults in Nanjing, China, and the V3-V4 region of 16S rDNA genes was sequenced using high-throughput sequencing. Differences in alpha diversity, beta diversity, and gut microbiota composition between the two groups were then compared.

Results

A beta diversity analysis revealed significant differences between adults with coronary atherosclerosis and controls, but there was no statistical difference in alpha diversity between the two groups. There were also differences in the composition of the gut microbiota between the two groups. The genera, Megamonas, Streptococcus, Veillonella, Ruminococcus_torques_group, Prevotella_2, Tyzzerella_4, were identified as potential biomarkers for coronary atherosclerosis.

Conclusion

There are some differences in the gut microbiota of adults with coronary atherosclerosis compared to healthy adults. The insights from this study could be used to explore microbiome-based mechanisms for coronary atherosclerosis.

Changes of Intestinal Flora in Patients with Atrial Fibrillation and Its Correlation with Cardiovascular Risk Factors

Background

Based on the 16S rDNA sequence, intestinal flora changes in atrial fibrillation (AF) patients were monitored, the correlation between the changes and CHA 2 DS 2 - VAS C score was analyzed, and the possible related factors affecting the changes of intestinal flora were investigated.

Methods

According to the inclusion criteria, 53 AF patients were selected as atrial fibrillation group (Group AF), detection of C-reactive protein (CRP), homocysteine (Hcy), total bile acid (TBA), brain natriuretic peptide (BNP), High-sensitivity cardiac troponin (Hs-cTn) and left ventricular ejection fraction (LVEF) were accomplished. A total of 29 healthy subjects who underwent physical examination with matched gender and age were selected as the healthy group (Group H), and the same examinations as in Group AF were handled. Structural composition of intestinal flora was detected and analyzed by 16S rRNA sequencing technology. Flora differences between Group AF and Group H were counted, and the correlation analysis among age, Hs-cTn, CRP, TBA, Hcy, BNP and LVEF were explored. Meanwhile, CHA 2 DS 2 - VAS C score of 53 AF patients was fulfilled, then patients were divided into three subgroups according to different scores, namely: 0 point (AF-0, n = 9), 1 point (AF-1, n = 15), ≥ 2 points (AF-2, n = 29). Finally, the correlation of intestinal flora differences and CHA 2 DS 2 - VAS C scores were analyzed.

Results

In terms of Alpha diversity, compared with the control group, the abundance and diversity of flora in Group AF were observably reduced. However, at phylum and class level, there was no notable difference in community structure between Group AF and Group H (p > 0.05). Further statistics revealed that the composition and abundance of intestinal flora in Group AF were prominently different from those in Group H at phylum, class, order and family levels, which were correlated with CRP and LVEF. Additionally, bioinformatics analysis comparison was performed on three CHA 2 DS 2 - VAS C score subgroups of Group AF with Group H. It was reported that at phylum level, the relative abundance of Firmicutes in Group AF-2 and Chloroflexi in Group H was higher. At class level, the relative abundance of Sphingobacteriia, Flavobacteriia and Alphaproteobacteria was higher in group H. At order level, the relative abundance of Sphingobacteriales, Micrococcales, Flavobacteriales, Sphingobacteriales and Rhizobiales in group H was higher. At family level, the relative abundance of Sphingobacteriaceae, Flavobacteriaceae and Clostridiaceae in group H was higher. At genus level, the relative abundance of Sphingobacterium in group H, Clostridiumsensustricto-1 in Group AF-2, Dialister and Allisonella in Group AF-1, and Prevotella-9 in Group AF-0 were higher.

Conclusions

There were changes in the relative abundance of intestinal flora at phylum, class, order and family levels, which was concerned with LVEF and CRP value, whereas Alpha diversity index of the flora decreased. The composition and relative abundance of intestinal flora varied in AF patients with CHA 2 DS 2 - VAS C scores of 0, 1, and ≥ 2.

Efficacy and Mechanism of Qianshan Huoxue Gao in Acute Coronary Syndrome via Regulation of Intestinal Flora and Metabolites

Purpose

To study the efficacy of Qianshan Huoxue Gao (QS) in treating acute coronary syndrome (ACS) and to explore the mechanism of action from the perspective of intestinal flora regulation.

Methods

Male Sprague-Dawley rats were divided into control, model, QS, and atorvastatin groups; except for the control group, rats underwent ligation of the left anterior descending branch of the coronary artery. Following treatment for 28 days, cardiac function was evaluated using an echocardiographic assay; ELISAs for serum creatine kinase isoenzyme (CK-MB), cardiac troponin I (cTnI), high-sensitivity C-reactive protein (hs-CRP), interleukin (IL)-2 (IL-2), IL-6, and tumor necrosis factor-α (TNF-α); assessment of cardiac enzymes and inflammatory response; hematoxylin and eosin (HE) staining for histopathological changes in the heart, skin, and viscera; 16S rRNA gene sequencing for intestinal flora diversity and structural differences analysis; and we further investigated intestinal contents using metabolomics.

Results

Compared with controls, CK-MB and cTnI were increased (P<0.01); ejection factor and fractional shortening were decreased (P<0.01); left ventricular internal end-diastolic dimension and left ventricular internal end-systolic dimension were increased (P<0.01); and IL-2, IL-6, TNF-α, and hs-CRP were increased in the model group. Myocardial damage and inflammation were also observed by HE staining. QS improved these indexes, similar to the atorvastatin group; therefore, QS could effectively treat ACS. QS modulates the structure and abundance of the intestinal flora in ACS model rats, among which Bacteroides, Lactobacillus, and Rikenellaceae_RC9_gut_group are associated with cardiovascular disease. Metabolomics revealed that the intestinal metabolite content changed in ACS, with ethanolamine (EA) being the most relevant metabolite for ACS treatment by QS. EA was significantly positively correlated with Eubacterium xylanophilum group, Ruminococcus, unclassified f__Oscillospiraceae, Intestinimonas, Eubacterium siraeum group, Lachnospiraceae NK4A136 group, and norank f__Desulfovibrionaceae.

Conclusion

QS can effectively treat ACS and can restore regulation of the intestinal flora. EA may be the primary metabolite of QS, exerting a therapeutic effect in ACS.

Microbiota: Not Just a Gut Feeling

Every year, an increasing number of scientific papers are published on the gut microbiome [...].

Analysis of Gut Microbiota in Patients with Coronary Artery Disease and Hypertension

Cardiovascular and cerebrovascular diseases are characterized by high rates of morbidity and mortality. Microbiota is closely associated with cardiovascular disease. We aimed to comprehensively analyze the microbiotas of 300 healthy controls, 300 patients with high blood pressure (HBP), and 300 patients with coronary heart disease (CHD). The results indicated no significant difference in microbiota diversity among the three groups (P > 0.05). However, differences in microbiota richness among the three groups were significant (P < 0.05). Bacteroidetes and Bacteroidia were the dominant bacteria in the CHD group, Enterobacteriales and Escherichia-shigella in the HBP group, and Acidaminococcaceae and Phascolarctobacterium in the healthy control group. The prediction results of the random forest model indicated that the population with CHD displayed prominent features with high sensitivity, indicating that microbiota detection might become a novel clinical indicator to predict and monitor the risk of cardiovascular events. The prediction of microbiota function suggested differences in oxygen supply and chronic inflammation between populations with HBP/CHD and healthy populations. Although there is no difference in gut microbiota diversity among the three groups, each group has its dominant microbiota in terms of richness.