Signature of Alzheimer’s Disease in Intestinal Microbiome: Results From the AlzBiom Study

Meta-analysis of the human gut microbiome uncovers shared and distinct microbial signatures between diseases

Microbiome studies have revealed gut microbiota's potential impact on complex diseases. However, many studies often focus on one disease per cohort. We developed a meta-analysis workflow for gut microbiome profiles and analyzed shotgun metagenomic data covering 11 diseases. Using interpretable machine learning and differential abundance analysis, our findings reinforce the generalization of binary classifiers for Crohn's disease (CD) and colorectal cancer (CRC) to hold-out cohorts and highlight the key microbes driving these classifications. We identified high microbial similarity in disease pairs like CD vs ulcerative colitis (UC), CD vs CRC, Parkinson's disease vs type 2 diabetes (T2D), and schizophrenia vs T2D. We also found strong inverse correlations in Alzheimer's disease vs CD and UC. These findings, detected by our pipeline, provide valuable insights into these diseases.

IMPORTANCE

Assessing disease similarity is an essential initial step preceding a disease-based approach for drug repositioning. Our study provides a modest first step in underscoring the potential of integrating microbiome insights into the disease similarity assessment. Recent microbiome research has predominantly focused on analyzing individual diseases to understand their unique characteristics, which by design excludes comorbidities in individuals. We analyzed shotgun metagenomic data from existing studies and identified previously unknown similarities between diseases. Our research represents a pioneering effort that utilizes both interpretable machine learning and differential abundance analysis to assess microbial similarity between diseases.

Infant microbes and metabolites point to childhood neurodevelopmental disorders

This study has followed a birth cohort for over 20 years to find factors associated with neurodevelopmental disorder (ND) diagnosis. Detailed, early-life longitudinal questionnaires captured infection and antibiotic events, stress, prenatal factors, family history, and more. Biomarkers including cord serum metabolome and lipidome, human leukocyte antigen (HLA) genotype, infant microbiota, and stool metabolome were assessed. Among the 16,440 Swedish children followed across time, 1,197 developed an ND. Significant associations emerged for future ND diagnosis in general and for specific ND subtypes, spanning intellectual disability, speech disorder, attention-deficit/hyperactivity disorder, and autism. This investigation revealed microbiome connections to future diagnosis as well as early emerging mood and gastrointestinal problems. The findings suggest links to immunodysregulation and metabolism, compounded by stress, early-life infection, and antibiotics. The convergence of infant biomarkers and risk factors in this prospective, longitudinal study on a large-scale population establishes a foundation for early-life prediction and intervention in neurodevelopment.

Gut instincts: Unveiling the connection between gut microbiota and Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder marked by neuroinflammation and gradual cognitive decline. Recent research has revealed that the gut microbiota (GM) plays an important role in the pathogenesis of AD through the microbiota-gut-brain axis. However, the mechanism by which GM and microbial metabolites alter brain function is not clearly understood. GM dysbiosis increases the permeability of the intestine, alters the blood-brain barrier permeability, and elevates proinflammatory mediators causing neurodegeneration. This review article introduced us to the composition and functions of GM along with its repercussions of dysbiosis in relation to AD. We also discussed the importance of the gut-brain axis and its role in communication. Later we focused on the mechanism behind gut dysbiosis and the progression of AD including neuroinflammation, oxidative stress, and changes in neurotransmitter levels. Furthermore, we highlighted recent developments in AD management, such as microbiota-based therapy, dietary interventions like prebiotics, probiotics, and fecal microbiota transplantation. Finally, we concluded with challenges and future directions in AD research based on GM.

Exploring the Influence of Gut-Brain Axis Modulation on Cognitive Health: A Comprehensive Review of Prebiotics, Probiotics, and Symbiotics

Recent research exploring the relationship between the gut and the brain suggests that the condition of the gut microbiota can influence cognitive health. A well-balanced gut microbiota may help reduce inflammation, which is linked to neurodegenerative conditions. Prebiotics, probiotics, and symbiotics are nutritional supplements and functional food components associated with gastrointestinal well-being. The bidirectional communication of the gut-brain axis is essential for maintaining homeostasis, with pre-, pro-, and symbiotics potentially affecting various cognitive functions such as attention, perception, and memory. Numerous studies have consistently shown that incorporating pre-, pro-, and symbiotics into a healthy diet can lead to improvements in cognitive functions and mood. Maintaining a healthy gut microbiota can support optimal cognitive function, which is crucial for disease prevention in our fast-paced, Westernized society. Our results indicate cognitive benefits in healthy older individuals with probiotic supplementation but not in healthy older individuals who have good and adequate levels of physical activity. Additionally, it appears that there are cognitive benefits in patients with mild cognitive impairment and Alzheimer's disease, while mixed results seem to arise in younger and healthier individuals. However, it is important to acknowledge that individual responses may vary, and the use of these dietary supplements should be tailored to each individual's unique health circumstances and needs.

