Microbiome in 3P Medicine Strategies: The First Exploitation Guide

Description

The book analyses microbiome-relevant findings focused on clinical needs providing the roadmap to implement recent achievements in the area representing a valuable contribution to the paradigm shift from reactive to predictive, preventive and personalised medicine (PPPM / 3PM) considered as the most advanced concept in medicine. Already well-acknowledged as well as future advantages of application of pre-, pro- and pharma-biotics are detailed in the book. Socio-economic impacts of the area are considered in the context of the entire spectrum of healthcare services from disease care provided to patients up to health care provided to persons in suboptimal health conditions.   Innovative technologies including phenotyping, genotyping, individualised profiling, patient stratification, big data analysis, and multi-omics, amongst others are all involved in the book. The book is unique from view point of multi-professional expertise involved. International network presents more than 10 countries worldwide including Belgium, China, Germany, Israel, Ukraine and USA. The data presented are of great scientific value and of particular importance for educating a broad spectrum of professionals including researchers, healthcare givers, policy makers, business people, policy makers and general population. Preface What This Book Series Is About… Book Series Editor Contents About the Editors Chapter 1: Microbiome in the Framework of Predictive, Preventive and Personalised Medicine 1.1 Microbiota Composition Modulates Individual Immunity with Far-Reaching Consequences 1.2 Microbiome and Individual COVID-19 Outcomes 1.3 Microbiome in Female Health 1.4 Microbiome in Male Health 1.5 Outlook in the Framework of 3P Medicine: Microbiome-Relevant Fields Exemplified 1.5.1 Microbiome Is Instrumental for Primary Healthcare Towards Suboptimal Health Conditions: Focus on Reversing Epidemic Trends of Non-communicable Diseases 1.5.2 Microbiome of Overweight Versus Underweight Individuals: A Disease-Specific Phenotyping References Chapter 2: Artificial Intelligence-Based Predictive, Preventive, and Personalised Medicine Applied to Bacteraemia Diagnosis 2.1 Predictive, Preventive and Personalised Medicine and Bacteraemias 2.2 Relevance of Bacteraemia Prediction 2.3 Artificial Intelligence as a Key Technology for PPPM 2.4 World Health Organisation’s Recommendations About Artificial Intelligence 2.5 Interpretability Is a Key Issue in Artificial Intelligence for Health 2.6 Machine Learning Model’s Taxonomy According to Its Interpretability 2.7 Examples of the Usage of Artificial Intelligence in Medicine 2.8 Bacteraemia’s Definition 2.8.1 Bacteraemia’s Origin 2.8.2 Bacteraemia and Acquisition 2.8.3 Diagnosis of Bacteraemia and Blood Cultures 2.8.4 Contamination and Blood Cultures 2.8.5 Timing and Diagnosis of Bacteraemia 2.8.6 Bacteraemia and Physicians 2.8.7 Bacteraemia and Treatment 2.9 Clinical, Economic and Structural Consequences of Positive Blood Cultures 2.10 Bacteraemia and Prediction Models 2.11 Applying Machine Learning to Predict Bacteraemias 2.12 Databases Have to Represent the Patient’s Casuistry 2.13 Two Datasets for Predictions at Two Different Times 2.14 Data Preprocessing Is Mandatory Previous to Applying Machine Learning Techniques 2.15 Detection of Data Bias During Information Gathering 2.16 Handling Categorical Variables 2.17 Handling Missing Data 2.18 Data Values’ Renormalisation 2.19 Machine Learning Techniques for Bacteraemia Prediction 2.19.1 Support Vector Machine 2.19.2 Random Forest 2.19.3 K-Nearest Neighbours 2.20 Model Validation 2.21 Data Analysis Tools 2.22 Identification of Data Bias in Hospital Records 2.23 Ratio of Missing Data in Datasets 2.24 Method to Parameterise and Validate Machine Learning Techniques 2.25 SVM’s Hyperparameters and Performance Metrics for Prediction Previous to Culture 2.26 SVM’s Hyperparameters and Performance