A systematic analysis of mouth-to-gut microbial transmission dynamics across disease states = 질병 상태에 따른 구강-장 미생물 전이 역학에 대한 체계적인 분석

목차 (Table of Contents)

• Table of Contents
• List of Tables
• List of Figures
• Abbreviations
• Abstract
• Chapter I. Comparative analysis of mouth-to-gut microbial transmission across disease states
• 1. Introduction
• 1.1. The challenge of quantifying MTG microbial transmission
• 1.2. Methodological limitations and the need for a novel approach
• 2. Materials and Methods
• 2.1. Systematic search and selected datasets
• 2.2. Microbiota analysis
• 2.3. Mouth-to-feces bacterial transmission analysis
• 3. Results
• 3.1. Selection and characteristics of datasets for comparative analysis
• 3.2. Oral and fecal microbiota form distinct community structures
• 3.3. Disease-specific alterations in oral and gut microbiota composition
• 3.4. Alpha diversity varies with disease state but lacks strong oral-gut correlation
• 3.5. Identification of differentially abundant taxa in oral and gut microbiomes
• 3.6. A novel MF index reveals elevated MTG transmission in T2D and CRC
• 3.7. In-depth analysis of GI cancer reveals complex transmission dynamics
• 3.8. Elucidating complex transmission pathways in GI cancers
• 3.9. Transmission dynamics shift with cancer progression
• 3.10. Intercorrelation of transmission pathways and abundance of key bacteria
• 4. Discussion
• Chapter II. Mouth-gut microbiome axis in metabolic syndrome, hypertension, hyperlipidemia, type 2 diabetes, and gastrointestinal cancers
• 1. Introduction
• 2. Materials and Methods
• 2.1. Participant information
• 2.2. Sample collection and processing
• 2.3. Statistics
• 3. Results
• 3.1. Characteristics of the newly established Korean cohort
• 3.2. Oral and gut microbial community structures are primarily shaped by body site and host disease state
• 3.3. Oral and gut alpha diversity show disease-specific alterations and correlations
• 3.4. LEfSe analysis identifies distinct microbial biomarkers for GI cancers
• 3.5. MF microbial transmission is significantly elevated in GI cancers
• 3.6. High MF transmission level is strongly associated with GI cancers
• 3.7. Identification of host state-specific MF-transmitted bacteria
• 3.8. MF transmission index is significantly correlated with host clinical parameters and lifestyle factors
• 3.9. The abundance of key transmitted bacteria changes dynamically with GI cancer progression
• 3.10. Correlations between abundance of MF-transmitted bacteria and host clinical parameters in oral and fecal niches
• 3.11. Lifestyle factors such as exercise and alcohol consumption modify cancer-associated microbial signatures
• 4. Discussion
• Chapter III. Population-wide risk evaluation of type 2 diabetes and gastrointestinal cancers utilizing mouth-to-gut microbial profile-based models
• 1. Introduction
• 2. Materials and Methods
• 2.1 Systematic search and selected datasets
• 2.2. MF microbial profile-based disease classification model
• 2.3. T2D model validation and generalization
• 2.4. GI cancer model validation and generalization
• 3. Results
• 3.1. MF-transmitted microbial profiles serve as potent features for initial disease classification
• 3.2. Validation of MF-based classification model for GI cancers and T2D in external cohorts
• 3.3. Universality of MF microbial profile-based T2D classification
• 3.4. Universality of MF microbial profile-based CRC classification
• 3.5. Integrated models outperform traditional screening methods in sensitivity for T2D and CRC
• 3.6. Pooling strategy distills a core set of robust microbial biomarkers for T2D and CRC
• 4. Discussion
• 5. References