Meta-analysis of the human gut microbiome uncovers shared and distinct microbial signatures between diseases

Microbiome studies have revealed gut microbiota's potential impact on complex diseases. However, many studies often focus on one disease per cohort. We developed a meta-analysis workflow for gut microbiome profiles and analyzed shotgun metagenomic data covering 11 diseases. Using interpretable machine learning and differential abundance analysis, our findings reinforce the generalization of binary classifiers for Crohn's disease (CD) and colorectal cancer (CRC) to hold-out cohorts and highlight the key microbes driving these classifications. We identified high microbial similarity in disease pairs like CD vs ulcerative colitis (UC), CD vs CRC, Parkinson's disease vs type 2 diabetes (T2D), and schizophrenia vs T2D. We also found strong inverse correlations in Alzheimer's disease vs CD and UC. These findings detected by our pipeline provide valuable insights into these diseases.

Prognostic Value of Gut Microbiome for Conversion from Mild Cognitive Impairment to Alzheimer's Disease Dementia within 4 Years: Results from the AlzBiom Study

Alterations in the gut microbiome are associated with the pathogenesis of Alzheimer's disease (AD) and can be used as a diagnostic measure. However, longitudinal data of the gut microbiome and knowledge about its prognostic significance for the development and progression of AD are limited. The aim of the present study was to develop a reliable predictive model based on gut microbiome data for AD development. In this longitudinal study, we investigated the intestinal microbiome in 49 mild cognitive impairment (MCI) patients over a mean (SD) follow-up of 3.7 (0.6) years, using shotgun metagenomics. At the end of the 4-year follow-up (4yFU), 27 MCI patients converted to AD dementia and 22 MCI patients remained stable. The best taxonomic model for the discrimination of AD dementia converters from stable MCI patients included 24 genera, yielding an area under the receiver operating characteristic curve (AUROC) of 0.87 at BL, 0.92 at 1yFU and 0.95 at 4yFU. The best models with functional data were obtained via analyzing 25 GO (Gene Ontology) features with an AUROC of 0.87 at BL, 0.85 at 1yFU and 0.81 at 4yFU and 33 KO [Kyoto Encyclopedia of Genes and Genomes (KEGG) ortholog] features with an AUROC of 0.79 at BL, 0.88 at 1yFU and 0.82 at 4yFU. Using ensemble learning for these three models, including a clinical model with the four parameters of age, gender, body mass index (BMI) and Apolipoprotein E (ApoE) genotype, yielded an AUROC of 0.96 at BL, 0.96 at 1yFU and 0.97 at 4yFU. In conclusion, we identified novel and timely stable gut microbiome algorithms that accurately predict progression to AD dementia in individuals with MCI over a 4yFU period.

Fecal Metagenomics to Identify Biomarkers of Food Intake in Healthy Adults: Findings from Randomized, Controlled, Nutrition Trials

BACKGROUND

Undigested components of the human diet affect the composition and function of the microorganisms present in the gastrointestinal tract. Techniques like metagenomic analyses allow researchers to study functional capacity, thus revealing the potential of using metagenomic data for developing objective biomarkers of food intake.

OBJECTIVES

As a continuation of our previous work using 16S and metabolomic datasets, we aimed to utilize a computationally intensive, multivariate, machine-learning approach to identify fecal KEGG (Kyoto encyclopedia of genes and genomes) Orthology (KO) categories as biomarkers that accurately classify food intake.

METHODS

Data were aggregated from 5 controlled feeding studies that studied the individual impact of almonds, avocados, broccoli, walnuts, barley, and oats on the adult gastrointestinal microbiota. Deoxyribonucleic acid from preintervention and postintervention fecal samples underwent shotgun genomic sequencing. After preprocessing, sequences were aligned and functionally annotated with Double Index AlignMent Of Next-generation sequencing Data v2.0.11.149 and MEtaGenome ANalyzer v6.12.2, respectively. After the count normalization, the log of the fold change ratio for resulting KOs between pre- and postintervention of the treatment group against its corresponding control was utilized to conduct differential abundance analysis. Differentially abundant KOs were used to train machine-learning models examining potential biomarkers in both single-food and multi-food models.

RESULTS

We identified differentially abundant KOs in the almond (n = 54), broccoli (n = 2474), and walnut (n = 732) groups (q < 0.20), which demonstrated classification accuracies of 80%, 87%, and 86% for the almond, broccoli, and walnut groups using a random forest model to classify food intake into each food group's respective treatment and control arms, respectively. The mixed-food random forest achieved 81% accuracy.

CONCLUSIONS

Our findings reveal promise in utilizing fecal metagenomics to objectively complement self-reported measures of food intake. Future research on various foods and dietary patterns will expand these exploratory analyses for eventual use in feeding study compliance and clinical settings.