Metrics for Prediction During Culture 2.27 Interpretation of SVM’s Results 2.28 RF’s Hyperparameters and Performances Metrics for Prediction Previous to Culture 2.29 RF’s Hyperparameters and Performances Metrics for Prediction During Culture 2.30 KNN’s Hyperparameters and Performances Metrics for Both Models 2.31 ROC Comparison of the Three Machine Learning Models 2.32 Data Interpretation 2.33 Interplay Between COVID-19 and Bacteraemia 2.34 Conclusions and Recommendations in the Framework of 3P Medicine References Chapter 3: Vaginal Microbiome and Its Role in HPV Induced Cervical Carcinogenesis 3.1 Global Burden of HPV-Associated Cervical Cancer 3.2 Risk Factors Associated with HPV Infection 3.2.1 Non-modifiable Risk Factors 3.2.2 Modifiable Risk Factors 3.3 The Vaginal Microbiome: Its Composition and Interactions 3.4 Two Faces of Lactobacillus Species 3.5 Prognostic Role of Vaginal Microbiome Composition 3.5.1 Microbial Markers of LSIL 3.5.2 Microbial Markers of HSIL 3.6 The Relationship Between the Microbiome and the Epigenome of Cervical Cells 3.7 Inflammation in Response to Cervical Microbiome 3.8 Molecular Pathways Contributing to Inflammatory Response in the Epithelium of the Cervix 3.9 Personalized Diagnostics and Treatment of HPV-Associated Cervical Disease Based on Vaginal Microbiome Composition 3.9.1 State-of-the-Art Diagnostics of VM Composition 3.9.2 Individualized Therapy 3.9.3 Probiotics 3.9.4 Prebiotics 3.9.5 Penile Microbiota 3.10 Signature of Immune System and the Composition of Cervicovaginal Microbiome in Preventive, Predictive, and Personalized Medicine: Association with Cervical Cancer and HPV Clearance 3.11 Conclusions and Recommendations in the Framework of 3P Medicine 3.11.1 Predictive Diagnostics 3.11.2 Targeted Prevention 3.11.3 Personalization of Medical Services References Chapter 4: Microbiome in Lean Individuals: Phenotype-Specific Risks and Outcomes 4.1 Suboptimal Body Weight as a Fundamental Health Risk Factor 4.2 Eating Disorders: Epidemic Trends in Europe, Pathologies and Targeted Therapies Associated with Altered Microbiome Compositions 4.3 A Paradox of Non-alcoholic Fatty Liver Disease in Lean Individuals: The Clue by Altered Microbiome 4.4 Phenotyping of Underweight Individuals Is Crucial for PPPM Approach 4.4.1 Flammer Syndrome Phenotype Is Linked to Low BMI and Identifiable Early in Life 4.4.2 Anorexia Nervosa as an Extreme Case of the Flammer Syndrome Phenotype 4.5 Microbiome Profile Is Altered in Patients with Anorexia Nervosa 4.6 Starvation Strongly Impacts the Gut Microbiome Composition and Pathophysiology of AN 4.7 Irritable Bowel Disease Is Associated with AN and Specific Microflora References Chapter 5: Microbiome and Obesity 5.1 Introduction 5.2 Gut Microbiota Composition in Obesity 5.3 Preclinical Investigations and Studies: Evidence 5.4 Clinically Observed and Proved Data Material 5.5 Discussion/Conclusion/Obstacles and Limitation of Wide Implementation 5.6 Expert Recommendations in the Framework of 3PM to the Practical Medicine References Chapter 6: Pathophysiology-Based Individualized Use of Probiotics and Prebiotics for Metabolic Syndrome: Implementing Predictive, Preventive, and Personalized Medical Approach 6.1 Introduction 6.1.1 Microbiota and Metabolic Syndrome: Strains Stratification for Effective Personalized Probiotic Interventions 6.1.2 Probiotics and Prebiotics 6.1.3 Clinical Indication Prioritization 6.2 Patophysiology: Microbiota & MetS Interplay 6.2.1 Relevance of In Vitro Research 6.2.2 Probiotic Bacterial Cell Wall Heterogeneity: A Biomarker to Predict Host–Bacteria Interaction [32] 6.2.3 Diet and Microbiota 6.2.4 Calorie Restriction 6.2.5 Fructose Intake 6.2.6 Dietary Fibers – Fermentable Carbohydrates 6.2.7 Hereditary Factors and Family Diet History 6.2.8 Prebiotics 6.2.9 Antibiotics 6.2.10 Molecular Mechanisms of Probiotic Effects 6.2.11 Microbiota and Immunity – Allergy and Autoimmune Diseases 6.2.12 Cytokine Profiles of Toll-Like Receptors 6.2.13 Defining Causality vs Correlation – Is an Inflammation in Focus? 