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Gut Microbiota and Metabolic Alterations Associated with Heart Failure and Coronary Artery Disease
Adel A Yafarova1, Elena V Dementeva2, Olga A Zlobovskaya2
1National Medical Research Center for Therapy and Preventive Medicine, Petroverigskyj Lane 10, Bld. 3, 101990 Moscow, Russia.
Insights
Gut microbiota alterations, including higher Bacillota/Bacteroidota ratios, are linked to cardiovascular diseases like coronary artery disease and heart failure. These changes impact microbial diversity and are identified using advanced network and machine learning analyses.
Area of Science:
- Microbiome research
- Cardiovascular disease research
- Metabolomics
Background:
- The gut microbiota plays a crucial role in host health and disease.
- Alterations in gut microbial composition are increasingly associated with cardiovascular diseases (CVD).
- Specific microbial metabolites may influence the development of atherosclerosis and heart failure.
Purpose of the Study:
- To investigate the association between gut microbiota composition and pro-atherogenic metabolites in patients with coronary artery disease (CAD) and heart failure with reduced ejection fraction (HFrEF).
- To identify key microbial features and their interactions linked to CAD and HFrEF using advanced analytical techniques.
- To compare gut microbiota profiles and metabolite levels between CVD patients and healthy controls.
Main Methods:
- Cross-sectional study of 189 participants (93 CAD, 43 HFrEF, 53 controls).
- Gut microbiota analyzed via next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR).
- Network analysis, machine learning, and statistical methods (including diversity analyses) applied to identify microbial signatures and metabolite correlations.
Main Results:
- Significant differences in gut microbiota composition were observed, with higher Bacillota/Bacteroidota ratios in CAD and HFrEF groups (p < 0.001).
- Reduced alpha-diversity (Pielou, Chao1, Faith) and distinct beta-diversity profiles were noted in disease groups (p < 0.001).
- Lower trimethylamine N-oxide (TMAO) levels were found in CAD and HFrEF patients compared to controls (p < 0.05).
Conclusions:
- Gut microbiota composition is significantly altered in patients with CAD and HFrEF.
- Specific microbial shifts and altered metabolite profiles are associated with cardiovascular disease.
- Network and machine learning analyses reveal complex gut microbial interactions implicated in CVD pathogenesis.
Abstract:
This study investigates the role of gut microbiota in cardiovascular diseases, with an additional focus on pro-atherogenic metabolites. We use advanced network analysis and machine learning techniques to identify key microbial features linked to coronary artery disease (CAD) and heart failure with reduced ejection fraction (HFrEF). This cross-sectional study included 189 participants divided into three groups: coronary artery disease (n = 93), heart failure with reduced ejection fraction (n = 43), and controls (n = 53). Assessments included physical exams, echocardiography, dietary surveys, blood analysis, and fecal analysis. Gut microbiota composition was analyzed using next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR). Statistical analysis methods for testing hypotheses and correlations, alpha and beta-diversity analyses, co-occurrence networks, and machine learning were conducted using Python libraries or R packages with multiple comparisons corrected using the Benjamini-Hochberg procedure. Significant gut microbiota alterations were observed, with higher Bacillota/Bacteroidota ratios in CAD and HFrEF groups compared to controls (p < 0.001). Significant differences were observed in α-diversity indices (Pielou, Chao1, Faith) between disease groups and controls (p < 0.001). β-diversity analyses also revealed distinct microbial profiles (p = 0.0015). Interestingly, trimethylamine N-oxide (TMAO) levels were lower in CAD and HFrEF groups compared to controls (p < 0.05), while indoxyl sulfate (IS) levels were comparable between the study groups. Co-occurrence network analysis and machine learning identified key microbial features linked to these conditions, highlighting complex interactions within the gut microbiota associated with cardiovascular disease.
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