Effects of Vitamin E on the Gut Microbiome in Ageing and Its Relationship with Age-Related Diseases: A Review of the Current Literature

Ageing is inevitable in all living organisms and is associated with physical deterioration, disease and eventually death. Dysbiosis, which is the alteration of the gut microbiome, occurs in individuals during ageing, and plenty of studies support that gut dysbiosis is responsible for the progression of different types of age-related diseases. The economic burden of age-linked health issues increases as ageing populations increase. Hence, an improvement in disease prevention or therapeutic approaches is urgently required. In recent years, vitamin E has garnered significant attention as a promising therapeutic approach for delaying the ageing process and potentially impeding the development of age-related disease. Nevertheless, more research is still required to understand how vitamin E affects the gut microbiome and how it relates to age-related diseases. Therefore, we gathered and summarized recent papers in this review that addressed the impact of the gut microbiome on age-related disease, the effect of vitamin E on age-related disease along with the role of vitamin E on the gut microbiome and the relationship with age-related diseases which are caused by ageing. Based on the studies reported, different bacteria brought on various age-related diseases with either increased or decreased relative abundances. Some studies have also reported the positive effects of vitamin E on the gut microbiome as beneficial bacteria and metabolites increase with vitamin E supplementation. This demonstrates how vitamin E is vital as it affects the gut microbiome positively to delay ageing and the progression of age-related diseases. The findings discussed in this review will provide a simplified yet deeper understanding for researchers studying ageing, the gut microbiome and age-related diseases, allowing them to develop new preclinical and clinical studies.

A metagenomic study of gut viral markers in amyloid-positive Alzheimer's disease patients

BACKGROUND

Mounting evidence suggests the involvement of viruses in the development and treatment of Alzheimer's disease (AD). However, there remains a significant research gap in metagenomic studies investigating the gut virome of AD patients, leaving gut viral dysbiosis in AD unexplored. This study aimed to fill this gap by conducting a metagenomics analysis of the gut virome in both amyloid-positive AD patients (Aβ + ADs) and healthy controls (HCs), with the objective of identifying viral signatures linked with AD.

METHOD

Whole-genome sequence (WGS) data from 65 human participants, including 30 Aβ + ADs and 35 HCs, was obtained from the database NCBI SRA (Bio Project: PRJEB47976). The Metaphlan3 pipeline and linear discriminant analysis effect size (LEfSe) analysis were utilized for the bioinformatics process and the detection of viral signatures, respectively. In addition, the Benjamini-Hochberg method was applied with a significance cutoff of 0.05 to evaluate the false discovery rate for all biomarkers identified by LEfSe. The CombiROC model was employed to determine the discriminatory power of the viral signatures identified by LEfSe.

RESULTS

Compared to HCs, the gut virome profiles of Aβ + ADs showed lower alpha diversity, indicating a lower bacteriophage richness. The Siphoviridae family was decreased in Aβ + ADs. Significant decreases of Lactococcus phages were found in Aβ + ADs, including bIL285, Lactococcus phage bIL286, Lactococcus phage bIL309, and Lactococcus phage BK5 T, Lactococcus phage BM13, Lactococcus phage P335 sensu lato, Lactococcus phage phiLC3, Lactococcus phage r1t, Lactococcus phage Tuc2009, Lactococcus phage ul36, and Lactococcus virus bIL67. The predictive combined model of these viral signatures obtained an area under the curve of 0.958 when discriminating Aβ + ADs from HCs.

CONCLUSION

This is the first study to identify distinct viral signatures in the intestine that can be used to effectively distinguish individuals with AD from HCs.

A peripheral signature of Alzheimer's disease featuring microbiota-gut-brain axis markers

BACKGROUND

Increasing evidence links the gut microbiota (GM) to Alzheimer's disease (AD) but the mechanisms through which gut bacteria influence the brain are still unclear. This study tests the hypothesis that GM and mediators of the microbiota-gut-brain axis (MGBA) are associated with the amyloid cascade in sporadic AD.

METHODS

We included 34 patients with cognitive impairment due to AD (CI-AD), 37 patients with cognitive impairment not due to AD (CI-NAD), and 13 cognitively unimpaired persons (CU). We studied the following systems: (1) fecal GM, with 16S rRNA sequencing; (2) a panel of putative MGBA mediators in the blood including immune and endothelial markers as bacterial products (i.e., lipopolysaccharide, LPS), cell adhesion molecules (CAMs) indicative of endothelial dysfunction (VCAM-1, PECAM-1), vascular changes (P-, E-Selectin), and upregulated after infections (NCAM, ICAM-1), as well as pro- (IL1β, IL6, TNFα, IL18) and anti- (IL10) inflammatory cytokines; (3) the amyloid cascade with amyloid PET, plasma phosphorylated tau (pTau-181, for tau pathology), neurofilament light chain (NfL, for neurodegeneration), and global cognition measured using MMSE and ADAScog. We performed 3-group comparisons of markers in the 3 systems and calculated correlation matrices for the pooled group of CI-AD and CU as well as CI-NAD and CU. Patterns of associations based on Spearman's rho were used to validate the study hypothesis.