6.2.14 Infections 6.2.15 Intestinal Permeability 6.2.16 Oxidative Stress: Emerging Role of Nanomedicine 6.2.17 Microbiota Profile & Microorganism-Based Biomarkers 6.2.18 Plant- vs Animal-Based Diets 6.2.19 Vaginal, Oral and Dermal Microbial Profiles in Distant Sites [9] 6.2.20 Microbiome of Oral Cavity 6.2.21 Skin Microbiome 6.2.22 Wound Healing 6.2.23 The Gut Microbiota in Aging and Longevity 6.3 Disease- and Person-Specific Application of Probiotics 6.3.1 Obesity 6.3.2 CVD, Hypertension & Hypercholesterolemia 6.3.3 Diabetes Mellitus 6.3.4 Liver Disease and MetS 6.3.5 Kidney and MetS 6.3.5.1 Renal Doppler 6.3.6 Hyperuricemia and Gout 6.3.7 Asthma 6.3.8 Role of Spleen-Associated Biomarkers in Patient Stratification for Microbiota Modulating 6.3.9 Probiotics for Neuroendocrine Applications, APUD Cells, Serotonin, Glutamate Signaling 6.3.10 Collateral Pathologies Associated with the Obesity in Women 6.3.10.1 Progesteron 6.3.10.2 Thyroid Hormones 6.3.11 Gut Microbiota and Gut Motility 6.3.12 Probiotics for Musculoskeletal Diseases and Pain: Gut–Muscle Axis 6.3.12.1 Muscle Aging and Gut Microbiota 6.3.13 Vascular Regulation in Obesity, Congestion, Hypoxia and Ischemic Conditions 6.3.14 Hypoxia in the Gut 6.3.15 Cancer, Gut Microbiota and MetS 6.3.16 Gender-Specific Approach for Microbiota Modulation 6.3.17 Age 6.3.18 Ethnicity 6.3.19 Environment 6.4 Endnotes and Recommendations 6.4.1 Recommendation for Individualized Clinical Use of Probiotics 6.4.1.1 Recommendations 6.4.2 Dose & Periodicity of Probiotics Treatments 6.4.3 Recommendation for Probiotic Studies Design 6.4.4 Diet, Food and Prebiotics 6.4.5 Legislative Issues of Microbiome 6.4.6 Ethical Issues of Microbiome 6.4.7 Business Model Aspect of Probiotic Use: Guarantees & Warranties of Quality of Probiotic Products References Chapter 7: Selection of Prebiotic Substances for Individual Prescription 7.1 Introduction 7.2 New Era of Prebiotics 7.3 NANO Prebiotics 7.4 Prebiotics of Plant Origin 7.5 Pro-and Antibacterial Properties of Polyphenols and Anthocyanins In Vitro 7.6 Determination of Minimum Inhibitory Concentrations of Edible Plant Extracts on Bacterial Strains Isolated from Medical Equipment Surfaces and Bacterial Strains Isolated from Plant Surfaces 7.7 Application of Plum Extract as a Prebiotic Component of Biopreparations 7.8 PPPM Strategies in the Field 7.9 Expert Recommendations in the Frame-Work of 3 PM to the Practical Medicine References Chapter 8: Probiotic Administration for the Prevention and Treatment of Gastrointestinal, Metabolic and Neurological Disorders 8.1 Introduction 8.1.1 Probiotic Administration 8.1.2 Gastrointestinal Disorders 8.1.3 Metabolic Disorders 8.1.4 Neurological Disorders 8.2 Evidences Supporting Preclinical Studies 8.2.1 In Vitro Tests 8.2.2 Animals Experiments 8.3 Clinical Data 8.3.1 Clinical Trials 8.3.1.1 Probiotics in Gastrointestinal Disorders 8.3.1.2 Probiotics in Metabolic Disorders 8.3.1.3 Probiotics in Neurological Disorders 8.3.2 Mechanisms of Action of Probiotics 8.4 Remarks and Conclusion 8.5 PPPM Strategies in the Field of Probiotics Administration 8.6 Expert Recommendations in the Framework of 3P Medicine References Chapter 9: Microbial Therapy with Indigenous Bacteria: From Idea to Clinical Evidence 9.1 Introduction 9.2 The Concept and Methodology of Making Autoprobiotics 9.3 Usage of Autoprobiotic Enterococci in Medicine 9.4 Irritable Bowel Syndrome 9.5 Parkinson’s Disease 9.6 Metabolic Syndrome 9.7 Colorectal Cancer 9.8 Helicobacter pylori Gastritis 9.9 Chronic Generalized Periodontitis 9.10 Summary References Chapter 10: Fecal Microbiota Transplantation in Diseases Not Associated with Clostridium difficile: Current Status and Future Therapeutic Option 10.1 Introduction 10.2 FMT in Focus of Predictive Approach, Targeted Prevention and Personalisation of Medical Services 10.3 Ulcerative Colitis (UC) 10.4 Pouchitis 10.5 Crohn’s Disease (CD) 10.6 Irritable Bowel Syndrome (IBS) 10.7 Microscopic Сolitis (MC) 10.8 Functional Constipation 10.9 Antibiotic-Associated Diarrhea (AAD) 10.10 Immune Checkpoint Inhibitors Associated Colitis and Gastro-intestinal Cancers 10.11 Chronic Liver Disease 10.12 Acute Pancreatitis 10.13 Non-gastroenterological Diseases 10.13.1 Systemic Lupus Erythematosus (SLE) and Sjögren’s Syndrome (SS) 10.13.2 Psoriasis 10.13.3 Multiple Sclerosis 10.13.4 Parkinson’s Disease (PD) 10.13.5 Autism Spectrum Disease (ASD) 10.13.6 Epilepsy 10.13.7 Other Neurological Disorders 10.13.8 Metabolic Syndrome/Obesity/Hypertension 10.14 Discussion/Conclusion/Obstacles and Limitation of Wide Implementation 10.15 Expert Recommendations in the Framework of 3PM to the Practical Medicine References Chapter 11: Personalized Microbiome Correction by Application of Individual Nutrition for Type 2 Diabetes Treatment 11.1 Introduction 11.2 Effect of Edible Plant Extracts on Intestinal Microbiota: In Vitro Studies 11.3 Investigation of the Impact of Individually Designed Nutrition on Gut Microbiota and Metabolism: In Vivo Studies 11.4 Personalized Nutrition for Microbiota Correction and Metabolism Restore in Type 2 Diabetes Mellitus Patients: Clinical Trail 11.5 Analysis of Experimental Data, Development and Application of Methods for Selecting Markers of the Process of Intestinal Microbiota Personalized Correction 11.6 PPPM Strategies in the Field 11.7 Expert Recommendations in the Frame-Work of 3PM to the Practical Medicine References Chapter 12: Pro- Pre- and Synbiotic Supplementation and Oxalate Homeostasis in 3 PM Context: Focus on Microbiota Oxalate-Degrading Activity 12.1 Introduction 12.2 The Differential Sensitivity of Narrow-Profile Vs. Broad-Profile Oxalotrophs to Oxalate-Rich Diet and Antibiotic Violence: A Preclinical Study 12.3 Methods for Urine Oxalate Determination 12.4 Methods for Total Fecal Bacteria ODA Measuring 12.5 The Proof of Concept on the Significance of Total Fecal ODA Vs. ODB to Support Oxalate Homeostasis: A Preclinical Study 12.6 The Proof of Concept on the Significance of Total Fecal ODA Vs. ODB to Support Oxalate Homeostasis: A Clinical Study 12.7 ODA in Fecal Microbiota Is a Key Point for Personalized Probiotic Therapy in Kidney Stone Disease Patients 12.8 Conclusion 12.9 Expert recommendations in the Framework of 3 PM to the Practical Medicine References Chapter 13: In Vitro Study of Specific Properties of Probiotic Strains for Effective and Personalized Probiotic Therapy 13.1 Relevance of In Vitro Research to Support Strains Stratification for Effective Personalized Probiotic Interventions 13.2 Cultural-Morphological and Tinctorial Properties 13.3 Tolerance of Probiotic Bacteria to Gastric Juice, Bile Salts and Proteolytic Enzymes (Pancreatin) 13.4 Adhesive Properties of Probiotic Bacteria 13.5 Antibiotic Resistant of Probiotic Bacteria 13.6 Data Interpretation References Chapter 14: Probiotic Concepts of Predictive, Preventive, and Personalized Medical Approach for Obesity: Lactic Acid Bacteria and Bifidobacteria Probiotic Strains Improve Glycemic and Inflammation Profiles 14.1 Introduction 14.2 Study Design 14.2.1 Animals 14.2.2 Ethics 14.2.3 Bacteria and Culture Conditions 14.2.4 Diet 14.2.5 Design of the Experiment 14.2.6 Glucose Measurements 14.2.7 Cytokines Production Measurements 14.2.8 Macrophages Harvest 14.2.9 Respiratory Burst and Phagocytic Activity Measurements 14.2.10 Statistics 14.3 Achievements 14.4 Data Interpretation 14.5 Future Outlooks References Chapter 15: Oral Microbiome and Innate Immunity in Health and Disease: Building a Predictive, Preventive and Personalized Therapeutic Approach 15.1 Introduction 15.1.1 Oral Microbiome 15.2 Innate Immunity and Oral Microbiome 15.2.1 Oral Microbiome and Diseases of the Mouth 15.3 Systemic Health and Oral Microbiome 15.4 Oral Microbiome and Diseases: Impact of COVID-19 on Oral Microbiome 15.5 Practice Guidelines for the Maintenance of Oral Health References Index