RESULTS

CI-AD were characterized by (1) higher abundance of Clostridia_UCG-014 and decreased abundance of Moryella and Blautia (p < .04); (2) elevated levels of LPS (p < .03), upregulation of CAMs, Il1β, IL6, and TNFα, and downregulation of IL10 (p < .05); (3) increased brain amyloid, plasma pTau-181, and NfL (p < 0.004) compared with the other groups. CI-NAD showed (1) higher abundance of [Eubacterium] coprostanoligenes group and Collinsella and decreased abundance of Lachnospiraceae_ND3007_group, [Ruminococcus]_gnavus_group and Oscillibacter (p < .03); (2) upregulation of PECAM-1 and TNFα (p < .03); (4) increased plasma levels of NfL (p < .02) compared with CU. Different GM genera were associated with immune and endothelial markers in both CI-NAD and CI-AD but these mediators were widely related to amyloid cascade markers only in CI-AD.

CONCLUSIONS

Specific bacterial genera are associated with immune and endothelial MGBA mediators, and these are associated with amyloid cascade markers in sporadic AD. The physiological mechanisms linking the GM to the amyloid cascade should be further investigated to elucidate their potential therapeutic implications.

The gut microbiome and Alzheimer's disease: Complex and bidirectional interactions

Structural and functional alterations to the gut microbiome, referred to as gut dysbiosis, have emerged as potential key mediators of neurodegeneration and Alzheimer disease (AD) pathogenesis through the "gut -brain" axis. Emerging data from animal and clinical studies support an important role for gut dysbiosis in mediating neuroinflammation, central and peripheral immune dysregulation, abnormal brain protein aggregation, and impaired intestinal and brain barrier permeability, leading to neuronal loss and cognitive impairment. Gut dysbiosis has also been shown to directly influence various mechanisms involved in neuronal growth and repair, synaptic plasticity, and memory and learning functions. Aging and lifestyle factors including diet, exercise, sleep, and stress influence AD risk through gut dysbiosis. Furthermore, AD is associated with characteristic gut microbial signatures which offer value as potential markers of disease severity and progression. Together, these findings suggest the presence of a complex bidirectional relationship between AD and the gut microbiome and highlight the utility of gut modulation strategies as potential preventative or therapeutic strategies in AD. We here review the current literature regarding the role of the gut-brain axis in AD pathogenesis and its potential role as a future therapeutic target in AD treatment and/or prevention.

Direct Oral Anticoagulants (DOACs) for Therapeutic Targeting of Thrombin, a Key Mediator of Cerebrovascular and Neuronal Dysfunction in Alzheimer’s Disease

Although preclinical research and observer studies on patients with atrial fibrillation concluded that direct oral anticoagulants (DOACs) can protect against dementia like Alzheimer’s disease (AD), clinical investigation towards therapeutical approval is still pending. DOACs target pathological thrombin, which is, like toxic tau and amyloid-ß proteins (Aß), an early hallmark of AD. Especially in hippocampal and neocortical areas, the release of parenchymal Aß into the blood induces thrombin and proinflammatory bradykinin synthesis by activating factor XII of the contact system. Thrombin promotes platelet aggregation and catalyzes conversion of fibrinogen to fibrin, leading to degradation-resistant, Aß-containing fibrin clots. Together with oligomeric Aß, these clots trigger vessel constriction and cerebral amyloid angiopathy (CAA) with vessel occlusion and hemorrhages, leading to vascular and blood–brain barrier (BBB) dysfunction. As consequences, brain blood flow, perfusion, and supply with oxygen (hypoxia) and nutrients decrease. In parenchymal tissue, hypoxia stimulates Aß synthesis, leading to Aß accumulation, which is further enhanced by BBB-impaired perivascular Aß clearance. Aß trigger neuronal damage and promote tau pathologies. BBB dysfunction enables thrombin and fibrin(ogen) to migrate into parenchymal tissue and to activate glial cells. Inflammation and continued Aß production are the results. Synapses and neurons die, and cognitive abilities are lost. DOACs block thrombin by inhibiting its activity (dabigatran) or production (FXa-inhibitors, e.g., apixaban, rivaroxaban). Therefore, DOAC use could preserve vascular integrity and brain perfusion and, thereby, could counteract vascular-driven neuronal and cognitive decline in AD. A conception for clinical investigation is presented, focused on DOAC treatment of patients with diagnosed AD in early-stage and low risk of major bleeding.